{"meta":{"query_hash":"fafbeba439f0","filters":{"topic":"Data Visualization and Analytics"},"cohort_total":1448,"direct_labels_cover":4,"predictions_cover":1448,"exported":1448,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/fafbeba439f0","api":"https://metacan.xera.ac/api/v1/cohort?topic=Data+Visualization+and+Analytics"},"results":[{"id":"W106189515","doi":"10.14236/ewic/hci2010.10","title":"Novel User Interfaces for Diagram Versioning and Differencing","year":2010,"lang":"en","type":"article","venue":"Electronic workshops in computing","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Software versioning; Computer science; Diagram; Software; Programming language; Software engineering; Database","score_opus":0.01292498983713109,"score_gpt":0.2857150008033587,"score_spread":0.2727900109662276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W106189515","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24593928,0.00007465906,0.75325966,0.00024006676,0.0002503354,0.00009221788,5.024348e-7,0.000073981246,0.00006930943],"genre_scores_gemma":[0.9629782,0.000010072625,0.036667407,0.00017552839,0.000082700084,0.0000026855384,0.0000052719697,0.000009792831,0.000068366935],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998857,0.000017753582,0.00021394853,0.0003487004,0.00010968698,0.000452886],"domain_scores_gemma":[0.99923295,0.00036127606,0.000081447295,0.00023411974,0.00003834249,0.000051841773],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042210438,0.00012299832,0.00014749198,0.00012273603,0.00016831394,0.00027288072,0.00048166933,0.00006682889,0.000003722708],"category_scores_gemma":[0.00018196472,0.0001204432,0.000027093964,0.00035021477,0.000029922181,0.0002470925,0.00033384384,0.0003835957,0.000001652267],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001212927,0.0001735244,0.009747568,0.00005291115,0.000040061983,0.0000025323586,0.0026514232,0.0026207506,0.013724763,0.5235096,0.0005017838,0.44696292],"study_design_scores_gemma":[0.00052615075,0.000039723145,0.0016209228,0.00006895775,0.000004109944,0.000009715604,0.000084076855,0.9930871,0.0012389927,0.0014049205,0.0017266276,0.0001887155],"about_ca_topic_score_codex":0.000009861054,"about_ca_topic_score_gemma":0.00013360273,"teacher_disagreement_score":0.99046636,"about_ca_system_score_codex":0.00004277649,"about_ca_system_score_gemma":0.0000656789,"threshold_uncertainty_score":0.4911531},"labels":[],"label_agreement":null},{"id":"W109627659","doi":"","title":"Improved Efficiency of Spring Embedders: Taking Advantage of GPU Programming","year":2007,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Computer science; Computation; Parallel computing; General-purpose computing on graphics processing units; Visualization; Context (archaeology); Computational science; CUDA; Software; Graph; Computer engineering; Computer architecture; Computer graphics (images); Graphics; Theoretical computer science; Programming language; Artificial intelligence","score_opus":0.019081230608349754,"score_gpt":0.2836258117395772,"score_spread":0.2645445811312274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W109627659","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01789431,0.0005232222,0.97177404,0.00041304817,0.00019756478,0.00034548354,0.000021171638,0.00018514106,0.008646033],"genre_scores_gemma":[0.700425,0.00017638401,0.2987397,0.000033341395,0.000011321378,0.000009466047,0.000077641525,0.000025278481,0.00050183694],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9962234,0.001166702,0.0009366261,0.00072736637,0.00056722877,0.0003787152],"domain_scores_gemma":[0.993005,0.0006758,0.0016684707,0.0024736677,0.0020368767,0.00014021882],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0057332846,0.00028539114,0.00045951366,0.00041998975,0.00014673048,0.00029245828,0.0027552412,0.00020672822,0.000025819794],"category_scores_gemma":[0.0014426443,0.00030990085,0.00023047526,0.00085614796,0.00023420368,0.00027710004,0.002778076,0.00041336994,0.0000039376628],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012593202,0.0020436496,0.005389392,0.0016853362,0.00018014951,0.000011420717,0.020294238,0.00049210445,0.022412779,0.58214957,0.00009131591,0.36523744],"study_design_scores_gemma":[0.00076159707,0.0000020479436,0.0011769314,0.0041614138,0.000067858884,0.0000066986154,0.000508313,0.69767946,0.28882244,0.0012919994,0.00475595,0.0007652907],"about_ca_topic_score_codex":0.00067434355,"about_ca_topic_score_gemma":0.00033120092,"teacher_disagreement_score":0.69718736,"about_ca_system_score_codex":0.000061796716,"about_ca_system_score_gemma":0.00029955435,"threshold_uncertainty_score":0.9999353},"labels":[],"label_agreement":null},{"id":"W113755528","doi":"10.1524/itit.2009.0534","title":"Science and Smart GraphicsWissenschaft und intelligente Grafiken","year":2009,"lang":"en","type":"article","venue":"it - Information Technology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Graphics; Field (mathematics); Variety (cybernetics); Computer graphics; Scholarship; Data science; Human–computer interaction; Informatics; Analytics; Interdisciplinarity; Multimedia; Artificial intelligence; Computer graphics (images); Engineering; Sociology; Social science; Political science","score_opus":0.01166043033236617,"score_gpt":0.29332442480483406,"score_spread":0.28166399447246787,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W113755528","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0045193005,0.0000734003,0.96698594,0.020014208,0.00017812413,0.00014352576,0.0000038703142,0.00062303606,0.00745858],"genre_scores_gemma":[0.97757024,0.00021066093,0.015629698,0.006456937,0.000009107439,0.0000026527648,0.000013266718,0.0000024454605,0.00010498396],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99907875,0.000006439252,0.00027252923,0.0001481232,0.00028062056,0.0002135152],"domain_scores_gemma":[0.9990727,0.000011364273,0.00011269083,0.0004151526,0.00032111793,0.00006697807],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038091728,0.00008857048,0.0000930355,0.0015537388,0.0002018915,0.00029215185,0.00081701094,0.00008453494,0.000005022865],"category_scores_gemma":[0.00026538988,0.000083688996,0.000014276918,0.0030621144,0.00029483243,0.0026083963,0.00021765137,0.000119604694,0.00010146073],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.871635e-7,0.000010131019,0.000110019624,0.0000034631148,0.0000025555173,6.6878437e-7,0.00019934004,0.000004243001,0.00012656352,0.90534675,0.0016696857,0.09252599],"study_design_scores_gemma":[0.00044160886,0.00039360838,0.0015036738,0.0000404766,0.000012120761,0.000100705605,0.0005473098,0.20794855,0.014471535,0.13123077,0.6428622,0.00044744925],"about_ca_topic_score_codex":0.0000031110462,"about_ca_topic_score_gemma":0.0000030453375,"teacher_disagreement_score":0.97305095,"about_ca_system_score_codex":0.00002893163,"about_ca_system_score_gemma":0.00010647055,"threshold_uncertainty_score":0.3412738},"labels":[],"label_agreement":null},{"id":"W118734219","doi":"","title":"Beyond Keywords and Hierarchies","year":2005,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Interface (matter); Simple (philosophy); Work (physics); Information sharing; Human–computer interaction; Knowledge management; World Wide Web","score_opus":0.012476102012716572,"score_gpt":0.27649429773716305,"score_spread":0.26401819572444646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W118734219","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023862962,0.00007205187,0.90780693,0.005461572,0.00004598303,0.000021433305,0.0000012156063,0.00012663104,0.0840779],"genre_scores_gemma":[0.6707816,0.00017425772,0.29157594,0.010187574,0.00016054283,0.0000016153098,0.000007856188,0.0000060199623,0.02710458],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99969894,0.0000073609076,0.00005719938,0.00009880038,0.00006980623,0.00006791656],"domain_scores_gemma":[0.999782,0.000013134495,0.0000098863875,0.00014025022,0.000012382721,0.00004229393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000053661595,0.0000329153,0.000035009863,0.00004169676,0.00003978307,0.00012196225,0.0001721601,0.000009535588,0.00005317671],"category_scores_gemma":[0.000007879401,0.000026452215,0.0000074127265,0.000116418116,0.000020339969,0.00033274209,0.00011786191,0.000019471745,0.000056080207],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.2812276e-7,0.000009952099,0.0002726571,0.0000011680015,0.0000017670761,4.358598e-7,0.0001365462,0.000006449038,0.000024269071,0.9043577,0.011154289,0.084034696],"study_design_scores_gemma":[0.00021311115,0.000026139363,0.0017014658,0.000003271474,0.0000022512293,0.000009848365,0.000028351438,0.39996606,0.0010383959,0.015434997,0.5814268,0.00014933091],"about_ca_topic_score_codex":0.000002225525,"about_ca_topic_score_gemma":0.000010388495,"teacher_disagreement_score":0.88892263,"about_ca_system_score_codex":0.0000028035088,"about_ca_system_score_gemma":0.000008565885,"threshold_uncertainty_score":0.11760847},"labels":[],"label_agreement":null},{"id":"W1196342823","doi":"10.11575/prism/30494","title":"ChatVis: A visualization Tool for Instant Messaging","year":2008,"lang":"en","type":"article","venue":"Open MIND","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Conversation; Instant messaging; Zoom; Visualization; Variety (cybernetics); XML; Animation; Human–computer interaction; Instant; Multimedia; World Wide Web; Artificial intelligence; Computer graphics (images); Communication; Engineering","score_opus":0.08014841260602265,"score_gpt":0.36682926881248273,"score_spread":0.2866808562064601,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1196342823","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010686742,0.00001562088,0.9781299,0.0002448941,0.000061637336,0.00029816333,0.000013944186,0.000008099166,0.01054098],"genre_scores_gemma":[0.89115757,0.000041052524,0.1013025,0.00067315716,0.00003841053,0.000028850396,0.000121239114,0.000015057397,0.006622174],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99926275,0.000022236089,0.00017901136,0.00025518757,0.00013984254,0.00014098072],"domain_scores_gemma":[0.99949557,0.000026685817,0.000075103504,0.0002861167,0.00007369382,0.000042833013],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023181537,0.00007279943,0.000103241924,0.00006221892,0.0001842664,0.00032990763,0.0007562896,0.000025285592,0.00009399122],"category_scores_gemma":[0.00005168895,0.000068848,0.000026290125,0.00030778305,0.000018615316,0.0009472833,0.00028186716,0.000022202492,0.00009968844],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000414995,0.00065309164,0.0033029558,0.000044403223,0.00009745829,0.00006670883,0.008598847,0.00032358244,0.0023322639,0.5619069,0.016263062,0.40636927],"study_design_scores_gemma":[0.0008070665,0.00006625549,0.0004339134,0.00003545066,0.000008327844,0.000020575642,0.00008015378,0.20100658,0.008805417,0.00037683803,0.7881011,0.00025832176],"about_ca_topic_score_codex":0.000002903845,"about_ca_topic_score_gemma":0.000003024686,"teacher_disagreement_score":0.8804708,"about_ca_system_score_codex":0.000018675233,"about_ca_system_score_gemma":0.00008390489,"threshold_uncertainty_score":0.3181307},"labels":[],"label_agreement":null},{"id":"W12123458","doi":"10.1046/j.1365-2958.2002.03025.x","title":"Recommender narrative visualization","year":2013,"lang":"en","type":"article","venue":"Molecular Microbiology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Visualization; Presentation (obstetrics); Data visualization; Focus (optics); Recommender system; Narrative; Information visualization; Data science; Maturity (psychological); World Wide Web; Human–computer interaction; Data mining","score_opus":0.010914461669735547,"score_gpt":0.2731365306258255,"score_spread":0.26222206895608996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W12123458","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008392278,0.000055437795,0.9881249,0.0016017372,0.00017523207,0.00012473878,0.0000029275966,0.00010849379,0.0014142641],"genre_scores_gemma":[0.9649927,0.00001812002,0.019264743,0.014377841,0.000027072649,0.000025839885,0.00032395686,0.000017389075,0.000952351],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992463,0.00012906139,0.00015780157,0.00025532104,0.000031319687,0.00018022413],"domain_scores_gemma":[0.99947405,0.000015371457,0.00006107444,0.00029268928,0.000110923036,0.00004592002],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007378887,0.00009402034,0.00010334951,0.000083801824,0.0000643504,0.00009303201,0.00040286573,0.00006818188,0.00030180966],"category_scores_gemma":[0.00002882077,0.00008579536,0.000035365705,0.00026034596,0.000036133082,0.00021680955,0.00016775602,0.000050052393,0.00051517243],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.0008724e-7,0.000075168566,0.000100835845,0.0000055971163,0.000038233997,0.0000076009737,0.0010624515,0.00003222747,0.6966902,0.23546338,0.06281599,0.003707603],"study_design_scores_gemma":[0.0015765922,0.00038163355,0.00035226514,0.00003333799,0.000022714816,0.00021737978,0.00063216256,0.09752622,0.32647803,0.019281982,0.55220497,0.0012926934],"about_ca_topic_score_codex":0.000012039324,"about_ca_topic_score_gemma":0.0000014649263,"teacher_disagreement_score":0.96886015,"about_ca_system_score_codex":0.000019070118,"about_ca_system_score_gemma":0.000021104886,"threshold_uncertainty_score":0.6621671},"labels":[],"label_agreement":null},{"id":"W139043267","doi":"10.17705/1thci.00055","title":"Interaction Design for Complex Cognitive Activities with Visual Representations: A Pattern-Based Approach","year":2013,"lang":"en","type":"article","venue":"AIS Transactions on Human-Computer Interaction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":144,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Visual analytics; Visualization; Human–computer interaction; Data science; Information visualization; Cognition; Creativity; Action (physics); Knowledge management; Artificial intelligence; Psychology","score_opus":0.10688321322544632,"score_gpt":0.37379170870414813,"score_spread":0.2669084954787018,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W139043267","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0030892522,0.0000020341104,0.99406147,0.0003364747,0.00043934907,0.0012711503,0.00002761453,0.00040077302,0.0003718738],"genre_scores_gemma":[0.9188881,0.000002448878,0.07836551,0.0012294365,0.00014533733,0.00081665,0.00029419063,0.00004231411,0.00021598948],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977568,0.0002416256,0.00048132066,0.0007917058,0.00038232357,0.00034624012],"domain_scores_gemma":[0.9980404,0.0007015738,0.00029937545,0.00043078815,0.0004008463,0.00012705903],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016956875,0.0003575779,0.0003006917,0.0006250258,0.00060905627,0.0010031488,0.00039990406,0.00009534338,0.00026315122],"category_scores_gemma":[0.000009645853,0.00033255457,0.00018034557,0.00045645685,0.00008490685,0.002866919,0.000013779049,0.00030685376,0.000093691],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005695502,0.00653639,0.00015932918,0.00030726296,0.0010456436,0.0000114822515,0.004472617,0.3793041,0.0032556062,0.0022654019,0.011504395,0.5905682],"study_design_scores_gemma":[0.0014605464,0.0011294717,0.00051971205,0.00014258036,0.0000674457,0.000029555313,0.00074030017,0.9883615,0.006386759,0.000115641655,0.00063552754,0.00041097024],"about_ca_topic_score_codex":0.00017047075,"about_ca_topic_score_gemma":0.00002766603,"teacher_disagreement_score":0.91579884,"about_ca_system_score_codex":0.00016040938,"about_ca_system_score_gemma":0.00006201149,"threshold_uncertainty_score":0.9999126},"labels":[],"label_agreement":null},{"id":"W1408912568","doi":"10.1016/j.ifacol.2015.06.067","title":"A Visual and Results-Driven Rules Composition Approach for Better Information Extraction","year":2015,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Computer science; Precision and recall; Information extraction; Process (computing); Artificial intelligence; Recall; Data mining; Extraction (chemistry); Pattern recognition (psychology); Machine learning; Natural language processing","score_opus":0.034894436509985215,"score_gpt":0.31831334752146667,"score_spread":0.2834189110114815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1408912568","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013063666,0.00001661213,0.9837876,0.0018487795,0.0001143992,0.00020700216,0.00014003085,0.00012077182,0.0007011454],"genre_scores_gemma":[0.039623555,0.000012899105,0.9560691,0.0013345887,0.00016574867,0.000014629548,0.002677937,0.000006644227,0.00009487823],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99911714,0.00003214043,0.00029279958,0.00019229502,0.00022138937,0.00014425289],"domain_scores_gemma":[0.9993666,0.000039258644,0.00015016615,0.00016421362,0.00016986975,0.00010990805],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023934379,0.00010779915,0.0001158208,0.00011089305,0.00009509653,0.00025927598,0.00017132521,0.0000646412,0.0000012678258],"category_scores_gemma":[0.00007050455,0.00009821312,0.00003156147,0.00014776144,0.000029609952,0.0017233575,0.00006982134,0.000065703745,0.00002034657],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013956978,0.0030882,0.002117683,0.00077745086,0.00039870277,0.000016921145,0.03073091,0.012771135,0.020762747,0.119211696,0.012114482,0.79661435],"study_design_scores_gemma":[0.0013729802,0.00013159054,0.00042116822,0.000011328129,0.000013235387,0.000015293066,0.00020946877,0.988192,0.00025589459,0.0001407691,0.009088482,0.00014776271],"about_ca_topic_score_codex":0.000011756884,"about_ca_topic_score_gemma":0.0000022391778,"teacher_disagreement_score":0.9754209,"about_ca_system_score_codex":0.000037627335,"about_ca_system_score_gemma":0.00003756591,"threshold_uncertainty_score":0.4005015},"labels":[],"label_agreement":null},{"id":"W143101661","doi":"","title":"A Mandala Browser User Study: Visualizing XML Versions of Shakespeare's Plays","year":2009,"lang":"en","type":"article","venue":"Visible Language","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Mandala; Computer science; World Wide Web; Venn diagram; Information retrieval; Interface (matter); User interface; Human–computer interaction; Multimedia; Psychology","score_opus":0.01590518737692463,"score_gpt":0.31929758422131543,"score_spread":0.3033923968443908,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W143101661","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6825657,0.0003079298,0.29943892,0.0007546628,0.00030574505,0.00054736657,0.00007256801,0.0005684107,0.015438719],"genre_scores_gemma":[0.9942716,0.000008250228,0.0035575372,0.0007444719,0.00004633896,0.0000015786412,0.00002228236,0.000009125987,0.0013388135],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988197,0.00006425095,0.00024685712,0.00029283884,0.00035023433,0.00022609076],"domain_scores_gemma":[0.99907863,0.000042307976,0.000096037176,0.000614613,0.00007314508,0.00009526896],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024236416,0.00012466541,0.00019196453,0.00020950938,0.00008819923,0.00013854456,0.0007071536,0.00004171972,0.00012384389],"category_scores_gemma":[0.00006232308,0.00011313569,0.00006411541,0.000757691,0.000017669156,0.0004304442,0.00018010398,0.00008381837,0.000055815188],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001211081,0.008713775,0.038462207,0.00024651256,0.00044663006,0.001365653,0.1116563,0.0013355446,0.0754367,0.60375714,0.08836213,0.07009633],"study_design_scores_gemma":[0.02068815,0.0087916795,0.26890868,0.0012083389,0.00051458547,0.00014276414,0.055234686,0.41303965,0.10015184,0.0033600458,0.12260132,0.005358272],"about_ca_topic_score_codex":0.00006001622,"about_ca_topic_score_gemma":0.000022152311,"teacher_disagreement_score":0.60039705,"about_ca_system_score_codex":0.00002086161,"about_ca_system_score_gemma":0.000042701795,"threshold_uncertainty_score":0.46135396},"labels":[],"label_agreement":null},{"id":"W1456458654","doi":"10.1007/978-3-540-89682-1_3","title":"Procedural Natural Phenomena from Least-Cost Paths in a Weighted Graph","year":2008,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Graph; Computer science; Lattice (music); Generator (circuit theory); Process (computing); Path (computing); Topology (electrical circuits); Algorithm; Theoretical computer science; Combinatorics; Mathematics; Physics; Programming language","score_opus":0.03366037246700519,"score_gpt":0.2894592462549842,"score_spread":0.255798873787979,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1456458654","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00040196185,0.0024802284,0.76005745,0.0034593446,0.001358578,0.0016786816,0.0002013963,0.0004062875,0.22995608],"genre_scores_gemma":[0.3959567,0.0533053,0.51558334,0.022296213,0.00038731218,0.00023357896,0.004203235,0.000086033804,0.007948296],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998037,0.000033604516,0.0007992855,0.0003517603,0.0005108579,0.00026753504],"domain_scores_gemma":[0.9973618,0.000113960006,0.000342697,0.0017490446,0.0003202442,0.00011229849],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004391365,0.00024998962,0.00028416867,0.0014079249,0.00035522913,0.0006145099,0.0037300878,0.000105194726,0.000008773615],"category_scores_gemma":[0.00003632167,0.00024552233,0.00004623795,0.0009769412,0.0006992158,0.007842627,0.0020652902,0.0004942086,0.00006692177],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005144757,0.0000721164,0.00024869194,0.000031161737,0.000011623368,0.0000030023443,0.008195121,0.0001593618,0.0000032524936,0.63462234,0.0025085132,0.3541397],"study_design_scores_gemma":[0.00045772965,0.000021624805,0.0018693422,0.00020798825,0.0000029350672,0.000016193111,0.000029441293,0.8139742,0.000004108934,0.0049512507,0.17809087,0.00037429432],"about_ca_topic_score_codex":0.000039996463,"about_ca_topic_score_gemma":0.000055238666,"teacher_disagreement_score":0.8138149,"about_ca_system_score_codex":0.00015372856,"about_ca_system_score_gemma":0.00037186858,"threshold_uncertainty_score":0.9999997},"labels":[],"label_agreement":null},{"id":"W146143225","doi":"","title":"Guiding multidimensional analysis using decision trees","year":2013,"lang":"en","type":"article","venue":"Conference of the Centre for Advanced Studies on Collaborative Research","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Computer science; Decision tree; Visualization; Curse of dimensionality; Process (computing); Data mining; Set (abstract data type); Feature (linguistics); Machine learning; Tree (set theory); Data visualization; Artificial intelligence; Mathematics","score_opus":0.21199718185188554,"score_gpt":0.4624321178283322,"score_spread":0.25043493597644667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W146143225","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3013673,0.0010663684,0.68580854,0.00692592,0.0008896131,0.0030071405,0.0002754543,0.0000798546,0.0005797665],"genre_scores_gemma":[0.934115,0.00023747727,0.064631,0.000060471928,0.000021533437,0.000037758833,0.0000067855744,0.000008686526,0.0008813233],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977836,0.0002861368,0.00036397504,0.0004225967,0.0007909945,0.00035272175],"domain_scores_gemma":[0.990788,0.0014903991,0.00020568399,0.00061696314,0.006816479,0.000082520055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007189817,0.00014766098,0.0003557739,0.00033854818,0.0006037314,0.00012639079,0.00087018224,0.00003675655,0.000021972251],"category_scores_gemma":[0.0031954804,0.000094856725,0.000119694436,0.0037452097,0.00028149024,0.00043885075,0.0007049723,0.000091574955,0.000010012534],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022948101,0.00069219293,0.003240692,0.00012772589,0.002770124,0.000003313348,0.010701843,0.11159437,0.06189081,0.740575,0.017794605,0.05037984],"study_design_scores_gemma":[0.0010845565,0.00021914816,0.0008430607,0.00037412622,0.000080419595,2.4152783e-7,0.0137545355,0.90663135,0.059002794,0.013249105,0.0044711335,0.00028950005],"about_ca_topic_score_codex":0.000007821586,"about_ca_topic_score_gemma":0.00010695062,"teacher_disagreement_score":0.79503703,"about_ca_system_score_codex":0.00014292741,"about_ca_system_score_gemma":0.00024993665,"threshold_uncertainty_score":0.46434745},"labels":[],"label_agreement":null},{"id":"W1480851260","doi":"10.1109/gem.2014.7048110","title":"Scale effects in &amp;#x0022;bullet hell&amp;#x0022; games","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Scaling; Silver bullet; Computer science; Scale (ratio); Materials science; Physics; Metallurgy; Mathematics","score_opus":0.016175091886931153,"score_gpt":0.2866721009601315,"score_spread":0.27049700907320035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1480851260","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008633942,0.000044312827,0.97472143,0.0012191655,0.0003125164,0.00012939303,0.0000026162054,0.0002631991,0.014673444],"genre_scores_gemma":[0.4431122,0.00020229068,0.39743903,0.022442795,0.0005378357,0.000056170284,0.00021690095,0.00009203649,0.13590074],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984647,0.0001627134,0.00028108156,0.00045735962,0.00028055857,0.0003536001],"domain_scores_gemma":[0.9986831,0.00020198278,0.00006745056,0.0008338947,0.00005817638,0.00015542514],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00049135194,0.00017472972,0.00023993483,0.0002103301,0.00007310868,0.00026598774,0.0008839774,0.000074934345,0.00022929806],"category_scores_gemma":[0.00019252452,0.0001362008,0.00006293319,0.00067246094,0.000046518217,0.0003531426,0.00035339472,0.00011997011,0.0018199343],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013753024,0.0009387482,0.019314123,0.00029384185,0.000047745652,0.000010745096,0.0020461013,0.00047308995,0.003310616,0.46661878,0.29934302,0.20758945],"study_design_scores_gemma":[0.0006393882,0.00005245623,0.002127313,0.000055828903,0.0000059462377,0.000007666166,0.000010708063,0.036650717,0.0014774078,0.005655017,0.9529568,0.00036076602],"about_ca_topic_score_codex":0.00008585781,"about_ca_topic_score_gemma":0.00054176454,"teacher_disagreement_score":0.65361375,"about_ca_system_score_codex":0.000028550447,"about_ca_system_score_gemma":0.00003246764,"threshold_uncertainty_score":0.9989573},"labels":[],"label_agreement":null},{"id":"W1481798173","doi":"10.1007/978-3-540-78243-8_7","title":"NetBytes Viewer: An Entity-Based NetFlow Visualization Utility for Identifying Intrusive Behavior","year":2008,"lang":"en","type":"book-chapter","venue":"Mathematics and visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Byte; Visualization; NetFlow; Subnet; Graph; Data mining; Computer network; Theoretical computer science; Operating system","score_opus":0.08392167241934823,"score_gpt":0.35973022857721704,"score_spread":0.2758085561578688,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1481798173","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000119815406,0.00032775704,0.9956151,0.000026165588,0.00039891168,0.0010953643,0.00014819736,0.00029007782,0.0019786085],"genre_scores_gemma":[0.04286063,0.018106295,0.73014545,0.0070171077,0.0033567706,0.0014126869,0.055176433,0.0021191617,0.13980545],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972364,0.00004617981,0.0010214942,0.00079155003,0.0006008029,0.0003035762],"domain_scores_gemma":[0.9973177,0.0001332831,0.00087222306,0.0007943269,0.00068624807,0.00019622657],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00053154706,0.00050665933,0.0006070407,0.00044336106,0.0004741958,0.00073991594,0.00058350706,0.0003689072,0.00011136799],"category_scores_gemma":[0.00016181117,0.00053059927,0.00016582987,0.00020437679,0.00012124327,0.0008026539,0.00021186285,0.00012254083,0.00001926327],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005568469,0.0003338808,0.0000604662,0.0008865617,0.000046844478,0.00000559289,0.0010575367,0.000028703666,0.000050131184,0.98845804,0.0032445283,0.005822131],"study_design_scores_gemma":[0.00060969865,0.00020263164,0.000042363223,0.00038716852,0.0002301807,0.0000122955325,0.0000338606,0.9189199,0.00038178754,0.020712629,0.057723332,0.0007441027],"about_ca_topic_score_codex":0.000006210596,"about_ca_topic_score_gemma":0.000021752732,"teacher_disagreement_score":0.9677454,"about_ca_system_score_codex":0.00006682833,"about_ca_system_score_gemma":0.00015486564,"threshold_uncertainty_score":0.99971455},"labels":[],"label_agreement":null},{"id":"W1485616050","doi":"10.1002/asi.23002","title":"Adjustable properties of visual representations: Improving the quality of human‐information interaction","year":2014,"lang":"en","type":"article","venue":"Journal of the Association for Information Science and Technology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Visual analytics; Computer science; Human–computer interaction; Situated; Visualization; Cognition; Quality (philosophy); Mediation; Analytics; Analytic reasoning; Data science; Artificial intelligence; Psychology","score_opus":0.028974477069423226,"score_gpt":0.34137986371083723,"score_spread":0.312405386641414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1485616050","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.57345647,0.000037992402,0.41205266,0.011066594,0.0010629168,0.0006514516,0.000017549348,0.000056977122,0.0015973803],"genre_scores_gemma":[0.9991159,0.00000952288,0.0006759469,0.00015672053,0.0000118508815,0.0000032327348,0.0000014638459,8.23716e-7,0.000024558234],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99836135,0.000048783084,0.0008242557,0.000043471002,0.0006269529,0.000095189935],"domain_scores_gemma":[0.9937873,0.000102936785,0.0029339665,0.00019379886,0.0029657478,0.000016258247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0045217127,0.00004622213,0.00013025745,0.00047394863,0.00030367705,0.00016410134,0.00067722535,0.00005180692,5.522091e-7],"category_scores_gemma":[0.0059132883,0.00002711217,0.000044656485,0.0012212571,0.00015692606,0.006780776,0.00016737699,0.00009651757,8.349378e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023498758,0.00007503628,0.010768138,0.00018068496,0.000047732705,6.5460743e-9,0.004968785,0.0005919065,0.046118747,0.86258835,0.0011664674,0.07347066],"study_design_scores_gemma":[0.0028238387,0.0008596238,0.028911509,0.00023418939,0.00009751408,0.000024780995,0.017274382,0.36028367,0.54024893,0.02034036,0.02856802,0.00033319904],"about_ca_topic_score_codex":0.000017437851,"about_ca_topic_score_gemma":0.000003400976,"teacher_disagreement_score":0.84224796,"about_ca_system_score_codex":0.000098744335,"about_ca_system_score_gemma":0.00016151757,"threshold_uncertainty_score":0.7079186},"labels":[],"label_agreement":null},{"id":"W148815022","doi":"10.1007/978-3-319-51966-1_8","title":"Towards Metric-Driven, Application-Specific Visualization of Attack Graphs","year":2016,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Visualization; Scalability; Situation awareness; Information visualization; Graph drawing; Graph; Metric (unit); Theoretical computer science; Vulnerability (computing); Network security; Data mining; Computer security","score_opus":0.02985442333875248,"score_gpt":0.3053683455029229,"score_spread":0.2755139221641704,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W148815022","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000007998143,0.00032150393,0.99355537,0.00027732138,0.0007044697,0.00030414958,0.000023917366,0.00012889362,0.004676406],"genre_scores_gemma":[0.35677814,0.0020053976,0.6359215,0.0026714262,0.00088554685,0.00003261485,0.00014139176,0.0001540004,0.0014099779],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9963496,0.00003605165,0.0007361324,0.0012522861,0.001220805,0.00040513184],"domain_scores_gemma":[0.99683446,0.00024762552,0.00058209157,0.001541323,0.0006404377,0.00015406134],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006024559,0.00040395962,0.00051243516,0.0017108533,0.00014508258,0.0002915997,0.0032982975,0.00025217945,0.000035874906],"category_scores_gemma":[0.00007813012,0.00033614988,0.00014544796,0.0020517842,0.0005860473,0.0006727159,0.0009401977,0.00021772861,0.00006697835],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016953173,0.000032437943,0.000074251264,0.000029876737,0.000009697549,0.0000042012543,0.00014759612,0.0031395247,0.0001528825,0.58085185,0.00010777043,0.4154482],"study_design_scores_gemma":[0.00054217316,0.00019653875,0.00022042177,0.0005056604,0.000016455064,0.00002042637,2.156705e-7,0.72206163,0.004298147,0.23550591,0.035590895,0.0010415372],"about_ca_topic_score_codex":0.000004786656,"about_ca_topic_score_gemma":0.00001106188,"teacher_disagreement_score":0.7189221,"about_ca_system_score_codex":0.00017946972,"about_ca_system_score_gemma":0.00036902883,"threshold_uncertainty_score":0.99990904},"labels":[],"label_agreement":null},{"id":"W1489992831","doi":"10.1016/j.neunet.2007.12.030","title":"An axiomatic approach to intrinsic dimension of a dataset","year":2007,"lang":"en","type":"article","venue":"Neural Networks","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":42,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; University of Ottawa","keywords":"Intrinsic dimension; Dimension (graph theory); Curse of dimensionality; Axiomatic system; Manifold (fluid mechanics); Axiom; Mathematics; Computer science; Sample (material); Artificial intelligence; Algorithm; Pure mathematics; Geometry","score_opus":0.025466014181499002,"score_gpt":0.3026456454636503,"score_spread":0.2771796312821513,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1489992831","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017271223,0.000018025305,0.98211837,0.00005403263,0.00014716806,0.00009783669,0.000018453145,0.000056648012,0.00021825144],"genre_scores_gemma":[0.97935814,0.0000023775071,0.018621614,0.0014279318,0.000071384,9.767502e-7,0.00050140504,0.000005768491,0.000010429043],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99912125,0.00003826664,0.00022830078,0.00022869921,0.00018582711,0.0001976356],"domain_scores_gemma":[0.9991192,0.00003764368,0.00006819496,0.0005912751,0.000037376103,0.00014626223],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003168357,0.00008158923,0.00011986129,0.00009233688,0.000043213637,0.000061380684,0.000595084,0.000036648093,0.0000029895602],"category_scores_gemma":[0.000016774347,0.000069975504,0.000019391015,0.0006349845,0.000019448753,0.00031701673,0.00018478151,0.000066055436,0.000007345815],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006997092,0.0014041944,0.0023796214,0.00009892318,0.000044536577,0.000054107408,0.0012268642,0.25445613,0.0015932787,0.19873872,0.100305215,0.43962842],"study_design_scores_gemma":[0.0001092403,0.00008080925,0.0014771031,0.000007178461,0.0000039924007,0.0000072806292,0.000013300708,0.99686486,0.00012931258,0.000054133216,0.0011662134,0.000086580854],"about_ca_topic_score_codex":0.000009934784,"about_ca_topic_score_gemma":0.000005530069,"teacher_disagreement_score":0.96349674,"about_ca_system_score_codex":0.000008193493,"about_ca_system_score_gemma":0.000006460645,"threshold_uncertainty_score":0.2853518},"labels":[],"label_agreement":null},{"id":"W1496305014","doi":"10.1007/3-540-45486-1_18","title":"CViz: An Interactive Visualization System for Rule Induction","year":2000,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Visualization; Computer graphics (images); Artificial intelligence","score_opus":0.02490884525193125,"score_gpt":0.30734135595722434,"score_spread":0.28243251070529307,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1496305014","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000051807572,0.000043176,0.99531966,0.00010908948,0.00177579,0.00044593232,0.000025489693,0.0002880524,0.0019409885],"genre_scores_gemma":[0.46518505,0.00010416612,0.52643603,0.0032343357,0.0028576574,0.00006999433,0.00065741385,0.00018526451,0.0012700892],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99708724,0.000046124398,0.0005160035,0.0012956905,0.0006496419,0.00040527302],"domain_scores_gemma":[0.9979923,0.00016605969,0.0003337239,0.000973129,0.0003775925,0.00015719059],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005996281,0.00039040504,0.0003933995,0.0009033407,0.00029306693,0.00088897074,0.0019515032,0.00026903604,0.000021419859],"category_scores_gemma":[0.000052970907,0.0003777251,0.00009602601,0.00061784923,0.00021981612,0.0017648259,0.00034908153,0.00029476197,0.000039410428],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021743788,0.000073603704,0.000010211147,0.00009783008,0.000018278577,0.000013863588,0.0012612523,0.023802705,0.00012580871,0.22592585,0.000048329446,0.74860054],"study_design_scores_gemma":[0.000270299,0.00025886498,0.000016380207,0.00036205575,0.000012473889,0.00003995916,0.0000012477378,0.9482714,0.0014314762,0.04486998,0.0039710575,0.0004947913],"about_ca_topic_score_codex":0.000015852565,"about_ca_topic_score_gemma":0.000028438111,"teacher_disagreement_score":0.9244687,"about_ca_system_score_codex":0.00040998077,"about_ca_system_score_gemma":0.00035323558,"threshold_uncertainty_score":0.99986744},"labels":[],"label_agreement":null},{"id":"W1499478300","doi":"","title":"A case for iconic icons","year":2006,"lang":"en","type":"article","venue":"Australasian User Interface Conference","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Icon; USable; Computer science; Human–computer interaction; Creativity; Representation (politics); User interface; Interface (matter); World Wide Web; Multimedia; Programming language; Psychology","score_opus":0.050386488979059785,"score_gpt":0.32716867465445115,"score_spread":0.27678218567539137,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1499478300","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028431846,0.000014802618,0.9664362,0.0013926396,0.00024791824,0.00022864419,0.000047797093,0.00021338055,0.002986738],"genre_scores_gemma":[0.9791171,0.0000024486865,0.012612798,0.00016610343,0.000048904505,0.000021511201,0.00001865731,0.000011723336,0.00800075],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987664,0.000031112926,0.00029991567,0.00042628456,0.00012267081,0.00035357487],"domain_scores_gemma":[0.9990451,0.00006313577,0.00010239893,0.0005600246,0.00012719416,0.0001021579],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000119225115,0.00017779386,0.00016960556,0.000095686635,0.00011529623,0.0005199546,0.00077386014,0.000073691364,0.00011164256],"category_scores_gemma":[0.000036096484,0.00017366678,0.00007370129,0.0002324857,0.00007459689,0.0005758838,0.00014889303,0.00010551089,0.00014443585],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007039259,0.00017706597,0.0012749336,0.00004512393,0.000037193797,0.0003221763,0.00042171913,0.00014532439,0.002029121,0.9409833,0.049729202,0.004827812],"study_design_scores_gemma":[0.003982908,0.0007786621,0.0020398153,0.00028766878,0.00013486895,0.005214087,0.001099376,0.39647847,0.09017551,0.036539994,0.46083868,0.0024299817],"about_ca_topic_score_codex":0.000088751825,"about_ca_topic_score_gemma":0.00023680025,"teacher_disagreement_score":0.95382345,"about_ca_system_score_codex":0.000031206204,"about_ca_system_score_gemma":0.000111914254,"threshold_uncertainty_score":0.7081926},"labels":[],"label_agreement":null},{"id":"W1504007998","doi":"10.2312/vissym/eurovis07/043-050","title":"KeyStrokes: Personalizing Typed Text with Visualization","year":2007,"lang":"en","type":"article","venue":"Eurographics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Visualization; Computer science; Handwriting; Style (visual arts); Human–computer interaction; Information visualization; Data visualization; World Wide Web; Artificial intelligence","score_opus":0.019268035940394238,"score_gpt":0.2909504516757582,"score_spread":0.271682415735364,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1504007998","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006702815,0.00005259816,0.9868619,0.00014600957,0.00010856182,0.00006661371,0.0000019512104,0.00027001652,0.0057895677],"genre_scores_gemma":[0.94124824,0.000075084565,0.056164287,0.0017575056,0.00012885268,0.0000019613242,0.000056261088,0.000032588174,0.00053519226],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989507,0.00003286372,0.00017126801,0.00025626904,0.00035079935,0.00023810813],"domain_scores_gemma":[0.99928075,0.00005030781,0.00008646061,0.0003086689,0.00016885456,0.000104962106],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003965372,0.000111325695,0.000089860514,0.0002470333,0.00013159667,0.00022059357,0.00039596637,0.000039907754,0.000016207028],"category_scores_gemma":[0.000040185554,0.00009591292,0.00004040861,0.0015817574,0.000064689724,0.0004091961,0.00006477584,0.00008272925,0.00004173891],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000105467725,0.00012531847,0.015059919,0.00002386399,0.000036956688,0.00004832501,0.0010522706,0.000016772832,0.0004054163,0.9758693,0.0016208327,0.0057304935],"study_design_scores_gemma":[0.0031268916,0.0013549066,0.04819405,0.00026416997,0.00012748763,0.0002129223,0.0022206244,0.24002647,0.004785261,0.0024214808,0.69518316,0.0020825707],"about_ca_topic_score_codex":0.0000050264007,"about_ca_topic_score_gemma":0.000021181168,"teacher_disagreement_score":0.9734478,"about_ca_system_score_codex":0.000010137683,"about_ca_system_score_gemma":0.000033210457,"threshold_uncertainty_score":0.39112154},"labels":[],"label_agreement":null},{"id":"W1512734143","doi":"10.1108/rmj-01-2014-0009","title":"Meeting Big Data challenges with visual analytics","year":2014,"lang":"en","type":"article","venue":"Records Management Journal","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Data science; Big data; Context (archaeology); Visual analytics; Data management; Computer science; Exploratory research; Analytics; Visualization; Knowledge management; Data mining; Geography","score_opus":0.07964229327395393,"score_gpt":0.3131988829620281,"score_spread":0.23355658968807413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1512734143","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00023154974,0.0001303164,0.9536511,0.0016350937,0.0005812351,0.000058327227,0.0000018402684,0.000085695705,0.043624863],"genre_scores_gemma":[0.58218664,0.021809835,0.37768114,0.004057984,0.0048720473,0.0000073631636,0.00014346684,0.00012825422,0.009113278],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998308,0.00012512012,0.0003162248,0.0003937382,0.0005490527,0.0003078342],"domain_scores_gemma":[0.9985165,0.000049355334,0.00025892846,0.0009224593,0.00009408625,0.0001586593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014720903,0.00015391878,0.00017644433,0.00027708372,0.00022191249,0.00064923783,0.0019919567,0.000027858221,0.000017306344],"category_scores_gemma":[0.000051890387,0.00012038636,0.00003417933,0.00041352116,0.000027252792,0.00069336785,0.0009506811,0.00016732841,0.000051327683],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005959846,0.0001594899,0.0005681589,0.000059854923,0.00019453782,0.00008812938,0.000081924154,0.00027219323,0.0000016615587,0.08030148,0.0081882905,0.91007835],"study_design_scores_gemma":[0.0006420192,0.00020901291,0.00073596515,0.00015728714,0.00007893979,0.000109536144,0.00023164859,0.6172676,0.000009444653,0.0028401674,0.37741953,0.0002988288],"about_ca_topic_score_codex":0.0000027889548,"about_ca_topic_score_gemma":0.000027265673,"teacher_disagreement_score":0.9097795,"about_ca_system_score_codex":0.00003155699,"about_ca_system_score_gemma":0.000027879458,"threshold_uncertainty_score":0.6260615},"labels":[],"label_agreement":null},{"id":"W1515744550","doi":"10.1007/978-3-540-24595-7_31","title":"Fixed Parameter Algorithms for one-sided crossing minimization Revisited","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Minification; Graph; Algebraic number; Combinatorics; Mathematics; Algorithm; Vertex (graph theory); Discrete mathematics; Computer science; Mathematical optimization","score_opus":0.04726902589280202,"score_gpt":0.3136463611387548,"score_spread":0.2663773352459528,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1515744550","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000008818854,0.00014008864,0.99719685,0.0006348676,0.00084986974,0.00055476616,0.00003251163,0.00018968574,0.0003925559],"genre_scores_gemma":[0.008062063,0.000035950867,0.98755825,0.003257213,0.00042784555,0.00001136108,0.00014424027,0.000046612724,0.0004564545],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9963625,0.000027978956,0.00069291453,0.001498113,0.0008286646,0.0005898179],"domain_scores_gemma":[0.9970821,0.0006036121,0.0004255801,0.0012285516,0.00048689113,0.00017327834],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0006497361,0.00047011083,0.000555449,0.00079302,0.0004727423,0.0022886673,0.0023286694,0.00031972927,0.000028804941],"category_scores_gemma":[0.00050259987,0.00046254028,0.00016642951,0.0008418828,0.00057841785,0.0008968658,0.0006912206,0.00035553283,0.00002236961],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012117617,0.00009937707,0.00002749718,0.00018349968,0.00003826263,0.000034041044,0.0011812502,0.06916407,0.00015206469,0.1259371,0.00016115444,0.80300957],"study_design_scores_gemma":[0.00049385265,0.00011208832,0.000026083633,0.0007416822,0.000016872329,0.000012196198,9.969127e-8,0.84011215,0.0011873578,0.15450405,0.002217809,0.00057573715],"about_ca_topic_score_codex":0.000008837408,"about_ca_topic_score_gemma":0.000011453755,"teacher_disagreement_score":0.80243385,"about_ca_system_score_codex":0.00032769734,"about_ca_system_score_gemma":0.00081988564,"threshold_uncertainty_score":0.9997826},"labels":[],"label_agreement":null},{"id":"W1516174417","doi":"10.2312/compaesth/compaesth07/057-064","title":"The Aesthetics of Graph Visualization","year":2007,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":105,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Heuristics; Computer science; Gestalt psychology; Visualization; Graph drawing; Readability; Graph; Perception; Theoretical computer science; Variety (cybernetics); Artificial intelligence; Human–computer interaction; Psychology; Programming language","score_opus":0.017599704664504938,"score_gpt":0.3129092007925621,"score_spread":0.2953094961280572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1516174417","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006297962,0.00002357163,0.99153924,0.00021220683,0.000088227585,0.000026456384,3.1284983e-7,0.000044978544,0.0074351844],"genre_scores_gemma":[0.98282033,0.00015478206,0.014202512,0.0007869919,0.000023442803,5.0457834e-7,0.000006962761,0.0000060836496,0.001998412],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99950004,0.000013634579,0.00016126543,0.000070944254,0.00016326833,0.00009086535],"domain_scores_gemma":[0.9995108,0.00005419395,0.000057780835,0.00025605565,0.0000931313,0.000028022656],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045940324,0.000033679626,0.000036744575,0.00004699443,0.00007386032,0.00005424353,0.00038891216,0.000015603064,0.0000052007754],"category_scores_gemma":[0.000031992542,0.000021171962,0.000021546155,0.0004608459,0.000038438422,0.00011229205,0.00006435095,0.000016119626,0.000010066666],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.2963617e-7,0.0000146265,0.0003120942,0.0000011086585,0.0000017632435,2.6679774e-7,0.000062076084,0.00000888419,0.00006199984,0.98618925,0.0014007534,0.011946731],"study_design_scores_gemma":[0.0006234073,0.00022226264,0.00649457,0.000024074108,0.000014983968,0.000015037597,0.0005171163,0.40819514,0.05927278,0.07272741,0.45148486,0.0004083728],"about_ca_topic_score_codex":0.000003758637,"about_ca_topic_score_gemma":0.000015693118,"teacher_disagreement_score":0.9821905,"about_ca_system_score_codex":0.000003661494,"about_ca_system_score_gemma":0.000013373307,"threshold_uncertainty_score":0.086336754},"labels":[],"label_agreement":null},{"id":"W1516668301","doi":"10.1109/vlhcc.2004.43","title":"Reduction of Cognitive Load Through the Addition of High-Level Semantics to ReactoGraph","year":2005,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Semantics (computer science); Cognitive load; Visual programming language; Human–computer interaction; Usability; Context (archaeology); Programming language; Component (thermodynamics); User interface; Graphical user interface; Reduction (mathematics); Cognition","score_opus":0.041335965923538665,"score_gpt":0.31060712646492894,"score_spread":0.2692711605413903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1516668301","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00987007,0.000008223039,0.9841871,0.0024465078,0.000096093914,0.000108045046,0.000070088856,0.00003428714,0.0031795318],"genre_scores_gemma":[0.96841896,0.000032947773,0.03052447,0.0004918901,0.00004768389,0.0000021345827,0.000035949583,0.0000031381703,0.00044281152],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992756,0.000030620326,0.00021338434,0.00013646865,0.00026319828,0.00008071755],"domain_scores_gemma":[0.9992239,0.000060019385,0.000117910015,0.00024530632,0.00032911563,0.000023774295],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013431553,0.000057961694,0.00009287833,0.000054689877,0.000036809557,0.000023932433,0.0002654514,0.000025395153,0.00006862355],"category_scores_gemma":[0.00008520377,0.00004090899,0.00003641818,0.00058777037,0.00005384491,0.00038347128,0.000082692146,0.000035534104,0.000023360753],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017123515,0.00038190448,0.000045194523,0.00002205683,0.00006860643,4.752413e-7,0.0052029844,0.00035511548,0.0025776327,0.86333925,0.05002084,0.07796884],"study_design_scores_gemma":[0.0028737965,0.0011105348,0.0122223385,0.0008029655,0.00026115787,0.00005956869,0.008376071,0.10728509,0.7553079,0.03627479,0.0742999,0.0011258905],"about_ca_topic_score_codex":0.000113740665,"about_ca_topic_score_gemma":0.0000364254,"teacher_disagreement_score":0.9585489,"about_ca_system_score_codex":0.000011418177,"about_ca_system_score_gemma":0.000039331328,"threshold_uncertainty_score":0.16682203},"labels":[],"label_agreement":null},{"id":"W1525467666","doi":"10.1007/978-3-642-19167-1_3","title":"Self-organized Middle-Out Abstraction","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Abstraction; Rendering (computer graphics); Representation (politics); Theoretical computer science; Process (computing); Expressive power; Artificial intelligence; Distributed computing; Programming language","score_opus":0.03650520912462103,"score_gpt":0.26621596059910796,"score_spread":0.22971075147448694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1525467666","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000008559066,0.00012586894,0.98095834,0.00024610583,0.0021386289,0.00021390182,0.0000057181874,0.00038032542,0.015922565],"genre_scores_gemma":[0.050591003,0.00034272735,0.9387615,0.004374378,0.001141421,0.0000074150835,0.000050710274,0.00010650987,0.004624344],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99683166,0.000026127873,0.0005255413,0.0012739453,0.0008388046,0.0005038987],"domain_scores_gemma":[0.99761444,0.00015685661,0.00035348843,0.0013779874,0.0002995471,0.00019766281],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00061761803,0.00044635657,0.0004149831,0.00073542877,0.00021970888,0.0006351328,0.0030886414,0.00031020757,0.00011331476],"category_scores_gemma":[0.000069422014,0.00041859754,0.00011011481,0.000526928,0.00028198797,0.00093523634,0.0009931923,0.00058181613,0.00046738517],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011070401,0.00025994683,0.00009086129,0.00021092403,0.00007559016,0.00024059856,0.005665291,0.0022778306,0.00026316333,0.2961553,0.00042088452,0.69432855],"study_design_scores_gemma":[0.0007804768,0.00026660948,0.0001420962,0.0005450985,0.000045128276,0.00015229791,4.2739683e-7,0.64248645,0.004760559,0.29580614,0.05307681,0.001937882],"about_ca_topic_score_codex":0.000011485998,"about_ca_topic_score_gemma":0.000049719634,"teacher_disagreement_score":0.6923907,"about_ca_system_score_codex":0.00022796863,"about_ca_system_score_gemma":0.0004971773,"threshold_uncertainty_score":0.9998266},"labels":[],"label_agreement":null},{"id":"W1531389491","doi":"","title":"A comparison of fisheye lenses for interactive layout tasks","year":2004,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Distortion (music); Computer science; Computer vision; Lens (geology); Artificial intelligence; Pyramid (geometry); Computer graphics (images); Mathematics; Engineering; Geometry","score_opus":0.062298096718175454,"score_gpt":0.3999734374338524,"score_spread":0.33767534071567695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1531389491","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0050694174,0.0000066192333,0.99140817,0.0005165797,0.00009063858,0.00007238817,0.000012491247,0.00004718626,0.0027764968],"genre_scores_gemma":[0.95875347,0.0000012520517,0.040364597,0.00043894514,0.0000130909475,0.0000028485592,0.000014610201,0.000002679389,0.0004085104],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995451,0.0000074957425,0.00015669609,0.00012223351,0.00008826012,0.00008020047],"domain_scores_gemma":[0.9995712,0.000052668256,0.00007062866,0.00018334921,0.00009381552,0.000028334653],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000052262367,0.00004835656,0.00011203246,0.000049464954,0.000027568267,0.000048666054,0.0002976033,0.000017536395,0.00001699385],"category_scores_gemma":[0.000055612803,0.00004057186,0.000037875274,0.00013038637,0.000018374663,0.00028200448,0.00007764613,0.000024979365,0.000012960793],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015229469,0.0005754984,0.002442948,0.000044297314,0.000048716724,0.0000010222291,0.004116957,0.0013196813,0.0011574568,0.964309,0.014637685,0.011331548],"study_design_scores_gemma":[0.0032307243,0.0011321903,0.0022211587,0.00014529798,0.00004037102,0.0000063393063,0.0021772191,0.5260068,0.3578261,0.027047016,0.07955846,0.0006082881],"about_ca_topic_score_codex":0.000026564856,"about_ca_topic_score_gemma":0.00002694451,"teacher_disagreement_score":0.95368403,"about_ca_system_score_codex":0.000013765058,"about_ca_system_score_gemma":0.000035618556,"threshold_uncertainty_score":0.16544725},"labels":[],"label_agreement":null},{"id":"W1531821269","doi":"10.1007/11527886_47","title":"Exploring Eye Tracking to Increase Bandwidth in User Modeling","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Human–computer interaction; Eye tracking; User modeling; Bandwidth (computing); User interface; User interface design; User experience design; Artificial intelligence; Telecommunications","score_opus":0.08011123054097231,"score_gpt":0.30825178920949675,"score_spread":0.22814055866852445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1531821269","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011625005,0.000095791096,0.9959296,0.0007021316,0.0006888005,0.00024745474,0.000004082286,0.0001398515,0.0010297936],"genre_scores_gemma":[0.46022,0.00015641276,0.5325815,0.0055739977,0.00087204063,0.000019534724,0.000015582273,0.000071962386,0.0004889696],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9962619,0.00003398658,0.0006482859,0.0014475688,0.0009256603,0.0006826058],"domain_scores_gemma":[0.9980802,0.00015704532,0.00013850872,0.0011564814,0.00018828253,0.0002794759],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010074858,0.00045870067,0.00047906174,0.0016486016,0.00016460379,0.00085062714,0.0029705695,0.00015611065,0.00001854477],"category_scores_gemma":[0.0001603099,0.00045766923,0.00008904444,0.0011894982,0.00011358366,0.001955894,0.0014250447,0.0006082467,0.00006283343],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000029922553,0.000025807629,0.00010083421,0.00001653599,0.000003248604,0.000057968944,0.0011717153,0.67000145,0.000031991465,0.012239946,0.000007060424,0.31634048],"study_design_scores_gemma":[0.00019984863,0.00004045907,0.000059114558,0.000539452,0.0000036431377,0.000008858672,4.968352e-7,0.9896243,0.00020406718,0.0065854066,0.002171935,0.0005623894],"about_ca_topic_score_codex":0.0000895991,"about_ca_topic_score_gemma":0.00035601656,"teacher_disagreement_score":0.4633481,"about_ca_system_score_codex":0.0003481656,"about_ca_system_score_gemma":0.0003246896,"threshold_uncertainty_score":0.9997875},"labels":[],"label_agreement":null},{"id":"W1535286859","doi":"10.1007/11866763_49","title":"Using Registration Uncertainty Visualization in a User Study of a Simple Surgical Task","year":2006,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kingston General Hospital; Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Visualization; Computer science; Task (project management); Simple (philosophy); Reduction (mathematics); Uncertainty reduction theory; Human–computer interaction; Artificial intelligence; Computer vision; Mathematics","score_opus":0.031217186383807622,"score_gpt":0.3398570405038726,"score_spread":0.308639854120065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1535286859","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32207623,0.000008760317,0.6776005,0.000038566068,0.00009270315,0.00014775684,9.571285e-7,0.000026761056,0.0000077728055],"genre_scores_gemma":[0.9665898,0.0000010784281,0.03325091,0.000089367255,0.00005368946,0.0000022660054,0.000007648811,0.000004497829,7.149672e-7],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979816,0.00013185557,0.0004811811,0.0005489424,0.0005808236,0.00027556397],"domain_scores_gemma":[0.99901694,0.00013483808,0.00017627157,0.00047680887,0.00015401166,0.000041116236],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080176955,0.00013207347,0.00020106345,0.0004908055,0.00009416388,0.00024282618,0.00083784614,0.000050091516,0.000002619371],"category_scores_gemma":[0.00008261232,0.00012134301,0.000024557494,0.0038866156,0.00012863062,0.000713226,0.00027837773,0.00009657681,8.460761e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000048240827,0.00049021083,0.03522694,0.0000095420755,0.0000013555833,0.000027918179,0.00091017445,0.94851375,0.00068910833,0.0061759083,0.000005888545,0.007944379],"study_design_scores_gemma":[0.0005699402,0.00011647322,0.0063088634,0.000026051523,0.0000018587511,0.000009753222,0.00000469905,0.9880662,0.00081992644,0.0039012078,0.000039086965,0.00013594843],"about_ca_topic_score_codex":0.0012382385,"about_ca_topic_score_gemma":0.0016913878,"teacher_disagreement_score":0.6445136,"about_ca_system_score_codex":0.00011620294,"about_ca_system_score_gemma":0.00018232931,"threshold_uncertainty_score":0.49482244},"labels":[],"label_agreement":null},{"id":"W1536561502","doi":"10.1002/9781118801628.ch08","title":"Visualizing Scale‐Domain Manifolds: A Multiscale Geo‐Object‐Based Approach","year":2014,"lang":"en","type":"other","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Scale (ratio); Domain (mathematical analysis); Computer science; Object (grammar); Computer graphics (images); Geology; Artificial intelligence; Mathematics; Geography; Cartography; Mathematical analysis","score_opus":0.017279880145241087,"score_gpt":0.2800799103045402,"score_spread":0.26280003015929915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1536561502","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[3.9623214e-7,0.000047972204,0.5573611,0.000052204807,0.00015386104,0.00016122709,0.000016607672,0.00068621204,0.4415204],"genre_scores_gemma":[0.00034232164,0.000018285009,0.33301702,0.0023962902,0.00034772075,0.000027032605,0.00031581274,0.0003406799,0.66319484],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975676,0.00016053353,0.0003665118,0.00089865836,0.0005604163,0.00044628352],"domain_scores_gemma":[0.99813384,0.000043213528,0.00027126833,0.0013020409,0.000044274362,0.00020538701],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003716277,0.0004199273,0.00047870586,0.0005100241,0.000091915135,0.00042342348,0.0015943442,0.00032676818,0.0010762032],"category_scores_gemma":[0.000021179158,0.00036988893,0.00016146447,0.00052783865,0.00007207846,0.00013931826,0.0003780855,0.00017221482,0.0010631994],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001246179,0.00022669455,0.00006742209,0.00019101005,0.00004368703,0.000008296425,0.00007876685,0.000032887507,0.000025953519,0.08740034,0.90963507,0.0022886214],"study_design_scores_gemma":[0.00045281093,0.000026279296,0.000012102649,0.000108114946,0.000014920868,0.0000054929683,0.000028828665,0.3057166,0.000043745255,0.00013448187,0.6929716,0.00048505623],"about_ca_topic_score_codex":0.00016305476,"about_ca_topic_score_gemma":0.00013681703,"teacher_disagreement_score":0.3056837,"about_ca_system_score_codex":0.000038994574,"about_ca_system_score_gemma":0.00008716462,"threshold_uncertainty_score":0.9998753},"labels":[],"label_agreement":null},{"id":"W1537892751","doi":"10.1111/cgf.12644","title":"Detangler: Visual Analytics for Multiplex Networks","year":2015,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Computer science; Multiplex; Cohesion (chemistry); Visual analytics; Feature (linguistics); Network analysis; Human–computer interaction; Data mining; Visualization; Distributed computing; Artificial intelligence","score_opus":0.04452672229331042,"score_gpt":0.30661352408226444,"score_spread":0.26208680178895405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1537892751","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00028741235,0.000115125265,0.9969936,0.0006898813,0.0012403629,0.00023980248,0.000012264556,0.0003072962,0.00011423351],"genre_scores_gemma":[0.69143146,0.00008080444,0.29406273,0.012381821,0.0011495319,0.00004113768,0.00038288283,0.000080199025,0.0003894191],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99820083,0.000051313742,0.00038158058,0.0004883739,0.0003427361,0.00053519],"domain_scores_gemma":[0.9983095,0.00012841632,0.00014827913,0.00063051813,0.00042651026,0.0003567785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044698967,0.0002294931,0.00026619429,0.00027504636,0.00017366048,0.00042780375,0.0011435029,0.00012639123,0.0000017270111],"category_scores_gemma":[0.00004966332,0.00022124263,0.00018590313,0.0009717687,0.00007629038,0.00052824034,0.00054166245,0.00014049797,0.000017925917],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011579661,0.00020055201,0.0050586085,0.000016144451,0.0000873018,0.000010435226,0.00016241758,0.009308158,0.0000020590078,0.8655214,0.10206167,0.017559705],"study_design_scores_gemma":[0.00077147316,0.00020712247,0.00017993651,0.000012605011,0.000015767497,0.000008207019,0.000020866439,0.918721,0.000020967638,0.0072987475,0.07247073,0.00027252952],"about_ca_topic_score_codex":0.0000051879056,"about_ca_topic_score_gemma":0.0000276155,"teacher_disagreement_score":0.90941286,"about_ca_system_score_codex":0.000032447322,"about_ca_system_score_gemma":0.00009502394,"threshold_uncertainty_score":0.9022013},"labels":[],"label_agreement":null},{"id":"W1538648148","doi":"10.1007/11795018_4","title":"Experiments in the Perception of Causality","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Animation; Causality (physics); Metaphor; Perception; Simple (philosophy); Artificial intelligence; Human–computer interaction; Cognitive science; Cognitive psychology; Natural language processing; Computer graphics (images); Epistemology; Linguistics; Psychology; Philosophy","score_opus":0.03359837867885808,"score_gpt":0.314826521982209,"score_spread":0.28122814330335094,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1538648148","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00026338952,0.00006856218,0.995261,0.0003033861,0.00035670275,0.00017571013,0.000005848117,0.000026730075,0.0035386798],"genre_scores_gemma":[0.89232,0.00003578563,0.104507715,0.0024418347,0.00026607857,0.000006226627,0.00003619707,0.00001890017,0.0003672692],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977759,0.000053901404,0.00044003778,0.0006458858,0.00082071585,0.00026354744],"domain_scores_gemma":[0.9985263,0.00014651072,0.000205695,0.0009771057,0.00010831948,0.00003611214],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00090128934,0.0002239951,0.0002661655,0.00044018045,0.00007862706,0.00022753546,0.002563964,0.00013155788,0.000015510583],"category_scores_gemma":[0.0000339649,0.00016717987,0.00006334688,0.00058579294,0.00038416262,0.0003656984,0.000505312,0.00028916955,0.000011577386],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010169846,0.0005113299,0.0025939255,0.00017620578,0.000019161882,0.00017484797,0.011777819,0.069398485,0.0011816333,0.22505042,0.0012930541,0.687813],"study_design_scores_gemma":[0.00041351197,0.00015701496,0.003779269,0.00036260727,0.000007892697,0.000032894994,0.0000027945098,0.9097926,0.0008594631,0.08077537,0.0031617875,0.00065480504],"about_ca_topic_score_codex":0.00009759645,"about_ca_topic_score_gemma":0.00007485482,"teacher_disagreement_score":0.8920566,"about_ca_system_score_codex":0.00012435259,"about_ca_system_score_gemma":0.00017532494,"threshold_uncertainty_score":0.6817397},"labels":[],"label_agreement":null},{"id":"W1540636713","doi":"10.1007/3-540-47887-6_52","title":"Interactive Construction of Classification Rules","year":2002,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Visualization; Classifier (UML); Human–computer interaction; Process (computing); Interactive visualization; Table (database); Domain (mathematical analysis); Multidimensional data; Data mining; Artificial intelligence; Machine learning; Information retrieval; Programming language","score_opus":0.031236686092690216,"score_gpt":0.2853442404498113,"score_spread":0.2541075543571211,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1540636713","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00002645043,0.000064528605,0.9912234,0.00035966892,0.0008575149,0.0001316702,0.000013266925,0.00006788741,0.007255598],"genre_scores_gemma":[0.12478666,0.00029127317,0.8729786,0.00078286964,0.00033512528,0.0000044653907,0.00004608914,0.00003294214,0.0007419677],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99794805,0.00002483324,0.00045951485,0.0007510795,0.00059383793,0.0002226879],"domain_scores_gemma":[0.9981223,0.00019629527,0.00045394528,0.00082668907,0.00032676366,0.000074027266],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029621433,0.00024491732,0.00031364482,0.0007386137,0.00009072484,0.00023129584,0.0015859517,0.0001639926,0.000051090294],"category_scores_gemma":[0.00007419033,0.00023196892,0.00007615368,0.0004439133,0.0006374365,0.00068671897,0.0004701813,0.0003172799,0.00004896034],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000019974882,0.000030817082,0.000055226516,0.00002804795,0.000010336488,0.000006318285,0.00044654228,0.0013095923,0.00012047883,0.3496028,0.000046779947,0.64834106],"study_design_scores_gemma":[0.00013458365,0.0000704208,0.00013072768,0.00025613722,0.000007309713,0.000031157637,4.3053714e-7,0.8837775,0.0012938085,0.11179509,0.0022065055,0.0002963158],"about_ca_topic_score_codex":0.0000055022697,"about_ca_topic_score_gemma":0.000005766692,"teacher_disagreement_score":0.8824679,"about_ca_system_score_codex":0.00014880035,"about_ca_system_score_gemma":0.00017119845,"threshold_uncertainty_score":0.9459418},"labels":[],"label_agreement":null},{"id":"W1545081977","doi":"10.1007/978-3-540-70956-5_5","title":"Creation and Collaboration: Engaging New Audiences for Information Visualization","year":2008,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":103,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Mainstream; Visualization; Computer science; Information visualization; Data science; World Wide Web; Data visualization; Human–computer interaction; Multimedia; Artificial intelligence","score_opus":0.019901538312893735,"score_gpt":0.2938227848890942,"score_spread":0.27392124657620043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1545081977","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000010638386,0.00019939519,0.9963647,0.000830113,0.00064656197,0.00040430564,0.000010734636,0.000112654416,0.0014208585],"genre_scores_gemma":[0.053071056,0.0013979741,0.9358802,0.0065331636,0.0011104371,0.00002723391,0.00040803966,0.000045336812,0.0015265724],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998082,0.000019521613,0.0004670982,0.0005794175,0.00058868836,0.00026327692],"domain_scores_gemma":[0.9983892,0.00023997857,0.0003486687,0.00041449748,0.0004803216,0.00012737315],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0004843372,0.00026489337,0.00025918678,0.0007783196,0.0004353544,0.001056778,0.0008136562,0.00015971981,0.000005491847],"category_scores_gemma":[0.00025088995,0.00025864906,0.00003775693,0.0007908314,0.0002599127,0.0030638531,0.0003071889,0.00014892897,0.0000092381015],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005325926,0.000011865721,0.00005743578,0.00006157639,0.00000837731,0.0000024560377,0.005178969,0.016766742,0.000016997381,0.23949379,0.00079413684,0.73760235],"study_design_scores_gemma":[0.00032168406,0.00011288619,0.000056828565,0.00014890659,0.0000073999445,0.000018819883,0.000001571315,0.9325469,0.00033198105,0.024930373,0.041159637,0.0003629991],"about_ca_topic_score_codex":0.000010419603,"about_ca_topic_score_gemma":0.00003764621,"teacher_disagreement_score":0.9157802,"about_ca_system_score_codex":0.00013740076,"about_ca_system_score_gemma":0.00076116214,"threshold_uncertainty_score":0.9999866},"labels":[],"label_agreement":null},{"id":"W1549014346","doi":"10.1111/j.1756-8765.2011.01148.x","title":"Visual Analytics as a Translational Cognitive Science","year":2011,"lang":"en","type":"article","venue":"Topics in Cognitive Science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Visual analytics; Cognition; Data science; Analytics; Human–computer interaction; Field (mathematics); Cognitive computing; Human-centered computing; Cognitive science; Visualization; Information science; Artificial intelligence; Psychology","score_opus":0.09229028274844656,"score_gpt":0.3890536577681853,"score_spread":0.2967633750197387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1549014346","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13469014,0.00003628046,0.7409609,0.0002837995,0.00048930687,0.00033278932,0.000024118302,0.00012639309,0.12305629],"genre_scores_gemma":[0.99240136,0.00001554262,0.006113248,0.001039888,0.000047790385,0.00000805774,0.000005501333,0.0000056010153,0.0003630324],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99694544,0.00004728739,0.00034353507,0.00085852173,0.0012197434,0.000585491],"domain_scores_gemma":[0.9981966,0.00014971099,0.00011672003,0.00025864004,0.0010271819,0.00025115404],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015640032,0.0001749985,0.00017188361,0.0008840965,0.0004452683,0.0003597885,0.0016043726,0.000047148125,0.00017246246],"category_scores_gemma":[0.0013050904,0.00017245141,0.000044807042,0.0056024664,0.0025325296,0.002483598,0.00044179783,0.00020433565,0.00014309306],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029796094,0.00067065936,0.03105812,0.000014375783,0.000014661841,0.00010259227,0.010063374,0.000011299386,0.0006865856,0.86667556,0.000024109317,0.090648845],"study_design_scores_gemma":[0.0030418532,0.00083006476,0.31909367,0.0005060545,0.000062564475,0.00010365482,0.0037668818,0.47209588,0.07851191,0.119700395,0.00057517167,0.0017118981],"about_ca_topic_score_codex":0.000041877807,"about_ca_topic_score_gemma":0.000028943023,"teacher_disagreement_score":0.8577112,"about_ca_system_score_codex":0.00007515899,"about_ca_system_score_gemma":0.0014629725,"threshold_uncertainty_score":0.93312114},"labels":[],"label_agreement":null},{"id":"W1549048100","doi":"","title":"VisiQ: Supporting visual and interactive query refinement","year":2007,"lang":"en","type":"article","venue":"Web Intelligence and Agent Systems An International Journal","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Query expansion; Information retrieval; Web query classification; Query language; Query optimization; Web search query; Sargable; Spatial query; Process (computing); Representation (politics); Information needs; Search engine; World Wide Web","score_opus":0.03351170831330354,"score_gpt":0.37327701204261754,"score_spread":0.339765303729314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1549048100","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10477636,0.00016123064,0.89188594,0.00034693704,0.0018218507,0.0000853013,0.0000068903605,0.00004328509,0.0008721902],"genre_scores_gemma":[0.99646896,0.00051674474,0.0015277446,0.00044565907,0.000510136,0.0000017808894,0.000012193633,0.000008492625,0.0005083071],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981636,0.000067489236,0.00066836586,0.00030687472,0.0005402616,0.00025342626],"domain_scores_gemma":[0.99878466,0.000078676625,0.00037616378,0.00013787347,0.0003603116,0.00026231058],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0013878497,0.00015048168,0.00015532663,0.00031363283,0.00017771218,0.0012106264,0.000566474,0.000047780126,0.000050624654],"category_scores_gemma":[0.00008859633,0.00012829523,0.000044669396,0.00012829466,0.00004792134,0.0013790263,0.00023743493,0.00020215953,0.000019645397],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011377252,0.00070713623,0.036655996,0.000068962974,0.0005249439,0.0012568758,0.0067969575,0.00067644473,0.0043817577,0.41153303,0.002176419,0.53510773],"study_design_scores_gemma":[0.0007106675,0.0007957952,0.010393269,0.0007260405,0.00003825822,0.0044471,0.011216717,0.85267055,0.0038797471,0.0021816834,0.111997664,0.00094250595],"about_ca_topic_score_codex":0.000058411264,"about_ca_topic_score_gemma":0.000025109055,"teacher_disagreement_score":0.8916926,"about_ca_system_score_codex":0.00008345735,"about_ca_system_score_gemma":0.00006761451,"threshold_uncertainty_score":0.9998262},"labels":[],"label_agreement":null},{"id":"W1549927893","doi":"10.1007/978-3-540-30178-3_33","title":"AgentViz: A Visualization System for Mobile Agents","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Visualization; Network topology; Mobile agent; Process (computing); Variety (cybernetics); Graphics; Distributed computing; Computer graphics; Human–computer interaction; Architecture; Computer network; Computer graphics (images); Artificial intelligence; Operating system","score_opus":0.02752594945974822,"score_gpt":0.30567850555567927,"score_spread":0.27815255609593104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1549927893","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000010532807,0.00013090717,0.9955713,0.00008374754,0.0017979856,0.00081761123,0.00003184125,0.00028201097,0.0012740247],"genre_scores_gemma":[0.3609781,0.00012827531,0.62927574,0.004814125,0.0015864187,0.00017154217,0.00039611867,0.0002011488,0.0024485325],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99666375,0.000023144406,0.0005876931,0.0013234153,0.00087566534,0.0005263255],"domain_scores_gemma":[0.99782616,0.00015011398,0.0003615403,0.0011193225,0.00036494256,0.00017791796],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006531203,0.00043655044,0.0004516128,0.0007875622,0.0002895345,0.00078635116,0.0026230267,0.0002582546,0.000021663398],"category_scores_gemma":[0.000060847316,0.000419288,0.00015040305,0.0007082574,0.00024301388,0.00062950846,0.0007714417,0.00021527357,0.000057156776],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000057821744,0.00008102022,0.00001971866,0.00042871808,0.000027620528,0.000053809465,0.0010436284,0.105456635,0.00006288764,0.70043206,0.0001886247,0.19219948],"study_design_scores_gemma":[0.0004892706,0.00018778034,0.000008633935,0.0006628438,0.000015833204,0.000024375675,5.121475e-7,0.9516248,0.0010155699,0.038637474,0.00674695,0.0005859298],"about_ca_topic_score_codex":0.0000092918,"about_ca_topic_score_gemma":0.000013869991,"teacher_disagreement_score":0.84616816,"about_ca_system_score_codex":0.000623015,"about_ca_system_score_gemma":0.0006293413,"threshold_uncertainty_score":0.9998259},"labels":[],"label_agreement":null},{"id":"W1550585620","doi":"10.1109/hicss.2015.138","title":"Interactivity in Visual Analytics: Use of Conceptual Frameworks to Support Human-Centered Design of a Decision-Support Tool","year":2015,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Interactivity; Visual analytics; Computer science; Human–computer interaction; Analytics; Visualization; Data science; Conceptual framework; Component (thermodynamics); Knowledge management; Multimedia; Artificial intelligence","score_opus":0.15717754343305715,"score_gpt":0.39758341749294657,"score_spread":0.24040587405988942,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1550585620","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07945491,0.0000012704976,0.91992366,0.000054193737,0.00013154851,0.00019504355,0.000016248965,0.000033133554,0.0001899994],"genre_scores_gemma":[0.89079803,0.0000022519282,0.108168624,0.0007203096,0.000014134797,0.000003440782,0.00001941684,0.000008942925,0.00026482777],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99793625,0.00013044017,0.0007710713,0.00037257624,0.0005453365,0.0002443387],"domain_scores_gemma":[0.9981803,0.00039084686,0.00023250512,0.00060027663,0.0003948797,0.00020118772],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007510572,0.00015933026,0.00040405896,0.00039294237,0.00001903587,0.00010764439,0.0007397068,0.00013291152,0.00022502066],"category_scores_gemma":[0.0009004049,0.00014557698,0.00007156144,0.0008212919,0.0001068572,0.0010550554,0.0005374794,0.00018390578,0.000044178545],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011940248,0.011213904,0.12627633,0.00012422653,0.000478947,0.000494696,0.033765018,0.06681028,0.007940824,0.31318867,0.2955553,0.14295779],"study_design_scores_gemma":[0.0028356723,0.0030945947,0.0038409056,0.00024008138,0.000036379548,0.000018869196,0.0016124077,0.9674008,0.011752317,0.0023183236,0.006107506,0.0007421593],"about_ca_topic_score_codex":0.00007034453,"about_ca_topic_score_gemma":0.00005272384,"teacher_disagreement_score":0.9005905,"about_ca_system_score_codex":0.000064014384,"about_ca_system_score_gemma":0.0002630273,"threshold_uncertainty_score":0.5936457},"labels":[],"label_agreement":null},{"id":"W1554947157","doi":"10.2307/25148635","title":"The Effect of Relationship Encoding, Task Type, and Complexity on Information Representation: An Empirical Evaluation of 2D and 3D Line Graphs1","year":2004,"lang":"en","type":"article","venue":"MIS Quarterly","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":92,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Representation (politics); Task (project management); Encoding (memory); Line (geometry); Computer science; Theoretical computer science; Type (biology); Empirical research; Mathematics; Artificial intelligence; Statistics; Management; Economics; Political science","score_opus":0.08922569040527267,"score_gpt":0.3899525265632039,"score_spread":0.3007268361579312,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1554947157","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9027509,0.00005197831,0.09588601,0.00046519775,0.000074400625,0.0002442594,0.000012782872,0.00002680494,0.00048765057],"genre_scores_gemma":[0.99873716,0.000005270743,0.0011279071,0.00004528952,0.000010529205,0.0000029260475,0.00006503065,0.0000016684882,0.0000042347706],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990456,0.00020989732,0.0002494103,0.000106429536,0.00032883533,0.000059837123],"domain_scores_gemma":[0.999173,0.00017678308,0.0001539739,0.00024663113,0.00021213638,0.000037484322],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00090416777,0.00005953699,0.000090528,0.0000826134,0.000113956004,0.00008402497,0.0001266056,0.000031120195,0.0000028822606],"category_scores_gemma":[0.00015763452,0.00004308476,0.000014143488,0.00033480767,0.000089409565,0.0006011746,0.000011737627,0.000048173326,0.000002687234],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002721587,0.00029273567,0.17720076,0.0002451577,0.00010312965,0.0000013152454,0.04300443,0.005193353,0.00063157215,0.25507784,0.0014186864,0.5165589],"study_design_scores_gemma":[0.0027430095,0.0049767597,0.2880762,0.00007244014,0.00007904837,0.000009470098,0.0005735557,0.67987984,0.00153373,0.021475734,0.000394875,0.0001853318],"about_ca_topic_score_codex":0.00003057074,"about_ca_topic_score_gemma":0.000031404208,"teacher_disagreement_score":0.6746865,"about_ca_system_score_codex":0.000013895037,"about_ca_system_score_gemma":0.000035194,"threshold_uncertainty_score":0.17569456},"labels":[],"label_agreement":null},{"id":"W1557561505","doi":"10.5555/1412433.1412436","title":"Geographic Information Systems (GIS) in public administrationc An introduction to a series of articles","year":2000,"lang":"en","type":"article","venue":"Information Polity archive","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Technocracy; Public domain; Democracy; Rationality; Informatization; Information and Communications Technology; The Internet; Public relations; Sociology; Public administration; Work (physics); Political science; Computer science; Politics; World Wide Web","score_opus":0.01755108126428731,"score_gpt":0.2609572815296338,"score_spread":0.2434062002653465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1557561505","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23612644,0.0000056706913,0.7390234,0.01116818,0.0003611386,0.00092339976,0.00051630795,0.00033985564,0.01153564],"genre_scores_gemma":[0.99571323,0.000010971765,0.0030018706,0.0005363313,0.000044445624,0.000021794285,0.0006519181,0.0000014850591,0.000017934399],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986399,0.000093169736,0.00068718207,0.00009463625,0.00030019632,0.0001849221],"domain_scores_gemma":[0.99911517,0.000019500472,0.00017875279,0.00038469883,0.00017319275,0.00012870459],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00041549993,0.0000899208,0.0001206325,0.00062450924,0.00008143233,0.00047299624,0.00035266465,0.000034192417,0.00003702593],"category_scores_gemma":[0.00011338852,0.0000916628,0.000026876949,0.00085077755,0.000051812895,0.015946716,0.000050486804,0.000069694,0.00013600207],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028929542,0.00008102508,0.0016375409,0.00006909537,0.000008825721,1.7898071e-7,0.009652121,0.006533149,0.000023531564,0.9459212,0.0016771242,0.034367286],"study_design_scores_gemma":[0.0010447301,0.00070452923,0.08570834,0.000050690305,0.0000099914205,0.00005156196,0.0039428836,0.4678794,0.0008884123,0.01198169,0.42716408,0.00057368394],"about_ca_topic_score_codex":0.00022561547,"about_ca_topic_score_gemma":0.00009261543,"teacher_disagreement_score":0.9339395,"about_ca_system_score_codex":0.0000313925,"about_ca_system_score_gemma":0.00011090516,"threshold_uncertainty_score":0.99781674},"labels":[],"label_agreement":null},{"id":"W1566418190","doi":"","title":"Interactive Data Visualization Tool to Analyze Word Count Frequencies Over Time","year":2011,"lang":"en","type":"article","venue":"Sound Ideas (University of Puget Sound)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Word lists by frequency; Word (group theory); Computer science; Word processing; Linguistics; Natural language processing","score_opus":0.04052045473259253,"score_gpt":0.28324165967866766,"score_spread":0.24272120494607513,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1566418190","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23264197,0.000016770513,0.7646288,0.00009843541,0.00013101702,0.00013297315,0.00012731797,0.00012376436,0.0020988982],"genre_scores_gemma":[0.97007364,0.000026956875,0.025394108,0.0007231512,0.00005401367,2.9975743e-7,0.00045854246,0.000018658873,0.003250606],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99852824,0.00008503516,0.00019968578,0.0005307076,0.00041192054,0.00024443615],"domain_scores_gemma":[0.99813384,0.00005830387,0.00022132616,0.00115928,0.00028957808,0.00013765322],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035485296,0.00016364912,0.00024437153,0.0003191833,0.00022209893,0.00014984567,0.0020898732,0.000072024646,0.00082200783],"category_scores_gemma":[0.00012269456,0.00019670668,0.000070512426,0.00093039294,0.00012164035,0.0027799755,0.0011063946,0.00008798624,0.00046320847],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036729285,0.00018438927,0.0032893675,0.000022422524,0.00014411873,0.00002076711,0.00790382,0.00004507472,0.000058827813,0.97084194,0.017184258,0.00026827064],"study_design_scores_gemma":[0.0005584897,0.00012824335,0.009847208,0.00005077555,0.00009114271,0.000006420837,0.0018487676,0.10057298,0.0000121233,0.8772725,0.009099394,0.0005119431],"about_ca_topic_score_codex":0.00049988244,"about_ca_topic_score_gemma":0.00035209866,"teacher_disagreement_score":0.73923475,"about_ca_system_score_codex":0.00011701883,"about_ca_system_score_gemma":0.00011589129,"threshold_uncertainty_score":0.900041},"labels":[],"label_agreement":null},{"id":"W1568647029","doi":"10.1007/978-3-642-14600-8_5","title":"The Graduate Student Symposium of Diagrams 2010","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Graduate students; Mathematics education; Library science; Psychology; Pedagogy","score_opus":0.027098211573725137,"score_gpt":0.2937318296303837,"score_spread":0.26663361805665853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1568647029","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006774284,0.00014018959,0.9926834,0.0017729099,0.0035202322,0.00023759277,0.0000072870866,0.00006856077,0.001502067],"genre_scores_gemma":[0.41203254,0.0029654119,0.5623818,0.007927695,0.0028737406,0.000041887153,0.00007505951,0.00021909185,0.011482778],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99678254,0.00003257695,0.0005621251,0.0008622756,0.0013039861,0.00045649084],"domain_scores_gemma":[0.9967601,0.0005058267,0.00040204028,0.0018181805,0.00037479482,0.00013911349],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0011931853,0.0003488682,0.00036712099,0.00033748732,0.00035119764,0.0007465749,0.005464562,0.00020574454,0.000007466714],"category_scores_gemma":[0.00008494554,0.00023947777,0.00012500976,0.0005223676,0.0011454347,0.0003505019,0.0018283523,0.00080893387,0.000031992204],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005240172,0.00013972893,0.0002516332,0.000059603142,0.000048342215,0.000054309145,0.0026441664,0.006329549,0.0011451278,0.33887562,0.0002924035,0.6501543],"study_design_scores_gemma":[0.0006194104,0.00042958293,0.0010315409,0.0005061063,0.00004114765,0.000068962305,0.0000014208207,0.6712098,0.01220715,0.28467473,0.027648391,0.0015617486],"about_ca_topic_score_codex":0.00001529117,"about_ca_topic_score_gemma":0.00016128838,"teacher_disagreement_score":0.6648803,"about_ca_system_score_codex":0.00006587315,"about_ca_system_score_gemma":0.0003503065,"threshold_uncertainty_score":0.9999164},"labels":[],"label_agreement":null},{"id":"W1577730630","doi":"10.1002/9781118445112.stat01372","title":"Minard, Charles Joseph","year":2014,"lang":"en","type":"other","venue":"Wiley StatsRef: Statistics Reference Online","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Encyclopedia; Citation; Library science; Computer science","score_opus":0.03634774108868412,"score_gpt":0.32225379851821695,"score_spread":0.28590605742953284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1577730630","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[7.580131e-7,0.0006474092,0.9219543,0.00016502402,0.0006135084,0.0002210874,0.021153022,0.00058542594,0.054659463],"genre_scores_gemma":[0.000048974038,0.0060510915,0.516965,0.0010019843,0.0004919617,0.000014916548,0.015370548,0.00041942316,0.45963612],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9968021,0.00015925436,0.0006364457,0.00097272015,0.00082161964,0.0006078787],"domain_scores_gemma":[0.99705625,0.00014806062,0.0006592197,0.0015559961,0.00023823405,0.00034222213],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00021228722,0.0006144423,0.0007354119,0.0005070636,0.00010612452,0.00034848347,0.0019968494,0.00034102215,0.0020982197],"category_scores_gemma":[0.00022770141,0.0005703698,0.00006689183,0.00045964523,0.00018549463,0.00014478342,0.0005231213,0.00043748427,0.0015126171],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000020698585,0.00014017924,0.000016458882,0.00012386021,0.00004849916,0.00003029139,0.00003784293,0.000003866798,0.0000047691483,0.22892603,0.7362622,0.0344039],"study_design_scores_gemma":[0.00035910413,0.00013044952,0.00003118662,0.0004139525,0.00004828238,0.000007459345,0.000017619204,0.024315089,0.000004585188,0.0046293656,0.9693488,0.00069411076],"about_ca_topic_score_codex":0.00015792977,"about_ca_topic_score_gemma":0.000804585,"teacher_disagreement_score":0.40498933,"about_ca_system_score_codex":0.00006412287,"about_ca_system_score_gemma":0.00030428125,"threshold_uncertainty_score":0.9996748},"labels":[],"label_agreement":null},{"id":"W1579196442","doi":"10.1038/nmeth.3451","title":"Unentangling complex plots","year":2015,"lang":"en","type":"article","venue":"Nature Methods","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"Engineering and Physical Sciences Research Council","keywords":"Computational biology; Biology; Computer science","score_opus":0.13225052429907336,"score_gpt":0.4817479263527825,"score_spread":0.34949740205370916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1579196442","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006540259,0.00028866043,0.9873348,0.00088596594,0.00074741046,0.000038266677,0.0000025268164,0.00019239767,0.010444586],"genre_scores_gemma":[0.012687022,0.000004801133,0.9833342,0.0032736638,0.00012583954,0.0000010439809,0.000016293658,0.000007159234,0.0005499764],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990266,0.00024020967,0.00012836399,0.00021864093,0.00024054597,0.00014561662],"domain_scores_gemma":[0.99915534,0.000102339254,0.000051462146,0.0004133605,0.00013953127,0.00013797224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010745821,0.000080793805,0.000116290146,0.00008366386,0.000046025176,0.00012900925,0.00066494086,0.00011054438,0.000014124823],"category_scores_gemma":[0.00048718962,0.00006885582,0.000034503642,0.00055177097,0.000018533541,0.0002421645,0.00021672445,0.0002314492,0.000039110495],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000037676018,0.000072286486,0.00035155757,0.000011592819,0.0000257292,0.000019664569,0.0006914724,0.00014933705,0.0018051396,0.75822914,0.085852265,0.15278806],"study_design_scores_gemma":[0.00028695716,0.000024271854,0.00027101056,0.000007364987,0.0000063431958,0.00001124851,0.00004732685,0.2792505,0.0032017108,0.014430093,0.70230794,0.00015524487],"about_ca_topic_score_codex":0.0000025177897,"about_ca_topic_score_gemma":0.0000011885869,"teacher_disagreement_score":0.74379903,"about_ca_system_score_codex":0.000031148633,"about_ca_system_score_gemma":0.000054161395,"threshold_uncertainty_score":0.2807859},"labels":[],"label_agreement":null},{"id":"W1582226505","doi":"10.1007/978-3-540-24595-7_46","title":"Degree Navigator TM : The Journey of a Visualization Software","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Visualization; Scope (computer science); Computer science; Software; Software visualization; Degree (music); Data science; Software engineering; Software development; Artificial intelligence; Software construction; Programming language","score_opus":0.03565101307521272,"score_gpt":0.3002408994293612,"score_spread":0.2645898863541485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1582226505","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000021094686,0.0003319248,0.99737376,0.00051776314,0.00080941914,0.00024276257,0.00001382488,0.00010495591,0.0005844813],"genre_scores_gemma":[0.23528673,0.00050012354,0.7524861,0.009271154,0.0011201407,0.000014881129,0.00010102039,0.00014677478,0.001073046],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99697626,0.000040464096,0.0006072917,0.0008349987,0.001150571,0.0003904002],"domain_scores_gemma":[0.99732363,0.00027869793,0.00049565337,0.0013234258,0.00044700498,0.00013158085],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000799847,0.00036436334,0.00039909245,0.0004987851,0.00025247067,0.0004671242,0.0037697484,0.00021127265,0.000039107053],"category_scores_gemma":[0.0002568351,0.00026647645,0.00012991483,0.0010248004,0.0006901283,0.0005710785,0.0011169757,0.00043494848,0.000025338144],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000044406615,0.000077401935,0.00013328977,0.00012200987,0.000029063054,0.00005666657,0.0020646802,0.042782575,0.000064461885,0.39970237,0.00012682825,0.5548362],"study_design_scores_gemma":[0.00058181694,0.0002571347,0.00020939931,0.0015227658,0.00003234931,0.00010625648,8.932865e-7,0.59432346,0.0024481216,0.39441022,0.0051578735,0.0009496816],"about_ca_topic_score_codex":0.000020678968,"about_ca_topic_score_gemma":0.00003973261,"teacher_disagreement_score":0.55388653,"about_ca_system_score_codex":0.00018332459,"about_ca_system_score_gemma":0.001014999,"threshold_uncertainty_score":0.9999787},"labels":[],"label_agreement":null},{"id":"W1588502470","doi":"10.20380/gi2001.13","title":"Interacting with Image Sequences: Detail-in-Context and Thumbnails","year":2001,"lang":"en","type":"article","venue":"Canada Human-Computer Communications Society","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Simon Fraser University","funders":"","keywords":"Thumbnail; Computer science; Context (archaeology); Image (mathematics); Presentation (obstetrics); Software; Artificial intelligence; Computer vision; Sequence (biology); Computer graphics (images); Information retrieval; Programming language","score_opus":0.0316161060161684,"score_gpt":0.29543808420799467,"score_spread":0.2638219781918263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1588502470","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.047067735,0.00063874957,0.9375284,0.0098635405,0.00018687108,0.0003694595,0.000013339166,0.00021806404,0.004113855],"genre_scores_gemma":[0.8557383,0.00021402258,0.14047684,0.0032286628,0.0000324683,0.000014593162,0.00004107012,0.000013579603,0.00024050492],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987906,0.00010433,0.00031137536,0.00032384144,0.00020792888,0.00026192388],"domain_scores_gemma":[0.997844,0.00023393206,0.00014430952,0.0015298836,0.00013993368,0.00010795716],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024626666,0.0001617331,0.00018729537,0.0000499287,0.0004931128,0.0003904193,0.0018574947,0.00003868349,0.000013429912],"category_scores_gemma":[0.0000124920625,0.00015122557,0.00004410258,0.00048048003,0.00018341177,0.0007681008,0.00074676727,0.00026575522,0.0000026838163],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012447982,0.00089411676,0.06979399,0.0002565649,0.0006393549,0.0002323458,0.056238685,0.0008907731,0.0010451261,0.5660109,0.12650718,0.17747849],"study_design_scores_gemma":[0.0011393292,0.000068725465,0.005894239,0.00029798268,0.000025470094,0.00015968963,0.0037201152,0.84876996,0.000091684946,0.0010232985,0.13801664,0.0007928674],"about_ca_topic_score_codex":0.052822232,"about_ca_topic_score_gemma":0.47930446,"teacher_disagreement_score":0.8478792,"about_ca_system_score_codex":0.00020824857,"about_ca_system_score_gemma":0.00035519488,"threshold_uncertainty_score":0.95348513},"labels":[],"label_agreement":null},{"id":"W1590369708","doi":"","title":"Map morphing: making sense of incongruent maps","year":2004,"lang":"en","type":"article","venue":"Graphics Interface","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Morphing; Computer science; Visualization; Schematic; Computer vision; Interface (matter); Projection (relational algebra); Overlay; Computer graphics (images); Artificial intelligence; Data visualization; Human–computer interaction; Engineering","score_opus":0.029414694757616922,"score_gpt":0.3123380867359756,"score_spread":0.28292339197835864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1590369708","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014792403,0.00011219936,0.98247004,0.001170299,0.00040965513,0.0000668343,0.000015007548,0.00010660149,0.00085693924],"genre_scores_gemma":[0.9856575,0.00002406783,0.013643699,0.0005501033,0.000018521805,0.0000011067725,0.000005524416,0.000008515168,0.000090948575],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99899966,0.000030681633,0.00028047693,0.00025016363,0.00026237266,0.00017667888],"domain_scores_gemma":[0.99912703,0.000027453945,0.00014113296,0.0005268139,0.00012179922,0.00005577858],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024174272,0.000113242015,0.00014130979,0.00019701793,0.000058053214,0.000100196004,0.00058416574,0.000051627594,0.000012554404],"category_scores_gemma":[0.000038046688,0.00011006831,0.00006847989,0.00042284286,0.00007829369,0.00028475202,0.00034206797,0.0001309734,0.000052892014],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000034289267,0.00009141284,0.00024849817,0.000043248117,0.000029003662,0.000019859484,0.0008473179,0.002298856,0.0010088024,0.9935693,0.001335839,0.0005044397],"study_design_scores_gemma":[0.0033156977,0.00061318855,0.0010185894,0.001373376,0.00008145246,0.00021928406,0.00096099207,0.17368428,0.15497002,0.54685414,0.11515592,0.0017530466],"about_ca_topic_score_codex":0.000034924386,"about_ca_topic_score_gemma":0.000026535996,"teacher_disagreement_score":0.97086513,"about_ca_system_score_codex":0.000029096685,"about_ca_system_score_gemma":0.00004812225,"threshold_uncertainty_score":0.44884554},"labels":[],"label_agreement":null},{"id":"W1593161808","doi":"10.1007/978-3-540-69554-7_20","title":"Toward Quality-Driven Development of 3D Computer Games","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Quality (philosophy); Computer science; Video game development; Perspective (graphical); Implementation; Game Developer; Video game; Multimedia; Multidisciplinary approach; Development (topology); Game design; Human–computer interaction; Software engineering; Artificial intelligence","score_opus":0.0699017961035294,"score_gpt":0.33359984271226234,"score_spread":0.26369804660873297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1593161808","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000051070663,0.00012722546,0.9952444,0.00016122675,0.0011653007,0.00022712129,0.00000916913,0.0001331866,0.002881335],"genre_scores_gemma":[0.017226787,0.000027866006,0.98038965,0.0017048841,0.0003032576,0.0000020562256,0.000027755328,0.00002905213,0.00028869882],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9953019,0.000044361983,0.0011939417,0.0013339012,0.0015061953,0.000619716],"domain_scores_gemma":[0.997061,0.00037303445,0.0006037499,0.0012879153,0.00046270763,0.00021160446],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0014836675,0.00051941845,0.0007365404,0.0011537082,0.00017266754,0.0003615215,0.0037663188,0.00030100995,0.00003803951],"category_scores_gemma":[0.000060292045,0.0004806033,0.00012822283,0.00080222706,0.0006367243,0.00050771714,0.002050081,0.0005016117,0.000058783186],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003782365,0.000063215586,0.000090916175,0.000118814045,0.000026946314,0.00003678128,0.0026622768,0.009465508,0.000048572154,0.06917764,0.000052621483,0.91825294],"study_design_scores_gemma":[0.000636832,0.00020050931,0.00057800487,0.00096851226,0.000015848107,0.00004515892,8.8624523e-7,0.9418008,0.0034689645,0.01963571,0.031072926,0.0015758837],"about_ca_topic_score_codex":0.000011830268,"about_ca_topic_score_gemma":0.00006678446,"teacher_disagreement_score":0.93233526,"about_ca_system_score_codex":0.00024019064,"about_ca_system_score_gemma":0.0009657717,"threshold_uncertainty_score":0.99976456},"labels":[],"label_agreement":null},{"id":"W1596291969","doi":"10.1007/978-3-642-17650-0_31","title":"IDS Alert Visualization and Monitoring through Heuristic Host Selection","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Visualization; Heuristic; Intrusion detection system; Visual analytics; Metric (unit); Animation; Data mining; Heuristics; Task (project management); Human–computer interaction; Artificial intelligence; Computer graphics (images)","score_opus":0.021991865317523954,"score_gpt":0.3004483520345478,"score_spread":0.27845648671702383,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1596291969","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00013537589,0.00018031086,0.99652267,0.00017167248,0.0017859684,0.00018579075,0.0000041338335,0.00018514319,0.00082892587],"genre_scores_gemma":[0.3487133,0.0007312403,0.6452771,0.0019196111,0.002072167,0.000011389838,0.0000419299,0.000104857914,0.0011283827],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99730873,0.000026883406,0.00040892026,0.0011324566,0.00072259223,0.00040040968],"domain_scores_gemma":[0.99852824,0.00018223928,0.00024002738,0.0006408024,0.0002812346,0.00012744805],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004431766,0.00038102997,0.00033381008,0.0004919361,0.00036996324,0.0009261224,0.0012708675,0.00031220773,0.000014403408],"category_scores_gemma":[0.00013032321,0.00037192338,0.000050429193,0.0007223652,0.00041247415,0.0010348512,0.00074913324,0.0005793189,0.000020115958],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010797585,0.00013906632,0.0024052097,0.0002612874,0.000047140198,0.0000806654,0.0043824776,0.0062215,0.0052035614,0.48405954,0.00009458226,0.49709415],"study_design_scores_gemma":[0.00027535317,0.00016013422,0.00048058326,0.00039381307,0.000017712624,0.00009208734,4.0221158e-7,0.9171692,0.008432643,0.065986626,0.006175529,0.000815923],"about_ca_topic_score_codex":0.00002230994,"about_ca_topic_score_gemma":0.000033207598,"teacher_disagreement_score":0.9109477,"about_ca_system_score_codex":0.00012285104,"about_ca_system_score_gemma":0.00024766233,"threshold_uncertainty_score":0.9998733},"labels":[],"label_agreement":null},{"id":"W1597028771","doi":"","title":"A Strategy for Uncertainty Visualization Design","year":2009,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Visualization; Computer science; Uncertainty analysis; Data visualization; Focus (optics); Data science; Representation (politics); Information visualization; Uncertainty quantification; Creative visualization; Data mining; Management science; Machine learning; Simulation; Engineering","score_opus":0.07679228800910015,"score_gpt":0.3629856319289798,"score_spread":0.28619334391987966,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1597028771","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000017746304,0.000008008045,0.99729,0.00041926265,0.00003864244,0.00013906661,0.0000017219587,0.0001706248,0.0019149255],"genre_scores_gemma":[0.7747823,0.000020675194,0.21407612,0.0068655903,0.00008638465,0.000011154022,0.000088046385,0.000008104845,0.0040616086],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99945956,0.000025318232,0.00012352897,0.00016705581,0.00010146364,0.0001230509],"domain_scores_gemma":[0.99959564,0.000037425893,0.000035455723,0.00019071004,0.00009325026,0.000047509162],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017957985,0.000059735386,0.00006328385,0.000053544765,0.00006298551,0.00018558885,0.00029790623,0.000025444546,0.00002183428],"category_scores_gemma":[0.000039518,0.000050520895,0.00002527842,0.00027545542,0.0000062160807,0.0003378449,0.00001514346,0.000013543663,0.000017160837],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002025358,0.000037861424,0.0000025767417,0.0000016939578,0.00000216688,3.2610663e-7,0.00004055212,0.0075141476,0.00012692477,0.95835036,0.0131371375,0.020784238],"study_design_scores_gemma":[0.00019292331,0.00016419783,0.000046186913,0.000002687353,0.0000023039083,9.142174e-7,0.000014332914,0.96354556,0.0009260628,0.028849829,0.0061729806,0.000082046194],"about_ca_topic_score_codex":0.0000023369123,"about_ca_topic_score_gemma":0.0000017412115,"teacher_disagreement_score":0.9560314,"about_ca_system_score_codex":0.00001302657,"about_ca_system_score_gemma":0.000049324633,"threshold_uncertainty_score":0.20601824},"labels":[],"label_agreement":null},{"id":"W1597907781","doi":"10.1007/11783183_33","title":"Perceiving Relationships: A Physiological Examination of the Perception of Scatterplots","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Bivariate analysis; Readability; Computer science; Perception; Cognitive psychology; Artificial intelligence; Pattern recognition (psychology); Psychology; Machine learning; Neuroscience","score_opus":0.03916538226403094,"score_gpt":0.2784495025827133,"score_spread":0.23928412031868235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1597907781","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003463536,0.000027074533,0.99470943,0.00017893543,0.00029448402,0.00016570157,0.0000064759233,0.000033444692,0.0011208938],"genre_scores_gemma":[0.9551876,0.0000095309715,0.044313926,0.0001737934,0.0000912549,0.0000014085649,0.000010386147,0.000008864668,0.00020321786],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99799466,0.000098243196,0.0004759315,0.0005538989,0.0006932273,0.00018406412],"domain_scores_gemma":[0.99822915,0.0002394676,0.00042451642,0.0008150208,0.00025858928,0.00003325233],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080419116,0.00019829292,0.0002760126,0.00037425937,0.00015356144,0.00008974178,0.0018030741,0.00017469209,0.000012674383],"category_scores_gemma":[0.00015704133,0.00014313558,0.00010613583,0.0006190221,0.0006177576,0.00036757332,0.0006871469,0.0003476546,0.0000052780856],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005001784,0.00031246807,0.0032133302,0.0003402398,0.00002719087,0.0000068969293,0.007912798,0.21440293,0.014299274,0.097655356,0.00034194777,0.6614826],"study_design_scores_gemma":[0.00012726978,0.00007657019,0.12408897,0.00051955844,0.000011108453,0.000008460145,0.0000011001846,0.8479621,0.00057832774,0.026290506,0.00006822621,0.00026779046],"about_ca_topic_score_codex":0.000014896953,"about_ca_topic_score_gemma":0.000019530167,"teacher_disagreement_score":0.9517241,"about_ca_system_score_codex":0.00010703667,"about_ca_system_score_gemma":0.00014848904,"threshold_uncertainty_score":0.5836899},"labels":[],"label_agreement":null},{"id":"W1602338941","doi":"10.1007/3-540-45490-x_59","title":"Implementation Issues and Paradigms of Visual KDD Systems","year":2001,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Visualization; Knowledge extraction; Data mining; Data science; Artificial intelligence; Information retrieval","score_opus":0.02427486315615486,"score_gpt":0.334340150202316,"score_spread":0.31006528704616115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1602338941","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000101889615,0.0006496477,0.9965322,0.00021780435,0.00079447025,0.00022029325,0.0000098316195,0.0000562358,0.0014176263],"genre_scores_gemma":[0.70514685,0.003029402,0.28268912,0.0028788587,0.0028486685,0.000022673312,0.00017725729,0.00013466687,0.003072525],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977414,0.000028633282,0.000499671,0.0007512999,0.00067834905,0.00030062755],"domain_scores_gemma":[0.9987258,0.00012966138,0.00031639382,0.0005506156,0.00017382826,0.00010373124],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005293493,0.00027149875,0.0003859128,0.00056360627,0.000106055646,0.00045855655,0.0011314448,0.00012752085,0.000017466024],"category_scores_gemma":[0.000021615677,0.000249126,0.00004463484,0.0004544193,0.00035581898,0.00054762175,0.0005984405,0.00018098537,0.000008064143],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000033211404,0.000047966143,0.0009357452,0.00014749805,0.000025335128,0.000042502554,0.0010257596,0.0073267967,0.00010580635,0.34797615,0.00027230257,0.6420908],"study_design_scores_gemma":[0.0003661129,0.0003033369,0.00025811023,0.00035676896,0.000015062258,0.00007164529,0.0000020108616,0.9504919,0.0007510699,0.025160436,0.021651557,0.00057195476],"about_ca_topic_score_codex":0.000105414656,"about_ca_topic_score_gemma":0.000052568364,"teacher_disagreement_score":0.9431651,"about_ca_system_score_codex":0.00007256065,"about_ca_system_score_gemma":0.00018441076,"threshold_uncertainty_score":0.9999961},"labels":[],"label_agreement":null},{"id":"W1602561032","doi":"10.1007/978-3-642-39872-8_7","title":"A Visual Interface for Analyzing Text Conversations","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in business information processing","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Interface (matter); Human–computer interaction; Natural language user interface; Asynchronous communication; User interface; Conversation; Population; Task (project management); Natural user interface; Process (computing); Formative assessment; World Wide Web; User interface design; User experience design; Engineering; Communication","score_opus":0.01785101074853722,"score_gpt":0.2860322274140917,"score_spread":0.26818121666555444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1602561032","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000004781934,0.00020336511,0.98905915,0.0010765572,0.00032144214,0.00041459003,0.000022027667,0.00017208967,0.008726001],"genre_scores_gemma":[0.51329714,0.0007512993,0.44129834,0.016209027,0.0013506695,0.00039665666,0.0064303675,0.00034259516,0.01992394],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983692,0.000009745446,0.0007660194,0.00028610672,0.00030579465,0.00026310724],"domain_scores_gemma":[0.99775517,0.00014577378,0.0006834721,0.00031018892,0.0010457828,0.000059616592],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00020614007,0.00034210578,0.0003491601,0.00077560934,0.00020101345,0.0012026649,0.00060774066,0.00032042435,0.000113197304],"category_scores_gemma":[0.00042397043,0.00032850687,0.00007265145,0.0005016279,0.00005479279,0.0043636872,0.00019061538,0.00026069683,0.000139637],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011897404,0.000026498277,0.00003088194,0.0012734706,0.00004097761,9.850244e-7,0.0023339784,0.01820825,0.000015954414,0.092775814,0.0008521185,0.88442916],"study_design_scores_gemma":[0.00054732664,0.000023528977,0.00003326765,0.00093651155,0.000036125046,0.0000055942646,0.000016626416,0.8372654,0.0002118558,0.01976484,0.14050858,0.00065037544],"about_ca_topic_score_codex":0.000008368361,"about_ca_topic_score_gemma":0.00001436907,"teacher_disagreement_score":0.8837788,"about_ca_system_score_codex":0.0001513512,"about_ca_system_score_gemma":0.00033713927,"threshold_uncertainty_score":0.9999167},"labels":[],"label_agreement":null},{"id":"W1602715715","doi":"10.1007/978-3-540-89900-6_7","title":"Computational Modeling of Criminal Activity","year":2008,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Computational model; Criminal behaviour; Management science; Range (aeronautics); Criminal investigation; Data science; Operations research; Computer security; Criminology; Artificial intelligence; Engineering","score_opus":0.04812752710449014,"score_gpt":0.30185778814895503,"score_spread":0.2537302610444649,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1602715715","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00016193841,0.00010266652,0.99709374,0.00016947452,0.00044579347,0.00012150158,0.000011909624,0.00007222791,0.001820772],"genre_scores_gemma":[0.53542054,0.000072806346,0.46355528,0.00060500327,0.00017297346,0.0000013965034,0.000016156251,0.00002161865,0.00013421894],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972188,0.000024266415,0.00044553628,0.00089538586,0.0010807236,0.00033531527],"domain_scores_gemma":[0.99823743,0.00020628501,0.0002761358,0.0007693469,0.00039230255,0.00011851416],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00038956187,0.0003184828,0.00042894107,0.00072504755,0.0001706127,0.00016675115,0.0021143577,0.00016965032,0.000014402766],"category_scores_gemma":[0.00006127669,0.00031237592,0.00011471451,0.0005011689,0.00048345554,0.00061676407,0.0008936708,0.00039763836,0.000016075233],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000028086165,0.000036239166,0.000010076367,0.00003395223,0.0000070647357,0.000023952529,0.0004441293,0.84644747,0.00001581291,0.02025168,0.00002262158,0.13270417],"study_design_scores_gemma":[0.0001418865,0.00006228167,0.000020662694,0.0001409086,0.0000062331355,0.000046017205,8.269976e-8,0.96549267,0.00018953069,0.03344695,0.00015254163,0.00030022283],"about_ca_topic_score_codex":0.000018253339,"about_ca_topic_score_gemma":0.00001024236,"teacher_disagreement_score":0.5352586,"about_ca_system_score_codex":0.0001279934,"about_ca_system_score_gemma":0.0007147556,"threshold_uncertainty_score":0.9999328},"labels":[],"label_agreement":null},{"id":"W1604239240","doi":"10.1109/iv.2015.47","title":"Literature Visualization and Similarity Measurement Based on Citation Relations","year":2015,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Similarity (geometry); Citation; Computer science; Information retrieval; Relation (database); Visualization; Graph; Citation analysis; Natural language processing; Data mining; Artificial intelligence; Theoretical computer science; World Wide Web; Image (mathematics)","score_opus":0.08739348716039871,"score_gpt":0.3173489160409885,"score_spread":0.2299554288805898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1604239240","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00019993252,0.00002967907,0.9918481,0.0013874775,0.0000904132,0.0000761236,0.0000034564462,0.000121708596,0.006243126],"genre_scores_gemma":[0.9765494,0.0000058160776,0.019705916,0.0031425632,0.000030718336,0.0000044279655,0.00011027335,0.0000061099636,0.0004447727],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99909127,0.00007390884,0.0001235164,0.00018763122,0.00044913215,0.00007456638],"domain_scores_gemma":[0.9992135,0.0000259772,0.000043155636,0.00021266083,0.0004034008,0.00010129289],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004957055,0.00006865268,0.000055032015,0.00014158843,0.00007130593,0.00029673654,0.000119905024,0.00004188242,0.000009478946],"category_scores_gemma":[0.00032242638,0.000059363978,0.000013330402,0.0005544056,0.000011261781,0.0004741897,0.000031514155,0.000044152068,0.000021294352],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000046012724,0.000118052834,0.001599485,0.000010440034,0.000005237013,0.0000016662556,0.0008483462,0.0023077046,0.00003540449,0.9679873,0.025189595,0.0018921559],"study_design_scores_gemma":[0.00031912045,0.000057627563,0.0014344892,0.000026512289,0.000003873372,5.434063e-7,0.000027229104,0.98619884,0.00013384593,0.004051444,0.0076615503,0.000084915395],"about_ca_topic_score_codex":0.0000027363133,"about_ca_topic_score_gemma":0.0000076080546,"teacher_disagreement_score":0.9838911,"about_ca_system_score_codex":0.000048793376,"about_ca_system_score_gemma":0.00007099861,"threshold_uncertainty_score":0.28614375},"labels":[],"label_agreement":null},{"id":"W1608061033","doi":"10.1007/11556992_2","title":"SVision: A Network Host-Centered Anomaly Visualization Technique","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Denial-of-service attack; Intrusion detection system; Anomaly detection; Visualization; Network security; Ping (video games); Botnet; Data mining; Host (biology); Network administrator; Internet Control Message Protocol; Anomaly (physics); Computer security; Computer network; The Internet; World Wide Web; Network packet","score_opus":0.01989551824396039,"score_gpt":0.2870438955490729,"score_spread":0.2671483773051125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1608061033","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000004189506,0.00032042497,0.99361575,0.0005240615,0.0010637192,0.0005148984,0.000009463611,0.00033432886,0.0036131928],"genre_scores_gemma":[0.054458555,0.000386156,0.93131644,0.008826304,0.0025380037,0.000030145911,0.00012048857,0.00011833895,0.0022055716],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99587274,0.00005742267,0.0007303319,0.001559998,0.0010753794,0.00070412183],"domain_scores_gemma":[0.9972465,0.00017947223,0.00043011253,0.0015789975,0.00034632455,0.0002185812],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009895755,0.00055993476,0.00053112494,0.0008284444,0.0003106891,0.0009335489,0.0034734895,0.000386828,0.00007926834],"category_scores_gemma":[0.00008408976,0.00053622236,0.0001420617,0.0013505818,0.00038872365,0.0009727354,0.0016221938,0.00051003345,0.00008806817],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012020545,0.00014927836,0.00025622503,0.00008574092,0.000032416392,0.00015074553,0.0005582845,0.04630256,0.000250059,0.35011023,0.0012046397,0.6008878],"study_design_scores_gemma":[0.00030291264,0.00018546497,0.000098285935,0.00069915043,0.000012153234,0.000082714265,9.424676e-8,0.9233349,0.00077491434,0.03430446,0.039295178,0.0009098035],"about_ca_topic_score_codex":0.0000076603055,"about_ca_topic_score_gemma":0.000052329076,"teacher_disagreement_score":0.87703234,"about_ca_system_score_codex":0.00028859146,"about_ca_system_score_gemma":0.0004872388,"threshold_uncertainty_score":0.99970895},"labels":[],"label_agreement":null},{"id":"W1626228617","doi":"10.1007/978-3-642-25878-7_20","title":"Optimizing a Radial Layout of Bipartite Graphs for a Tool Visualizing Security Alerts","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Bipartite graph; Enhanced Data Rates for GSM Evolution; Computer science; Visualization; Graph drawing; Graph; Clutter; Theoretical computer science; Minification; Algorithm; Data mining; Artificial intelligence; World Wide Web; Radar","score_opus":0.03367026177666435,"score_gpt":0.2912855808593612,"score_spread":0.25761531908269686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1626228617","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009437669,0.0002214239,0.9970036,0.00008672317,0.0010222474,0.00043383247,0.000035749454,0.00010798576,0.0009940686],"genre_scores_gemma":[0.23818983,0.00015786754,0.75856364,0.0021861494,0.00048319378,0.000026279205,0.000052795665,0.00008267151,0.00025758005],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9968575,0.000032973938,0.00071045035,0.0011578565,0.0006746941,0.00056648883],"domain_scores_gemma":[0.9976246,0.00031741185,0.0004854234,0.0010926614,0.00035397505,0.00012594133],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009485948,0.00043066402,0.0006087404,0.0009458294,0.00019344655,0.00035376253,0.0025661106,0.00025051556,0.000019708163],"category_scores_gemma":[0.0001440562,0.0004117711,0.00022999496,0.0006765574,0.0005228437,0.00073894416,0.00096204877,0.00031235444,0.0000074809027],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027704302,0.00013758885,0.00010450611,0.00028860147,0.00005989843,0.00003664183,0.007298492,0.010856764,0.0002578782,0.7527564,0.00017340122,0.22800213],"study_design_scores_gemma":[0.00041870493,0.00021227615,0.000011020599,0.00046274168,0.000021540061,0.000017134318,3.3247392e-7,0.7420083,0.0029932926,0.25005352,0.0031845768,0.00061650714],"about_ca_topic_score_codex":0.000020909283,"about_ca_topic_score_gemma":0.000041487358,"teacher_disagreement_score":0.7311516,"about_ca_system_score_codex":0.00008513452,"about_ca_system_score_gemma":0.0004108104,"threshold_uncertainty_score":0.9998334},"labels":[],"label_agreement":null},{"id":"W1648195614","doi":"10.1007/978-3-642-14600-8_46","title":"An Examination of Cleveland and McGill’s Hierarchy of Graphical Elements","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of New Brunswick; Queen's University","funders":"","keywords":"Perception; Hierarchy; Computer science; Graph; Reading (process); Affect (linguistics); Graph theory; Information retrieval; Artificial intelligence; Theoretical computer science; Psychology; Mathematics; Communication; Linguistics; Combinatorics","score_opus":0.01934599227403942,"score_gpt":0.28444936085891914,"score_spread":0.2651033685848797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1648195614","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023540426,0.00002955998,0.99666995,0.00007217974,0.00026162784,0.00012397105,0.000028953042,0.00002315862,0.0004365853],"genre_scores_gemma":[0.69762355,0.00005158471,0.3019594,0.00025091346,0.00005171647,9.702841e-7,0.000017703373,0.000011104165,0.00003308356],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980329,0.0000337219,0.00045927803,0.00062829175,0.00064802583,0.00019776536],"domain_scores_gemma":[0.99847585,0.00014462501,0.0003171939,0.00070024544,0.00025583463,0.00010626568],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008455342,0.00019782153,0.00030688423,0.0007321758,0.000092108334,0.000086396954,0.0013639994,0.00018947363,0.000009548182],"category_scores_gemma":[0.00006138365,0.00017838951,0.000038597176,0.00042207408,0.00067715294,0.00046362527,0.0004928164,0.00030923428,8.297339e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000025982085,0.0000675344,0.0003846931,0.0000658311,0.00000893589,0.0000065602703,0.00037444537,0.0002429309,0.0021872874,0.16594592,0.0000017129947,0.83071154],"study_design_scores_gemma":[0.00058479403,0.0006035541,0.0087431995,0.00032225068,0.00001781152,0.000027886517,3.8048168e-7,0.78656334,0.014904254,0.18651296,0.0011184771,0.0006010763],"about_ca_topic_score_codex":0.0000068338863,"about_ca_topic_score_gemma":0.000040107032,"teacher_disagreement_score":0.8301105,"about_ca_system_score_codex":0.000021130687,"about_ca_system_score_gemma":0.00010082736,"threshold_uncertainty_score":0.7274513},"labels":[],"label_agreement":null},{"id":"W1656389077","doi":"10.14778/2735479.2735485","title":"Rapid sampling for visualizations with ordering guarantees","year":2015,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":102,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Institute of General Medical Sciences","keywords":"Computer science; Bar chart; Visualization; Focus (optics); Sampling (signal processing); Chart; Theoretical computer science; Property (philosophy); Algorithm; Data mining; Mathematics; Statistics; Computer vision","score_opus":0.07172555247471732,"score_gpt":0.31408397678660194,"score_spread":0.24235842431188462,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1656389077","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008944848,0.000120233424,0.9858029,0.0015128406,0.00020855539,0.00055727793,0.000011149411,0.00013807246,0.0027041093],"genre_scores_gemma":[0.82699096,0.000048744645,0.1715887,0.00060775795,0.00009691161,0.00008523791,0.0000075583603,0.000026105798,0.0005479872],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99918526,0.000002819071,0.00019005343,0.00018654151,0.0002775141,0.00015779384],"domain_scores_gemma":[0.9992229,0.000023112716,0.00016183457,0.00013025966,0.0004044468,0.000057492067],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026222557,0.00009329687,0.00011655676,0.000067316716,0.00010635403,0.0001379919,0.00067925197,0.000018275323,0.0000022961588],"category_scores_gemma":[0.00012833712,0.00005999887,0.00004045055,0.00042715008,0.000035534787,0.00035357772,0.00022129857,0.000032700078,0.0000016336035],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028952405,0.0002120583,0.0024033627,0.0001689449,0.000085463646,1.2236166e-7,0.0030682608,0.0007315007,0.0051216017,0.97430307,0.0070352433,0.006841437],"study_design_scores_gemma":[0.0054413993,0.001120515,0.0006800156,0.000747427,0.00017637748,0.000045396548,0.0038682467,0.45422578,0.2367887,0.035179563,0.26070443,0.0010221543],"about_ca_topic_score_codex":0.0000067432675,"about_ca_topic_score_gemma":0.0000017713617,"teacher_disagreement_score":0.9391235,"about_ca_system_score_codex":0.000031194766,"about_ca_system_score_gemma":0.00005217185,"threshold_uncertainty_score":0.24466829},"labels":[],"label_agreement":null},{"id":"W1660789187","doi":"10.5220/0004686603370346","title":"Visualizing Large Scale Vehicle Traffic Network Data - A Survey of the State-of-the-art","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Visualization; Computer science; Field (mathematics); Data science; Process (computing); Data visualization; Scale (ratio); State (computer science); Information visualization; Creative visualization; Data mining; Geography","score_opus":0.04331277554157737,"score_gpt":0.31079774117957953,"score_spread":0.26748496563800217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1660789187","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07624682,0.000033256347,0.92159355,0.00037039816,0.00045338154,0.00014277115,0.00011784022,0.00006094607,0.0009810408],"genre_scores_gemma":[0.99621516,0.0000063447446,0.0020390302,0.0006472391,0.000021385365,5.0637846e-7,0.000043643136,0.0000069893604,0.0010196816],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99868256,0.0003351731,0.00027570082,0.00022314845,0.00029322453,0.00019018559],"domain_scores_gemma":[0.9979623,0.00015227268,0.00015521437,0.0015995242,0.00009249539,0.000038220893],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016623664,0.00007198298,0.0001358855,0.000018579305,0.000103935556,0.00006406352,0.0025034845,0.000020703445,0.000018506365],"category_scores_gemma":[0.00016160488,0.000042325235,0.000036614256,0.0008401026,0.000057525234,0.00026200066,0.0014118876,0.000058791255,0.00001482711],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022409018,0.001211028,0.2241498,0.00018216003,0.00015122883,6.653897e-7,0.0026714902,0.0397317,0.000618874,0.12365832,0.5472565,0.060345806],"study_design_scores_gemma":[0.00016189484,0.000013283149,0.03425674,0.000024071935,0.0000047530316,3.637877e-7,0.000008021744,0.9493763,0.0003751098,0.00016558022,0.015548775,0.00006512084],"about_ca_topic_score_codex":0.000074127944,"about_ca_topic_score_gemma":0.0016170373,"teacher_disagreement_score":0.91996837,"about_ca_system_score_codex":0.000005033896,"about_ca_system_score_gemma":0.000058063757,"threshold_uncertainty_score":0.46521387},"labels":[],"label_agreement":null},{"id":"W169688737","doi":"","title":"Supporting Coherence with a 3D Instant Messenger Visualization","year":2002,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Instant; Conversation; Computer science; Human–computer interaction; Coherence (philosophical gambling strategy); Metaphor; Visualization; Casual; Point (geometry); Space (punctuation); Multimedia; Artificial intelligence; Communication; Psychology","score_opus":0.028704508314227453,"score_gpt":0.30681966240258535,"score_spread":0.2781151540883579,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W169688737","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010334493,0.000018174052,0.97012204,0.00026769142,0.00003268011,0.00007013044,0.0000013235826,0.00023821603,0.028216299],"genre_scores_gemma":[0.96078056,0.000020421016,0.031360272,0.0015713224,0.000019203779,0.0000047496214,0.000012766175,0.000010000996,0.006220723],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990988,0.000026636844,0.00018952249,0.00023749463,0.00025788174,0.00018970994],"domain_scores_gemma":[0.9994159,0.000021170197,0.00009485593,0.0002986204,0.000097746124,0.00007172167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012609789,0.00008724717,0.00008926533,0.000070857386,0.00008264842,0.00021331444,0.0003346207,0.00002419486,0.000751721],"category_scores_gemma":[0.00003294083,0.00006474313,0.000013746595,0.0006102165,0.000024172074,0.0006497438,0.0000846376,0.00003771039,0.000117534495],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002722027,0.00029549835,0.004364309,0.000036996113,0.00003197432,0.000055553828,0.0018004234,0.00035488207,0.0008443138,0.9479705,0.020651672,0.023591138],"study_design_scores_gemma":[0.00023521548,0.00006700269,0.00016065969,0.00001919006,0.0000047863646,0.00001438521,0.00006710784,0.96566194,0.0010424824,0.00011443266,0.03243584,0.00017697767],"about_ca_topic_score_codex":0.0000070800957,"about_ca_topic_score_gemma":0.000014015753,"teacher_disagreement_score":0.96530706,"about_ca_system_score_codex":0.000013931913,"about_ca_system_score_gemma":0.00001911909,"threshold_uncertainty_score":0.82308173},"labels":[],"label_agreement":null},{"id":"W1721597202","doi":"","title":"Graph Comprehension: An Experiment in Displaying Data as Bar Charts, Pie Charts and Tables with and without the Gratuitous 3rd Dimension","year":2008,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Bar chart; Pie chart; Chart; Dimension (graph theory); Graph; Computer science; \\bar x and R chart; Bar (unit); Table (database); Statistics; Mathematics; Control chart; Data mining; Combinatorics; Geography; EWMA chart; Process (computing); Theoretical computer science","score_opus":0.028481819582942148,"score_gpt":0.2884754510224593,"score_spread":0.25999363143951715,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1721597202","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93862087,0.0068688192,0.05304683,0.0010869743,0.00010061362,0.00018295548,0.000004955787,0.000040119652,0.00004788405],"genre_scores_gemma":[0.99038947,0.008283855,0.00077967445,0.00034802433,0.00005244604,0.000002232922,0.000022651891,0.000012664319,0.00010895997],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99815667,0.000114715316,0.00021640013,0.00038649098,0.0003311189,0.000794589],"domain_scores_gemma":[0.99913865,0.000025409578,0.00011593697,0.0005472953,0.00004647673,0.00012625454],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006913696,0.00016569866,0.0001800632,0.00010697037,0.00056443736,0.00022185352,0.00060100015,0.00003382788,0.0000036976605],"category_scores_gemma":[0.000012243569,0.000104138424,0.000013337597,0.00023636645,0.00012526997,0.0010348074,0.00031576204,0.00051227177,0.0000020101857],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002970501,0.0009446245,0.11382268,0.000039790008,0.00036512074,0.00028958629,0.011440129,0.00042203843,0.0069403704,0.8278222,0.0016227653,0.03599365],"study_design_scores_gemma":[0.015671693,0.007289873,0.04876396,0.0010459375,0.0002710352,0.05851738,0.019183327,0.7388237,0.0026430804,0.07373598,0.030319698,0.0037343423],"about_ca_topic_score_codex":0.00008411838,"about_ca_topic_score_gemma":0.00030726253,"teacher_disagreement_score":0.7540862,"about_ca_system_score_codex":0.000057775134,"about_ca_system_score_gemma":0.00039959076,"threshold_uncertainty_score":0.4341253},"labels":[],"label_agreement":null},{"id":"W1727854234","doi":"10.1007/978-3-540-73214-3_15","title":"Visualization of Uncertainty and Reasoning","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":66,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Visualization; Data visualization; Process (computing); Data science; Visual reasoning; Cognition; Analytic reasoning; Information visualization; Visual analytics; Uncertainty analysis; Artificial intelligence; Reasoning system; Psychology; Simulation; Programming language","score_opus":0.025701768726409516,"score_gpt":0.30809851065156424,"score_spread":0.28239674192515474,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1727854234","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000039708975,0.00023509742,0.99615353,0.0000727546,0.00035980766,0.00012045495,0.0000041747307,0.00006227912,0.0029522122],"genre_scores_gemma":[0.26122433,0.000492891,0.7335972,0.0032306754,0.00049470813,0.0000026830917,0.000065963584,0.00006975022,0.00082176394],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99784774,0.00001866751,0.00043276788,0.00074701017,0.00066415465,0.0002896919],"domain_scores_gemma":[0.9984755,0.00020828508,0.00030016043,0.0006393265,0.00026813993,0.00010857864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00090934744,0.00024975074,0.0003276393,0.0007553316,0.00010876712,0.00022950163,0.001164815,0.00017561919,0.0000110453775],"category_scores_gemma":[0.00013774652,0.00023410471,0.00004536082,0.0006596918,0.00048050372,0.0004120365,0.0007461787,0.00020896306,0.000004213139],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000029102064,0.000019784235,0.0001936389,0.000059678536,0.00000801258,0.000017819704,0.00062058447,0.016418058,0.000059156828,0.51416653,0.00001695417,0.4684169],"study_design_scores_gemma":[0.00015413556,0.000080462145,0.00010830587,0.00035858498,0.0000061819037,0.000020471945,2.1103087e-7,0.95680946,0.000527601,0.04010574,0.001524856,0.00030399195],"about_ca_topic_score_codex":0.00002013669,"about_ca_topic_score_gemma":0.0000461619,"teacher_disagreement_score":0.9403914,"about_ca_system_score_codex":0.0000838751,"about_ca_system_score_gemma":0.00023425584,"threshold_uncertainty_score":0.9546513},"labels":[],"label_agreement":null},{"id":"W1741715216","doi":"10.1002/0470013192.bsa261","title":"Graphical Presentation of Longitudinal Data","year":2005,"lang":"en","type":"other","venue":"Encyclopedia of Statistics in Behavioral Science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; TRACE (psycholinguistics); Graphics; Presentation (obstetrics); Representation (politics); Simple (philosophy); Process (computing); Longitudinal data; Theoretical computer science; External Data Representation; Data science; Computer graphics (images); Artificial intelligence; Programming language; Data mining; Linguistics; Epistemology","score_opus":0.05226451410764097,"score_gpt":0.3875277921156081,"score_spread":0.3352632780079671,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1741715216","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00015761431,0.0001749246,0.8680975,0.00004584872,0.0007892607,0.00033692643,0.0031417005,0.00007291072,0.12718335],"genre_scores_gemma":[0.01619166,0.0030800481,0.9191357,0.000031282976,0.00022055888,0.000010669152,0.0010875287,0.00013134864,0.06011121],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99749017,0.00003925524,0.0005337007,0.00062885677,0.0010456966,0.00026233317],"domain_scores_gemma":[0.99797225,0.00005903887,0.00047681262,0.0012585674,0.00013022301,0.00010311847],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052183453,0.00016969722,0.00030781137,0.00071862433,0.000031581472,0.000052324835,0.0034829187,0.00009654725,0.00034069494],"category_scores_gemma":[0.00016466505,0.00016747726,0.000020035879,0.0015604252,0.0008019064,0.0005011321,0.0009961108,0.00015755872,0.000009962705],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006960393,0.0015740745,0.060444523,0.00023096325,0.00001438257,0.0000680661,0.00057497976,0.000050854585,0.00014686892,0.41142395,0.3788818,0.14658257],"study_design_scores_gemma":[0.0029381665,0.0010133551,0.24573456,0.0017349531,0.0003853076,0.000033388533,0.00026609842,0.17246042,0.00046361805,0.0088972645,0.5626501,0.00342277],"about_ca_topic_score_codex":0.00078401715,"about_ca_topic_score_gemma":0.00085640344,"teacher_disagreement_score":0.40252668,"about_ca_system_score_codex":0.000031763302,"about_ca_system_score_gemma":0.00038682218,"threshold_uncertainty_score":0.68295246},"labels":[],"label_agreement":null},{"id":"W1748422605","doi":"10.1007/978-3-642-21852-1_40","title":"Visual Analytics of Social Networks: Mining and Visualizing Co-authorship Networks","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Visual analytics; Data science; Representation (politics); Social network analysis; Social network (sociolinguistics); Visualization; Information retrieval; World Wide Web; Data mining; Social media","score_opus":0.04011063968085067,"score_gpt":0.3133402153665318,"score_spread":0.2732295756856811,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1748422605","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000104792205,0.00035459062,0.9970876,0.00007197989,0.00066981325,0.00016281892,0.0000053421445,0.00009554276,0.0014474976],"genre_scores_gemma":[0.85727835,0.0002663375,0.13898803,0.0017966892,0.0011777944,0.000003747018,0.000055271874,0.00008838227,0.00034537638],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9965466,0.00007645084,0.0007893277,0.0011690701,0.00075725943,0.00066124176],"domain_scores_gemma":[0.9978615,0.00039645575,0.0006291284,0.00062592817,0.00027229727,0.00021467922],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0013890882,0.00048969407,0.000729408,0.0008376629,0.00031894055,0.00050588284,0.0019746067,0.00047290753,0.000021038375],"category_scores_gemma":[0.000089165915,0.00050049415,0.00013066297,0.00089981215,0.0009935729,0.00054047955,0.0012433445,0.00054871524,0.0000031801142],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001926694,0.000104316496,0.0009210687,0.0001333579,0.00008575411,0.00008462898,0.00452253,0.06413418,0.000026548298,0.18822055,0.00019237041,0.74155545],"study_design_scores_gemma":[0.00019742735,0.00014075538,0.00022555231,0.0002513356,0.000025986574,0.000019502912,9.087759e-7,0.9865514,0.00009051877,0.01145304,0.00050508557,0.00053846516],"about_ca_topic_score_codex":0.000009295837,"about_ca_topic_score_gemma":0.000030939045,"teacher_disagreement_score":0.9224172,"about_ca_system_score_codex":0.000094559546,"about_ca_system_score_gemma":0.00025511865,"threshold_uncertainty_score":0.99974465},"labels":[],"label_agreement":null},{"id":"W1759766770","doi":"10.3138/cart.50.2.2662","title":"POI Pulse: A Multi-granular, Semantic Signature–Based Information Observatory for the Interactive Visualization of Big Geosocial Data","year":2015,"lang":"en","type":"article","venue":"Cartographica The International Journal for Geographic Information and Geovisualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":111,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Data science; Granularity; Visualization; Variety (cybernetics); Social media; Key (lock); Big data; Thematic map; Data visualization; Function (biology); World Wide Web; Information retrieval; Data mining; Artificial intelligence; Computer security; Geography","score_opus":0.05256202212160623,"score_gpt":0.33624360006953796,"score_spread":0.28368157794793175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1759766770","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012349766,0.0002552372,0.9914511,0.003221656,0.0024201293,0.00092772895,0.00038123655,0.0000733516,0.00003461749],"genre_scores_gemma":[0.9793838,0.00068758684,0.006002062,0.0071561495,0.00044889227,0.00014156513,0.0061284713,0.000025519135,0.000025929583],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99727017,0.00014412568,0.0011061991,0.00020742537,0.0010052604,0.0002668408],"domain_scores_gemma":[0.99368346,0.00047956803,0.0012810924,0.000546285,0.003868136,0.00014147698],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0027061426,0.00024585563,0.00023608922,0.000903833,0.00062554405,0.001291214,0.0020815812,0.00015332372,0.000004568504],"category_scores_gemma":[0.0015396881,0.00017023442,0.0002084265,0.001094944,0.00020816842,0.0054157064,0.0003208952,0.00020505738,0.0000021319668],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013883563,0.0006778069,0.016611027,0.0005008511,0.0017974938,0.0000030653243,0.018798845,0.017272394,0.00012582449,0.69362843,0.036636107,0.21255982],"study_design_scores_gemma":[0.0027506098,0.0001554704,0.0018112469,0.00007309038,0.00012646099,0.000031301854,0.001351362,0.8637285,0.00008755382,0.0029507594,0.12670293,0.00023065557],"about_ca_topic_score_codex":0.000072959,"about_ca_topic_score_gemma":0.0000706568,"teacher_disagreement_score":0.985449,"about_ca_system_score_codex":0.000047346493,"about_ca_system_score_gemma":0.00035547846,"threshold_uncertainty_score":0.99974555},"labels":[],"label_agreement":null},{"id":"W1764416848","doi":"10.15353/joci.v12i3.3278","title":"Urban Data in the primary classroom: bringing data literacy to the UK curriculum","year":2016,"lang":"en","type":"article","venue":"The Journal of Community Informatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Curriculum; Context (archaeology); Everyday life; Computer science; Premise; Narrative; Mathematics education; Qualitative property; Literacy; Data science; Pedagogy; Multimedia; Psychology; Geography","score_opus":0.06207645175822331,"score_gpt":0.3415265119577447,"score_spread":0.2794500601995214,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1764416848","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.050629016,0.00013208344,0.92765534,0.019024078,0.000294135,0.00020110508,0.000114924944,0.000021184049,0.0019281165],"genre_scores_gemma":[0.9788511,0.00037373797,0.0059681186,0.014471145,0.00017631205,5.3611365e-7,0.00007569544,0.0000072625685,0.000076111246],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975425,0.00088273734,0.0007736,0.000022428667,0.00057837646,0.00020036321],"domain_scores_gemma":[0.9925676,0.001405486,0.0005378266,0.005260748,0.00016974434,0.00005858384],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.010328155,0.00010687822,0.00015901926,0.00011929851,0.0004146683,0.000504267,0.021560108,0.00002562836,0.0000064857877],"category_scores_gemma":[0.00082137587,0.000039917657,0.000026652238,0.00062097557,0.00006940256,0.0032355634,0.0059609455,0.0006919615,0.000036733334],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001322477,0.00024937146,0.0026622606,0.000061105566,0.000068509275,0.0000023591326,0.19793622,0.00020263309,0.000013272339,0.0070041595,0.69529545,0.09649144],"study_design_scores_gemma":[0.0009344607,0.00018764942,0.006905927,0.0006634166,0.00008334704,0.00044474463,0.034046825,0.17713945,0.000015641652,0.0012115943,0.7780603,0.0003066076],"about_ca_topic_score_codex":0.000044809854,"about_ca_topic_score_gemma":0.000051366565,"teacher_disagreement_score":0.92822206,"about_ca_system_score_codex":0.000038413986,"about_ca_system_score_gemma":0.00011992367,"threshold_uncertainty_score":0.9837337},"labels":[],"label_agreement":null},{"id":"W179179730","doi":"","title":"Why Soccer Players Yell: Using RoboCup to Model the Advantage of Signaling.","year":2004,"lang":"en","type":"article","venue":"International Conference on Cognitive Modelling","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Artificial intelligence","score_opus":0.1507201680497561,"score_gpt":0.3716975937796816,"score_spread":0.2209774257299255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W179179730","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011411815,0.000007877065,0.9840149,0.001168832,0.00015705466,0.0001385997,0.00006803219,0.000037563896,0.0029953115],"genre_scores_gemma":[0.95893836,0.000024481555,0.036902685,0.0039490084,0.000041867144,0.000005603056,0.000022195994,0.00001147465,0.000104342376],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986225,0.000031507443,0.0002915055,0.00034087003,0.0005345061,0.00017915732],"domain_scores_gemma":[0.9987777,0.00008672887,0.00014610708,0.00019008126,0.0007226711,0.000076705306],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020222423,0.0001519305,0.00013979446,0.0001871123,0.000108019165,0.00018066901,0.000831318,0.000039409006,0.000037941165],"category_scores_gemma":[0.00005245643,0.0001250442,0.00007269649,0.0002214339,0.00006315389,0.00040122613,0.0001787304,0.00013906413,0.000027786415],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015109929,0.000043018434,0.00000696646,0.0000026850032,0.000024116229,0.000002122441,0.0005698536,0.6821209,0.0010343604,0.31572568,0.000014992874,0.00044014293],"study_design_scores_gemma":[0.00031791578,0.000039177787,9.221353e-7,0.00023225574,0.000011693211,0.0000020770146,0.00030536897,0.97034746,0.007416635,0.021119937,0.00005705905,0.00014951792],"about_ca_topic_score_codex":0.000057418787,"about_ca_topic_score_gemma":0.0000084928215,"teacher_disagreement_score":0.9475265,"about_ca_system_score_codex":0.00006551209,"about_ca_system_score_gemma":0.00016726248,"threshold_uncertainty_score":0.5099155},"labels":[],"label_agreement":null},{"id":"W1794864439","doi":"10.14288/sa.v1i1.186324","title":"University Journal Subscription Costs in the UK: An Exploratory Study","year":2015,"lang":"en","type":"article","venue":"Open Collections","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Publishing; License; Leverage (statistics); Computer science; Analytics; Business; World Wide Web; Political science; Data science","score_opus":0.10317017721965907,"score_gpt":0.33053105108125075,"score_spread":0.22736087386159168,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1794864439","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05773543,0.00003080951,0.6585924,0.0019999347,0.0022571627,0.0020191753,0.000029145802,0.0001469829,0.27718896],"genre_scores_gemma":[0.9614901,0.000016960677,0.0019191436,0.00058873254,0.00007969,0.000007160784,0.000010468632,0.000005814967,0.035881918],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991256,0.00040810794,0.00009003329,0.00012151434,0.00017315116,0.000081598075],"domain_scores_gemma":[0.9994559,0.000017111914,0.000043366595,0.00026349872,0.00014065018,0.00007942655],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.000909499,0.00004287822,0.00005585581,0.00009239879,0.0009949798,0.0023122204,0.001132437,0.000014694235,0.000028293578],"category_scores_gemma":[0.00003796229,0.000035306934,0.000011635628,0.0017130327,0.000013261924,0.00138746,0.00018525468,0.000101948375,0.000009622992],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002086512,0.0014852021,0.0039047927,4.892167e-7,0.000018599356,0.00008636312,0.0194025,0.00043624762,0.0000049339783,0.008533732,0.9651752,0.0009310572],"study_design_scores_gemma":[0.0068838415,0.0021354584,0.008712203,0.000028352559,0.000056843688,0.00023005554,0.39347696,0.10670535,0.000021867398,0.0049500735,0.47619194,0.000607052],"about_ca_topic_score_codex":0.00082236936,"about_ca_topic_score_gemma":0.015800366,"teacher_disagreement_score":0.9037547,"about_ca_system_score_codex":0.00015212895,"about_ca_system_score_gemma":0.00026385425,"threshold_uncertainty_score":0.99872345},"labels":[],"label_agreement":null},{"id":"W1821624969","doi":"10.1111/cgf.12393","title":"Evaluating the Impact of User Characteristics and Different Layouts on an Interactive Visualization for Decision Making","year":2014,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":71,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Visualization; Personalization; Human–computer interaction; Interactive visualization; Information visualization; Set (abstract data type); Visual analytics; User experience design; Focus (optics); Interactive visual analysis; Data visualization; World Wide Web; Data mining","score_opus":0.04802186889588619,"score_gpt":0.41210370332887425,"score_spread":0.3640818344329881,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1821624969","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27501366,0.0000030921406,0.72451484,0.00004535564,0.00020320056,0.00016635416,0.000015353728,0.00003219841,0.0000059292515],"genre_scores_gemma":[0.98927486,0.0000078381845,0.010067929,0.00050275004,0.00007947135,0.0000066896077,0.00004362687,0.000013703426,0.0000031523186],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99878836,0.00014437732,0.0003133482,0.0003103521,0.00025057048,0.00019300393],"domain_scores_gemma":[0.9982007,0.0007551431,0.0002768721,0.00046843482,0.00023948465,0.00005934953],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050939905,0.00016080291,0.00020455389,0.00018230616,0.00019455537,0.00028444445,0.0004975931,0.000050411694,0.0000018004829],"category_scores_gemma":[0.00017223322,0.00010369468,0.000098253484,0.00024682735,0.00004563379,0.0003588544,0.0002677182,0.0000826825,7.580137e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010010466,0.00028870278,0.018004134,0.00003475851,0.00007687628,3.5741155e-7,0.0011627403,0.0011375973,0.00015688229,0.75170004,0.00058987626,0.22674793],"study_design_scores_gemma":[0.00028389858,0.0012899768,0.0489618,0.00014028116,0.000011581151,0.0000021976816,0.000010665674,0.9392472,0.000049079837,0.0098079825,0.00007649244,0.00011883822],"about_ca_topic_score_codex":0.0000033329309,"about_ca_topic_score_gemma":0.0000042765682,"teacher_disagreement_score":0.93810964,"about_ca_system_score_codex":0.000020712729,"about_ca_system_score_gemma":0.000019080455,"threshold_uncertainty_score":0.42285463},"labels":[],"label_agreement":null},{"id":"W1826169607","doi":"10.1007/978-3-642-31223-6_33","title":"The Use of Diagrams in Science","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Sample (material); Graph; Representation (politics); Selection (genetic algorithm); Theoretical computer science; Data science; Information retrieval; Artificial intelligence","score_opus":0.049771448276070863,"score_gpt":0.29125751748439693,"score_spread":0.24148606920832608,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1826169607","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000093416034,0.00037450943,0.99730104,0.00040606078,0.0010768098,0.00020550867,0.000004772994,0.000041397903,0.00049649837],"genre_scores_gemma":[0.55773365,0.001073581,0.43614206,0.003341781,0.0005648566,0.000012584791,0.000012354515,0.00006531808,0.001053803],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9965135,0.000034426295,0.00057203276,0.00087218574,0.0013098769,0.0006979821],"domain_scores_gemma":[0.9968122,0.0007452323,0.00032576054,0.0016381289,0.00031562918,0.00016300025],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018947755,0.00029872646,0.00033391902,0.0008714497,0.00030612032,0.00094783946,0.005031556,0.00013162148,0.000006465553],"category_scores_gemma":[0.00041238143,0.0002140576,0.00007223185,0.0019227474,0.0026359223,0.001621309,0.0020236871,0.00044812355,0.000019848892],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000018755263,0.000037163572,0.00058464415,0.000015417862,0.0000030915737,0.000010296558,0.00058509107,0.009218726,0.000096129654,0.2090916,0.000031429787,0.7803245],"study_design_scores_gemma":[0.00018964014,0.000077794095,0.0010880631,0.0003135385,0.000005310765,0.000019683328,2.9072277e-7,0.9316124,0.0014240887,0.045535833,0.019197678,0.0005357255],"about_ca_topic_score_codex":0.000033758646,"about_ca_topic_score_gemma":0.00018476768,"teacher_disagreement_score":0.9223936,"about_ca_system_score_codex":0.00020165829,"about_ca_system_score_gemma":0.000744418,"threshold_uncertainty_score":0.97121656},"labels":[],"label_agreement":null},{"id":"W1837891624","doi":"10.1002/meet.2014.14505101020","title":"Filmmaker showcase: Film as an information medium: Connecting cultures and communities","year":2014,"lang":"en","type":"article","venue":"Proceedings of the American Society for Information Science and Technology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Filmmaking; Film director; Presentation (obstetrics); Theme (computing); Session (web analytics); Visual arts; Sociology; Media studies; Multimedia; Art; Computer science; World Wide Web; Movie theater; Medicine","score_opus":0.01279658571300732,"score_gpt":0.28951780317913983,"score_spread":0.2767212174661325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1837891624","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94619954,0.000010387915,0.04318529,0.008123914,0.0000791127,0.00033489577,0.000021001362,0.00025672305,0.0017891496],"genre_scores_gemma":[0.98025066,0.00005700459,0.016612437,0.0030443396,0.00000753184,0.000012738092,0.0000065269955,0.000001840265,0.000006921808],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992022,0.0000027127123,0.00023981024,0.0000815825,0.00029588156,0.00017784245],"domain_scores_gemma":[0.99830276,0.000043853903,0.00047218695,0.00014902747,0.0009833106,0.00004886024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009620295,0.0000809055,0.00012849414,0.00018318805,0.0006281414,0.0004126111,0.0008435766,0.000040603954,6.3766424e-7],"category_scores_gemma":[0.0006046644,0.000058582336,0.00003119226,0.001452514,0.0013645666,0.0072534895,0.00046712923,0.00009097567,9.887913e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000046962414,0.000013478554,0.0018598986,0.00009590933,0.0000141681785,2.7610012e-9,0.017510964,0.000008748552,0.0013221547,0.86206985,0.0033476888,0.11375245],"study_design_scores_gemma":[0.0007181648,0.00062833936,0.0019303929,0.00006488293,0.000027737893,0.00007036563,0.17137915,0.6006275,0.018831858,0.018303784,0.18702886,0.00038900113],"about_ca_topic_score_codex":0.000028320206,"about_ca_topic_score_gemma":0.0000017409369,"teacher_disagreement_score":0.84376603,"about_ca_system_score_codex":0.000018873354,"about_ca_system_score_gemma":0.000060246308,"threshold_uncertainty_score":0.5258604},"labels":[],"label_agreement":null},{"id":"W1845475795","doi":"10.22230/src.2012v3n2a78","title":"Showcase Browsing with Texttiles 2.0 and BubbleLines","year":2012,"lang":"en","type":"article","venue":"Scholarly and Research Communication","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; World Wide Web; Visualization; Task (project management); Context (archaeology); Interface (matter); Annotation; Information retrieval; User interface; Application programming interface; Human–computer interaction; Multimedia; Data mining; Programming language; Artificial intelligence","score_opus":0.11882510959070897,"score_gpt":0.40973322509481735,"score_spread":0.2909081155041084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1845475795","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.75565064,0.026403237,0.19642313,0.015192108,0.00009440338,0.0006056226,0.000021601953,0.00024471697,0.0053645214],"genre_scores_gemma":[0.9814242,0.0016674496,0.016497206,0.0001361897,0.000022054506,0.0000051789557,0.000021993194,0.0000048622524,0.00022088258],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9987376,0.00048994226,0.000100583384,0.00013168088,0.0003283627,0.00021183799],"domain_scores_gemma":[0.99849063,0.0002671595,0.000030446525,0.00064862287,0.0004142437,0.00014887698],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0031282518,0.000056668534,0.00006450858,0.00014467989,0.00060834596,0.0013351901,0.0004922763,0.000039105023,0.0000039153283],"category_scores_gemma":[0.00043988472,0.00004261534,0.0000057975294,0.00043965766,0.00018100193,0.0041565937,0.0006546498,0.0003196151,0.0000098069995],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047629546,0.00041889382,0.24509291,0.0001021208,0.000052561827,0.0000033129209,0.007181353,0.0000061463434,0.0020960711,0.52686775,0.0049879067,0.21314336],"study_design_scores_gemma":[0.002228152,0.00051963265,0.6903543,0.00060968613,0.000030228673,0.0002044281,0.003852946,0.092972346,0.0035417634,0.014603761,0.19009717,0.0009856191],"about_ca_topic_score_codex":0.000088895285,"about_ca_topic_score_gemma":0.00006468921,"teacher_disagreement_score":0.51226395,"about_ca_system_score_codex":0.000012406327,"about_ca_system_score_gemma":0.000035854795,"threshold_uncertainty_score":0.9997015},"labels":[],"label_agreement":null},{"id":"W1852932948","doi":"","title":"An Exploratory Study of Interactivity in Visualization Tools: ‘Flow’ of Interaction","year":2010,"lang":"en","type":"article","venue":"The Journal of Interactive Learning Research","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Interactivity; Computer science; Visualization; Exploratory research; Human–computer interaction; Flow (mathematics); Multimedia; Artificial intelligence; Sociology","score_opus":0.11704586310689008,"score_gpt":0.48101702047364525,"score_spread":0.36397115736675517,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1852932948","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94341695,0.0000073961287,0.055903535,0.000082488936,0.00026899055,0.00014143238,8.9171925e-7,0.000007629891,0.0001706657],"genre_scores_gemma":[0.9994962,0.000024572884,0.0003645444,0.000011785062,0.00006330471,0.0000020549264,0.0000018675937,0.000010535647,0.000025142883],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9952792,0.002843749,0.00069820177,0.00015327879,0.00084960135,0.00017597426],"domain_scores_gemma":[0.99492514,0.0019528705,0.0008451306,0.00040217343,0.0018069444,0.00006775784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0069785104,0.00009907161,0.0002699388,0.0009424847,0.00009584437,0.00013166392,0.0011437439,0.00004675954,0.000055789063],"category_scores_gemma":[0.0032276858,0.000071713,0.000051464787,0.0010635362,0.00010005281,0.0032222844,0.00028525208,0.0017784176,0.000005077553],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022028864,0.010266299,0.05301719,0.000094533236,0.00027607116,0.000051714956,0.29222867,0.030803239,0.50980145,0.0034125214,0.00040712493,0.097438276],"study_design_scores_gemma":[0.0021687783,0.008379046,0.03609759,0.00055790856,0.00003220926,0.00008696098,0.17535056,0.67910975,0.096427366,0.00057494186,0.0009474577,0.00026741726],"about_ca_topic_score_codex":0.00009316339,"about_ca_topic_score_gemma":0.0003352172,"teacher_disagreement_score":0.64830655,"about_ca_system_score_codex":0.000076200355,"about_ca_system_score_gemma":0.00015187082,"threshold_uncertainty_score":0.77264386},"labels":[],"label_agreement":null},{"id":"W1855751840","doi":"10.1007/978-3-540-73345-4_39","title":"Facilitating Visual Queries in the TreeMap Using Distortion Techniques","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Zoom; Distortion (music); Computer science; Visualization; Simple (philosophy); Space (punctuation); Theoretical computer science; Data mining","score_opus":0.04455614935199955,"score_gpt":0.3389099099083765,"score_spread":0.29435376055637696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1855751840","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00019541617,0.00012399118,0.9975396,0.00018360396,0.00037271096,0.00024503746,0.0000047869535,0.000111529014,0.0012233505],"genre_scores_gemma":[0.15845437,0.000041939893,0.8371579,0.0035933214,0.00047536023,0.000007553777,0.000029870815,0.00003588164,0.00020378435],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971842,0.000061980194,0.0005559731,0.0008383484,0.0009215617,0.00043793107],"domain_scores_gemma":[0.9983236,0.0004866451,0.00025368278,0.00073111546,0.00014315186,0.000061759216],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0018249546,0.00033229857,0.0003130862,0.0008610632,0.00024403339,0.0005938782,0.0021282965,0.00019415274,0.000006851015],"category_scores_gemma":[0.00018116852,0.00025742583,0.000077549565,0.00095058605,0.000540288,0.0007489623,0.00058905367,0.0005204238,0.0000067825795],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000037028478,0.000053531272,0.00019578724,0.000053336655,0.000004832395,0.000089193825,0.004918477,0.004386647,0.00020729643,0.047589134,0.000014042223,0.942484],"study_design_scores_gemma":[0.00013138344,0.00015536744,0.00012904374,0.0005023732,0.0000071141167,0.000058577843,0.0000069840403,0.95024854,0.0017184102,0.04286655,0.003510523,0.0006651468],"about_ca_topic_score_codex":0.00006520741,"about_ca_topic_score_gemma":0.0003279721,"teacher_disagreement_score":0.9458619,"about_ca_system_score_codex":0.00028765792,"about_ca_system_score_gemma":0.00026100804,"threshold_uncertainty_score":0.9999878},"labels":[],"label_agreement":null},{"id":"W1862139890","doi":"10.9776/14301","title":"ProjectTales: Reusing Change Decisions and Rationales in Project Management","year":2014,"lang":"en","type":"article","venue":"iConference 2014 Proceedings","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Reuse; Computer science; Process management; Business; Engineering; Waste management","score_opus":0.07949744775557026,"score_gpt":0.3260167018841945,"score_spread":0.24651925412862424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1862139890","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.105280355,0.0004244293,0.8321253,0.004381637,0.0004078604,0.0024146347,0.000014084828,0.0006715844,0.054280106],"genre_scores_gemma":[0.96575624,0.0004524654,0.032592334,0.0006542548,0.000070127695,0.00008654403,0.000010953701,0.0000098918945,0.0003671663],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988986,0.000014016445,0.00021970709,0.00041265602,0.0002419166,0.00021306738],"domain_scores_gemma":[0.99953175,0.000045079418,0.000091146096,0.00015900358,0.00011849275,0.000054524644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004259393,0.00012719417,0.00013731208,0.00034020646,0.00009732035,0.0003219425,0.0004701972,0.00004502456,0.0000056616113],"category_scores_gemma":[0.00013086254,0.00011398675,0.000021400121,0.0004339153,0.00004964517,0.0010439919,0.00031693128,0.0000774202,0.000026766396],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000036174313,0.00007548297,0.010509723,0.00008150166,0.0000089543655,0.0000021705828,0.0023849057,7.623529e-7,0.00015399349,0.92257303,0.0049465736,0.0592593],"study_design_scores_gemma":[0.0019610971,0.00029941584,0.07034482,0.001352363,0.00003708922,0.000052638276,0.0018352539,0.69241667,0.00063180644,0.047272608,0.18255644,0.0012397824],"about_ca_topic_score_codex":0.00002503271,"about_ca_topic_score_gemma":0.00002118761,"teacher_disagreement_score":0.8753004,"about_ca_system_score_codex":0.000022389635,"about_ca_system_score_gemma":0.000034507935,"threshold_uncertainty_score":0.4648245},"labels":[],"label_agreement":null},{"id":"W186609715","doi":"","title":"The presentation of graphs in annual reports: The case of the KLSE corporate awards winners","year":2005,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Impression management; Accounting; Graph; Graph product; Graphics; Certification; Mathematics; Marketing; Advertising; Statistics; Business; Computer science; Psychology; Economics; 1-planar graph; Management; Social psychology; Chordal graph; Discrete mathematics","score_opus":0.022266810282320856,"score_gpt":0.3007366452392919,"score_spread":0.27846983495697103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W186609715","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8223196,0.00019546764,0.14589003,0.021054007,0.0008109351,0.0008882862,0.00005897043,0.00009145899,0.0086912345],"genre_scores_gemma":[0.9983157,0.000019736925,0.0005516561,0.00027805133,0.000010765704,0.000002342172,0.000002241813,0.0000023438574,0.0008171672],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991821,0.000109689965,0.00033276723,0.0001120446,0.00017878947,0.00008459359],"domain_scores_gemma":[0.99884355,0.00008979566,0.00034713245,0.0005723668,0.00012954502,0.00001760245],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065347046,0.000050219056,0.00006448911,0.000038524297,0.000086416854,0.000043812077,0.00043829775,0.000017231345,0.0000061292394],"category_scores_gemma":[0.00010654049,0.000021930071,0.000040333813,0.0006910845,0.00013451699,0.00026964975,0.00014922176,0.00004975957,8.917696e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011501495,0.00023728459,0.022711173,0.000021254718,0.0000507214,0.00014474323,0.0069208667,0.008836532,0.00029663692,0.8798987,0.045518663,0.035351872],"study_design_scores_gemma":[0.0008728795,0.00011637797,0.025919052,0.00005464562,0.000043102078,0.00085085013,0.010669121,0.883158,0.015974497,0.0335928,0.028413163,0.00033549394],"about_ca_topic_score_codex":0.0003069169,"about_ca_topic_score_gemma":0.0010942811,"teacher_disagreement_score":0.87432146,"about_ca_system_score_codex":0.000008433209,"about_ca_system_score_gemma":0.00006715265,"threshold_uncertainty_score":0.08942824},"labels":[],"label_agreement":null},{"id":"W1867947061","doi":"10.1007/978-3-540-73345-4_38","title":"Towards a Metrics-Based Framework for Assessing Comprehension of Software Visualization Systems","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Visualization; Computer science; Software visualization; Comprehension; Information visualization; Visual analytics; Program comprehension; Context (archaeology); Human–computer interaction; Domain (mathematical analysis); Data science; Creative visualization; Variety (cybernetics); Software; Data visualization; Software engineering; Software system; Artificial intelligence; Component-based software engineering; Programming language","score_opus":0.061536321860768,"score_gpt":0.36057287457589393,"score_spread":0.2990365527151259,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1867947061","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000010852231,0.00044530767,0.99668676,0.000070564965,0.0019030264,0.0005153667,0.000026081609,0.00017125925,0.00017076086],"genre_scores_gemma":[0.03376274,0.00002019417,0.9648882,0.0009192901,0.00025262157,0.000005525918,0.00007141573,0.000042366763,0.000037599057],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99618125,0.000044717704,0.00085037126,0.0010896582,0.0013506099,0.00048340813],"domain_scores_gemma":[0.99553365,0.0014007253,0.00076367415,0.0010914425,0.0010583575,0.00015217233],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0014548424,0.00042657516,0.0006683075,0.0019613572,0.00022504697,0.0008182812,0.002136939,0.0004582943,0.000005837499],"category_scores_gemma":[0.0007611445,0.00040271005,0.00016138647,0.0019192873,0.00035585288,0.0006142861,0.0005488366,0.00035641473,0.0000037668087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008193753,0.00008673242,0.0001284377,0.00053413416,0.000018536246,0.000015155716,0.00023352716,0.13109963,0.00004631251,0.41411948,0.00003329128,0.45367655],"study_design_scores_gemma":[0.00024291947,0.00012436,0.000037891823,0.0012495822,0.000017076945,0.000006299519,3.8132205e-7,0.9465381,0.0009132648,0.048766896,0.0016754535,0.00042776807],"about_ca_topic_score_codex":0.00001863077,"about_ca_topic_score_gemma":0.0000072525495,"teacher_disagreement_score":0.8154385,"about_ca_system_score_codex":0.0002614729,"about_ca_system_score_gemma":0.00080797385,"threshold_uncertainty_score":0.99984246},"labels":[],"label_agreement":null},{"id":"W1882754082","doi":"10.6082/j3k00-1nh26","title":"Four Ways of Making Sense: Designing and Implementing Searchling, a Visual Thesaurus-Enhanced Interface for Multilingual Digital Libraries","year":2009,"lang":"en","type":"article","venue":"Knowledge@UChicago (University of Chicago)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Interface (matter); Computer science; Ideal (ethics); Thesaurus; Process (computing); User interface; World Wide Web; Human–computer interaction; Artificial intelligence; Programming language; Operating system","score_opus":0.04708897762945275,"score_gpt":0.30567841782002053,"score_spread":0.2585894401905678,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1882754082","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1354611,0.00008697731,0.861651,0.00074372045,0.00004052636,0.0002016487,0.000028219045,0.00010760095,0.0016792077],"genre_scores_gemma":[0.9457844,0.00001193185,0.053868793,0.0001037832,0.00004155793,1.881668e-7,0.000014232505,0.000010387993,0.00016473218],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986384,0.00006180822,0.00027782313,0.00042771106,0.00021993883,0.0003743505],"domain_scores_gemma":[0.99873245,0.0003418949,0.00028038595,0.00028851602,0.00026315256,0.000093585455],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036396843,0.00018390546,0.00034485836,0.0002537371,0.00032671582,0.00016988379,0.0005981267,0.00009782261,0.0000139361755],"category_scores_gemma":[0.0001966796,0.00021044664,0.0001240412,0.00042351114,0.00016429926,0.0010283758,0.0005464909,0.00018316334,0.0000036393485],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000443664,0.001047591,0.000943233,0.0008931803,0.000473325,0.000055913944,0.09580469,0.0002647103,0.077473104,0.16378331,0.0027764686,0.6560408],"study_design_scores_gemma":[0.004233101,0.0014336678,0.0014928314,0.00078540284,0.00013918885,0.00003275896,0.010859573,0.8489841,0.100713365,0.01469545,0.015552475,0.001078058],"about_ca_topic_score_codex":0.000003935732,"about_ca_topic_score_gemma":0.000017385255,"teacher_disagreement_score":0.8487194,"about_ca_system_score_codex":0.000020070933,"about_ca_system_score_gemma":0.00013831229,"threshold_uncertainty_score":0.85817647},"labels":[],"label_agreement":null},{"id":"W1898493273","doi":"10.1109/vl.1997.626556","title":"Making distortions comprehensible","year":2002,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Comprehension; Focus (optics); Perception; Perspective (graphical); Confusion; Phenomenon; Human–computer interaction; Representation (politics); Space (punctuation); Distortion (music); Visualization; Cognitive science; Artificial intelligence; Psychology","score_opus":0.11886131969349964,"score_gpt":0.3327301123636501,"score_spread":0.21386879267015044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1898493273","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006806359,0.00003159716,0.903577,0.00073537265,0.00008735383,0.000015173977,7.344198e-7,0.00017055884,0.09531414],"genre_scores_gemma":[0.9320427,0.000011382824,0.04930615,0.0022930985,0.000029046523,0.0000012055575,0.0000032462306,0.000003513432,0.016309613],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996448,0.000008578952,0.00007558867,0.00010272842,0.00008818905,0.000080126214],"domain_scores_gemma":[0.999681,0.000010709235,0.000017348642,0.00024066349,0.000022138543,0.00002816737],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000022967813,0.000033376702,0.00003699965,0.000039681086,0.0000712875,0.00010114691,0.00026487894,0.000009829879,0.00056292705],"category_scores_gemma":[0.000007630415,0.000029605602,0.000018038423,0.00023523552,0.000010769104,0.00024514535,0.000077863384,0.000021227099,0.0005715967],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.5189665e-8,0.00004045245,0.00034761667,0.0000018479527,0.000002882324,0.0000022872866,0.00009427007,0.00005210668,0.00002945011,0.8985717,0.09217275,0.008684566],"study_design_scores_gemma":[0.000048665992,0.0000057340594,0.00032099872,0.0000030207618,0.0000011555551,0.0000034952286,0.000007848214,0.7536326,0.000039189537,0.00075112947,0.24512681,0.00005936909],"about_ca_topic_score_codex":0.0000017831294,"about_ca_topic_score_gemma":0.000003460973,"teacher_disagreement_score":0.93197465,"about_ca_system_score_codex":0.000008060233,"about_ca_system_score_gemma":0.0000025024033,"threshold_uncertainty_score":0.734691},"labels":[],"label_agreement":null},{"id":"W1901890693","doi":"10.1109/tvcg.2015.2467325","title":"TimeSpan: Using Visualization to Explore Temporal Multi-dimensional Data of Stroke Patients","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":78,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Visualization; Session (web analytics); Data visualization; Stroke (engine); Process (computing); Artificial intelligence; Data science; World Wide Web","score_opus":0.15390397827047744,"score_gpt":0.36295013104919566,"score_spread":0.20904615277871821,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1901890693","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020998528,0.000014559686,0.9777151,0.000027772669,0.00067537586,0.00027340263,0.00013848579,0.00015006539,0.0000067554392],"genre_scores_gemma":[0.9660604,0.000029970695,0.031711716,0.0015622866,0.000058384965,0.0000071826516,0.00044897254,0.00004150978,0.000079550235],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977529,0.00017421685,0.00055149803,0.0006219731,0.0006750322,0.00022435335],"domain_scores_gemma":[0.99803305,0.00004959053,0.00020706629,0.0007581091,0.0006293579,0.0003228414],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00034048065,0.0002479067,0.00027846402,0.0006703182,0.0001895617,0.00017742744,0.0006751924,0.000112053276,0.0000074057866],"category_scores_gemma":[0.000016314272,0.0002532073,0.000055730856,0.0012801588,0.000070349066,0.00095339824,0.000058262343,0.00010034697,0.000009865876],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042996928,0.013493333,0.019811584,0.00047204236,0.00086324074,0.000023954848,0.018287642,0.14436878,0.00039538872,0.74612427,0.01709395,0.038635843],"study_design_scores_gemma":[0.0011468413,0.0003024065,0.00026751458,0.00006022746,0.000031687956,0.000003598114,0.000056015084,0.9958662,0.0008392133,0.00006451301,0.0010887777,0.00027300278],"about_ca_topic_score_codex":0.000039701757,"about_ca_topic_score_gemma":0.000018424424,"teacher_disagreement_score":0.9460033,"about_ca_system_score_codex":0.000038909708,"about_ca_system_score_gemma":0.00013529956,"threshold_uncertainty_score":0.999992},"labels":[],"label_agreement":null},{"id":"W192803415","doi":"10.1007/978-1-4614-7485-2_4","title":"Individual Differences and Translational Science in the Design of Human-Centered Visualizations","year":2013,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Translational science; Human–computer interaction; Data science; Computer science; Psychology; Sociology; Social science","score_opus":0.12899595670604785,"score_gpt":0.3332896361825093,"score_spread":0.20429367947646143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W192803415","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00014220689,0.00008091523,0.90526664,0.00032525745,0.00006976157,0.00038601735,0.00004078748,0.00003351634,0.0936549],"genre_scores_gemma":[0.86209303,0.00045975728,0.03267598,0.0017492926,0.00010278086,0.000031385458,0.00023982048,0.00004116709,0.1026068],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985542,0.000040350897,0.00033976577,0.00030571924,0.0006313234,0.00012860572],"domain_scores_gemma":[0.9992491,0.00013400389,0.00015083281,0.00029975182,0.00012420864,0.000042127092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004884112,0.00014604886,0.00017739082,0.00036831704,0.00015053699,0.00033484763,0.0013055209,0.00006813724,0.00023359488],"category_scores_gemma":[0.000018986235,0.000098716104,0.000027016624,0.00020522505,0.00041935613,0.00046009515,0.0001515326,0.00009593405,0.000009515649],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.3572296e-7,0.000024394041,0.0001969461,0.000008282995,0.0000059194995,4.6504312e-7,0.00072024844,0.0000086773225,0.000017724255,0.99754596,0.00039902108,0.0010721384],"study_design_scores_gemma":[0.0017681393,0.0005651892,0.049407847,0.0006239621,0.000135203,0.00003088339,0.00041641126,0.3685004,0.00015643369,0.5679981,0.008782317,0.0016151215],"about_ca_topic_score_codex":0.0000099841445,"about_ca_topic_score_gemma":0.000013143844,"teacher_disagreement_score":0.87259066,"about_ca_system_score_codex":0.00000570785,"about_ca_system_score_gemma":0.00014232875,"threshold_uncertainty_score":0.40255257},"labels":[],"label_agreement":null},{"id":"W19322915","doi":"10.1007/978-3-319-08786-3_19","title":"Eye Tracking to Understand User Differences in Visualization Processing with Highlighting Interventions","year":2014,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visualization; Computer science; Human–computer interaction; Eye tracking; Gaze; Bar chart; Task (project management); Visual analytics; Information visualization; Artificial intelligence; Engineering","score_opus":0.04554174995530865,"score_gpt":0.32307575677781986,"score_spread":0.2775340068225112,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W19322915","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00043142578,0.00008124711,0.9977299,0.00058863626,0.00030333592,0.00027237038,0.0000022094518,0.00011956913,0.00047130333],"genre_scores_gemma":[0.855343,0.000016167523,0.14278404,0.0011638172,0.00016577957,0.000005001181,0.000014377169,0.000037036047,0.0004707947],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.996958,0.00004805192,0.0005913269,0.0011456147,0.00079693197,0.00046008494],"domain_scores_gemma":[0.99854416,0.00015237457,0.00032458646,0.00058387563,0.00025274447,0.00014223914],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0007396774,0.00037848073,0.00044825725,0.001303548,0.00024521112,0.0013802267,0.0017675196,0.0001516094,0.000011623065],"category_scores_gemma":[0.00009738088,0.00031553028,0.00006826134,0.0013387947,0.00024003015,0.0007844182,0.000586431,0.00032499357,0.000010920092],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016557777,0.0001631705,0.005534849,0.00064531504,0.00002673411,0.000083802006,0.011121583,0.07206054,0.00010322649,0.33310893,0.0000388183,0.57709646],"study_design_scores_gemma":[0.00035701672,0.00025131472,0.0011999541,0.00504483,0.000013272747,0.000011673701,0.0000050961894,0.9776573,0.00027611226,0.013915515,0.0004904574,0.00077743223],"about_ca_topic_score_codex":0.000016176036,"about_ca_topic_score_gemma":0.00056983414,"teacher_disagreement_score":0.9055968,"about_ca_system_score_codex":0.00024412043,"about_ca_system_score_gemma":0.00025901233,"threshold_uncertainty_score":0.99992967},"labels":[],"label_agreement":null},{"id":"W1935632789","doi":"","title":"Application of Frameworks in the Analysis and (Re)design of Interactive Visual Learning Tools","year":2009,"lang":"en","type":"article","venue":"The Journal of Interactive Learning Research","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Instructional design; Human–computer interaction; Educational technology; Multimedia; Teaching method; Visualization; Computer-Assisted Instruction; Mathematics education; Psychology; Artificial intelligence","score_opus":0.058090979228409625,"score_gpt":0.445760108405885,"score_spread":0.38766912917747537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1935632789","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11900052,0.000082072096,0.8793376,0.0012086901,0.000016126856,0.0001276793,4.5742772e-7,0.000004247069,0.00022258589],"genre_scores_gemma":[0.9981003,0.0001770082,0.0015585335,0.00008028944,0.000032164393,0.0000014137977,0.0000017439975,0.000004260289,0.000044288172],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9954385,0.0029428913,0.00051799894,0.00014015991,0.0007739135,0.00018651581],"domain_scores_gemma":[0.99219674,0.005871139,0.0007272228,0.00022651792,0.00093728426,0.000041086827],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0072975974,0.00009165448,0.00029221957,0.0008502747,0.00013233317,0.0001550631,0.0009930277,0.00006915366,0.00001663807],"category_scores_gemma":[0.003183577,0.000054999,0.00008874022,0.0022132006,0.00013154639,0.0007386094,0.00016075194,0.0024008877,0.0000024622734],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017953449,0.001207211,0.023186466,0.00004898855,0.0011728944,0.000032000065,0.11936269,0.32379493,0.041012958,0.007203887,0.00040095623,0.48078167],"study_design_scores_gemma":[0.0003891837,0.0016575467,0.060364313,0.00022349482,0.0000919673,0.000026474454,0.017548675,0.91220725,0.005379007,0.0017149302,0.00029080105,0.00010634136],"about_ca_topic_score_codex":0.00004848545,"about_ca_topic_score_gemma":0.000004496656,"teacher_disagreement_score":0.8790998,"about_ca_system_score_codex":0.000058110898,"about_ca_system_score_gemma":0.000071129245,"threshold_uncertainty_score":0.99990064},"labels":[],"label_agreement":null},{"id":"W1959645386","doi":"10.7202/1030268ar","title":"Définitions opérationnelles du temps pour l’analyse des données longitudinales : illustration dans le champ des mobilités spatiales","year":2015,"lang":"fr","type":"article","venue":"Nouvelles perspectives en sciences sociales","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Humanities; Political science; Art","score_opus":0.2277315855516797,"score_gpt":0.35793518331519414,"score_spread":0.13020359776351445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1959645386","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3753966,0.0092904,0.59496397,0.008215337,0.0007079013,0.0004135268,0.00020512761,0.00026872277,0.010538419],"genre_scores_gemma":[0.9360342,0.0039148848,0.055942066,0.00010903088,0.001024741,0.000033450146,0.00005814696,0.00003436351,0.0028490974],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.99394375,0.001877328,0.00086484075,0.0013226647,0.001120838,0.00087057316],"domain_scores_gemma":[0.99593806,0.0009590502,0.00050287007,0.00052817655,0.0016016852,0.00047017608],"candidate_categories":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":["sts"],"category_scores_codex":[0.0036772753,0.00058208045,0.0005899505,0.0005081828,0.0037430876,0.0018178271,0.0016285367,0.00028720868,0.00012966632],"category_scores_gemma":[0.002586953,0.00057903124,0.0003315842,0.0026604699,0.013043443,0.0038139564,0.0005149104,0.00027841594,0.00016237306],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010258661,0.0010011824,0.012548311,0.000080430545,0.00012913068,0.000019228197,0.31596372,0.0059995684,0.00042520158,0.660693,0.0012334107,0.0018965473],"study_design_scores_gemma":[0.000685969,0.00037265135,0.007425776,0.00027846455,0.0000794875,0.0000708892,0.81973517,0.058681782,0.0012587568,0.10927208,0.0012982902,0.00084065506],"about_ca_topic_score_codex":0.004233776,"about_ca_topic_score_gemma":0.020090401,"teacher_disagreement_score":0.5606376,"about_ca_system_score_codex":0.0011594996,"about_ca_system_score_gemma":0.0070999586,"threshold_uncertainty_score":0.9996661},"labels":[],"label_agreement":null},{"id":"W1963867137","doi":"10.1145/1385569.1385609","title":"KMVQL","year":2008,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Visualization; Data visualization; Process (computing); Information retrieval; Data mining","score_opus":0.04277853547372463,"score_gpt":0.2934323813260728,"score_spread":0.2506538458523482,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1963867137","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004870448,0.000004662502,0.9379205,0.0004063517,0.000047100395,0.000007304252,1.9032703e-7,0.00010896149,0.0610179],"genre_scores_gemma":[0.8414573,0.000052639592,0.102638446,0.0061976695,0.000053694068,8.7955243e-7,0.0000054491916,0.0000035702278,0.049590353],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997797,0.000004210023,0.000038765455,0.00006427412,0.00006591287,0.00004715697],"domain_scores_gemma":[0.99978477,0.0000052425526,0.000006861846,0.00016148014,0.000015234898,0.000026417189],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000021811637,0.00001880306,0.000021793994,0.000019434347,0.000038478152,0.000018941244,0.00023241788,0.000006379619,0.00008987954],"category_scores_gemma":[0.0000077324685,0.0000150405895,0.000009449073,0.000135328,0.000008973706,0.00017096984,0.0000582445,0.000010601585,0.0004236182],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.088384e-8,0.000017407354,0.00088089803,5.2792564e-7,0.0000014088953,0.000008679434,0.00009082824,0.0000062043905,0.000031212763,0.8959595,0.10039091,0.0026123563],"study_design_scores_gemma":[0.00019466442,0.000023944613,0.003859273,0.0000017433498,8.428832e-7,0.000060320413,0.000011037495,0.3347779,0.0022341434,0.0027328187,0.6559483,0.00015503251],"about_ca_topic_score_codex":0.000002945224,"about_ca_topic_score_gemma":6.7017163e-7,"teacher_disagreement_score":0.8932267,"about_ca_system_score_codex":0.0000021779679,"about_ca_system_score_gemma":0.000013030636,"threshold_uncertainty_score":0.5444897},"labels":[],"label_agreement":null},{"id":"W1963907209","doi":"10.1109/cw.2014.39","title":"Interactive Visualization of Energy System","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Canada School of Energy and Environment","keywords":"Computer science; Visualization; Data visualization; Animation; Energy flow; Interactive visualization; Human–computer interaction; Data flow diagram; Representation (politics); Energy (signal processing); Information visualization; Diagram; Data mining; Computer graphics (images); Database","score_opus":0.012049885143498387,"score_gpt":0.2852675624540384,"score_spread":0.27321767731054003,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1963907209","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000115092305,0.000002128227,0.96048325,0.000030605705,0.000106258034,0.000010662404,5.5267446e-7,0.000089559246,0.039161902],"genre_scores_gemma":[0.9952895,0.0000016585844,0.003854408,0.00021759635,0.000018270475,7.89026e-7,0.000009216227,0.0000025920365,0.0006059878],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99954313,0.00004852644,0.00013640107,0.000106186366,0.000112430316,0.00005333179],"domain_scores_gemma":[0.99956024,0.00003506489,0.00007606212,0.00020494343,0.000096776464,0.00002691632],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001000205,0.00003939712,0.000072353665,0.000071139046,0.000018187398,0.00003811111,0.0002549078,0.000015818901,0.000013051244],"category_scores_gemma":[0.000028199716,0.000032965774,0.000018893152,0.00023052111,0.000008991838,0.00026488112,0.000081003156,0.0000089373825,0.000014820551],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.0496226e-7,0.000014137494,0.00008929622,0.000008874092,0.0000036321185,9.7179786e-8,0.000049799728,0.000034952915,0.00012801118,0.99599767,0.00075393496,0.002919204],"study_design_scores_gemma":[0.00009009091,0.00003039312,0.00008954947,0.000019555328,0.0000021686403,0.0000015270513,0.000042530562,0.9757875,0.010543814,0.0004964291,0.01284475,0.00005166387],"about_ca_topic_score_codex":0.000022275213,"about_ca_topic_score_gemma":0.000004271683,"teacher_disagreement_score":0.9955012,"about_ca_system_score_codex":0.000011648585,"about_ca_system_score_gemma":0.000010364097,"threshold_uncertainty_score":0.13443053},"labels":[],"label_agreement":null},{"id":"W1965562619","doi":"10.1007/s11205-008-9363-z","title":"On Adding Affect to Time-Diary Accounts","year":2008,"lang":"en","type":"article","venue":"Social Indicators Research","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Quality of Life Research; Affect (linguistics); Human geography; Public health; Psychology; Environmental health; Geography; Medicine; Economic geography; Nursing","score_opus":0.09915431696934973,"score_gpt":0.4382205083801249,"score_spread":0.33906619141077515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965562619","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7364528,0.00008837528,0.08316166,0.010672746,0.0008668621,0.0017132956,0.00018127974,0.0011439684,0.16571902],"genre_scores_gemma":[0.9957395,0.000012986713,0.00045379272,0.00084031775,0.00023483433,0.00001774949,0.000018482797,0.0000149638945,0.0026673556],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99755275,0.0003570236,0.00013859339,0.00035767708,0.0011131279,0.0004808013],"domain_scores_gemma":[0.9990114,0.0003166832,0.0000337732,0.00031871113,0.000103837934,0.0002156194],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0014864486,0.00009074824,0.0001290643,0.0007605193,0.000953363,0.00016822912,0.0011757293,0.00008747325,0.00017811662],"category_scores_gemma":[0.0005411024,0.000087980974,0.00005240544,0.002695737,0.00013732027,0.00025065307,0.0005011738,0.0003157685,0.0042051775],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001571905,0.0002517282,0.0018301286,0.000013194831,0.000034766494,0.000085841355,0.004907408,0.000012422951,0.00041822778,0.20408137,0.763367,0.0249822],"study_design_scores_gemma":[0.0034168279,0.002295143,0.084283225,0.00032101967,0.000023086082,0.000047716792,0.0010514305,0.06275164,0.019643508,0.02415052,0.7986138,0.0034020701],"about_ca_topic_score_codex":0.000018424942,"about_ca_topic_score_gemma":0.0000021456074,"teacher_disagreement_score":0.25928673,"about_ca_system_score_codex":0.00013416773,"about_ca_system_score_gemma":0.00024616785,"threshold_uncertainty_score":0.99657017},"labels":[],"label_agreement":null},{"id":"W1965616957","doi":"10.1145/2501988.2502046","title":"Transmogrification","year":2013,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":53,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Quadrilateral; Computer graphics (images); Simple (philosophy); Visualization; Human–computer interaction; On the fly; Artificial intelligence; Engineering","score_opus":0.04158909804028151,"score_gpt":0.3076056456613614,"score_spread":0.2660165476210799,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965616957","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00008854628,0.000029226883,0.9790209,0.0016066316,0.00027926636,0.0000946176,0.0000036783158,0.00025826637,0.018618887],"genre_scores_gemma":[0.40055695,0.00051538297,0.5572808,0.005316686,0.00029622033,0.000101916885,0.0007557736,0.000033181714,0.0351431],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99933505,0.000020815114,0.00014716668,0.00027457322,0.00014053719,0.000081876824],"domain_scores_gemma":[0.9991183,0.000008947044,0.000056290442,0.00069735316,0.000071160655,0.000047907644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007732204,0.00008334981,0.000084459614,0.00006779139,0.00002275375,0.0003814626,0.000978999,0.00008729378,0.00019234969],"category_scores_gemma":[0.000007219596,0.00007121943,0.000044044296,0.00010302039,0.00001031609,0.00018218285,0.00032365727,0.00011175071,0.00052297494],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.335674e-8,0.000027144491,0.000020696223,0.000024497727,0.000008378225,3.279123e-7,0.000111149835,0.00012948719,0.000025762669,0.9436568,0.031416535,0.02457916],"study_design_scores_gemma":[0.0000559446,0.0000053891345,0.00037418894,0.000017707129,0.000005494704,7.72945e-7,0.000005988135,0.88438064,0.000443778,0.04071083,0.07378998,0.00020926648],"about_ca_topic_score_codex":0.000027339254,"about_ca_topic_score_gemma":0.0000015657566,"teacher_disagreement_score":0.902946,"about_ca_system_score_codex":0.000010874741,"about_ca_system_score_gemma":0.00005102911,"threshold_uncertainty_score":0.672196},"labels":[],"label_agreement":null},{"id":"W1966338750","doi":"10.1117/12.2042589","title":"FilooT: a visualization tool for exploring genomic data","year":2013,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Visual analytics; Visualization; Data visualization; Interactive visualization; Data exploration; Card sorting; Process (computing); Human–computer interaction; Sorting; Domain (mathematical analysis); Graph drawing; Data science; Graph; Information visualization; Task (project management); Data mining; Theoretical computer science; Programming language","score_opus":0.039618024413711234,"score_gpt":0.2736896888442603,"score_spread":0.23407166443054908,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966338750","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97039986,0.000044180535,0.025837077,0.0019236992,0.00031830548,0.0008178003,0.00011653994,0.00014827195,0.00039427157],"genre_scores_gemma":[0.17830203,0.00027574584,0.81804895,0.0006677587,0.0009809667,0.00079345546,0.00022248339,0.00012767826,0.0005809223],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99782157,1.4524651e-8,0.0007040707,0.00053750485,0.00056563294,0.00037120006],"domain_scores_gemma":[0.99746466,0.000153362,0.00038109694,0.00017385936,0.0017199559,0.00010706023],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006640963,0.000259231,0.00031886986,0.0001209126,0.000112528265,0.00045317665,0.0029278407,0.00011004747,0.000014689061],"category_scores_gemma":[0.0007989204,0.00022646486,0.0003077285,0.00041788252,0.00009580486,0.0027847963,0.0007491385,0.00013341282,0.000005523242],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010948478,0.000090118825,0.00017303809,0.000314791,0.00019135968,1.8351562e-8,0.00017175668,0.00008870363,0.1472207,0.83701414,0.013723822,0.0010006082],"study_design_scores_gemma":[0.0009898298,0.00020315243,0.0006998075,0.00019885474,0.00009524685,0.000006665417,0.00052357325,0.9418526,0.033613455,0.0037522984,0.017623069,0.00044142612],"about_ca_topic_score_codex":0.000008577864,"about_ca_topic_score_gemma":8.537489e-8,"teacher_disagreement_score":0.94176394,"about_ca_system_score_codex":0.00009735009,"about_ca_system_score_gemma":0.000044719607,"threshold_uncertainty_score":0.9234969},"labels":[],"label_agreement":null},{"id":"W1966697435","doi":"10.1016/j.jda.2006.12.008","title":"Fixed parameter algorithms for one-sided crossing minimization revisited","year":2007,"lang":"en","type":"article","venue":"Journal of Discrete Algorithms","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Minification; Vertex (graph theory); Algorithm; Graph; Computer science; Crossing number (knot theory); Combinatorics; Mathematics; Mathematical optimization","score_opus":0.049295907580973075,"score_gpt":0.3497608363701669,"score_spread":0.30046492878919384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966697435","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012492392,0.00021026147,0.9970137,0.00062208704,0.000526368,0.00016880201,0.000027499758,0.000043366515,0.00013869411],"genre_scores_gemma":[0.031498723,0.00008351472,0.96617573,0.0009785419,0.0007466533,0.0000020779119,0.00006649065,0.000031879736,0.00041640276],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997657,0.000064228865,0.0010321568,0.00027097666,0.0005902509,0.00038540232],"domain_scores_gemma":[0.99739397,0.0004274724,0.0008631355,0.00036964423,0.0007083327,0.00023747158],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014524508,0.00019073178,0.00038827388,0.000355305,0.00024820797,0.0008081526,0.0007673919,0.00010590013,0.000018938596],"category_scores_gemma":[0.0007648326,0.00016393243,0.00024973994,0.0006986681,0.00007920531,0.001299413,0.00010876628,0.00017908224,0.0000062175],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034298812,0.0010034775,0.0016108169,0.0002901565,0.00094084686,0.00027277137,0.004505172,0.0017760384,0.0064944956,0.028750163,0.032592703,0.9214204],"study_design_scores_gemma":[0.0034886738,0.0007717778,0.0026742062,0.00046843782,0.00017463815,0.00018448118,0.00024429412,0.9346052,0.013485372,0.005833684,0.03738211,0.00068713585],"about_ca_topic_score_codex":0.00000382304,"about_ca_topic_score_gemma":0.0000016773722,"teacher_disagreement_score":0.93282914,"about_ca_system_score_codex":0.00007604769,"about_ca_system_score_gemma":0.00013923233,"threshold_uncertainty_score":0.77930343},"labels":[],"label_agreement":null},{"id":"W1967451046","doi":"10.1145/2449396.2449439","title":"User-adaptive information visualization","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":148,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visualization; Computer science; Human–computer interaction; Information visualization; Visual analytics; Data visualization; Perception; User interface; Artificial intelligence","score_opus":0.01589117803304085,"score_gpt":0.27304998442259315,"score_spread":0.2571588063895523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1967451046","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0003182056,0.000001569371,0.9790035,0.00031800198,0.00007974804,0.00009114163,8.6588744e-7,0.00019627628,0.019990707],"genre_scores_gemma":[0.8962953,0.000020325053,0.08828902,0.010100345,0.000055020893,0.000028521357,0.00014020586,0.00000799258,0.0050632632],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995113,0.0000169867,0.00014815264,0.000076097414,0.00015504468,0.000092400085],"domain_scores_gemma":[0.9995228,0.000012430013,0.00005196981,0.00019408335,0.00016934925,0.000049359427],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000060936076,0.000051615207,0.00004515427,0.00009040559,0.000050978117,0.0003806076,0.0002807387,0.000023766474,0.0002893049],"category_scores_gemma":[0.000027229293,0.000043348948,0.000015179026,0.00034899105,0.0000093398285,0.0048440127,0.000094885465,0.00002019457,0.0024367606],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.4063492e-7,0.0000105785875,0.00013352364,0.0000017029762,0.0000024443984,5.249787e-8,0.0001479341,0.00003866472,0.000017123528,0.95819384,0.030002547,0.011451451],"study_design_scores_gemma":[0.00012648907,0.000028974917,0.0017931295,0.0000034287132,0.0000012677871,0.0000011395326,0.00009518034,0.93866,0.0006409931,0.0033122199,0.055233832,0.00010332646],"about_ca_topic_score_codex":0.00004789097,"about_ca_topic_score_gemma":0.0000021034562,"teacher_disagreement_score":0.9548816,"about_ca_system_score_codex":0.000013680005,"about_ca_system_score_gemma":0.00002037857,"threshold_uncertainty_score":0.99833995},"labels":[],"label_agreement":null},{"id":"W1967952393","doi":"10.1145/2678025.2701376","title":"Prediction of Users' Learning Curves for Adaptation while Using an Information Visualization","year":2015,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Leverage (statistics); Human–computer interaction; Learning curve; Visualization; User interface; User modeling; Adaptation (eye); User interface design; Task (project management); Eye tracking; Data visualization; Multi-task learning; User experience design; Interface (matter); Machine learning; Artificial intelligence","score_opus":0.14949056302479247,"score_gpt":0.3379030994939007,"score_spread":0.18841253646910822,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1967952393","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002956868,0.000012201183,0.996228,0.00004391608,0.00012757782,0.00015291137,0.000011327749,0.00012717787,0.00034003245],"genre_scores_gemma":[0.88901025,0.00004355221,0.10853305,0.000457043,0.0000862912,0.000010555801,0.0016982086,0.000010692129,0.00015036575],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99928564,0.000050405582,0.00026717733,0.00009290451,0.00022638585,0.00007749292],"domain_scores_gemma":[0.9990616,0.000018814919,0.00018610213,0.00013264893,0.0005416487,0.000059178918],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004267165,0.000055401764,0.00007471448,0.00013604177,0.00005907097,0.00009301217,0.00014893943,0.000032718446,0.0000049052715],"category_scores_gemma":[0.00019535508,0.00005492458,0.000018725577,0.00034677715,0.000010435851,0.004575594,0.000033181244,0.000022159193,0.000003042344],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035067816,0.00024815527,0.0044956785,0.0005217498,0.000043104643,1.5215691e-7,0.019704752,0.5138952,0.0010357782,0.42119458,0.00782978,0.030995995],"study_design_scores_gemma":[0.00028483765,0.00014321646,0.00010242987,0.000036766272,0.000008562932,8.541161e-7,0.00092118175,0.99225336,0.0007496622,0.00027794228,0.005166269,0.000054898057],"about_ca_topic_score_codex":0.00003137045,"about_ca_topic_score_gemma":0.0000056714525,"teacher_disagreement_score":0.88769495,"about_ca_system_score_codex":0.000028653974,"about_ca_system_score_gemma":0.00009154221,"threshold_uncertainty_score":0.3317195},"labels":[],"label_agreement":null},{"id":"W1968305741","doi":"10.1109/vast.2012.6400543","title":"Using translational science in visual analytics","year":2012,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Visual analytics; Computer science; Analytics; Data science; Interactive visual analysis; Visualization; Human–computer interaction; Artificial intelligence","score_opus":0.09028880107387988,"score_gpt":0.39366984564679963,"score_spread":0.30338104457291976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968305741","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024258757,0.000012984485,0.9707264,0.0001263051,0.00014741534,0.000027167414,7.232419e-7,0.000035922836,0.00466438],"genre_scores_gemma":[0.9346882,0.0000016221668,0.064864814,0.00030892369,0.00003400916,2.2868491e-7,0.0000017906087,0.0000020870484,0.0000983246],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913675,0.000014659463,0.000144616,0.00013733281,0.00031789334,0.0002487613],"domain_scores_gemma":[0.9996592,0.00001978985,0.000025382886,0.00014519722,0.000049787282,0.000100659825],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005114478,0.000052173193,0.0000586299,0.0002693429,0.00007359813,0.00011852124,0.00039286568,0.000016932578,0.000055366818],"category_scores_gemma":[0.000029907304,0.000047488902,0.000016406226,0.0015135595,0.00006985078,0.0016990949,0.00008465363,0.000039083367,0.000026818676],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.3528825e-7,0.00017232454,0.094176844,0.0000036358035,0.0000021584435,0.0000010726119,0.00046394454,0.0016548827,0.0016827233,0.8974779,0.00009059273,0.0042732856],"study_design_scores_gemma":[0.0000950497,0.000004228476,0.015719457,0.0000032256946,0.0000014246963,0.0000036266908,0.000024790823,0.9820172,0.0008198571,0.00044111678,0.0007900839,0.00007994719],"about_ca_topic_score_codex":0.000010912141,"about_ca_topic_score_gemma":0.0000052254577,"teacher_disagreement_score":0.9803623,"about_ca_system_score_codex":0.000031179865,"about_ca_system_score_gemma":0.00012905197,"threshold_uncertainty_score":0.19365412},"labels":[],"label_agreement":null},{"id":"W1969477511","doi":"10.1117/12.588115","title":"Interactive simulation and visualization using the GPU","year":2005,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Interactivity; Computer science; Visualization; Graphics; Computer graphics (images); Metadata; Throughput; Computer graphics; Interactive visualization; Data visualization; Human–computer interaction; Multimedia; Operating system; Artificial intelligence","score_opus":0.02001700746073517,"score_gpt":0.29385087025864054,"score_spread":0.2738338627979054,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969477511","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97073185,0.000051075636,0.02602041,0.0021929415,0.00013335793,0.00030201708,0.000013784568,0.000071929746,0.00048263618],"genre_scores_gemma":[0.86296654,0.000056105444,0.13607396,0.00036870257,0.00036098607,0.000022609258,0.000007803215,0.000030765812,0.00011253673],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99850416,2.475584e-8,0.00047817934,0.00029791586,0.00050348626,0.00021623533],"domain_scores_gemma":[0.998088,0.00017249137,0.00035512957,0.00006267259,0.0012521514,0.00006956585],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049945974,0.00019235225,0.00020741933,0.00009206078,0.00012737293,0.00029198927,0.0008766277,0.00009124344,0.0000049001324],"category_scores_gemma":[0.0004313439,0.00014138514,0.00020738022,0.00040893973,0.00013475725,0.0014292067,0.0002714145,0.00015293842,8.5014125e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018598417,0.00007571327,0.00019804377,0.00009871651,0.00015803124,2.137203e-8,0.0006747308,0.0065993713,0.07286047,0.9175413,0.0007122138,0.0010627937],"study_design_scores_gemma":[0.00036506535,0.00006739669,0.00023239061,0.00009918436,0.000052478572,0.0000064489836,0.0005326222,0.97517556,0.018188924,0.00087538245,0.0042456337,0.00015888954],"about_ca_topic_score_codex":0.000004543012,"about_ca_topic_score_gemma":1.4990363e-7,"teacher_disagreement_score":0.9685762,"about_ca_system_score_codex":0.00010661107,"about_ca_system_score_gemma":0.000024715719,"threshold_uncertainty_score":0.57655185},"labels":[],"label_agreement":null},{"id":"W1969917881","doi":"10.1109/tvcg.2014.2362543","title":"VectorLens: Angular Selection of Curves within 2D Dense Visualizations","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Selection (genetic algorithm); Computer science; Visualization; Data visualization; Angular displacement; Position (finance); Parallel coordinates; Computer vision; Artificial intelligence; Geometry; Mathematics","score_opus":0.017559050545206255,"score_gpt":0.27892401828864355,"score_spread":0.2613649677434373,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969917881","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0031927074,0.000058176065,0.99559164,0.00006874158,0.00051023904,0.00020270442,0.000015003881,0.00031110953,0.000049663566],"genre_scores_gemma":[0.99210155,0.00070326065,0.0038438628,0.0030881644,0.00006709953,0.000017771114,0.00004612109,0.000034949062,0.00009720855],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99800617,0.0002889129,0.0005673849,0.0004768164,0.0004503584,0.00021034971],"domain_scores_gemma":[0.99866146,0.00012874464,0.00025594476,0.00040058923,0.00040713302,0.0001461374],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00041336854,0.0002461062,0.0002946546,0.00059965445,0.0003179073,0.00015576552,0.0003410674,0.000120377656,0.000025461697],"category_scores_gemma":[0.000018380173,0.00025315507,0.00010775021,0.0018150301,0.00011526383,0.0005439998,0.000009132445,0.00014369356,0.000007538348],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008130518,0.00038373866,0.0002464115,0.00019258122,0.00006766205,6.800238e-7,0.0006054703,0.0023827467,0.00011148067,0.9927711,0.0007147952,0.0025152292],"study_design_scores_gemma":[0.00044381645,0.00031842088,0.00028940267,0.00019253843,0.00005250088,0.000016296231,0.000016440094,0.98979294,0.0064899386,0.0008194421,0.0012896378,0.00027862744],"about_ca_topic_score_codex":0.000016751454,"about_ca_topic_score_gemma":0.000034800163,"teacher_disagreement_score":0.99195164,"about_ca_system_score_codex":0.000019355874,"about_ca_system_score_gemma":0.00005375154,"threshold_uncertainty_score":0.9999921},"labels":[],"label_agreement":null},{"id":"W1969968931","doi":"10.1145/1897239.1897249","title":"Visual analytics and human-computer interaction","year":2011,"lang":"en","type":"article","venue":"interactions","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Citation; Analytics; Computer science; Visual analytics; World Wide Web; Data science; Visualization; Artificial intelligence","score_opus":0.06994976833430198,"score_gpt":0.36710079311538524,"score_spread":0.29715102478108324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969968931","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014385775,0.000004955665,0.9721109,0.00016845456,0.0007808261,0.00005073315,0.00000408869,0.00017978367,0.012314437],"genre_scores_gemma":[0.9822579,0.000007523051,0.016034262,0.00049911835,0.00012623591,0.00000392336,0.000016068358,0.000007990109,0.001046958],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993023,0.00003170417,0.00020439307,0.0002370405,0.0000984571,0.00012607982],"domain_scores_gemma":[0.99947053,0.00003683617,0.00008352577,0.00024164114,0.00008432979,0.00008315056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007018472,0.000095405405,0.000092202354,0.00020372248,0.00014749174,0.0001888451,0.0002332125,0.000026323876,0.00020823602],"category_scores_gemma":[0.000012968615,0.00009293934,0.000042113126,0.00023627059,0.000031543284,0.0010845112,0.00017655402,0.00012513487,0.00014639174],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001546344,0.0012968852,0.012011408,0.000034118857,0.00027032805,0.00006367121,0.0057486757,0.00008901004,0.0024782645,0.86014706,0.033189997,0.08465511],"study_design_scores_gemma":[0.0005880034,0.00040136193,0.031887032,0.00009431519,0.00006931692,0.00027731707,0.00044500126,0.80604964,0.0041957814,0.005704788,0.1496126,0.00067482144],"about_ca_topic_score_codex":0.0000644471,"about_ca_topic_score_gemma":0.00005258511,"teacher_disagreement_score":0.96787214,"about_ca_system_score_codex":0.00002702572,"about_ca_system_score_gemma":0.000012948312,"threshold_uncertainty_score":0.37899566},"labels":[],"label_agreement":null},{"id":"W1970569592","doi":"10.1109/tvcg.2012.213","title":"Design Study Methodology: Reflections from the Trenches and the Stacks","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":835,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Visualization; CLARITY; Field (mathematics); Data science; Domain (mathematical analysis); Management science; Human–computer interaction; Data visualization; Design methods; Software engineering; Artificial intelligence","score_opus":0.15969869803911688,"score_gpt":0.3767722830429787,"score_spread":0.21707358500386184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970569592","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018158562,0.00015658421,0.99636734,0.00047598383,0.000625392,0.0003850525,0.000009487941,0.00014647096,0.000017829849],"genre_scores_gemma":[0.9852419,0.0005842086,0.009859812,0.004031136,0.00013600722,0.000053864926,0.00000818564,0.000017528268,0.0000673427],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974684,0.0014666677,0.00029163237,0.00031307174,0.00025366718,0.00020653679],"domain_scores_gemma":[0.99784386,0.0014060868,0.000104505445,0.00045464167,0.000089064706,0.000101830214],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012577625,0.00018678604,0.00019985497,0.00015344024,0.00088486756,0.00037318733,0.0003699793,0.00007273253,0.000010545357],"category_scores_gemma":[0.00001374599,0.00011365159,0.000057504927,0.0008528982,0.00023505696,0.00046032193,0.000015392845,0.00020108956,0.0000046652394],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005415201,0.00071075454,0.00057809765,0.0000057896254,0.00026319074,8.4524874e-7,0.026524866,0.0006848944,0.000008542286,0.9569142,0.0008038846,0.013450814],"study_design_scores_gemma":[0.0017114232,0.0002501414,0.002040927,0.000014762327,0.00017115723,0.000014830992,0.0010390441,0.9875128,0.00029824022,0.0037049341,0.0029745128,0.00026717078],"about_ca_topic_score_codex":0.00008232726,"about_ca_topic_score_gemma":0.00007251757,"teacher_disagreement_score":0.98682797,"about_ca_system_score_codex":0.000010710249,"about_ca_system_score_gemma":0.000025939451,"threshold_uncertainty_score":0.6805775},"labels":[],"label_agreement":null},{"id":"W1971737641","doi":"10.1145/1080402.1080409","title":"Layered motion field visualization","year":2005,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer vision; Visualization; Computer science; Motion field; Motion (physics); Artificial intelligence; Structure from motion; Classification of discontinuities; Transparency (behavior); Focus (optics); Human visual system model; Position (finance); Motion estimation; Process (computing); Optics; Image (mathematics); Physics; Mathematics","score_opus":0.021788402786557012,"score_gpt":0.31477126020781343,"score_spread":0.2929828574212564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971737641","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00027599378,0.000006924215,0.9820052,0.0020642227,0.00007331703,0.000030219097,4.2803632e-7,0.00019827526,0.015345458],"genre_scores_gemma":[0.9603719,0.00001651543,0.02876102,0.006357902,0.00010825155,0.0000016279322,0.000020267287,0.000004190443,0.004358287],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995375,0.00001692399,0.00010995294,0.00013051643,0.000122065605,0.000083035084],"domain_scores_gemma":[0.9996641,0.000017192402,0.000028089027,0.00020731777,0.000045228153,0.000038060258],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008131019,0.000044127497,0.000041629937,0.00005766516,0.00004441016,0.000116854164,0.000241334,0.000026604392,0.0002469316],"category_scores_gemma":[0.00003636208,0.000039756615,0.000017983552,0.0002468216,0.0000038013657,0.0005801184,0.00006266921,0.000020433581,0.000286214],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.3492958e-7,0.000044494347,0.00030216828,0.0000021860806,0.000002683289,3.8140635e-7,0.00009419842,0.00029595828,0.00018111593,0.8964416,0.024130464,0.07850432],"study_design_scores_gemma":[0.00012580754,0.00001962161,0.00021302329,0.0000026507741,0.0000012371946,0.0000016841227,0.0000086028085,0.9014992,0.009381034,0.00072443835,0.0879444,0.00007826459],"about_ca_topic_score_codex":0.000005506035,"about_ca_topic_score_gemma":0.000011657087,"teacher_disagreement_score":0.96009594,"about_ca_system_score_codex":0.0000114445875,"about_ca_system_score_gemma":0.000010243064,"threshold_uncertainty_score":0.36787972},"labels":[],"label_agreement":null},{"id":"W1971896785","doi":"10.1145/1394281.1394314","title":"Comprehending Boolean queries","year":2008,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Boolean expression; And-inverter graph; Selection (genetic algorithm); Standard Boolean model; Theoretical computer science; Boolean circuit; Product term; Boolean function; Interface (matter); Visualization; Boolean algebra; Two-element Boolean algebra; Information retrieval; Data mining; Mathematics; Algorithm; Artificial intelligence; Algebra over a field","score_opus":0.048427377438139615,"score_gpt":0.290863018860497,"score_spread":0.24243564142235735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971896785","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014431984,0.0000122543515,0.9661897,0.0003321967,0.000086380634,0.00001473011,9.849168e-7,0.00021106812,0.031709522],"genre_scores_gemma":[0.87828857,0.000056059085,0.10360906,0.0025194262,0.000052521922,0.0000011607929,0.000011969393,0.000005668224,0.015455553],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.999629,0.000009797909,0.000074444506,0.000102969156,0.00009964675,0.00008414351],"domain_scores_gemma":[0.99970984,0.000012497152,0.00001634488,0.00020071714,0.000020338373,0.000040268365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003134632,0.000038560735,0.000046597102,0.00003901236,0.000105920946,0.000050264694,0.00030293418,0.000010195217,0.000100499274],"category_scores_gemma":[0.000008710009,0.000032941116,0.000016843125,0.00016521898,0.000027489461,0.00034560994,0.000110334586,0.000021535758,0.00016058653],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.9252305e-7,0.000016558768,0.0016587542,0.0000017961429,0.0000031178895,0.000009912212,0.00025910715,0.000018134193,0.00007478548,0.95977616,0.036704943,0.0014765149],"study_design_scores_gemma":[0.0002206243,0.00003279187,0.00302375,0.000007103373,0.0000016663819,0.00006868801,0.000083351806,0.30261528,0.0031918564,0.0018746542,0.6886468,0.00023342388],"about_ca_topic_score_codex":0.000008645332,"about_ca_topic_score_gemma":0.0000061218047,"teacher_disagreement_score":0.95790154,"about_ca_system_score_codex":0.0000055200057,"about_ca_system_score_gemma":0.000016172122,"threshold_uncertainty_score":0.20640685},"labels":[],"label_agreement":null},{"id":"W1972501111","doi":"10.1016/j.im.2006.10.004","title":"The impact of context-aware fisheye models on understanding business processes: An empirical study of data flow diagrams","year":2006,"lang":"en","type":"article","venue":"Information & Management","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Task (project management); Context (archaeology); Data flow diagram; Set (abstract data type); Process (computing); Information flow; Presentation (obstetrics); Human–computer interaction; Business process; Work in process; Engineering; Systems engineering; Operations management; Database","score_opus":0.12128681471871851,"score_gpt":0.3683759745139057,"score_spread":0.2470891597951872,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972501111","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00640842,0.0000047549656,0.99145615,0.00015528197,0.00003777168,0.00036875615,0.00003944379,0.00004329357,0.0014861285],"genre_scores_gemma":[0.9989669,0.000017177405,0.00057842955,0.00008783042,0.0000091608335,0.000006529183,0.0003100311,0.0000030245951,0.000020967676],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988378,0.000034977584,0.00044819797,0.00012683074,0.00043196997,0.00012022292],"domain_scores_gemma":[0.99864393,0.00004541821,0.00026686213,0.0008073117,0.00020847193,0.000027984177],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036430024,0.00009549285,0.00011495343,0.0001380584,0.00012613312,0.000302974,0.0011207211,0.000017980105,0.000003133548],"category_scores_gemma":[0.000018038478,0.00006327517,0.000018548457,0.0007700959,0.000027248034,0.0040685367,0.0003545685,0.000034844557,0.0000038911044],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005505781,0.0016317893,0.0027928292,0.0003663773,0.00020107094,0.0000026500861,0.006353547,0.7913604,1.9219645e-7,0.079879895,0.027960896,0.08939531],"study_design_scores_gemma":[0.000498818,0.00012603385,0.004814409,0.00003068806,0.000012526906,2.5408528e-7,0.003883201,0.98768514,0.000001481566,0.0022654864,0.0006033886,0.00007858668],"about_ca_topic_score_codex":0.00014384395,"about_ca_topic_score_gemma":0.00011201951,"teacher_disagreement_score":0.9925584,"about_ca_system_score_codex":0.00006754881,"about_ca_system_score_gemma":0.000046570894,"threshold_uncertainty_score":0.2949591},"labels":[],"label_agreement":null},{"id":"W1972524317","doi":"10.1145/2557500.2557524","title":"Towards facilitating user skill acquisition","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Human–computer interaction; Visualization; Dreyfus model of skill acquisition; Set (abstract data type); Process (computing); Gaze; Eye tracking; Usability; Learning curve; Key (lock); Multimedia; Artificial intelligence","score_opus":0.016824276657508623,"score_gpt":0.2932972091584391,"score_spread":0.27647293250093047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972524317","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016726104,0.0000023276714,0.97028947,0.00046983172,0.00008858344,0.00001999177,0.000001584293,0.00015242818,0.027303161],"genre_scores_gemma":[0.7980867,0.0000028212598,0.19191022,0.0047805635,0.00006318187,0.0000019688603,0.000023806711,0.0000045483016,0.0051261852],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99947613,0.00003377296,0.0001011261,0.00014700824,0.00014238061,0.000099560464],"domain_scores_gemma":[0.99960005,0.00003312702,0.000023911658,0.00024355695,0.000053118623,0.000046246227],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020396501,0.000047491358,0.00005236837,0.00003931628,0.00005233061,0.00013677147,0.00029051024,0.000018457562,0.0001231739],"category_scores_gemma":[0.00006764688,0.00003957921,0.00002178977,0.00016780349,0.000010214581,0.00038948422,0.00010748612,0.000023107288,0.00029874002],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.0637313e-7,0.000017517426,0.00021735669,0.0000051422794,0.0000027372291,3.4084005e-7,0.00032404234,0.00007295717,0.000116745134,0.9421198,0.0066365865,0.050486613],"study_design_scores_gemma":[0.00019489268,0.000042117354,0.0020453664,0.000008342302,0.0000021569776,0.0000020948823,0.00008219655,0.9020065,0.0015117704,0.008377526,0.08557391,0.00015313679],"about_ca_topic_score_codex":0.000011655999,"about_ca_topic_score_gemma":0.000002478265,"teacher_disagreement_score":0.9337422,"about_ca_system_score_codex":0.000008253274,"about_ca_system_score_gemma":0.000010746136,"threshold_uncertainty_score":0.38397983},"labels":[],"label_agreement":null},{"id":"W1972924322","doi":"10.1145/1385569.1385603","title":"An empirical evaluation of interactive visualizations for preferential choice","year":2008,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Task (project management); Set (abstract data type); Visualization; Empirical research; Process (computing); Outcome (game theory); Choice set; Interactive visualization; Human–computer interaction; Measure (data warehouse); Artificial intelligence; Data mining; Econometrics; Statistics; Mathematics; Engineering","score_opus":0.17491967646143713,"score_gpt":0.4778877704673096,"score_spread":0.3029680940058725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972924322","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025825854,0.0000033952747,0.97252035,0.00008648229,0.00010444188,0.00018027038,0.000011398108,0.00005470394,0.0012130957],"genre_scores_gemma":[0.9832609,0.0000029095213,0.01615604,0.00020910572,0.000044144545,0.000016407468,0.00013208132,0.00000435755,0.00017402068],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991366,0.0000930109,0.00018820514,0.00018300212,0.00031908724,0.00008006809],"domain_scores_gemma":[0.9988617,0.00008070511,0.00008073088,0.00026075583,0.00066711387,0.0000490121],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023922004,0.00005551372,0.0000824231,0.000092677314,0.00008089582,0.000034537865,0.0003075293,0.0000275456,0.000105611485],"category_scores_gemma":[0.00020955384,0.000049342332,0.000034494155,0.0002701708,0.000024712499,0.00071627286,0.000045084973,0.000021821645,0.0000063076427],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000076652505,0.006850919,0.047561493,0.000103296145,0.0003524712,0.0000010988705,0.018398132,0.016943669,0.008660443,0.72269785,0.104447365,0.07390661],"study_design_scores_gemma":[0.00043444487,0.000095504976,0.005668401,0.0000036172812,0.000018262284,0.0000013970166,0.000033553595,0.98673487,0.0038638657,0.00076942495,0.0023098108,0.000066829045],"about_ca_topic_score_codex":0.000011135985,"about_ca_topic_score_gemma":0.000023470613,"teacher_disagreement_score":0.96979123,"about_ca_system_score_codex":0.000022023714,"about_ca_system_score_gemma":0.0001388843,"threshold_uncertainty_score":0.2012122},"labels":[],"label_agreement":null},{"id":"W1973050785","doi":"10.1145/2812115","title":"Exploratory Visual Analysis and Interactive Pattern Extraction from Semi-Structured Data","year":2015,"lang":"en","type":"article","venue":"ACM Transactions on Interactive Intelligent Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Boeing","keywords":"Computer science; Metadata; Information retrieval; Unstructured data; Cluster analysis; Schema (genetic algorithms); Vocabulary; Visual analytics; Semi-structured data; Set (abstract data type); Visualization; Artificial intelligence; Big data; World Wide Web; Data mining; Relational database","score_opus":0.07415542636238066,"score_gpt":0.359062718772732,"score_spread":0.28490729241035134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973050785","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011509961,0.00011469852,0.98461705,0.00026329703,0.0023374576,0.0002969047,0.0005516457,0.00020692796,0.00010206362],"genre_scores_gemma":[0.99683964,0.00009525324,0.0016765957,0.00030461157,0.00014999796,0.0000451494,0.0005545701,0.000029432727,0.0003047249],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99679035,0.000448391,0.00070927467,0.0011411487,0.0006134076,0.0002974004],"domain_scores_gemma":[0.996076,0.00067751,0.00041805304,0.0020555446,0.00042528732,0.00034763187],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00040461274,0.0003834846,0.0005089546,0.0008397406,0.00017261795,0.0007059875,0.0016749782,0.00014283207,0.00012596429],"category_scores_gemma":[0.00020286617,0.00035999055,0.00013839992,0.0011099718,0.00007160329,0.003223553,0.00017416822,0.00048963755,0.0002072148],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011956979,0.004645072,0.011911216,0.00017141357,0.023241116,0.00032182253,0.052634932,0.04398115,0.0059461277,0.0010877195,0.010562192,0.8443015],"study_design_scores_gemma":[0.00066723116,0.00032891554,0.00085659383,0.00019717003,0.00075204956,0.000045885998,0.013448665,0.94532084,0.017747993,0.00038176004,0.019458488,0.0007944034],"about_ca_topic_score_codex":0.001685121,"about_ca_topic_score_gemma":0.00050845643,"teacher_disagreement_score":0.9853297,"about_ca_system_score_codex":0.00030117418,"about_ca_system_score_gemma":0.00009940596,"threshold_uncertainty_score":0.9998852},"labels":[],"label_agreement":null},{"id":"W1973227779","doi":"10.1145/1518701.1518740","title":"Friend or foe?","year":2009,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Formality; Computer science; Workflow; Transparency (behavior); Domain (mathematical analysis); Management science; Data science; Mathematics","score_opus":0.032114082244732625,"score_gpt":0.3261412098639601,"score_spread":0.2940271276192275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973227779","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000108745386,0.0000039220063,0.9442472,0.001882484,0.000048074686,0.000014544833,4.4281532e-7,0.00012334604,0.05357124],"genre_scores_gemma":[0.75043917,0.000024026223,0.1656889,0.02133618,0.00009494691,7.188198e-7,0.000009960994,0.0000039991273,0.062402114],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.999685,0.0000055513174,0.000059255734,0.00009530868,0.00008177594,0.000073089555],"domain_scores_gemma":[0.99971855,0.000007671639,0.000011496142,0.00020486895,0.000017983415,0.00003943755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000042071446,0.000030058292,0.000033811313,0.000026785174,0.000028075618,0.00010291946,0.0003089687,0.000010510427,0.00020072478],"category_scores_gemma":[0.000016828431,0.000019966285,0.0000110452465,0.00021421319,0.000004315527,0.00025490427,0.000033802455,0.000015029876,0.00018442098],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.4864163e-7,0.000024715424,0.000018038181,4.2275008e-7,9.1605966e-7,0.0000047215544,0.000060591778,0.000003598228,0.000033088505,0.9219674,0.0431234,0.03476264],"study_design_scores_gemma":[0.00031037934,0.0001655505,0.0012654582,0.0000056619406,0.0000025176992,0.000013988899,0.000041007494,0.32627553,0.0021431588,0.016644718,0.65292716,0.00020487509],"about_ca_topic_score_codex":0.000001217027,"about_ca_topic_score_gemma":0.0000023904768,"teacher_disagreement_score":0.9053227,"about_ca_system_score_codex":0.0000033806168,"about_ca_system_score_gemma":0.00001709761,"threshold_uncertainty_score":0.237042},"labels":[],"label_agreement":null},{"id":"W1973331852","doi":"10.1145/2702613.2732778","title":"Exploring the Effect of Word-Scale Visualizations on Reading Behavior","year":2015,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Agence Nationale de la Recherche","keywords":"Memorization; Computer science; Reading (process); Affect (linguistics); Sentence; Task (project management); Natural language processing; Word (group theory); Visualization; Scale (ratio); Artificial intelligence; Human–computer interaction; Cognitive psychology; Linguistics; Psychology; Communication","score_opus":0.1303155489395774,"score_gpt":0.37040566434993444,"score_spread":0.24009011541035705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973331852","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07077659,0.000025767062,0.9161646,0.00031844544,0.0018010407,0.0006926528,0.00003771679,0.0003874213,0.009795818],"genre_scores_gemma":[0.99092644,0.0000968026,0.0051669185,0.00026308908,0.00021983623,0.000315687,0.00020507298,0.000045915534,0.002760261],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984968,0.0001906567,0.00032927268,0.00038320493,0.00043504726,0.00016504982],"domain_scores_gemma":[0.99824744,0.00018199858,0.00018740345,0.0011600939,0.00013713118,0.00008594585],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071402383,0.00019647852,0.00027288942,0.00018437524,0.000093507355,0.0002341582,0.0013529147,0.000065280554,0.000018580917],"category_scores_gemma":[0.00012791202,0.00012678826,0.00010579927,0.00043616077,0.000044388635,0.00025844484,0.0013152165,0.0002247012,0.000045380406],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005278646,0.001002751,0.022284068,0.0009820486,0.0002936895,0.000039320934,0.01109543,0.04155446,0.0006980092,0.67100996,0.061888795,0.18909867],"study_design_scores_gemma":[0.0017577684,0.0013363974,0.0073215514,0.0018467216,0.0006522029,0.000017225791,0.00048946746,0.8762577,0.079876214,0.0029238123,0.02530537,0.00221553],"about_ca_topic_score_codex":0.00004347682,"about_ca_topic_score_gemma":0.00000958724,"teacher_disagreement_score":0.9201498,"about_ca_system_score_codex":0.00005021977,"about_ca_system_score_gemma":0.00007058873,"threshold_uncertainty_score":0.51702756},"labels":[],"label_agreement":null},{"id":"W1973752528","doi":"10.1177/1473871611433713","title":"Note-taking in co-located collaborative visual analytics: Analysis of an observational study","year":2012,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Visual analytics; Computer science; Analytics; Scope (computer science); Visualization; Process (computing); Data science; Observational study; Interactive visual analysis; Data visualization; Cultural analytics; Human–computer interaction; Data analysis; Information retrieval; World Wide Web; Semantic analytics; Data mining; The Internet","score_opus":0.08260358718690645,"score_gpt":0.4163798796457103,"score_spread":0.33377629245880386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973752528","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2478636,0.0000065031036,0.75106627,0.000018499946,0.00010596285,0.00032633299,0.000041097228,0.00009216459,0.00047953211],"genre_scores_gemma":[0.9950939,0.0000052620217,0.0019968841,0.00034243136,0.000026788139,0.000016929667,0.0025021392,0.000006844389,0.000008814195],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99749315,0.00025727984,0.0010876349,0.00017562477,0.0007329188,0.00025338374],"domain_scores_gemma":[0.9977253,0.00009695415,0.00091792305,0.0003508132,0.0007938639,0.000115165865],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011804515,0.0001714122,0.00033986513,0.0019387655,0.00010794293,0.00023994167,0.00040657618,0.000088403154,0.00007202324],"category_scores_gemma":[0.00036856637,0.0001783415,0.00005584967,0.008805616,0.000033262768,0.009651908,0.00008129679,0.000072861505,0.000027308288],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000332142,0.0017923835,0.7333037,0.000038070946,0.00029989198,8.129785e-7,0.035982713,0.076905705,0.00011071423,0.14611799,0.00013304866,0.0052817184],"study_design_scores_gemma":[0.00043260082,0.00009360882,0.30207804,0.000007327675,0.00008958805,2.7655648e-7,0.0014818645,0.69495136,0.00035817438,0.000028711413,0.00033178905,0.00014666918],"about_ca_topic_score_codex":0.00007416436,"about_ca_topic_score_gemma":0.00009804996,"teacher_disagreement_score":0.7490694,"about_ca_system_score_codex":0.00013017442,"about_ca_system_score_gemma":0.00015784347,"threshold_uncertainty_score":0.7272555},"labels":[],"label_agreement":null},{"id":"W1974728355","doi":"10.1109/iv.2013.14","title":"How to Model a Customized Visualization","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Visualization; Computer science; Context (archaeology); Task (project management); Data visualization; Information visualization; Human–computer interaction; Context model; Creative visualization; Data science; User needs; Data modeling; Data mining; Artificial intelligence; Software engineering; Multimedia; Systems engineering; Engineering","score_opus":0.026059088967867773,"score_gpt":0.2948024896233396,"score_spread":0.2687434006554718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974728355","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004801392,0.0000018163696,0.9900577,0.004595268,0.000046907084,0.00013841466,8.284627e-7,0.00021405873,0.004464849],"genre_scores_gemma":[0.62060827,0.0000067411133,0.308249,0.012986352,0.000044917215,0.000040747862,0.000022451812,0.000014126452,0.058027416],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99940085,0.000017721859,0.0000956876,0.00018935361,0.00016686152,0.00012952757],"domain_scores_gemma":[0.9994067,0.000011314924,0.00002617541,0.00030673674,0.0001322981,0.00011676694],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000071051174,0.000064974534,0.00007635007,0.0000984223,0.000043856413,0.0007011815,0.00041855915,0.000022804907,0.00006576966],"category_scores_gemma":[0.000060983777,0.000052964046,0.000022444956,0.00040634756,0.000005962087,0.0009511733,0.00015889324,0.000017842907,0.0005283399],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.499246e-7,0.000031215917,0.00002572258,0.0000029100327,0.000003890496,2.318728e-7,0.00019384842,0.0017733191,0.0010297529,0.8851543,0.105821006,0.00596322],"study_design_scores_gemma":[0.00016989424,0.000009397642,0.000019122477,0.0000022252511,0.0000011758617,4.3091765e-7,0.000019964007,0.9887902,0.00078878243,0.003003541,0.0071085254,0.00008669742],"about_ca_topic_score_codex":0.000012403972,"about_ca_topic_score_gemma":0.0000030885362,"teacher_disagreement_score":0.9870169,"about_ca_system_score_codex":0.000013685032,"about_ca_system_score_gemma":0.000024614952,"threshold_uncertainty_score":0.67909163},"labels":[],"label_agreement":null},{"id":"W1976198606","doi":"10.1145/2254556.2254599","title":"Fluid Views","year":2012,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"University of Calgary","keywords":"Computer science; Information retrieval; Relevance (law); Zoom; World Wide Web; Bridge (graph theory); Dual (grammatical number); Position (finance); Semantic Web; Data science; Engineering","score_opus":0.06584761784360836,"score_gpt":0.3398251336138624,"score_spread":0.27397751577025403,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976198606","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00013243021,0.000053515912,0.9304879,0.00029576666,0.00015240052,0.0000130995395,2.689654e-7,0.00008134807,0.06878328],"genre_scores_gemma":[0.8144589,0.000050690353,0.1416733,0.012770972,0.00027768887,0.0000029719904,0.000012352552,0.0000072015882,0.030745924],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997194,0.000010108674,0.000055564917,0.00005024225,0.00006699143,0.0000977204],"domain_scores_gemma":[0.9997129,0.0000065321497,0.000010056838,0.00019930946,0.000011328855,0.000059874284],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00010847561,0.000025791813,0.000029886407,0.000019888772,0.000021481728,0.000044119683,0.00023322708,0.000008524893,0.00019305573],"category_scores_gemma":[0.0000097177235,0.000019299008,0.000012793717,0.00013212161,0.000004514905,0.0004635315,0.00008308894,0.0000113233655,0.0010826505],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.607252e-8,0.000022913957,0.0007661265,9.629887e-7,0.0000011720356,1.09461695e-7,0.000093048635,5.8639404e-7,0.0001182581,0.9211462,0.06902195,0.008828615],"study_design_scores_gemma":[0.000038580387,0.0000042136967,0.00067671656,9.500578e-7,8.276667e-7,0.0000020824132,0.00000747488,0.029466812,0.0014469669,0.00030294477,0.96799797,0.000054456566],"about_ca_topic_score_codex":0.0000014205524,"about_ca_topic_score_gemma":5.529699e-7,"teacher_disagreement_score":0.9208433,"about_ca_system_score_codex":0.0000034013374,"about_ca_system_score_gemma":0.0000051668508,"threshold_uncertainty_score":0.9996951},"labels":[],"label_agreement":null},{"id":"W1976281572","doi":"10.1145/2317956.2317970","title":"Discursive navigation of online news","year":2012,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario College of Art and Design","funders":"","keywords":"Variety (cybernetics); Sketch; Computer science; Heuristic; Visualization; Human memory; Associative property; Human–computer interaction; World Wide Web; Artificial intelligence; Psychology","score_opus":0.029589371290158095,"score_gpt":0.3311609238756794,"score_spread":0.3015715525855213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976281572","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010495925,0.000019297342,0.98626447,0.00050116057,0.00012016916,0.00002358677,0.000006172344,0.00003183678,0.0025374107],"genre_scores_gemma":[0.9582497,0.000008289539,0.0401179,0.00042321256,0.00005847637,3.6315018e-7,0.00007609318,0.0000020717173,0.0010638776],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996952,0.000010951935,0.000087654924,0.000049436974,0.000088346555,0.00006845021],"domain_scores_gemma":[0.99971646,0.000010681179,0.000039549897,0.00015853878,0.00003471989,0.00004005494],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004749777,0.000027132997,0.000041087624,0.000023256262,0.000012073604,0.000013042359,0.00017909329,0.000010852866,0.000030456524],"category_scores_gemma":[0.000013297531,0.000020416042,0.000015423866,0.00016843955,0.000010504635,0.000459174,0.00006274548,0.000015005699,0.000027457827],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.8892108e-7,0.00019506032,0.009039457,0.000008203723,0.0000057125585,1.5918073e-7,0.00061657524,0.000015558959,0.00047024555,0.96238315,0.0056849257,0.021580564],"study_design_scores_gemma":[0.0014767755,0.00025008633,0.08303787,0.0001386234,0.000051019168,0.000022941833,0.0027146824,0.62029195,0.05924891,0.01516522,0.21666113,0.0009407962],"about_ca_topic_score_codex":0.000014004813,"about_ca_topic_score_gemma":0.0000037976142,"teacher_disagreement_score":0.9477538,"about_ca_system_score_codex":0.0000042937068,"about_ca_system_score_gemma":0.000010078884,"threshold_uncertainty_score":0.0832542},"labels":[],"label_agreement":null},{"id":"W1977623637","doi":"10.1145/1923947.1924010","title":"The centre on innovation for information visualization and data driven design","year":2010,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Information visualization; Visualization; Data visualization; Computer science; Human–computer interaction; Data science; Knowledge management; Data mining","score_opus":0.05398899855077789,"score_gpt":0.34208137523322907,"score_spread":0.2880923766824512,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977623637","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00027487578,7.110036e-7,0.9974211,0.0014397163,0.00017372628,0.00018893396,0.000012174982,0.000060861814,0.00042789735],"genre_scores_gemma":[0.6545292,0.00011303556,0.3253196,0.012313779,0.00032440593,0.000033940698,0.0048194076,0.000026820378,0.002519814],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99950916,0.000017753078,0.00016096227,0.000113152084,0.00012026839,0.00007868777],"domain_scores_gemma":[0.99913025,0.00013437516,0.000082679544,0.00045544768,0.00017850324,0.00001877045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004585911,0.000047387213,0.00003348287,0.000074322095,0.0002019315,0.0005092766,0.0005000388,0.000027868207,0.0000031474492],"category_scores_gemma":[0.0003951641,0.00003173616,0.0000040910827,0.00035556027,0.000018060575,0.0015328475,0.00014779852,0.00003472545,0.000013305151],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000020646953,0.000007142182,0.000033315846,0.0000025912195,0.0000022556685,1.2762044e-8,0.00009709215,0.00003642473,0.00008610831,0.9530978,0.019349882,0.027285276],"study_design_scores_gemma":[0.00013759242,0.000017535243,0.00012315088,0.0000020872676,0.0000016251593,3.8792928e-7,0.00003048342,0.84698135,0.0005177759,0.0019322529,0.15021232,0.00004343524],"about_ca_topic_score_codex":0.0000015044155,"about_ca_topic_score_gemma":0.000010530423,"teacher_disagreement_score":0.95116556,"about_ca_system_score_codex":0.0000040169675,"about_ca_system_score_gemma":0.000032022104,"threshold_uncertainty_score":0.4910966},"labels":[],"label_agreement":null},{"id":"W1977985708","doi":"10.1145/1274871.1274886","title":"Engaging viewers through nonphotorealistic visualizations","year":2007,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Visualization; Rendering (computer graphics); Perception; Human visual system model; Data visualization; Visual perception; Human–computer interaction; Computer graphics (images); Artificial intelligence; Computer vision; Image (mathematics); Psychology","score_opus":0.03422264521007926,"score_gpt":0.3505516590489779,"score_spread":0.3163290138388986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977985708","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00008571797,0.000019546844,0.92460436,0.00019495901,0.00021897214,0.000054976445,0.0000029545058,0.00026951393,0.07454902],"genre_scores_gemma":[0.75296533,0.00008437871,0.22810549,0.013671065,0.0001932528,0.0000047301164,0.00013273569,0.000027794664,0.004815252],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.999067,0.00002704621,0.00022797339,0.0002244216,0.00022578333,0.00022775629],"domain_scores_gemma":[0.99928313,0.000102395585,0.000052336654,0.00038097327,0.000098037664,0.00008312129],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042561305,0.000087759065,0.00008876337,0.000087296496,0.00017008361,0.0001610439,0.0004888438,0.000029259398,0.000118481716],"category_scores_gemma":[0.00011462301,0.000079299745,0.000035702873,0.000740531,0.00003101332,0.0005540394,0.00012994137,0.000055647073,0.00012005878],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.4435166e-7,0.000035676476,0.00024650816,0.0000053149643,0.0000058066985,0.0000064651663,0.00046744678,0.000033701846,0.00009817854,0.9889787,0.007906159,0.0022157074],"study_design_scores_gemma":[0.00051578274,0.000050078772,0.0012283545,0.00003528425,0.000019767178,0.000023013665,0.0006131504,0.36703855,0.0057984646,0.012926371,0.61118513,0.0005660512],"about_ca_topic_score_codex":0.000055950484,"about_ca_topic_score_gemma":0.000042066793,"teacher_disagreement_score":0.97605234,"about_ca_system_score_codex":0.00002814795,"about_ca_system_score_gemma":0.000037383543,"threshold_uncertainty_score":0.323375},"labels":[],"label_agreement":null},{"id":"W1978519707","doi":"10.5555/2662737.2662740","title":"MAV-Vis: a notation for model uncertainty","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Notation; Reading (process); Computer science; Syntax; Programming language; Artificial intelligence; Arithmetic; Mathematics; Linguistics","score_opus":0.035849531410590024,"score_gpt":0.3091725953347126,"score_spread":0.27332306392412253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1978519707","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00038429617,0.0000023491289,0.9948964,0.00136854,0.00004072504,0.00013521277,0.000003324038,0.00010250972,0.0030666017],"genre_scores_gemma":[0.4948444,0.000006961918,0.48525575,0.0065032695,0.000042786534,0.00007915765,0.000064118154,0.000008489479,0.013195045],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99957925,0.0000058778714,0.000096528165,0.00013408184,0.000085706124,0.0000985422],"domain_scores_gemma":[0.9995999,0.000023825274,0.000026219795,0.00018851929,0.00011950811,0.00004206117],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006274098,0.000043779026,0.000045942776,0.00003575324,0.000043889628,0.00016855885,0.000263801,0.000017377384,0.00004554819],"category_scores_gemma":[0.00002733974,0.000035295183,0.000024119106,0.00011661095,0.0000072279254,0.00050154503,0.000048046764,0.000013918922,0.00014458002],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.758927e-7,0.000025642383,0.000015174723,0.000007782559,0.0000039969304,5.3989563e-8,0.00014834381,0.015958695,0.0001808474,0.9143145,0.052739162,0.016605336],"study_design_scores_gemma":[0.00012606083,0.000012125447,0.00002344922,0.0000020076197,0.0000013521171,2.2214861e-7,0.000019306866,0.97462726,0.00013971761,0.02223056,0.0027616837,0.0000562362],"about_ca_topic_score_codex":0.00002664035,"about_ca_topic_score_gemma":0.000006535836,"teacher_disagreement_score":0.9586686,"about_ca_system_score_codex":0.000010641761,"about_ca_system_score_gemma":0.00002779879,"threshold_uncertainty_score":0.18583319},"labels":[],"label_agreement":null},{"id":"W1979442950","doi":"10.1109/vast.2010.5653060","title":"Model based interactive analysis of interwoven, imprecise narratives: VAST 2010 mini challenge 1 award: Outstanding interaction model","year":2010,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Focus (optics); Synchronizing; Visual analytics; Dependency (UML); Narrative; Data visualization; Variety (cybernetics); Visualization; Process (computing); Data science; Analytics; Cluster analysis; Human–computer interaction; Information retrieval; Artificial intelligence; Programming language","score_opus":0.0505723566965089,"score_gpt":0.3459550518725201,"score_spread":0.29538269517601123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979442950","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01843938,0.0000036370252,0.97623074,0.00070078514,0.00041859725,0.00010354607,0.000064938635,0.00010077047,0.003937619],"genre_scores_gemma":[0.92831224,0.000008745101,0.07055137,0.00025154572,0.000020469808,0.000009399904,0.00006623312,0.000012886786,0.0007671198],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982945,0.000055412766,0.0005418393,0.00052618014,0.00035258345,0.0002295095],"domain_scores_gemma":[0.99821407,0.00013170765,0.00035910224,0.00079028873,0.00036300288,0.00014185513],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003394284,0.0002267699,0.0004332035,0.00096073566,0.000080906946,0.00018243495,0.0008247564,0.00010433434,0.00016967709],"category_scores_gemma":[0.000096727024,0.00019880883,0.00028496483,0.0009898474,0.00006568372,0.0015795954,0.00026683626,0.00032145032,0.000014630141],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018883217,0.0020992786,0.00095128163,0.00008498759,0.002298429,0.000008322936,0.041132197,0.7407307,0.04313478,0.14924122,0.0060364525,0.014093531],"study_design_scores_gemma":[0.00027489383,0.0000493874,0.000034887922,0.000023253691,0.00011496519,6.0996405e-7,0.001114957,0.9944844,0.00258294,0.00097381155,0.00013413183,0.00021170756],"about_ca_topic_score_codex":0.000029616664,"about_ca_topic_score_gemma":0.00042965615,"teacher_disagreement_score":0.90987283,"about_ca_system_score_codex":0.00006279217,"about_ca_system_score_gemma":0.000115949464,"threshold_uncertainty_score":0.8107189},"labels":[],"label_agreement":null},{"id":"W1979784788","doi":"10.1007/s00799-011-0066-8","title":"Interaction and the epistemic potential of digital libraries","year":2010,"lang":"en","type":"article","venue":"International Journal on Digital Libraries","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Leverage (statistics); Digital library; Human–computer interaction; Task (project management); Chunking (psychology); World Wide Web; Data science; Artificial intelligence","score_opus":0.010851543415436184,"score_gpt":0.25484236589341414,"score_spread":0.24399082247797796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979784788","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3609672,0.00034656495,0.46190032,0.07727416,0.014789375,0.00036424643,0.0005797011,0.000380355,0.08339809],"genre_scores_gemma":[0.99789697,0.000024341864,0.0006599714,0.00043592855,0.00030233132,9.438169e-7,0.00003237827,0.000007809926,0.00063930935],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989052,0.00002001646,0.0003602083,0.00014510803,0.0004641084,0.000105352185],"domain_scores_gemma":[0.9990763,0.00023715182,0.00027855218,0.00017560099,0.00015409468,0.000078323144],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.000102700964,0.00011243198,0.0001324659,0.00016588024,0.0000996727,0.007191111,0.0010269876,0.00004050407,0.000037648635],"category_scores_gemma":[0.00030888038,0.000073177005,0.00009684473,0.000116606585,0.00035923783,0.009233959,0.00039351522,0.00028150034,0.000020288111],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012725973,0.00006773167,0.00096537225,0.0000026482103,0.00007978284,0.000020531332,0.00022589092,0.000029443672,0.00007988394,0.97312933,0.0013965382,0.023875592],"study_design_scores_gemma":[0.003923608,0.00029482992,0.0035010546,0.00016597098,0.000026847494,0.0024586415,0.0006673682,0.036861967,0.004597304,0.80523586,0.14173338,0.00053315586],"about_ca_topic_score_codex":8.658567e-7,"about_ca_topic_score_gemma":3.160659e-7,"teacher_disagreement_score":0.6369298,"about_ca_system_score_codex":0.0000073713945,"about_ca_system_score_gemma":0.0000835369,"threshold_uncertainty_score":0.9938395},"labels":[],"label_agreement":null},{"id":"W1980572285","doi":"10.3389/fpsyg.2015.00387","title":"Instruction in information structuring improves Bayesian judgment in intelligence analysts","year":2015,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; Defence Research and Development Canada","funders":"","keywords":"Structuring; Psychology; Bayesian probability; Intelligence analysis; Cognitive psychology; Cognitive science; Data science; Artificial intelligence; Computer science; Political science","score_opus":0.02240247512795242,"score_gpt":0.3161508740113134,"score_spread":0.293748398883361,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980572285","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02360763,0.00005709211,0.9728964,0.0003483496,0.0017644659,0.00010836743,0.0000013177755,0.000028090037,0.0011883177],"genre_scores_gemma":[0.90345895,0.000084921216,0.09558476,0.0007962041,0.000024746401,0.0000103962775,0.000024562532,0.000004616139,0.000010842584],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988538,0.000085443775,0.00046026954,0.00023667104,0.00014650845,0.0002172788],"domain_scores_gemma":[0.9994716,0.0000062055888,0.00010955063,0.00031818086,0.00003211359,0.00006233934],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042420393,0.000095468284,0.00016332779,0.0010392979,0.000013264089,0.000061018567,0.0004926557,0.00009124628,0.000002969449],"category_scores_gemma":[0.00006375347,0.00010145274,0.000016820079,0.0011493189,0.00003833625,0.0011977722,0.00009031333,0.00016260179,0.000008233902],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036128386,0.00007983886,0.1495287,0.00001772483,0.000008631231,0.000015187078,0.00400334,0.0025295692,0.000020921638,0.010141593,0.0032594558,0.8303589],"study_design_scores_gemma":[0.0018695252,0.00012943668,0.075999446,0.00005171467,0.0000029992962,0.000021200423,0.0019175366,0.82119,0.00026843496,0.09133126,0.006859101,0.00035937026],"about_ca_topic_score_codex":0.000068147536,"about_ca_topic_score_gemma":0.00014185722,"teacher_disagreement_score":0.87985134,"about_ca_system_score_codex":0.00014961278,"about_ca_system_score_gemma":0.000043827706,"threshold_uncertainty_score":0.41371226},"labels":[],"label_agreement":null},{"id":"W1981830842","doi":"10.1177/1473871614550536","title":"A search-set model of path tracing in graphs","year":2014,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Shortest path problem; Set (abstract data type); Path (computing); Tracing; Node (physics); Graph; Theoretical computer science; Algorithm; Data mining","score_opus":0.030330826283329206,"score_gpt":0.31006125975255266,"score_spread":0.27973043346922344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981830842","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015840558,0.0000022723812,0.98216784,0.000050763767,0.00004617272,0.0000979699,0.000009504575,0.0000747138,0.0017102077],"genre_scores_gemma":[0.99387974,0.000015974196,0.0054454873,0.00044030108,0.0000056678045,0.0000040336813,0.00018922647,0.000003850683,0.000015709591],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99886197,0.000067417226,0.0005039005,0.000095521,0.00033790417,0.00013326653],"domain_scores_gemma":[0.99931216,0.000029871326,0.00018029654,0.00024162438,0.00019086564,0.00004516647],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006077742,0.00007980216,0.00011812938,0.00045975958,0.00004465674,0.00011751325,0.00030034213,0.000050940944,0.000006561553],"category_scores_gemma":[0.00012929662,0.00008096408,0.000029592577,0.00088690413,0.000020940182,0.0031671317,0.00006874727,0.000046875768,0.000023087561],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002374573,0.000027940509,0.001075709,0.000060240367,0.0000023082252,4.670333e-8,0.004246277,0.10428588,0.00011232043,0.883165,0.00021786358,0.0068040336],"study_design_scores_gemma":[0.00031468878,0.000026898737,0.00048037176,0.000035361885,0.0000016363488,5.672139e-7,0.00009983875,0.9932992,0.0013448495,0.003951023,0.0003558153,0.000089775975],"about_ca_topic_score_codex":0.000017584749,"about_ca_topic_score_gemma":0.0000044033704,"teacher_disagreement_score":0.9780392,"about_ca_system_score_codex":0.00002468731,"about_ca_system_score_gemma":0.000052026844,"threshold_uncertainty_score":0.3301619},"labels":[],"label_agreement":null},{"id":"W1983547589","doi":"10.2466/pms.104.3.707-721","title":"Perception of Linear and Nonlinear Trends: Using Slope and Curvature Information to Make Trend Discriminations","year":2007,"lang":"en","type":"article","venue":"Perceptual and Motor Skills","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Bar chart; Perception; Curvature; Nonlinear system; Graph; Sample (material); Psychology; Histogram; Mathematics; Statistics; Social psychology; Computer science; Artificial intelligence; Combinatorics","score_opus":0.018273755769460817,"score_gpt":0.3058868151858683,"score_spread":0.28761305941640747,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983547589","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7096311,0.000043254775,0.28923127,0.0003348003,0.00009499548,0.00010794997,0.00013008591,0.000039290102,0.0003872543],"genre_scores_gemma":[0.8473459,0.0002983841,0.15039247,0.0010878039,0.00012832937,0.0000022298852,0.0001730522,0.000010228337,0.00056163355],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9992886,0.000016334423,0.00023693814,0.00016539097,0.00015701517,0.00013571951],"domain_scores_gemma":[0.9995684,0.000030621188,0.000063524945,0.00013280759,0.000071044786,0.00013360447],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018680548,0.00010490991,0.00012624609,0.0002750493,0.00012116119,0.0000962196,0.000099619334,0.0000594668,0.000019085088],"category_scores_gemma":[0.000049153256,0.00009001241,0.000019995523,0.00028967808,0.00006712798,0.0006598669,0.00013526487,0.000058102232,0.000002510449],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023951723,0.00020462926,0.0038134758,0.000107776286,0.000026768394,0.0000022136464,0.051747914,0.000061322666,0.008760717,0.009184142,0.00053870515,0.9255284],"study_design_scores_gemma":[0.0014671267,0.000618754,0.5595128,0.00018404955,0.00010173013,0.00008031049,0.009593084,0.3689793,0.00025188658,0.00022771613,0.05821531,0.00076793955],"about_ca_topic_score_codex":0.000028391678,"about_ca_topic_score_gemma":0.000050942293,"teacher_disagreement_score":0.92476046,"about_ca_system_score_codex":0.00001293309,"about_ca_system_score_gemma":0.0000108956165,"threshold_uncertainty_score":0.36705995},"labels":[],"label_agreement":null},{"id":"W1983576710","doi":"10.1177/1548512912464532","title":"Visual Analytics for cyber security and intelligence","year":2014,"lang":"en","type":"article","venue":"The Journal of Defense Modeling and Simulation Applications Methodology Technology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Visual analytics; Computer science; Visualization; Intelligence analysis; Data science; Context (archaeology); Set (abstract data type); Analytics; Information visualization; Information overload; State (computer science); Computer security; World Wide Web; Artificial intelligence","score_opus":0.09619512117421646,"score_gpt":0.3999956883332149,"score_spread":0.30380056715899845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983576710","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014623374,0.00023945907,0.9826356,0.002259531,0.00004383162,0.00013441074,0.0000014543084,0.00004250289,0.000019848927],"genre_scores_gemma":[0.7488989,0.00016780282,0.2506338,0.0002383119,0.000041817722,0.0000049112527,0.0000013188059,0.000005005949,0.000008103814],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99894154,0.00025688196,0.00043493102,0.00015393141,0.00008870084,0.00012402936],"domain_scores_gemma":[0.9973834,0.0015951466,0.00029392433,0.00027746687,0.00040244067,0.000047593152],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027149203,0.00009146843,0.00022125953,0.00032083315,0.00021286898,0.00003517752,0.00035954613,0.00012939224,8.2437845e-7],"category_scores_gemma":[0.0007583071,0.00006790155,0.000033771696,0.0003943204,0.000149942,0.0001153826,0.00012441371,0.00017832294,8.749212e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019175768,0.000035325174,0.00012590906,0.000013030072,0.00003488222,1.247889e-7,0.0004363988,0.42365578,0.00018505943,0.49900517,0.000015119317,0.07647404],"study_design_scores_gemma":[0.00011921591,0.000072338466,0.00000381994,0.000004235033,0.0000418108,0.000042747935,0.00015028426,0.7471726,0.00012971343,0.25066394,0.0015463516,0.000052942436],"about_ca_topic_score_codex":0.0000013707428,"about_ca_topic_score_gemma":0.0000020207517,"teacher_disagreement_score":0.7342755,"about_ca_system_score_codex":0.000010138229,"about_ca_system_score_gemma":0.000024730252,"threshold_uncertainty_score":0.27689448},"labels":[],"label_agreement":null},{"id":"W1983744264","doi":"10.1145/2559206.2581338","title":"Exploring the need for visualizations in system administration tools","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Visualization; Human–computer interaction; Usability; Data visualization; Work (physics); Software engineering; System administrator; Data science; Engineering; Computer security","score_opus":0.15746582837478929,"score_gpt":0.3374223594631055,"score_spread":0.17995653108831622,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983744264","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001954768,0.0000012785697,0.9938928,0.0008554326,0.000167783,0.00015253366,0.0000022359911,0.00011109098,0.0028620628],"genre_scores_gemma":[0.9927615,0.000002263521,0.0064090025,0.00038483884,0.00005212172,0.000066732624,0.000024330671,0.0000040914465,0.00029511921],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99944645,0.00004435873,0.0001780538,0.00013061888,0.000100572666,0.00009996761],"domain_scores_gemma":[0.99947,0.00015315301,0.000039168648,0.0002579398,0.0000531822,0.000026574096],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035566735,0.000049637973,0.0000614902,0.00006115371,0.00009584808,0.00030672053,0.00033634223,0.000011941523,0.0000021733783],"category_scores_gemma":[0.0001301595,0.000035079247,0.000021718675,0.0003572831,0.000008279337,0.0007235416,0.000044428343,0.000020479822,0.000014256024],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.088393e-7,0.00001201302,0.000076751676,0.000011463156,0.000001343003,8.942385e-8,0.00012904387,0.00019358334,0.000024311556,0.9952333,0.00035278886,0.003964684],"study_design_scores_gemma":[0.00017235223,0.000036014164,0.00066436594,0.000018120558,0.0000024375656,0.0000013796652,0.00034186916,0.98036134,0.0007846302,0.00039673594,0.017150484,0.00007025036],"about_ca_topic_score_codex":0.0000058322657,"about_ca_topic_score_gemma":0.0000394747,"teacher_disagreement_score":0.99483657,"about_ca_system_score_codex":0.000018443174,"about_ca_system_score_gemma":0.000027952756,"threshold_uncertainty_score":0.29577133},"labels":[],"label_agreement":null},{"id":"W1983914482","doi":"10.1016/s0730-725x(01)00296-x","title":"Graphical display of fMRI data: visualizing multidimensional space","year":2001,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; National Research Council Institute for Biodiagnostics","funders":"","keywords":"Visualization; Computer science; Exploratory data analysis; Multidimensional data; Cluster analysis; Set (abstract data type); Data set; Data visualization; Pattern recognition (psychology); Artificial intelligence; Homogeneity (statistics); Data mining; Machine learning","score_opus":0.023200805715355172,"score_gpt":0.3117225956326516,"score_spread":0.28852178991729643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983914482","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011738981,0.00791058,0.97382146,0.003604672,0.0003899238,0.00017174183,0.00004344356,0.00018199976,0.0021371832],"genre_scores_gemma":[0.85430247,0.0010499888,0.14113519,0.0015519841,0.00017001382,0.0000074509426,0.0001280456,0.000038725266,0.0016161193],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982052,0.00007393346,0.00035779338,0.0005540733,0.00048511336,0.00032390186],"domain_scores_gemma":[0.99838567,0.00012154051,0.00011604821,0.0011626137,0.00010878258,0.00010533113],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040701168,0.00015415878,0.00020212922,0.00014797783,0.00010775466,0.00011249998,0.0012046158,0.000028087798,0.0000530162],"category_scores_gemma":[0.00016136226,0.0001449627,0.000045485962,0.0007781805,0.000145478,0.00076359254,0.0008753741,0.00011634378,0.000028643288],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023663328,0.00038956298,0.108992726,0.000050964714,0.000009814042,0.00025391363,0.00042372494,0.00008763247,0.0076859184,0.5224268,0.016478473,0.34317684],"study_design_scores_gemma":[0.00040279425,0.000025068415,0.021240631,0.00007777699,0.000008069751,0.0000515138,0.00003375799,0.7127928,0.00027676657,0.0003883445,0.26451287,0.00018962446],"about_ca_topic_score_codex":0.00006304522,"about_ca_topic_score_gemma":0.00000889598,"teacher_disagreement_score":0.8425635,"about_ca_system_score_codex":0.000009571875,"about_ca_system_score_gemma":0.000055817323,"threshold_uncertainty_score":0.59114075},"labels":[],"label_agreement":null},{"id":"W1984058975","doi":"10.1145/634067.634137","title":"Examining edge congestion","year":2001,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Enhanced Data Rates for GSM Evolution; Graph; Theoretical computer science; Graph drawing; Visualization; Data mining; Artificial intelligence","score_opus":0.07664161609354092,"score_gpt":0.3135067818725095,"score_spread":0.2368651657789686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1984058975","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027541514,0.0000072139655,0.93541044,0.00032125978,0.0001003788,0.000013688082,1.7145673e-7,0.00014343942,0.061249234],"genre_scores_gemma":[0.9649016,0.000032418884,0.020936668,0.0017472508,0.000053602565,0.0000010442125,0.000008343628,0.0000030087476,0.012316014],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996894,0.000010624379,0.000060266928,0.00009904038,0.000072537216,0.000068136644],"domain_scores_gemma":[0.9997447,0.000015494816,0.00001494801,0.00016548403,0.000025804131,0.00003353193],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000080319835,0.000029217153,0.000030732965,0.000034498928,0.000031617357,0.00009138852,0.00020594422,0.000012565865,0.00010062403],"category_scores_gemma":[0.000022923618,0.000025385623,0.000006439023,0.00020047934,0.000007282774,0.00028926483,0.00006136111,0.000017577882,0.00021514088],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.1857535e-7,0.000030148261,0.0066953935,0.0000016831019,0.0000034844616,0.000011204652,0.00010708874,0.000053637308,0.00020143927,0.8875907,0.014577143,0.090727665],"study_design_scores_gemma":[0.00030914668,0.000057877245,0.016648639,0.000011553614,0.0000034089844,0.000035131958,0.00007486556,0.65973026,0.00061769603,0.0025865335,0.31971407,0.00021079968],"about_ca_topic_score_codex":0.0000035637963,"about_ca_topic_score_gemma":0.000002657644,"teacher_disagreement_score":0.9621475,"about_ca_system_score_codex":0.000005425311,"about_ca_system_score_gemma":0.000009688972,"threshold_uncertainty_score":0.27652726},"labels":[],"label_agreement":null},{"id":"W1985548644","doi":"10.3758/brm.40.3.858","title":"Recovering data from scanned graphs: Performance of Frantz’s g3data software","year":2008,"lang":"en","type":"article","venue":"Behavior Research Methods","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trent University","funders":"Natural Sciences and Engineering Research Council of Canada; Trent University","keywords":"Computer science; Software; Computer graphics (images); Programming language","score_opus":0.5383671611823693,"score_gpt":0.5695334473161054,"score_spread":0.031166286133736176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1985548644","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2581378,0.00026689615,0.7402887,0.000062151565,0.00023720955,0.00023614077,0.0005060102,0.00012305379,0.00014204864],"genre_scores_gemma":[0.058614057,0.00091551425,0.9393123,0.000043329816,0.000048480582,0.00002274262,0.00057423045,0.000023642333,0.0004456953],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9966233,0.0008840977,0.00040117934,0.0006863535,0.0009625881,0.0004425033],"domain_scores_gemma":[0.9956142,0.0005708561,0.00010336364,0.0031954302,0.00033397635,0.00018222697],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039749295,0.0001346462,0.00026641967,0.0003737711,0.0003222853,0.00011078694,0.0046678213,0.00007989619,0.00015062767],"category_scores_gemma":[0.0011325293,0.00012741581,0.000049355716,0.0014725887,0.00026141354,0.0014446492,0.0030262058,0.00035540195,0.000044884007],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054763077,0.00081132713,0.15311454,0.000117453725,0.00007041169,0.00014005786,0.0011738928,0.000029253426,0.028736617,0.001477609,0.021001657,0.79327244],"study_design_scores_gemma":[0.002079111,0.0007601271,0.29762134,0.00045285875,0.00007256311,0.000092250455,0.0003352228,0.49684373,0.12504567,0.0015888774,0.07375501,0.0013532613],"about_ca_topic_score_codex":0.0004261503,"about_ca_topic_score_gemma":0.000017258331,"teacher_disagreement_score":0.7919192,"about_ca_system_score_codex":0.00003138557,"about_ca_system_score_gemma":0.00025354634,"threshold_uncertainty_score":0.86740506},"labels":[],"label_agreement":null},{"id":"W1987264910","doi":"10.1109/vissoft.2013.6650526","title":"DEVis: A tool for visualizing software document evolution","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Documentation; Software development; Process (computing); Software development process; Visualization; Software engineering; Software; Goal-Driven Software Development Process; Software visualization; Software analytics; Task (project management); Software evolution; Data science; Software construction; Data mining; Systems engineering; Engineering; Programming language","score_opus":0.018621062670158017,"score_gpt":0.3030205437427972,"score_spread":0.2843994810726392,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987264910","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008761133,0.000023459097,0.9976998,0.00049356703,0.00011478189,0.00024753803,0.0000017302287,0.00024282244,0.00030017766],"genre_scores_gemma":[0.31995168,0.0000118900225,0.66988456,0.0034921037,0.000113113136,0.00015960903,0.00004429253,0.000015511876,0.0063271928],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992857,0.000016450353,0.00016933536,0.00020541398,0.00014688724,0.00017619],"domain_scores_gemma":[0.999451,0.00004863404,0.00004504298,0.00026589353,0.00013693977,0.000052492007],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013533318,0.00007315399,0.00007440491,0.00006157913,0.00009510734,0.0003692271,0.0003520851,0.000026301188,0.00013605625],"category_scores_gemma":[0.00009662557,0.00006150485,0.00004259164,0.00019637925,0.00000970461,0.0009981279,0.00013123885,0.00002094757,0.0003039567],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.216988e-7,0.00003889626,0.00080891285,0.00002515926,0.000012487285,2.553644e-7,0.00010560786,0.000041149982,0.00014075049,0.9137665,0.053587537,0.0314721],"study_design_scores_gemma":[0.0008418985,0.00015783419,0.0032317725,0.000050436684,0.000015414116,0.0000058676405,0.0001385071,0.79429346,0.0015918477,0.07028961,0.12884343,0.00053993036],"about_ca_topic_score_codex":0.000032403426,"about_ca_topic_score_gemma":0.0000031508798,"teacher_disagreement_score":0.8434769,"about_ca_system_score_codex":0.000047078003,"about_ca_system_score_gemma":0.00003877787,"threshold_uncertainty_score":0.390685},"labels":[],"label_agreement":null},{"id":"W1987764636","doi":"10.1109/icde.2014.6816748","title":"VoidWiz: Resolving incompleteness using network effects","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Imputation (statistics); Computer science; Missing data; Knowledge graph; Analytics; Graph; Data mining; Value (mathematics); Data science; Machine learning; Theoretical computer science; Artificial intelligence","score_opus":0.021990002015137594,"score_gpt":0.2835746323535404,"score_spread":0.26158463033840285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987764636","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002006112,0.000017086297,0.99305826,0.00010050334,0.0003214967,0.00004122758,1.724466e-7,0.00016796119,0.004287196],"genre_scores_gemma":[0.72385156,0.0000035931787,0.27173346,0.0035328362,0.00036939004,0.0000014444663,0.000005995952,0.000012455217,0.00048924936],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99919325,0.00009412144,0.00013296415,0.00020986446,0.00015662852,0.00021316859],"domain_scores_gemma":[0.9992899,0.00014107136,0.000047813952,0.0004052432,0.00004417983,0.000071844916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003398689,0.00007843805,0.00010986971,0.000045546712,0.00015057654,0.0002191314,0.0005249545,0.000027140846,0.000012480881],"category_scores_gemma":[0.0000836404,0.00006788384,0.000028228955,0.00040563734,0.0000165022,0.0003101258,0.00031275905,0.00004410877,0.000050912928],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.5183297e-7,0.000025278621,0.00303088,0.000035143596,0.000010708141,0.0000041838844,0.0000724782,0.009260708,0.00053190434,0.9621467,0.0060082553,0.018872922],"study_design_scores_gemma":[0.000115240866,0.000015594955,0.00079037814,0.000027669312,0.0000031143372,0.0000031575435,0.0000018324737,0.9783201,0.00026983328,0.0037266263,0.016617939,0.000108468696],"about_ca_topic_score_codex":0.00002511389,"about_ca_topic_score_gemma":0.000009084563,"teacher_disagreement_score":0.96905947,"about_ca_system_score_codex":0.000014428087,"about_ca_system_score_gemma":0.000018224142,"threshold_uncertainty_score":0.27682227},"labels":[],"label_agreement":null},{"id":"W1988241068","doi":"10.1145/2591510","title":"Employing a Parametric Model for Analytic Provenance","year":2014,"lang":"en","type":"article","venue":"ACM Transactions on Interactive Intelligent Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Boeing","keywords":"Computer science; Scripting language; Theoretical computer science; Dependency graph; Reuse; Graph; Programming language; Data mining","score_opus":0.05893685629110146,"score_gpt":0.33796880513537714,"score_spread":0.2790319488442757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988241068","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0003967204,0.00002537079,0.99718887,0.0002895454,0.0008912133,0.0005795044,0.00004065062,0.00019189555,0.00039626146],"genre_scores_gemma":[0.98118967,0.000026196683,0.015530208,0.00033758723,0.000053721527,0.00024873723,0.000011702537,0.000026608324,0.0025755423],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998149,0.000105181454,0.0005257281,0.000584003,0.0003133096,0.0003227835],"domain_scores_gemma":[0.99744684,0.0008035225,0.0002340156,0.0010725771,0.0003150366,0.00012799849],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039525056,0.00023546048,0.00031299697,0.00053284055,0.00021667444,0.00034233346,0.0011498218,0.00007545021,0.000011617496],"category_scores_gemma":[0.00036941573,0.00021490746,0.00020785458,0.0007734832,0.000031556014,0.000693424,0.000020893425,0.000198817,0.00012998718],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008835953,0.0008475417,0.00006344271,0.00020949401,0.00034498138,0.0000021015658,0.0017912692,0.8174616,0.000305199,0.096513435,0.0013295598,0.08104302],"study_design_scores_gemma":[0.0002063602,0.00019809268,0.0000059810127,0.00014413877,0.00003051391,0.000007994158,0.00014009929,0.9866055,0.00267746,0.0027225644,0.0070195827,0.000241712],"about_ca_topic_score_codex":0.000040426854,"about_ca_topic_score_gemma":0.0000097974,"teacher_disagreement_score":0.98165864,"about_ca_system_score_codex":0.00018268196,"about_ca_system_score_gemma":0.000057703437,"threshold_uncertainty_score":0.87636715},"labels":[],"label_agreement":null},{"id":"W1988636446","doi":"10.1109/culture-computing.2011.17","title":"The Art-Space of a Global Community: The Network of Baroque Paintings in Hispanic-America","year":2011,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Baroque; Painting; Sustainability; Multidisciplinary approach; Computer science; Art; Visual arts; Humanities; Sociology; Social science; Ecology","score_opus":0.030687308040804738,"score_gpt":0.270793311665535,"score_spread":0.24010600362473025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988636446","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0089147035,0.00009247187,0.92813534,0.002664875,0.00012240554,0.0001413207,0.0000041210374,0.00005054111,0.05987421],"genre_scores_gemma":[0.9896486,0.00005397509,0.008848246,0.00101253,0.000009788499,0.0000018577538,0.0000014486437,0.000002750148,0.000420852],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999122,0.00030520343,0.00022154197,0.000070610884,0.00013654373,0.00014409708],"domain_scores_gemma":[0.9988582,0.00023088063,0.00014610702,0.00066665164,0.00007424633,0.000023873015],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00086018443,0.000057620007,0.00010688692,0.000006494217,0.00010536074,0.00003046995,0.0012762733,0.000019783054,0.000025147165],"category_scores_gemma":[0.00012846522,0.000031472155,0.000036041445,0.0006927268,0.00014935892,0.0000992017,0.00045743625,0.00009909099,0.000009018465],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000034617249,0.00007941559,0.011161794,0.0000055608793,0.000013479472,4.304993e-7,0.0014204991,0.00007573677,0.000009531558,0.9581739,0.023520065,0.0055361423],"study_design_scores_gemma":[0.000784954,0.0005085613,0.082475424,0.00016367759,0.00003176523,0.000009915022,0.006357806,0.6166156,0.00063236005,0.061198328,0.23076709,0.00045450544],"about_ca_topic_score_codex":0.00084046356,"about_ca_topic_score_gemma":0.00066191965,"teacher_disagreement_score":0.9807339,"about_ca_system_score_codex":0.0000135200435,"about_ca_system_score_gemma":0.000047568432,"threshold_uncertainty_score":0.23716545},"labels":[],"label_agreement":null},{"id":"W1988873435","doi":"10.1109/iv.2012.51","title":"Using Clustering to Personalize Visualization","year":2012,"lang":"en","type":"article","venue":"2012 16th International Conference on Information Visualisation","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Visualization; Computer science; Cluster analysis; Information visualization; Set (abstract data type); Data visualization; Data mining; Human–computer interaction; Machine learning","score_opus":0.13062986156645628,"score_gpt":0.3910976901110261,"score_spread":0.2604678285445698,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988873435","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0028560697,0.000005993488,0.97552174,0.0008466892,0.0016814831,0.00025539324,0.00003786916,0.00021682568,0.018577956],"genre_scores_gemma":[0.9700588,0.000022069084,0.02329076,0.005176315,0.0003855929,0.00003196143,0.0005740862,0.000016279479,0.0004441288],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978836,0.00009353164,0.000592184,0.00020332723,0.0008748921,0.00035244247],"domain_scores_gemma":[0.9984226,0.000036467318,0.0003397981,0.00032398934,0.00061710604,0.00026004566],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006350949,0.00021941654,0.0001555546,0.0006794722,0.00019630083,0.00071489386,0.00067743653,0.000096692864,0.00071029394],"category_scores_gemma":[0.00019691142,0.00022632253,0.00006198086,0.00054810476,0.000023544428,0.010727691,0.00021571135,0.00010335514,0.0011430554],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017439816,0.000063170606,0.0005593882,0.000014549139,0.000022650866,1.6763266e-7,0.0038736786,0.0015036807,0.0003834015,0.98260474,0.0026075786,0.008349574],"study_design_scores_gemma":[0.00042792794,0.000066181936,0.0017981271,0.00007071456,0.000009429179,0.000011992188,0.00058954424,0.94066924,0.0008825051,0.0006532772,0.0544383,0.00038277917],"about_ca_topic_score_codex":0.000023937162,"about_ca_topic_score_gemma":0.0000037484735,"teacher_disagreement_score":0.9819514,"about_ca_system_score_codex":0.00027246593,"about_ca_system_score_gemma":0.000088126064,"threshold_uncertainty_score":0.9996347},"labels":[],"label_agreement":null},{"id":"W1989846335","doi":"10.1145/1836135.1836141","title":"Design patterns to guide player movement in 3D games","year":2010,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Timeline; Computer science; Game design; Documentation; Visualization; Set (abstract data type); Human–computer interaction; Process (computing); Game art design; Game Developer; Movement (music); Multimedia; Preference; Video game development; Artificial intelligence","score_opus":0.029203604575885098,"score_gpt":0.31279346125706314,"score_spread":0.28358985668117803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989846335","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0048877015,7.2465843e-7,0.9913175,0.0009548446,0.00015227414,0.00007904775,0.0000014927651,0.000053592496,0.002552837],"genre_scores_gemma":[0.3646989,0.0000075581465,0.5936688,0.030652585,0.00007246852,0.000019218234,0.000008152389,0.000011848044,0.01086045],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993682,0.00001716923,0.00014764207,0.00018536356,0.00014474588,0.00013688902],"domain_scores_gemma":[0.9995138,0.000024913608,0.000018065504,0.00034163543,0.000028340875,0.00007322968],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002240374,0.00005827516,0.000059365208,0.00009429588,0.000017182258,0.000121413956,0.00049039716,0.000020778702,0.00027312484],"category_scores_gemma":[0.000029973358,0.00004858243,0.00001078858,0.00019461132,0.0000042028787,0.00018572353,0.00018256342,0.00004956994,0.00018475114],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006140487,0.0005722919,0.056067016,0.000021088408,0.0000260678,0.00006534358,0.0031775995,0.0052072923,0.027536763,0.52653253,0.21857853,0.16220932],"study_design_scores_gemma":[0.00045687737,0.00008641087,0.015494211,0.000019661802,0.0000022660479,0.0000020548969,0.00008153399,0.8490694,0.03074168,0.0014769178,0.10219885,0.0003701109],"about_ca_topic_score_codex":0.00009741063,"about_ca_topic_score_gemma":0.00030466478,"teacher_disagreement_score":0.8438621,"about_ca_system_score_codex":0.000011253021,"about_ca_system_score_gemma":0.000028115657,"threshold_uncertainty_score":0.29905254},"labels":[],"label_agreement":null},{"id":"W1990390858","doi":"10.3115/1599503.1599559","title":"Determining curricular coverage of student contributions to an online discourse environment through the use of latent semantic analysis and term clouds","year":2009,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Visualization; Latent semantic analysis; Probabilistic latent semantic analysis; Computer science; Term (time); Semantic analysis (machine learning); Tag cloud; Curriculum; Semantic differential; Information retrieval; Data visualization; Semantics (computer science); Data science; Semantic computing; Natural language processing; Artificial intelligence; Semantic Web; Psychology","score_opus":0.047752421105990914,"score_gpt":0.3581800367804853,"score_spread":0.3104276156744944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990390858","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4295449,0.0000095794785,0.56985104,0.00043981394,0.0000091897855,0.00007652215,0.00005721409,0.000007990674,0.000003744934],"genre_scores_gemma":[0.9916207,0.00010379764,0.007603073,0.0005769696,0.000008370115,0.0000010061582,0.000047315563,0.000001949876,0.000036822265],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99906784,0.00006284676,0.00029440483,0.00020160543,0.00025702978,0.00011629855],"domain_scores_gemma":[0.9992318,0.000038659917,0.00011753558,0.0005008224,0.000045498673,0.000065662345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011834586,0.000088017194,0.00020537565,0.00006850849,0.000062255276,0.00008321835,0.00032801912,0.000018427965,0.000013621674],"category_scores_gemma":[0.000016272139,0.000056150267,0.00006561849,0.00039559364,0.00004364188,0.00032012459,0.00017077483,0.00003423645,9.116912e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016791359,0.006747225,0.5471085,0.000032784603,0.001533306,0.00005125297,0.012058229,0.19994234,0.007139028,0.1460788,0.00043649398,0.078855254],"study_design_scores_gemma":[0.00034853318,0.0003303324,0.59451264,0.000023495002,0.00043075866,0.0000026397095,0.00015595104,0.4026118,0.00087896385,0.0001841939,0.0003582769,0.00016239272],"about_ca_topic_score_codex":0.000027769056,"about_ca_topic_score_gemma":0.000023104276,"teacher_disagreement_score":0.562248,"about_ca_system_score_codex":0.000016512098,"about_ca_system_score_gemma":0.000011912454,"threshold_uncertainty_score":0.22897415},"labels":[],"label_agreement":null},{"id":"W1990952334","doi":"10.3138/carto.49.4.2487","title":"A New Database Visualization Framework for the Automatic Construction of Non-standard Charts: Re-creating the Chart of Napoleon's Russian Campaign of 1812","year":2014,"lang":"en","type":"article","venue":"Cartographica The International Journal for Geographic Information and Geovisualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Chart; Visualization; Construct (python library); Information retrieval; Database; Programming language; Data mining","score_opus":0.010596033599586507,"score_gpt":0.3007982314606753,"score_spread":0.2902021978610888,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990952334","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004744753,0.00011646737,0.99122924,0.0021542474,0.0008748223,0.00064762327,0.00013493109,0.000028714598,0.000069217225],"genre_scores_gemma":[0.9694298,0.0008978962,0.028051399,0.0009133675,0.00027527282,0.000049648446,0.00035149333,0.000016616894,0.000014488935],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99757105,0.00012232258,0.0011715794,0.00014855537,0.0007966158,0.00018984622],"domain_scores_gemma":[0.995427,0.00086976803,0.0018356786,0.00040870847,0.0013807476,0.00007806483],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002250581,0.0001836616,0.0002640756,0.0005920467,0.0005582101,0.00035579503,0.0009958341,0.00009820181,0.00001810902],"category_scores_gemma":[0.000926041,0.000110236986,0.00024295645,0.00096279726,0.00027841819,0.0012120071,0.00012377315,0.00014266196,3.4887782e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007744741,0.000025635842,0.002822883,0.00013993605,0.00020162431,4.0331514e-8,0.0032789982,0.0005627134,0.00008010759,0.9609105,0.00073030137,0.031169837],"study_design_scores_gemma":[0.0017720232,0.00040040672,0.0035521747,0.00050711783,0.00021993721,0.000043251268,0.0032457805,0.9284509,0.0017674534,0.040699687,0.019100655,0.00024065594],"about_ca_topic_score_codex":0.00005028294,"about_ca_topic_score_gemma":0.000016787188,"teacher_disagreement_score":0.9646851,"about_ca_system_score_codex":0.000015970554,"about_ca_system_score_gemma":0.00014780211,"threshold_uncertainty_score":0.44953337},"labels":[],"label_agreement":null},{"id":"W1991278297","doi":"10.1007/pl00011645","title":"Intentions in the Coordinated Generation of Graphics and Text from Tabular Data","year":2000,"lang":"en","type":"article","venue":"Knowledge and Information Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Graphics; Computer science; Wizard; Chart; Set (abstract data type); Table (database); Declaration; ASCII; Computer graphics (images); Information retrieval; Focus (optics); Plotter; Programming language; Data mining; World Wide Web","score_opus":0.05029146975346122,"score_gpt":0.2904555233044631,"score_spread":0.2401640535510019,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1991278297","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1406749,0.00460981,0.82363206,0.00088963425,0.00063641684,0.00089520484,0.00044373868,0.000115611445,0.028102644],"genre_scores_gemma":[0.9986356,0.00045330936,0.00013150151,0.00012094837,0.000025743047,0.000004223161,0.00056650327,0.0000012255766,0.000060958173],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993726,0.00006938519,0.00031127574,0.000082306564,0.00011031562,0.000054086773],"domain_scores_gemma":[0.99943036,0.000033483426,0.00007567388,0.0003449594,0.00009479986,0.000020723337],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042281862,0.00005057245,0.00008281993,0.00010931153,0.00006764962,0.0002380663,0.00033385883,0.000032839514,0.000007424723],"category_scores_gemma":[0.000029587838,0.000036715883,0.000007322506,0.00039177362,0.000027860831,0.0026897744,0.000076031116,0.00004088875,0.00001657671],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000066966336,0.00017711116,0.005406687,0.00019826775,0.000058801947,0.000001004331,0.024306376,0.00029042785,0.00021505645,0.7412269,0.055079196,0.17303345],"study_design_scores_gemma":[0.00019824237,0.000011827757,0.0016047616,0.000029903214,0.00000457872,0.000002550176,0.00035507878,0.8326009,0.000015515445,0.000046291974,0.16508347,0.000046893838],"about_ca_topic_score_codex":0.0001159011,"about_ca_topic_score_gemma":0.00006728024,"teacher_disagreement_score":0.8579607,"about_ca_system_score_codex":0.000003936365,"about_ca_system_score_gemma":0.00002112452,"threshold_uncertainty_score":0.22956789},"labels":[],"label_agreement":null},{"id":"W1991929509","doi":"10.1145/1066129.1066131","title":"Advanced widgets for Eclipse","year":2004,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Eclipse; Plug-in; Visualization; Programming language; Java; Class diagram; Graph; Unified Modeling Language; Class (philosophy); Software engineering; Software; Theoretical computer science; Data mining; Artificial intelligence","score_opus":0.02219138972971604,"score_gpt":0.318055748385994,"score_spread":0.29586435865627797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1991929509","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00029775445,0.0000065561658,0.9916322,0.0012508131,0.00015944931,0.000060070903,0.0000023951736,0.00009712985,0.006493598],"genre_scores_gemma":[0.16895804,0.000022261702,0.8164737,0.0072298557,0.00021308009,0.000015919746,0.000030033096,0.000009656462,0.0070474306],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996506,0.000002447367,0.00007068356,0.00012299656,0.00006168159,0.00009157766],"domain_scores_gemma":[0.9996965,0.000012767232,0.000017522623,0.0001964144,0.00003797729,0.000038842456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000047638798,0.000036952646,0.000042273867,0.000025657797,0.000040605373,0.00005727829,0.0002732261,0.0000117699165,0.0000146121465],"category_scores_gemma":[0.00002874879,0.000031108386,0.000022284232,0.00011758782,0.0000073863653,0.00029206567,0.000050330924,0.000011829395,0.00007142998],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.063359e-7,0.000023287588,0.000006203258,0.0000028538466,0.0000018622351,6.903756e-7,0.000042720185,0.0004463009,0.000078852536,0.983565,0.003586987,0.012244669],"study_design_scores_gemma":[0.002708073,0.0002009426,0.00019651276,0.000021700247,0.0000061685455,0.0000065078625,0.000065284046,0.12778617,0.015790865,0.22029476,0.6325407,0.00038234136],"about_ca_topic_score_codex":0.0000012386497,"about_ca_topic_score_gemma":0.0000053844838,"teacher_disagreement_score":0.7632702,"about_ca_system_score_codex":0.000010360387,"about_ca_system_score_gemma":0.00002676236,"threshold_uncertainty_score":0.12685631},"labels":[],"label_agreement":null},{"id":"W1992606915","doi":"10.1057/palgrave/ivs/9500005","title":"Filtering and brushing with motion","year":2002,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":71,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Colligo (Canada)","funders":"","keywords":"Computer science; Motion (physics); Computer vision; Artificial intelligence; Computer graphics (images); Data science","score_opus":0.01898284192553616,"score_gpt":0.2502139247567247,"score_spread":0.23123108283118857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992606915","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0028108777,0.00001195857,0.9937409,0.00018669188,0.00005559466,0.000080776736,0.0000022980505,0.00020953765,0.0029013702],"genre_scores_gemma":[0.9886226,0.000067238565,0.009890662,0.0011585719,0.00002625962,0.0000062693784,0.000103770966,0.0000061525375,0.00011845102],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993553,0.000021383306,0.00021114286,0.00009476077,0.00021418522,0.00010319652],"domain_scores_gemma":[0.99954516,0.000013692585,0.00012341645,0.00015965269,0.00010759483,0.000050485705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011667005,0.00007791761,0.000063164734,0.00017652893,0.00013262987,0.00053665286,0.00013742538,0.00003175302,0.0000449928],"category_scores_gemma":[0.000040533676,0.000070022674,0.000009041656,0.00042144276,0.00001614068,0.0060215234,0.000058174624,0.000032475662,0.00007422349],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000037635139,0.000053353793,0.0024795975,0.00010187948,0.000018205454,0.0000014970977,0.009100495,0.002746772,0.000105669,0.7916996,0.003248312,0.19044088],"study_design_scores_gemma":[0.00026503293,0.000034695127,0.0010295333,0.000022659004,0.0000032295143,0.000014178217,0.00007628993,0.982734,0.00035131944,0.00014516983,0.015207731,0.000116153795],"about_ca_topic_score_codex":0.000004633463,"about_ca_topic_score_gemma":0.0000014873294,"teacher_disagreement_score":0.98581177,"about_ca_system_score_codex":0.000019581677,"about_ca_system_score_gemma":0.0000050133813,"threshold_uncertainty_score":0.51749563},"labels":[],"label_agreement":null},{"id":"W1992660093","doi":"10.1109/tvcg.2011.99","title":"A Space-Filling Visualization Technique for Multivariate Small-World Graphs","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Office of Electricity; University of Alberta; McGill University","keywords":"Computer science; Visualization; Grid; Theoretical computer science; Lattice graph; Graph; Graph drawing; Information visualization; Data visualization; Visibility graph; Power graph analysis; Data mining; Mathematics; Line graph; Voltage graph","score_opus":0.05343716226026767,"score_gpt":0.30253578105963175,"score_spread":0.24909861879936407,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992660093","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00024149485,0.00001920084,0.9975981,0.00003131355,0.00065334485,0.0007748032,0.000034561624,0.00052659266,0.00012059698],"genre_scores_gemma":[0.89345646,0.00041460007,0.1021841,0.0028987792,0.00011428039,0.00026416226,0.00011390603,0.00011936465,0.0004343496],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979648,0.00015838012,0.00054434803,0.0007003183,0.0002791045,0.00035302687],"domain_scores_gemma":[0.9985872,0.00012859033,0.00022805783,0.00048802214,0.00036478977,0.00020334132],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000416171,0.00034913834,0.00029977565,0.0011944067,0.0005315744,0.00028760737,0.00047311117,0.00016541738,0.000021022453],"category_scores_gemma":[0.000007890334,0.00035913003,0.00017239098,0.0019818952,0.00009742072,0.00059708074,0.000012716239,0.00015654166,0.000006409197],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024312887,0.00037850055,0.00004591136,0.00006458336,0.00006244743,0.0000020012255,0.001163828,0.00014997016,0.00012832935,0.9954138,0.00015989375,0.00240642],"study_design_scores_gemma":[0.00085387414,0.00033017204,0.000102501064,0.00010374898,0.000056685814,0.000011866818,0.000033251676,0.9634329,0.022756955,0.009394442,0.0024300765,0.0004935114],"about_ca_topic_score_codex":0.000042974814,"about_ca_topic_score_gemma":0.00007503182,"teacher_disagreement_score":0.9860194,"about_ca_system_score_codex":0.000028229904,"about_ca_system_score_gemma":0.00005737723,"threshold_uncertainty_score":0.9998861},"labels":[],"label_agreement":null},{"id":"W1993057789","doi":"10.1145/1240866.1241014","title":"Comparing visualizations for tracking off-screen moving targets","year":2007,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Visualization; Workspace; Viewport; Computer vision; Tracking (education); Artificial intelligence; Track (disk drive); BitTorrent tracker; Representation (politics); Computer graphics (images); Tracking system; Eye tracking; Robot; Kalman filter","score_opus":0.06510229512979872,"score_gpt":0.35665548447132017,"score_spread":0.29155318934152147,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993057789","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00053483265,0.00004131594,0.9890314,0.00014060979,0.00013460273,0.00012003867,0.0000034386837,0.00025662445,0.00973718],"genre_scores_gemma":[0.82033485,0.0000093309345,0.17648083,0.0012520789,0.00011621912,0.0000032566215,0.00008156011,0.000015283338,0.0017065711],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999043,0.000012233703,0.00027222032,0.00023484934,0.00017040892,0.00026730335],"domain_scores_gemma":[0.9993154,0.00011673987,0.000073333096,0.00026014016,0.00013922396,0.000095154945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005265195,0.000089303445,0.000117910684,0.00014411625,0.00020784457,0.00024802718,0.00048421914,0.000033367432,0.000031724143],"category_scores_gemma":[0.000102351536,0.000087048276,0.000050458777,0.00040799828,0.00001602401,0.000615409,0.00013591793,0.00003851363,0.000017528468],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000020355376,0.00006826733,0.0053063342,0.000013059908,0.000015641146,0.0000019904026,0.0003376267,0.0005963799,0.00038542898,0.9685583,0.004841054,0.019873876],"study_design_scores_gemma":[0.0002784741,0.00002097632,0.0031343657,0.000013974393,0.000006273533,0.0000025050679,0.00009087431,0.9475462,0.0030793408,0.0008625482,0.04479185,0.00017264333],"about_ca_topic_score_codex":0.000016106123,"about_ca_topic_score_gemma":0.00009960535,"teacher_disagreement_score":0.9676958,"about_ca_system_score_codex":0.000024802168,"about_ca_system_score_gemma":0.000026919819,"threshold_uncertainty_score":0.35497257},"labels":[],"label_agreement":null},{"id":"W1993261590","doi":"10.1108/07378830710820943","title":"Information visualization and large‐scale repositories","year":2007,"lang":"en","type":"article","venue":"Library Hi Tech","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Visualization; Information visualization; Leverage (statistics); Data visualization; Data science; USable; Interface (matter); Scale (ratio); User interface; Context (archaeology); Visual analytics; Scatter plot; Creative visualization; Human–computer interaction; Information retrieval; World Wide Web; Data mining; Artificial intelligence","score_opus":0.0062384827286103796,"score_gpt":0.25451444418723784,"score_spread":0.24827596145862746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993261590","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0058404496,0.00004160989,0.98557395,0.00026867632,0.00018688747,0.000060043632,0.0000063381317,0.00043579962,0.0075862734],"genre_scores_gemma":[0.93034524,0.00017295904,0.060806498,0.005009427,0.00026153968,0.0000049090972,0.00056079397,0.000020570043,0.0028180545],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99941987,0.000012876565,0.00020057846,0.0000927484,0.00014504936,0.00012885184],"domain_scores_gemma":[0.99960697,0.00002105276,0.000071048686,0.0002175424,0.000023561384,0.00005982716],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013655158,0.0000625188,0.00005999675,0.00012927652,0.00010763754,0.000363241,0.00022492174,0.00004827609,0.000013067943],"category_scores_gemma":[0.000017790882,0.000059473045,0.000012610531,0.00050602347,0.000015988342,0.005973116,0.00020230022,0.00003836323,0.00002050699],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004178959,0.000036981277,0.014268392,0.000029972623,0.000004875541,0.000003215876,0.0023417966,0.0000015030059,0.000083115134,0.95266116,0.018019052,0.012545753],"study_design_scores_gemma":[0.00035801888,0.000065760134,0.0098862965,0.000027753053,0.000005352523,0.000022155322,0.0007125163,0.06517502,0.018962169,0.004613052,0.89991117,0.00026077006],"about_ca_topic_score_codex":0.0000011594507,"about_ca_topic_score_gemma":6.077007e-7,"teacher_disagreement_score":0.9480481,"about_ca_system_score_codex":0.0000046549035,"about_ca_system_score_gemma":0.000018769444,"threshold_uncertainty_score":0.4330365},"labels":[],"label_agreement":null},{"id":"W1993415883","doi":"10.1145/1809400.1809407","title":"FpVAT","year":2010,"lang":"en","type":"article","venue":"ACM SIGKDD Explorations Newsletter","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":68,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Process (computing); Knowledge extraction; Representation (politics); Data mining; Simple (philosophy); Visualization; Information retrieval; Visual analytics; Machine learning; Artificial intelligence","score_opus":0.03376557419937707,"score_gpt":0.29607554267871694,"score_spread":0.26230996847933985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993415883","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008213704,0.0000055622604,0.9294605,0.05797812,0.00094441744,0.00010735584,0.0000064849028,0.00035528466,0.002928566],"genre_scores_gemma":[0.6315231,0.000018471595,0.29538885,0.06708454,0.0010891693,0.000083034385,0.00020870671,0.000041503707,0.004562652],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99907887,0.000028891493,0.0002042153,0.00028304494,0.00020833782,0.00019665879],"domain_scores_gemma":[0.9981973,0.00007614224,0.00005660593,0.0014821598,0.00009410874,0.00009364242],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001290463,0.000111255235,0.00009055741,0.00013118396,0.00017611316,0.0003949959,0.0013309806,0.000058214973,0.00024972894],"category_scores_gemma":[0.0002528138,0.000102577695,0.000046877707,0.00049793895,0.000044576467,0.0014936585,0.0003539959,0.00019263705,0.0016913218],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.040673e-7,0.000099740704,0.0008720043,0.0000040826303,0.000015835742,0.000012365439,0.00078847393,0.00003808741,0.037052758,0.39884892,0.55303115,0.009235666],"study_design_scores_gemma":[0.00030626735,0.00002716609,0.0005831405,0.0000049214127,0.000008884928,0.0000135041255,0.000041686842,0.019721733,0.010445629,0.014199102,0.95430523,0.0003427349],"about_ca_topic_score_codex":0.000005639026,"about_ca_topic_score_gemma":0.0000359033,"teacher_disagreement_score":0.63407165,"about_ca_system_score_codex":0.0000075956596,"about_ca_system_score_gemma":0.000041118034,"threshold_uncertainty_score":0.99908596},"labels":[],"label_agreement":null},{"id":"W1993614505","doi":"10.1109/ths.2011.6107846","title":"Visual analytics for maritime domain awareness","year":2011,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Geoscience BC; Defence Research and Development Canada","funders":"","keywords":"Visual analytics; Visualization; Computer science; Analytics; Domain (mathematical analysis); Mandate; Data science; Information overload; Task (project management); Data visualization; Anomaly detection; Human–computer interaction; World Wide Web; Data mining; Engineering; Systems engineering","score_opus":0.05793371599474906,"score_gpt":0.32738964840266443,"score_spread":0.2694559324079154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993614505","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004598971,0.0000060713396,0.98805237,0.000121306824,0.00012782378,0.00008010011,0.000008250722,0.00014325946,0.0110009145],"genre_scores_gemma":[0.3181205,0.000017262375,0.66953766,0.0032656088,0.00012844663,0.000021450849,0.000088671455,0.000024806563,0.008795594],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992779,0.000016905786,0.00016751065,0.00022480813,0.00012726041,0.0001856534],"domain_scores_gemma":[0.9994424,0.000033539498,0.00004208782,0.00029740352,0.00009903895,0.00008554205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001859964,0.000083075014,0.00010503399,0.000085380685,0.00008262472,0.0001034656,0.0005543244,0.00003723588,0.00015673216],"category_scores_gemma":[0.000024297387,0.0000727697,0.000053956617,0.00028763164,0.000025210198,0.00033044867,0.0001545184,0.000025757457,0.00007283921],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000031367995,0.000118904725,0.0014561435,0.000014048303,0.00001726191,0.0000034915915,0.00019145214,0.0000038408766,0.000030884807,0.98655987,0.007442867,0.004158079],"study_design_scores_gemma":[0.0005598809,0.0001906416,0.0015993296,0.000014043021,0.000019359091,0.000007996565,0.00014183167,0.8820911,0.003930439,0.05030881,0.0607132,0.00042338122],"about_ca_topic_score_codex":0.0000182654,"about_ca_topic_score_gemma":0.000021519922,"teacher_disagreement_score":0.9362511,"about_ca_system_score_codex":0.000011783448,"about_ca_system_score_gemma":0.00005745704,"threshold_uncertainty_score":0.29674622},"labels":[],"label_agreement":null},{"id":"W1995279738","doi":"10.1002/meet.1450390105","title":"Collaborative information synthesis","year":2002,"lang":"en","type":"article","venue":"Proceedings of the American Society for Information Science and Technology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"University of California, Irvine","keywords":"Computer science; Set (abstract data type); Process (computing); Soar; Task (project management); Information needs; Data science; Information retrieval; World Wide Web; Engineering; Artificial intelligence","score_opus":0.009890559291001112,"score_gpt":0.2549918250836471,"score_spread":0.245101265792646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995279738","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49783105,0.00018659238,0.30015054,0.15121844,0.00069417246,0.0038246152,0.0003258471,0.0018502607,0.043918487],"genre_scores_gemma":[0.959919,0.00024065512,0.037336566,0.0024125702,0.000006914154,0.000057222467,9.1463266e-7,0.000002057356,0.000024117515],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991334,9.540403e-7,0.00024554553,0.00008959808,0.00035063655,0.00017984166],"domain_scores_gemma":[0.9975627,0.000031826807,0.0005467515,0.00012594255,0.0016981236,0.000034639997],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050487136,0.00006852413,0.000118740834,0.00025488486,0.00035254285,0.00024831778,0.0009728399,0.00003008531,0.0000010578864],"category_scores_gemma":[0.00089135533,0.000049981252,0.000045237295,0.0055212723,0.0012934727,0.007083028,0.0003095538,0.00005366964,0.000005271298],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021672936,0.000018610739,0.0012566199,0.00006607627,0.000019106003,2.7172389e-9,0.004036234,0.0000030682017,0.0014641811,0.75241774,0.02263495,0.21808125],"study_design_scores_gemma":[0.0005567326,0.0002920135,0.0012660563,0.0000649268,0.000037818605,0.00001809961,0.028591678,0.44945124,0.07246507,0.006281873,0.44053128,0.00044319156],"about_ca_topic_score_codex":0.0000016439242,"about_ca_topic_score_gemma":7.904977e-8,"teacher_disagreement_score":0.74613583,"about_ca_system_score_codex":0.000041943083,"about_ca_system_score_gemma":0.00006194732,"threshold_uncertainty_score":0.5135025},"labels":[],"label_agreement":null},{"id":"W1995382327","doi":"10.1145/2816795.2818069","title":"Interactive design of probability density functions for shape grammars","year":2015,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Computer science; Procedural modeling; Rule-based machine translation; Artificial intelligence; Human–computer interaction","score_opus":0.10300382211957822,"score_gpt":0.3168682003687014,"score_spread":0.2138643782491232,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995382327","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011694374,0.000006302864,0.99724114,0.00070641097,0.00033046814,0.0003502781,0.000055307224,0.000112425376,0.000028203975],"genre_scores_gemma":[0.73916095,0.000020862499,0.26011673,0.00046095037,0.000017303955,0.000064587635,0.000026101781,0.000013195135,0.00011932356],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99895906,0.00009838074,0.00025388022,0.00029953974,0.00023325652,0.00015588797],"domain_scores_gemma":[0.99810034,0.00036863476,0.00010137359,0.00076744833,0.00053639937,0.00012578693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004629671,0.00011885078,0.0001578406,0.00021648321,0.00014360121,0.00005629938,0.0005831325,0.000070719165,0.000008683786],"category_scores_gemma":[0.00026139646,0.00011453444,0.00012207945,0.00078945427,0.00009392033,0.00046008016,0.000015319049,0.00013825244,0.000008890172],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001279109,0.009515862,0.0025054927,0.00036095548,0.0012478977,0.000009950413,0.0077218125,0.085100874,0.0014315955,0.62336713,0.01885576,0.24860352],"study_design_scores_gemma":[0.001389586,0.0010755094,0.0005083275,0.000042150918,0.0001287264,0.00001201268,0.00032438143,0.73884475,0.0045428113,0.24850383,0.004218513,0.00040939616],"about_ca_topic_score_codex":0.000018026272,"about_ca_topic_score_gemma":0.00003896895,"teacher_disagreement_score":0.7379915,"about_ca_system_score_codex":0.000041490865,"about_ca_system_score_gemma":0.00014897918,"threshold_uncertainty_score":0.4670579},"labels":[],"label_agreement":null},{"id":"W1995404202","doi":"10.3166/ria.26.409-427","title":"Visualisation de grands réseaux dynamiques. Application à la détection d'anomalies de routage dans l'Internet","year":2012,"lang":"fr","type":"article","venue":"Revue d intelligence artificielle","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Humanities; Political science; Philosophy","score_opus":0.044269217154885694,"score_gpt":0.328605373090308,"score_spread":0.28433615593542233,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995404202","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010806602,0.0009519199,0.9769943,0.0017854607,0.00083974155,0.00026916707,0.00002638384,0.00020410202,0.00812236],"genre_scores_gemma":[0.97045094,0.000711629,0.007401452,0.00039836924,0.0004791861,0.00005089688,0.00011333661,0.00003844578,0.020355752],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973778,0.00047144867,0.0006439768,0.00049097347,0.00025510733,0.00076067576],"domain_scores_gemma":[0.9983448,0.0002117221,0.0002910573,0.00065875973,0.00017292457,0.00032078623],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0019148403,0.00028809367,0.00024855795,0.00019240419,0.00023225635,0.0004956866,0.00067345635,0.00027183158,0.00022631083],"category_scores_gemma":[0.00021299491,0.00033882042,0.00015383709,0.0008560446,0.00024724074,0.0013676479,0.00019631277,0.00028997034,0.00073711656],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016748107,0.00081162894,0.01431681,0.0002852036,0.000045833156,0.000009829126,0.03312134,0.024346014,0.005820864,0.84937674,0.0024059818,0.06944301],"study_design_scores_gemma":[0.000047732814,0.00007861966,0.0008821434,0.00015042585,0.00005016532,0.00013602918,0.0013705839,0.8952488,0.038939524,0.004756006,0.05800714,0.00033288225],"about_ca_topic_score_codex":0.001162465,"about_ca_topic_score_gemma":0.00018923536,"teacher_disagreement_score":0.9695928,"about_ca_system_score_codex":0.00046158617,"about_ca_system_score_gemma":0.00014351602,"threshold_uncertainty_score":0.99990636},"labels":[],"label_agreement":null},{"id":"W1997073309","doi":"10.1142/9781860947322_0004","title":"A GRAPH DATABASE WITH VISUAL QUERIES FOR GENOMICS","year":2005,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Graph database; Graph; Information retrieval; Theoretical computer science","score_opus":0.020450427745632514,"score_gpt":0.3003532723753062,"score_spread":0.2799028446296737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997073309","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014672956,0.000013406627,0.99647534,0.000828549,0.000028129269,0.00008281152,0.00002020333,0.000108507105,0.00097575673],"genre_scores_gemma":[0.07779337,0.000036084544,0.91375554,0.0048521687,0.00013818183,0.000017171325,0.00015504009,0.000014066376,0.0032383676],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994998,0.0000066359307,0.00009663652,0.00017837694,0.0000908106,0.00012771919],"domain_scores_gemma":[0.99958736,0.000023505092,0.000030268402,0.00024800698,0.00005310309,0.00005777932],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000086423504,0.00006498722,0.0000649091,0.000056371366,0.00007013609,0.00014435418,0.0002989679,0.000013110702,0.00002428435],"category_scores_gemma":[0.000010740667,0.000048623704,0.000019721674,0.00018019062,0.00002645581,0.0005860746,0.00008623899,0.000020241643,0.00002534964],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010586397,0.00010552298,0.00017796255,0.000012508906,0.00001837583,0.0000014783425,0.00021480367,0.00018651287,0.00033107717,0.9669041,0.017590215,0.014446848],"study_design_scores_gemma":[0.0005219598,0.00012513813,0.00004967619,0.0000064325236,0.000008182423,0.0000077338855,0.00007818047,0.52879006,0.0050454447,0.00052598084,0.46464023,0.00020099695],"about_ca_topic_score_codex":0.000006488184,"about_ca_topic_score_gemma":0.00009834408,"teacher_disagreement_score":0.96637815,"about_ca_system_score_codex":0.0000109589155,"about_ca_system_score_gemma":0.000053846165,"threshold_uncertainty_score":0.1982817},"labels":[],"label_agreement":null},{"id":"W1997155188","doi":"10.1109/vast.2014.7042526","title":"Exploiting history to reduce interaction costs in collaborative analysis","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Dimension (graph theory); Computer science; Visualization; Perspective (graphical); Space (punctuation); Data science; Data visualization; Process (computing); Plan (archaeology); Cognitive dimensions of notations; Exploratory data analysis; Human–computer interaction; Exploratory analysis; Data mining; Cognition; Artificial intelligence","score_opus":0.030257063266256056,"score_gpt":0.32668043057909824,"score_spread":0.2964233673128422,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997155188","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008774697,0.00000763909,0.96695995,0.00059080543,0.00016818027,0.000048127044,7.735637e-7,0.0000665899,0.02338321],"genre_scores_gemma":[0.9785147,0.0000027833792,0.01784699,0.0019299464,0.000026133757,0.0000061663895,0.000011635491,0.0000030881965,0.0016585899],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993162,0.000082991384,0.00016291112,0.0002183383,0.00012289382,0.00009664158],"domain_scores_gemma":[0.99948126,0.00005787079,0.000053651427,0.00024025558,0.00010389425,0.000063093335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025923137,0.00005496834,0.00010785675,0.0004141082,0.000021842436,0.000067315574,0.0002562704,0.000016629572,0.000074187716],"category_scores_gemma":[0.00016325375,0.000053895863,0.00002358279,0.0016466756,0.0000070516253,0.0004621563,0.00008289093,0.000039900213,0.00007989415],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017508768,0.0002881989,0.007911844,0.000012838305,0.00017472572,0.000008579685,0.0107776085,0.01089856,0.004227781,0.7382307,0.110273644,0.117177986],"study_design_scores_gemma":[0.00016218527,0.00004023169,0.0019426635,0.000014742799,0.000017033664,4.4528545e-7,0.0006823144,0.87747645,0.001725826,0.00009027365,0.117683575,0.00016426003],"about_ca_topic_score_codex":0.00009852273,"about_ca_topic_score_gemma":0.00041929618,"teacher_disagreement_score":0.96974,"about_ca_system_score_codex":0.00029722904,"about_ca_system_score_gemma":0.000035753288,"threshold_uncertainty_score":0.21978095},"labels":[],"label_agreement":null},{"id":"W1997241531","doi":"10.4245/sponge.v6i1.16131","title":"Interpreting Feynman Diagrams as Visual Models","year":2012,"lang":"en","type":"article","venue":"Spontaneous Generations A Journal for the History and Philosophy of Science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"University of Bern; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Feynman diagram; Feynman graph; Theoretical physics; Computer science; Mathematics; Physics; Mathematical physics; Particle physics","score_opus":0.045891962473048754,"score_gpt":0.29867040514777055,"score_spread":0.25277844267472177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997241531","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.030661799,0.004246764,0.95644516,0.0019183038,0.0034348168,0.00020515957,0.000007751984,0.00003276639,0.0030474828],"genre_scores_gemma":[0.9901111,0.00011067425,0.008252255,0.0008010118,0.00027688555,0.0000046487635,0.0000013354038,0.000005228919,0.0004368764],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99897975,0.000040345018,0.0002598962,0.00015910274,0.00032760878,0.00023328337],"domain_scores_gemma":[0.9990818,0.00012655236,0.00018186845,0.00021807068,0.00021101977,0.00018072664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012714994,0.00009528045,0.00010782667,0.00016924903,0.0012663151,0.00013569026,0.0007264837,0.000024219225,0.0000136770395],"category_scores_gemma":[0.0001197143,0.00006884853,0.0000641463,0.00024660904,0.0006415667,0.0013081244,0.00011468591,0.000109197885,0.0000029505702],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000105674735,0.00007336778,0.000011465566,0.000007434072,0.000011015318,0.000005906464,0.0041549467,0.0012327159,0.0021933345,0.9862425,0.0009977091,0.00505906],"study_design_scores_gemma":[0.00023827178,0.00031272654,0.0000120636705,0.00004576115,0.000038049697,0.0036854243,0.00023688123,0.85918343,0.0007122071,0.104194134,0.031083995,0.00025708496],"about_ca_topic_score_codex":0.000006187891,"about_ca_topic_score_gemma":0.0000037047228,"teacher_disagreement_score":0.9594493,"about_ca_system_score_codex":0.00012355778,"about_ca_system_score_gemma":0.00021038722,"threshold_uncertainty_score":0.97396},"labels":[],"label_agreement":null},{"id":"W1997272439","doi":"10.1057/palgrave.ivs.9500047","title":"Application of Information Visualization Techniques to the Design of a Mathematical Mindtool: A Usability Study","year":2003,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Visualization; Computer science; Parsing; Usability; Information visualization; Human–computer interaction; Visual analytics; Data visualization; Artificial intelligence; Data science","score_opus":0.025666423098091626,"score_gpt":0.3326348940457385,"score_spread":0.30696847094764684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997272439","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015661314,0.0000030144033,0.9953029,0.00009018999,0.000072167655,0.002170875,0.000016959673,0.00016163335,0.00061611895],"genre_scores_gemma":[0.9596269,0.0000078117155,0.039338835,0.0005741787,0.000014436232,0.00022553343,0.00018904326,0.000010440026,0.000012821653],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99683094,0.00041626004,0.0015537626,0.00016870664,0.00084393774,0.00018641978],"domain_scores_gemma":[0.9968823,0.0001717615,0.00094172993,0.000780824,0.0011441952,0.0000791895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024347035,0.00019266132,0.0002769905,0.0005477179,0.00014784427,0.00021750519,0.0006685533,0.00009923413,0.000025568073],"category_scores_gemma":[0.0014831623,0.00015572706,0.000059446847,0.0023705878,0.000053837986,0.0046401047,0.00012292601,0.000063055166,0.00008545281],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027156797,0.0005566263,0.001729146,0.00020943544,0.00003353102,5.243139e-8,0.015918858,0.009414886,0.00022810893,0.9494349,0.00100959,0.021437755],"study_design_scores_gemma":[0.0007000178,0.00061601767,0.0015918794,0.000064957996,0.000051520416,0.000006010726,0.0025655273,0.94335127,0.02544515,0.0049475376,0.020292081,0.00036802024],"about_ca_topic_score_codex":0.000020320529,"about_ca_topic_score_gemma":0.0000029850905,"teacher_disagreement_score":0.95806074,"about_ca_system_score_codex":0.000077782315,"about_ca_system_score_gemma":0.00014344341,"threshold_uncertainty_score":0.6350365},"labels":[],"label_agreement":null},{"id":"W1997876555","doi":"10.1109/mcg.2006.44","title":"NIH-NSF visualization research challenges report summary","year":2006,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":142,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visualization; Computer science; Data science; Data visualization; Information visualization; Panel discussion; Data mining","score_opus":0.06740706389616379,"score_gpt":0.3621906452845775,"score_spread":0.2947835813884137,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997876555","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005458591,0.00058997684,0.99485654,0.001401982,0.000119281445,0.0002681141,0.00000898239,0.00020400377,0.0020052884],"genre_scores_gemma":[0.9096019,0.014663214,0.061953858,0.0031118703,0.0046155234,0.0008605843,0.0012019097,0.00013657707,0.0038545516],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983351,0.000089812536,0.00034143325,0.00056965824,0.00040474455,0.00025923408],"domain_scores_gemma":[0.99854624,0.00011997576,0.00010197778,0.00074691995,0.00038240282,0.00010248954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068937574,0.00013080967,0.00013892494,0.000359178,0.0004332215,0.00035486318,0.00055908057,0.00008345471,0.0000020939317],"category_scores_gemma":[0.0000050960816,0.00013155022,0.00004547921,0.0009773984,0.00013992003,0.00030941158,0.0002165157,0.00014599657,0.000021552261],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.5619505e-7,0.00012657448,0.00021967404,0.00002147733,0.000007532311,0.000008016052,0.00005495549,0.000038332226,0.000039170696,0.9783866,0.010821839,0.010275477],"study_design_scores_gemma":[0.00021690261,0.00004960707,0.003154259,0.000028690874,0.000008728815,0.00007407109,0.000016879674,0.25907367,0.00019226232,0.09760258,0.6392877,0.00029463018],"about_ca_topic_score_codex":0.000035645062,"about_ca_topic_score_gemma":0.000037282316,"teacher_disagreement_score":0.93290263,"about_ca_system_score_codex":0.000014756291,"about_ca_system_score_gemma":0.000050150247,"threshold_uncertainty_score":0.5364462},"labels":[],"label_agreement":null},{"id":"W2000127412","doi":"10.1109/icat.2006.81","title":"LensTree: Browsing and Navigating Large Hierarchical Information Structures","year":2006,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institute for Theoretical Astrophysics","keywords":"Scrolling; Computer science; Pointer (user interface); Focus (optics); Context (archaeology); Human–computer interaction; Hierarchy; Information retrieval; World Wide Web; Computer graphics (images); Artificial intelligence","score_opus":0.00747955959857205,"score_gpt":0.2665438788475885,"score_spread":0.25906431924901646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000127412","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034705047,0.000011347431,0.9597124,0.0002935351,0.000045931723,0.000027996593,0.0000048767715,0.00010786011,0.005091012],"genre_scores_gemma":[0.94884527,0.000002079544,0.050162647,0.00082917046,0.000035004497,3.475665e-7,0.000051766587,0.0000016936184,0.00007204601],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99953115,0.000013496487,0.00013834758,0.00007953614,0.00012726939,0.000110180634],"domain_scores_gemma":[0.99977213,0.000018591356,0.0000381965,0.00011170503,0.000029427027,0.000029920282],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000083501756,0.00004870627,0.00004678607,0.000032374468,0.000106919106,0.0003320424,0.00013202081,0.000023080767,0.000014457718],"category_scores_gemma":[0.000020041442,0.000040887702,0.0000104727205,0.00014643458,0.000017523302,0.0010586479,0.000120146695,0.00006355792,0.000007783577],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.7314601e-7,0.000005627737,0.0018845192,0.0000070304154,0.000001322955,5.853154e-7,0.00013330813,0.000046392972,0.00005551923,0.96429217,0.0013729926,0.032200284],"study_design_scores_gemma":[0.00042402477,0.000019169629,0.01830477,0.000021555023,0.0000030632193,0.000020743637,0.000095038486,0.93059963,0.0011945077,0.024750687,0.02437535,0.0001914661],"about_ca_topic_score_codex":0.00004012529,"about_ca_topic_score_gemma":0.00001430221,"teacher_disagreement_score":0.93954146,"about_ca_system_score_codex":0.000005620373,"about_ca_system_score_gemma":0.000012338164,"threshold_uncertainty_score":0.32018927},"labels":[],"label_agreement":null},{"id":"W2002083291","doi":"","title":"Quantifying the Space-Efficiency of 2D Graphical Representations of Trees","year":2010,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":55,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Representation (politics); Metric (unit); Tree (set theory); Set (abstract data type); Range (aeronautics); Theoretical computer science; Metric space; Space (punctuation); Exponent; Algorithm; Discrete mathematics; Mathematics; Combinatorics","score_opus":0.051068730225612,"score_gpt":0.36101495617377083,"score_spread":0.30994622594815885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002083291","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07823177,0.000009388518,0.91228485,0.0027162314,0.00023829538,0.000064383385,0.0000041757694,0.000041460655,0.0064094793],"genre_scores_gemma":[0.9903874,0.000007304742,0.009321435,0.0000689995,0.000010409252,7.395032e-7,0.0000018905737,0.0000016650557,0.00020015842],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994195,0.00002568679,0.00018015085,0.000113758455,0.00019041935,0.000070495065],"domain_scores_gemma":[0.99919164,0.00012394914,0.00008265702,0.00048588065,0.00009025647,0.00002560612],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022241707,0.00003821003,0.00007035386,0.00007603705,0.00005555473,0.00003395482,0.0005765935,0.000020588861,0.000047944646],"category_scores_gemma":[0.00014406856,0.000023423609,0.000046097535,0.0006181307,0.00012502038,0.00014262418,0.000117671814,0.00006337393,0.0000042430715],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.092773e-7,0.0000593873,0.0067271953,0.0000031794227,0.000003836739,1.950006e-7,0.0002492448,0.00003727357,0.010413236,0.98106354,0.00085517176,0.0005874353],"study_design_scores_gemma":[0.00037204643,0.00008460867,0.076295525,0.000018082384,0.000022943252,0.000008449798,0.0007153712,0.83103335,0.07994775,0.006557817,0.004747664,0.00019640021],"about_ca_topic_score_codex":0.00005810304,"about_ca_topic_score_gemma":0.0002497566,"teacher_disagreement_score":0.9745057,"about_ca_system_score_codex":7.258497e-7,"about_ca_system_score_gemma":0.000028343075,"threshold_uncertainty_score":0.107146375},"labels":[],"label_agreement":null},{"id":"W2003454829","doi":"10.1109/ccece.2013.6567826","title":"Multilevel label placement for execution trace events","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"TRACE (psycholinguistics); Computer science; Visualization; Graph; Data mining; Quality (philosophy); Theoretical computer science; Data visualization; Information retrieval; Machine learning","score_opus":0.04828618361476973,"score_gpt":0.32786114126401517,"score_spread":0.27957495764924545,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2003454829","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012207228,0.0000057407983,0.99655443,0.0007945073,0.00012219454,0.00023959545,0.0000053779795,0.00008237291,0.0009750286],"genre_scores_gemma":[0.43420097,0.000018409506,0.50154585,0.0033662643,0.000081698294,0.00016775748,0.00008267241,0.000014858022,0.060521502],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99947464,0.000010105224,0.000118057826,0.00015498708,0.000117925614,0.00012429306],"domain_scores_gemma":[0.999613,0.0000257654,0.000033747347,0.00019223687,0.00008240093,0.000052868992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008848767,0.000054741024,0.00005140924,0.000034498982,0.000055540764,0.000080742975,0.00028006575,0.000020637852,0.00012831687],"category_scores_gemma":[0.000024027231,0.000045608278,0.000019518757,0.00008029379,0.0000052071796,0.00044473872,0.000066603345,0.0000166892,0.00025868553],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000037234593,0.0005620161,0.00032749353,0.00003840101,0.00003227016,3.66678e-7,0.00048241435,0.00022641981,0.0023741056,0.570338,0.2960345,0.12958027],"study_design_scores_gemma":[0.0005199446,0.00003629166,0.0005448071,0.0000051330326,0.0000022032657,4.7585687e-7,0.00003098762,0.97377115,0.0013202978,0.0017769746,0.021906685,0.00008505728],"about_ca_topic_score_codex":0.000016036123,"about_ca_topic_score_gemma":0.000002526457,"teacher_disagreement_score":0.9735447,"about_ca_system_score_codex":0.000017643973,"about_ca_system_score_gemma":0.000016156495,"threshold_uncertainty_score":0.33249655},"labels":[],"label_agreement":null},{"id":"W2004017517","doi":"10.3166/ria.22.329-352","title":"Calcul et fouille visuelle orientée-pixel de cubes de données","year":2008,"lang":"fr","type":"article","venue":"Revue d intelligence artificielle","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mathematics; Computer science","score_opus":0.10432027516959959,"score_gpt":0.3352632890256119,"score_spread":0.23094301385601235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2004017517","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017354708,0.0040511237,0.9598378,0.0072729154,0.0013717078,0.00022829481,0.000044990284,0.00018660516,0.009651838],"genre_scores_gemma":[0.7772552,0.014868499,0.03479389,0.0054045906,0.000759342,0.000036820184,0.00007651473,0.00010173324,0.16670343],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9965241,0.0003637778,0.0007896321,0.00082118605,0.0004036155,0.0010977095],"domain_scores_gemma":[0.9975135,0.0003379287,0.00022473432,0.0010997645,0.00033162112,0.00049249956],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0011088856,0.00038479656,0.00040561095,0.00020480363,0.00066511787,0.00037508205,0.0013640202,0.00024535737,0.0010444346],"category_scores_gemma":[0.0005295518,0.0004308424,0.00025400336,0.0013904049,0.00053134473,0.00089051854,0.0005182804,0.0004253529,0.0027984786],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021389867,0.0014215797,0.003560656,0.00032835806,0.00008430468,0.00048514732,0.029154863,0.10640009,0.002236647,0.7660526,0.057738677,0.032515697],"study_design_scores_gemma":[0.000051827104,0.000116197014,0.00007467349,0.0002021811,0.00002272726,0.00038148588,0.00079931313,0.65492404,0.014370917,0.0028017368,0.3258953,0.00035959118],"about_ca_topic_score_codex":0.0003565938,"about_ca_topic_score_gemma":0.00009605885,"teacher_disagreement_score":0.92504394,"about_ca_system_score_codex":0.00023049353,"about_ca_system_score_gemma":0.0006718594,"threshold_uncertainty_score":0.99986875},"labels":[],"label_agreement":null},{"id":"W2004038202","doi":"10.1111/j.1467-8659.2012.03121.x","title":"ConnectedCharts: Explicit Visualization of Relationships between Data Graphics","year":2012,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Bar chart; Computer science; Graphics; Visualization; Parallel coordinates; Visual analytics; Tuple; Interactive visual analysis; Statistical graphics; Data visualization; Analytics; Data mining; Simple (philosophy); Process (computing); Scatter plot; Computer graphics (images); Programming language; Machine learning; Statistics; Mathematics","score_opus":0.11372435756231487,"score_gpt":0.33168601178919715,"score_spread":0.2179616542268823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2004038202","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0034332369,0.00022856047,0.99465746,0.00047463653,0.000538632,0.00017265495,0.00011558311,0.00024172828,0.00013752042],"genre_scores_gemma":[0.9823834,0.00011463258,0.015006967,0.0006778484,0.00028110942,0.0000043317677,0.0014867722,0.00002670078,0.000018266293],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977141,0.00022979215,0.0006478781,0.00045424863,0.00048635507,0.0004676483],"domain_scores_gemma":[0.9969408,0.00032846618,0.00036062708,0.0018640253,0.00026542597,0.00024064508],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011608975,0.0002172931,0.0003117204,0.0005375444,0.0002713732,0.00016316486,0.0020741571,0.00016098369,0.000008289115],"category_scores_gemma":[0.00012786055,0.0002206464,0.00008812147,0.0019595933,0.00008986694,0.002542187,0.0013475342,0.00022778101,0.000024742367],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.505544e-7,0.00008999957,0.14142765,0.000023607434,0.000043798424,3.9746485e-7,0.0002981457,0.0000065778777,0.000006668465,0.84812045,0.00909475,0.0008870949],"study_design_scores_gemma":[0.00081670575,0.00014983854,0.06481934,0.00013158923,0.000105446416,0.000015002453,0.000105431776,0.8292981,0.00049619,0.02532481,0.07793029,0.0008072623],"about_ca_topic_score_codex":0.000014650556,"about_ca_topic_score_gemma":0.000010636157,"teacher_disagreement_score":0.9796505,"about_ca_system_score_codex":0.000013525072,"about_ca_system_score_gemma":0.00005367312,"threshold_uncertainty_score":0.8997699},"labels":[],"label_agreement":null},{"id":"W2004099228","doi":"10.1145/1879211.1879218","title":"User evaluation of polymetric views using a large visualization wall","year":2010,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Visualization; Computer science; Java; Software visualization; Domain (mathematical analysis); Data visualization; Information visualization; Software; Software system; Human–computer interaction; Key (lock); Software engineering; Data mining; Programming language; Component-based software engineering; Operating system","score_opus":0.08923297967413084,"score_gpt":0.40338081557862177,"score_spread":0.3141478359044909,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2004099228","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.055086598,0.000022438944,0.9425812,0.000046163867,0.00022154719,0.00011859764,0.0000028707475,0.00005345832,0.0018671774],"genre_scores_gemma":[0.9783907,0.0000060765997,0.020711102,0.000436596,0.0000325305,0.00000201408,0.000029313642,0.000007294316,0.00038437004],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99878585,0.00009000726,0.00025867016,0.0001828956,0.0005578365,0.00012476166],"domain_scores_gemma":[0.99899614,0.00002423413,0.00014147251,0.00038303234,0.00040632798,0.000048800273],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012628485,0.000070049224,0.00010073048,0.00030343476,0.000053925643,0.00008370778,0.00034841156,0.00004875039,0.00035615146],"category_scores_gemma":[0.00021267452,0.000060965744,0.00003625331,0.0013452439,0.0000124235185,0.0005645522,0.00010893356,0.000045068948,0.000025696007],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012337285,0.00031346706,0.006050519,0.0000196254,0.000018122613,3.3632404e-7,0.00039922138,0.000225755,0.02532233,0.9504781,0.0016062454,0.015565044],"study_design_scores_gemma":[0.0003036326,0.000011663259,0.0011586255,0.0000048387406,0.000020016212,0.0000016056955,0.000011414277,0.98322266,0.007922857,0.00036567712,0.006896426,0.00008057897],"about_ca_topic_score_codex":0.000031252963,"about_ca_topic_score_gemma":0.00006444748,"teacher_disagreement_score":0.9829969,"about_ca_system_score_codex":0.000016544283,"about_ca_system_score_gemma":0.00010906999,"threshold_uncertainty_score":0.38996089},"labels":[],"label_agreement":null},{"id":"W200494573","doi":"","title":"Menu Structuring for Mobile Devices","year":2008,"lang":"de","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Structuring; Process (computing); Human–computer interaction; Context (archaeology); Mobile device; Mobile interaction; Orientation (vector space); Spatial contextual awareness; Smartwatch; Computer vision; Artificial intelligence; Multimedia; Computer graphics (images); World Wide Web; Wearable computer; Embedded system; Geography","score_opus":0.041680753042740805,"score_gpt":0.3166154875455013,"score_spread":0.27493473450276046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W200494573","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006448424,0.0011586021,0.9874044,0.00024668375,0.0013543228,0.0003632882,0.00004827198,0.00016429168,0.0028117152],"genre_scores_gemma":[0.810594,0.0012781034,0.14306764,0.0064385603,0.0015898737,0.00005264947,0.00015287224,0.000051181814,0.036775075],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989099,0.000020448759,0.00024633406,0.00033223056,0.00023276772,0.00025830304],"domain_scores_gemma":[0.99921393,0.00006061501,0.00008467114,0.00037508656,0.00012827112,0.00013742293],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011601564,0.00013017368,0.00015084347,0.000070715556,0.0002812262,0.000184369,0.0006051273,0.000057532772,0.00035770758],"category_scores_gemma":[0.000028073093,0.00011748514,0.00007110587,0.0002472251,0.00005180214,0.0004284582,0.00019639556,0.00005181179,0.0002838271],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018794237,0.00042129334,0.0031488403,0.0005046549,0.000379314,0.00006635411,0.0060413643,0.0035910713,0.0003536231,0.6902627,0.22157384,0.0736382],"study_design_scores_gemma":[0.0002791936,0.00008080438,0.00018565274,0.000014387199,0.000017443006,0.000007448587,0.000057178582,0.35438177,0.0019427944,0.0002650006,0.6425807,0.00018766653],"about_ca_topic_score_codex":0.00001032735,"about_ca_topic_score_gemma":0.000008538535,"teacher_disagreement_score":0.84433675,"about_ca_system_score_codex":0.000017673088,"about_ca_system_score_gemma":0.000119761666,"threshold_uncertainty_score":0.4790905},"labels":[],"label_agreement":null},{"id":"W2005906503","doi":"10.1109/pacificvis.2014.43","title":"Using Entropy-Related Measures in Categorical Data Visualization","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Science Foundation","keywords":"Categorical variable; Visualization; Computer science; Entropy (arrow of time); Data visualization; Joint entropy; Information visualization; Data mining; Visual analytics; Mutual information; Data science; Artificial intelligence; Machine learning; Principle of maximum entropy","score_opus":0.10779042592675706,"score_gpt":0.36431590584694434,"score_spread":0.25652547992018726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2005906503","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00077767373,0.000013201451,0.9969979,0.0001680074,0.00012849108,0.00004248069,0.0000012998316,0.00010500747,0.001765963],"genre_scores_gemma":[0.9885192,0.000012908649,0.010699201,0.00045034382,0.00002986141,4.1813854e-7,0.00012402865,0.000006943725,0.00015711748],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989521,0.00011890422,0.00023912941,0.00030675944,0.00023542022,0.00014772484],"domain_scores_gemma":[0.99912953,0.000032440028,0.000052332678,0.0006811711,0.000048945963,0.00005556666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048015144,0.000072469804,0.00009959578,0.00013129438,0.000044993303,0.0001596902,0.000911426,0.00004305434,0.000035341272],"category_scores_gemma":[0.00019462654,0.00006350709,0.000011511952,0.00068404526,0.000016338912,0.0007101005,0.00039773228,0.000047717323,0.00004807462],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.223429e-7,0.000051702747,0.002110527,0.0000028934596,0.00000405676,0.0000016186784,0.000073547424,0.0008488133,0.00028260055,0.99217135,0.0008855543,0.0035668241],"study_design_scores_gemma":[0.00019647561,0.000008352972,0.0003958632,0.0000045050274,0.0000033913066,0.0000034583052,0.00000836021,0.9874512,0.00013272387,0.004345459,0.0073594097,0.00009081787],"about_ca_topic_score_codex":0.00011856753,"about_ca_topic_score_gemma":0.00004947883,"teacher_disagreement_score":0.9878259,"about_ca_system_score_codex":0.000027736165,"about_ca_system_score_gemma":0.000039450864,"threshold_uncertainty_score":0.2589744},"labels":[],"label_agreement":null},{"id":"W2007342570","doi":"10.1177/1473871611425872","title":"Visualizing explicit and implicit relations of complex information spaces","year":2011,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Theoretical computer science; Visualization; Information visualization; Focus (optics); Set (abstract data type); Spatial relation; Similarity (geometry); Spatialization; Graph; Data visualization; Artificial intelligence; Programming language","score_opus":0.044132300363291764,"score_gpt":0.30113154801902065,"score_spread":0.2569992476557289,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007342570","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007164504,0.000010367951,0.9802826,0.00007662649,0.00010287423,0.00023488248,0.000026848173,0.00021650908,0.0118848],"genre_scores_gemma":[0.9825572,0.000055202443,0.015900835,0.0008242342,0.000015418063,0.000015338082,0.00058965635,0.000007195398,0.00003493761],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984674,0.00005516123,0.00083204213,0.000114676695,0.00035626753,0.00017449004],"domain_scores_gemma":[0.9984578,0.000040621377,0.0006290756,0.0003154726,0.00046543908,0.00009158953],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003405424,0.00015116128,0.00017885519,0.0005903617,0.00017898018,0.00028461317,0.00032359664,0.0000895655,0.00010060601],"category_scores_gemma":[0.0001577761,0.0001544213,0.0000393531,0.0009120148,0.00004526586,0.01239432,0.00017166008,0.00005609264,0.000115958035],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000057372,0.000031119223,0.0024789923,0.000063494655,0.000015210952,8.3774204e-8,0.011789832,0.000082444945,0.00012370381,0.9760857,0.0013845798,0.00793909],"study_design_scores_gemma":[0.0011774277,0.00021655342,0.04244919,0.000093713184,0.00003800194,0.000019592508,0.002834447,0.8820027,0.004213385,0.00621639,0.0601662,0.000572407],"about_ca_topic_score_codex":0.00007239508,"about_ca_topic_score_gemma":0.0000038258213,"teacher_disagreement_score":0.9753927,"about_ca_system_score_codex":0.000033013745,"about_ca_system_score_gemma":0.000055196404,"threshold_uncertainty_score":0.8985583},"labels":[],"label_agreement":null},{"id":"W2007802752","doi":"10.1109/hicss.2013.420","title":"Observations of Record-Keeping in Co-located Collaborative Analysis","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science","score_opus":0.04539410111329865,"score_gpt":0.3195853751464616,"score_spread":0.27419127403316296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007802752","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06716313,0.000009829367,0.92730224,0.00084024493,0.000031001167,0.00012450718,0.000008019875,0.000058199694,0.004462844],"genre_scores_gemma":[0.94770736,0.000011509363,0.050778925,0.0005937117,0.000004415063,0.00000935346,0.00005908386,0.0000026609841,0.0008329848],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993468,0.000046137262,0.00025926752,0.00014466287,0.000114254,0.00008886466],"domain_scores_gemma":[0.9992767,0.000057470814,0.00008783765,0.00026166838,0.0002825238,0.000033793636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000117215626,0.000049236998,0.00014208589,0.00031072745,0.00002578846,0.00007584908,0.00031388493,0.000022540584,0.0001854134],"category_scores_gemma":[0.000066506174,0.000044912464,0.000028695831,0.005007662,0.0000196097,0.00057041436,0.00005055582,0.000028496857,0.000042747764],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016078609,0.00032057017,0.5609191,0.000020308036,0.0003027678,0.0000028951233,0.0020780247,0.005800823,0.0034381784,0.40427825,0.01754789,0.0052895597],"study_design_scores_gemma":[0.00011629618,0.000013391241,0.1474154,0.0000053498998,0.000014917148,6.482008e-8,0.00022968826,0.84995633,0.0009355962,0.0005272684,0.0007091648,0.000076558004],"about_ca_topic_score_codex":0.00056957727,"about_ca_topic_score_gemma":0.00039020026,"teacher_disagreement_score":0.88054425,"about_ca_system_score_codex":0.000016366701,"about_ca_system_score_gemma":0.000053204807,"threshold_uncertainty_score":0.24060154},"labels":[],"label_agreement":null},{"id":"W2008795456","doi":"10.1109/tvcg.2012.255","title":"RelEx: Visualization for Actively Changing Overlay Network Specifications","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Software deployment; Visualization; Computer science; Summative assessment; Usability; Human–computer interaction; Process (computing); Domain (mathematical analysis); Data visualization; Software engineering; Formative assessment; Data mining; Operating system","score_opus":0.05032843922240114,"score_gpt":0.3053206346063957,"score_spread":0.25499219538399454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008795456","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004950833,0.00006525841,0.99700016,0.00010004515,0.0013468309,0.00044427015,0.000034694014,0.00040966284,0.00010397328],"genre_scores_gemma":[0.9818929,0.00063891325,0.012606724,0.0034179555,0.00071735197,0.000120335666,0.00015720483,0.00007061103,0.00037801615],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980765,0.00013834778,0.00043627305,0.00046989106,0.00034030518,0.00053869537],"domain_scores_gemma":[0.9986591,0.00020409925,0.00020605893,0.00042501395,0.0002630391,0.00024272793],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004920549,0.00027941473,0.00024317694,0.0006041958,0.00083450344,0.00033965515,0.00033750315,0.00014904408,0.000018083063],"category_scores_gemma":[0.000008207699,0.00029620246,0.00013101927,0.001931516,0.00006814071,0.0012249879,0.000011444375,0.00012632617,0.000015508234],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012968498,0.00029399284,0.00008573721,0.00003102464,0.00005108787,1.6639395e-7,0.0010150115,0.00105012,0.000014648613,0.9909972,0.0018596841,0.0045883423],"study_design_scores_gemma":[0.0005857025,0.0001743204,0.00039975194,0.00005277551,0.000048090344,0.000008017557,0.00007232457,0.9695906,0.001086254,0.0011828846,0.026396759,0.0004025113],"about_ca_topic_score_codex":0.0000027733179,"about_ca_topic_score_gemma":0.000004357904,"teacher_disagreement_score":0.98981434,"about_ca_system_score_codex":0.000046702546,"about_ca_system_score_gemma":0.000043200485,"threshold_uncertainty_score":0.99994904},"labels":[],"label_agreement":null},{"id":"W2008804228","doi":"10.1145/2588555.2594518","title":"SerpentTI","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Social media; Computer science; World Wide Web; Focus (optics); Analytics; Theme (computing); Social network service; Service (business); Data science; Business","score_opus":0.016924518941942666,"score_gpt":0.2820392664703517,"score_spread":0.265114747528409,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008804228","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000103399594,9.76374e-7,0.9153329,0.00058280677,0.00005546578,0.0000067265005,9.033841e-8,0.0000907147,0.083826914],"genre_scores_gemma":[0.89357376,0.0000033132483,0.08060397,0.008272383,0.000052653788,7.068712e-7,0.000004702805,0.0000029957805,0.017485488],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997754,0.000009779091,0.000038516893,0.00007008511,0.000058840076,0.000047378722],"domain_scores_gemma":[0.9997455,0.000009457704,0.000007906043,0.00019609863,0.000013620806,0.000027408405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007450494,0.000019252106,0.00002245224,0.000016661132,0.000018842024,0.00006619534,0.00026757168,0.000006192019,0.000078243225],"category_scores_gemma":[0.00001600175,0.00001517588,0.000008412627,0.000096253905,0.000003986663,0.00014972234,0.00006846633,0.000009676911,0.0004683102],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.351636e-8,0.000005252825,0.0001410265,5.3218565e-7,5.0767994e-7,8.547095e-8,0.000010940426,0.0000050402377,0.00001579228,0.9737388,0.012281074,0.01380093],"study_design_scores_gemma":[0.000050183375,0.000008195612,0.00038450086,8.156998e-7,3.6208783e-7,7.274539e-7,0.000001961385,0.58340895,0.00047442957,0.0047932337,0.4108385,0.000038133217],"about_ca_topic_score_codex":0.0000021807202,"about_ca_topic_score_gemma":0.0000014064283,"teacher_disagreement_score":0.96894556,"about_ca_system_score_codex":0.0000016808484,"about_ca_system_score_gemma":0.0000040674727,"threshold_uncertainty_score":0.60193366},"labels":[],"label_agreement":null},{"id":"W2010700167","doi":"10.1007/s00799-006-0003-4","title":"Generating customized yet factually consistent information: a constraint satisfaction approach","year":2006,"lang":"en","type":"article","venue":"International Journal on Digital Libraries","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Constraint satisfaction problem; Personalization; Consistency (knowledge bases); Set (abstract data type); Constraint (computer-aided design); Constraint satisfaction; Snippet; Information retrieval; World Wide Web; Artificial intelligence; Mathematics","score_opus":0.01486148997786254,"score_gpt":0.23816791054841646,"score_spread":0.22330642057055392,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010700167","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007905493,0.000024161434,0.9268884,0.001766451,0.0011534155,0.00009148949,0.00014669448,0.00017204632,0.06185183],"genre_scores_gemma":[0.971347,0.000009714867,0.025312344,0.002206109,0.0003105993,0.0000037630523,0.0003229131,0.000007895515,0.0004796901],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99842733,0.00003107435,0.0005445656,0.00014299221,0.0006973445,0.00015667053],"domain_scores_gemma":[0.9990579,0.00010086027,0.00032703346,0.00014241466,0.00028159417,0.000090203175],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.000119018936,0.00014671664,0.00014023903,0.00025836096,0.00015417342,0.007524288,0.0005753325,0.00004755145,0.00005597011],"category_scores_gemma":[0.0001562855,0.00012422915,0.00010421,0.00014312338,0.000081932216,0.008426933,0.00015015189,0.00016992775,0.0000945981],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003539392,0.000099302924,0.0013746136,0.000003961214,0.000092166505,0.00002645066,0.00024350201,0.0066576162,0.000023184903,0.9247591,0.015876079,0.05080866],"study_design_scores_gemma":[0.0055640936,0.00028127513,0.0061792163,0.00017352281,0.000024720486,0.0022380538,0.0008013629,0.5062244,0.0009791225,0.04964786,0.42673635,0.001149988],"about_ca_topic_score_codex":0.000005548641,"about_ca_topic_score_gemma":7.365114e-7,"teacher_disagreement_score":0.9634415,"about_ca_system_score_codex":0.000074950745,"about_ca_system_score_gemma":0.00019343075,"threshold_uncertainty_score":0.993506},"labels":[],"label_agreement":null},{"id":"W2010997497","doi":"10.1145/2254556.2254653","title":"Hierarchically animated transitions in visualizations of tree structures","year":2012,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Animation; Computer science; Visualization; Tree (set theory); Computer animation; Computer graphics (images); Computer facial animation; Tree structure; Skeletal animation; Data visualization; Human–computer interaction; Artificial intelligence; Data structure; Programming language","score_opus":0.023969711895484767,"score_gpt":0.31867389478181607,"score_spread":0.2947041828863313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010997497","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0076740077,0.00001967255,0.9850968,0.00043802953,0.00004918853,0.00005284405,0.000012434427,0.0000719639,0.0065850616],"genre_scores_gemma":[0.9725288,0.0000062778436,0.027017768,0.00028667136,0.000012169946,0.0000016131924,0.000034992994,0.0000035586581,0.00010813107],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993813,0.00004400652,0.00020905935,0.00009222093,0.00012890462,0.00014451213],"domain_scores_gemma":[0.9996401,0.00002249087,0.00003395036,0.00019279055,0.00004401843,0.0000666235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010522851,0.000055463337,0.00008911883,0.00017169178,0.000030611183,0.00002826932,0.0002611782,0.000028906157,0.0001230211],"category_scores_gemma":[0.000028781526,0.000048167145,0.000025058553,0.00072051946,0.00003011424,0.00043737332,0.000041721192,0.000038089947,0.000007694898],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.895831e-7,0.00011054998,0.002230438,0.0000059797135,0.0000040027007,2.8092697e-7,0.0008026447,0.00007799772,0.0012893981,0.9940159,0.00042267304,0.0010394834],"study_design_scores_gemma":[0.0014148416,0.00013597577,0.21649438,0.000047905643,0.000026420874,0.000018319442,0.00050145393,0.7267883,0.013010528,0.032863315,0.008101964,0.00059664715],"about_ca_topic_score_codex":0.000010263511,"about_ca_topic_score_gemma":0.000049212078,"teacher_disagreement_score":0.96485484,"about_ca_system_score_codex":0.000007920892,"about_ca_system_score_gemma":0.00002829813,"threshold_uncertainty_score":0.19641992},"labels":[],"label_agreement":null},{"id":"W2011751385","doi":"10.1109/vast.2009.5333895","title":"MassVis: Visual analysis of protein complexes using mass spectrometry","year":2009,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Scatter plot; Computer science; Workflow; Plot (graphics); Visualization; Cluster analysis; Data visualization; Function (biology); Data mining; Mass spectrometry; Tandem mass spectrometry; Biological system; Information retrieval; Chemistry; Database; Artificial intelligence; Machine learning; Biology; Mathematics; Chromatography","score_opus":0.03051407900671463,"score_gpt":0.3333892834232682,"score_spread":0.3028752044165536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011751385","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.042617258,0.0000127505,0.9551694,0.00016935666,0.000014885824,0.00005846311,0.0000050521116,0.00007902942,0.0018738274],"genre_scores_gemma":[0.7948884,0.0000015667779,0.20462456,0.00028279106,0.00001221777,2.4228504e-7,0.000013506652,0.0000023148527,0.00017440158],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99900264,0.000042676595,0.00026987508,0.0002274009,0.00029463274,0.00016279724],"domain_scores_gemma":[0.99938995,0.000016336964,0.00011630234,0.00033754818,0.00007876704,0.00006112726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017791656,0.00009055052,0.00024293232,0.0006624131,0.000046913545,0.00010873655,0.0004665588,0.00002813882,0.00013792908],"category_scores_gemma":[0.000023517134,0.000079871934,0.00010801485,0.0035146216,0.000027128015,0.00031709232,0.000064035696,0.00003992596,0.000007541109],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000040975497,0.0003160728,0.0033927718,0.000013380277,0.00045112197,0.000008809922,0.00009241544,0.0020803255,0.20216027,0.7879114,0.00018715872,0.0033821536],"study_design_scores_gemma":[0.00010355236,0.0000751974,0.0048240973,0.000007260422,0.00009800012,6.690224e-7,0.000027655915,0.9727082,0.020362025,0.0015244815,0.0001463201,0.00012250438],"about_ca_topic_score_codex":0.000027488331,"about_ca_topic_score_gemma":0.0000038615544,"teacher_disagreement_score":0.9706279,"about_ca_system_score_codex":0.000025128213,"about_ca_system_score_gemma":0.000033025677,"threshold_uncertainty_score":0.3257083},"labels":[],"label_agreement":null},{"id":"W2011816842","doi":"10.1117/12.768317","title":"Exploration of uncertainty in bidirectional vector fields","year":2007,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Glyph (data visualization); Computer science; Visualization; Task (project management); Domain (mathematical analysis); Implementation; Property (philosophy); Data visualization; Field (mathematics); Data mining; Theoretical computer science; Human–computer interaction; Data science; Programming language; Systems engineering; Engineering","score_opus":0.020927952207880348,"score_gpt":0.2676253491487234,"score_spread":0.24669739694084303,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011816842","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9875532,0.000031396223,0.008661049,0.0016946596,0.00025811992,0.0002284436,0.000018100705,0.000053582055,0.0015014621],"genre_scores_gemma":[0.8916234,0.0000798131,0.1076036,0.00015748081,0.00026092472,0.000034078155,0.000014590267,0.000024642408,0.00020147089],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982114,1.4144087e-8,0.00067136606,0.00027384,0.000596629,0.00024678407],"domain_scores_gemma":[0.9981992,0.00014693408,0.0003271524,0.000058158505,0.0011959597,0.00007254485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009211537,0.00016709122,0.00025853427,0.00017369713,0.000039458537,0.00007142736,0.00092785025,0.00012972536,0.0000069434614],"category_scores_gemma":[0.0004937084,0.00014660791,0.00027663237,0.00065879634,0.000103424674,0.0010407553,0.0001569173,0.0001774175,8.081254e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003351851,0.0001360094,0.00044302896,0.00016687434,0.000088985806,7.612216e-8,0.00035251697,0.0008432057,0.09690281,0.8990407,0.0014094486,0.0005828462],"study_design_scores_gemma":[0.0024333238,0.00066797936,0.0062731686,0.0006348306,0.00009081547,0.000015458314,0.0024992637,0.67472506,0.2879429,0.014714208,0.0092413435,0.00076169125],"about_ca_topic_score_codex":0.000019219406,"about_ca_topic_score_gemma":0.0000015504661,"teacher_disagreement_score":0.88432646,"about_ca_system_score_codex":0.00010698877,"about_ca_system_score_gemma":0.00003911257,"threshold_uncertainty_score":0.5978497},"labels":[],"label_agreement":null},{"id":"W2013729144","doi":"10.1145/2633043","title":"Inferring Visualization Task Properties, User Performance, and User Cognitive Abilities from Eye Gaze Data","year":2014,"lang":"en","type":"article","venue":"ACM Transactions on Interactive Intelligent Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":84,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visualization; Computer science; Human–computer interaction; Information visualization; Gaze; Eye tracking; Data visualization; Task (project management); Perception; Visual analytics; Classifier (UML); User interface; User modeling; Artificial intelligence; Psychology","score_opus":0.05378051185742397,"score_gpt":0.3125240347274856,"score_spread":0.25874352287006164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013729144","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.048641358,0.00006479098,0.949112,0.00010102409,0.0009774582,0.00039129143,0.00019418217,0.00017939927,0.00033850968],"genre_scores_gemma":[0.9969758,0.00020839518,0.0007263833,0.00026368684,0.00010021765,0.00006143831,0.00022469282,0.000029726414,0.0014096631],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977511,0.00028364384,0.00055498217,0.00075991376,0.00038828468,0.00026203878],"domain_scores_gemma":[0.99755937,0.00051107135,0.0002012874,0.0012746984,0.00032659183,0.000126988],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003583503,0.00028647704,0.00030710382,0.00028617788,0.000274213,0.00059897674,0.0011315668,0.00009380286,0.00007786026],"category_scores_gemma":[0.00027788756,0.00025024457,0.00004943704,0.00032935856,0.00010003255,0.0025306717,0.0001384327,0.00024493324,0.00016462593],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021639736,0.00911983,0.08361941,0.0035848503,0.0076244776,0.000040326242,0.10074328,0.059296146,0.01183778,0.08159743,0.011175307,0.6291972],"study_design_scores_gemma":[0.00051634415,0.0003251482,0.0013211218,0.0014482494,0.000100010264,0.0000107172755,0.0032313303,0.916975,0.012236939,0.00011313895,0.06311537,0.00060661143],"about_ca_topic_score_codex":0.0005462716,"about_ca_topic_score_gemma":0.000071158465,"teacher_disagreement_score":0.9483856,"about_ca_system_score_codex":0.00010389223,"about_ca_system_score_gemma":0.00005412497,"threshold_uncertainty_score":0.999995},"labels":[],"label_agreement":null},{"id":"W2013892175","doi":"10.1145/2018556.2018559","title":"Visualizing and understanding players' behavior in video games","year":2011,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":72,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Visualization; Game design; Game Developer; Data visualization; Human–computer interaction; Game mechanics; Task (project management); Video game; Game art design; Video game development; Video game design; Data science; Multimedia; Artificial intelligence","score_opus":0.12818998688315342,"score_gpt":0.3259557865690352,"score_spread":0.19776579968588176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013892175","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017311065,0.000027348773,0.9718745,0.000047724287,0.0000699174,0.000057706893,8.180106e-7,0.00009024814,0.010520693],"genre_scores_gemma":[0.9885708,0.000024336776,0.01080036,0.0003244289,0.0000056171866,0.0000024741933,0.0000013266081,0.000003806476,0.00026685884],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99945956,0.000018400833,0.00012474954,0.00017950153,0.0000909477,0.0001268614],"domain_scores_gemma":[0.99973786,0.00002247185,0.000026403512,0.00015020548,0.000009355625,0.000053678352],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013895165,0.000059798844,0.000071500726,0.00014145563,0.000039861497,0.00010133397,0.0001998965,0.00002515966,0.00005930762],"category_scores_gemma":[0.000014667412,0.000054265645,0.0000121783705,0.0002311297,0.000024897216,0.0004796793,0.00013914944,0.000037547983,0.000011094048],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010900515,0.00004485271,0.026941046,0.0000051881193,0.0000024062845,0.000015320638,0.0014829739,4.937121e-7,0.00010096245,0.969603,0.00032981383,0.0014728628],"study_design_scores_gemma":[0.003896982,0.0005891332,0.18387204,0.0002828448,0.000067916815,0.00012066617,0.016399438,0.71417785,0.01398261,0.05794802,0.0064676027,0.0021948898],"about_ca_topic_score_codex":0.00006195039,"about_ca_topic_score_gemma":0.000072381285,"teacher_disagreement_score":0.9712597,"about_ca_system_score_codex":0.00002754375,"about_ca_system_score_gemma":0.000014526065,"threshold_uncertainty_score":0.22128887},"labels":[],"label_agreement":null},{"id":"W2013989095","doi":"10.1016/j.csda.2008.11.033","title":"Escaping RGBland: Selecting colors for statistical graphics","year":2009,"lang":"en","type":"article","venue":"Computational Statistics & Data Analysis","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":209,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"McGill University","keywords":"Categorical variable; Hue; Graphics; Artificial intelligence; Computer science; Luminance; Color space; HSL and HSV; Statistical graphics; Coding (social sciences); Computer vision; Computer graphics (images); RGB color model; Mathematics; Statistics","score_opus":0.04945520726689731,"score_gpt":0.3684192233551133,"score_spread":0.318964016088216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013989095","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009536513,0.000041989944,0.9923673,0.00039243896,0.00007445441,0.00014482303,0.0067033935,0.00012332456,0.00005689489],"genre_scores_gemma":[0.12933758,0.000023371234,0.83752185,0.0012725219,0.00007285864,0.000004400411,0.031714562,0.000010097771,0.00004274572],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99758726,0.00010531692,0.00058979605,0.0007732234,0.00059097866,0.0003533935],"domain_scores_gemma":[0.99703205,0.0012499377,0.0002573496,0.00078491645,0.0004943484,0.00018139105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071625435,0.00020569768,0.00037914858,0.0004852795,0.00040734868,0.0005976312,0.0013139346,0.00005673454,0.000040741023],"category_scores_gemma":[0.00079064665,0.00021639102,0.00007990404,0.0021959273,0.000058814396,0.000569139,0.00024486583,0.0001238975,0.000017958911],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007965893,0.00012395711,0.00096399325,0.000017223516,0.0005250759,0.000010267238,0.00009830343,0.045277067,0.000003092022,0.8954924,0.039805606,0.01767507],"study_design_scores_gemma":[0.00027541726,0.00006480863,0.0103683,0.0000053000244,0.00050207693,0.0000028280676,0.000009502364,0.8848414,0.0000017499657,0.10028722,0.003403117,0.00023832018],"about_ca_topic_score_codex":0.00004693658,"about_ca_topic_score_gemma":0.00008522395,"teacher_disagreement_score":0.83956426,"about_ca_system_score_codex":0.000046483146,"about_ca_system_score_gemma":0.00016864734,"threshold_uncertainty_score":0.88241696},"labels":[],"label_agreement":null},{"id":"W2014774959","doi":"10.1109/smc.2014.6974242","title":"Towards a system for visualizing Alberta's cemeteries","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"MacEwan University","funders":"MacEwan University","keywords":"Visualization; Architecture; Computer science; State (computer science); Data science; Data visualization; Work (physics); Government (linguistics); World Wide Web; Archaeology; Geography; Engineering; Data mining","score_opus":0.029242312622738745,"score_gpt":0.3045031773070867,"score_spread":0.27526086468434796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2014774959","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00016770513,0.000003773052,0.97505003,0.00038113596,0.00024467907,0.00007429381,0.000002041812,0.00017959796,0.023896752],"genre_scores_gemma":[0.86807555,0.0000018615976,0.12520422,0.0014099032,0.00012453688,0.000022947204,0.000021714208,0.000012818255,0.0051264362],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993388,0.000028616849,0.0001577649,0.00019947434,0.0001214821,0.00015386984],"domain_scores_gemma":[0.99943334,0.00008293405,0.0000466034,0.0003051201,0.00007091858,0.000061113074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002319978,0.00007552801,0.000112958274,0.000056813464,0.0000892701,0.00026539154,0.00043656898,0.000025172743,0.000011042394],"category_scores_gemma":[0.00010333635,0.000061345214,0.000046917787,0.00016512178,0.000012839023,0.00030949994,0.00012478745,0.000015521156,0.000049257444],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.0163863e-7,0.000008668832,0.000021447107,0.000043640946,0.000005723785,1.1629714e-7,0.00012223114,0.0000052672194,0.00009664275,0.988877,0.0026093724,0.008209105],"study_design_scores_gemma":[0.00023311912,0.00007252132,0.000023642011,0.000021414333,0.0000057420157,0.000003986584,0.00008736511,0.7159305,0.003945855,0.00089687743,0.27863947,0.00013949042],"about_ca_topic_score_codex":0.00007327351,"about_ca_topic_score_gemma":0.0000275799,"teacher_disagreement_score":0.9879801,"about_ca_system_score_codex":0.000015435386,"about_ca_system_score_gemma":0.000021633276,"threshold_uncertainty_score":0.25591767},"labels":[],"label_agreement":null},{"id":"W2014848270","doi":"10.1145/966131.966135","title":"Perceptually based brush strokes for nonphotorealistic visualization","year":2004,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":77,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Glyph (data visualization); Visualization; Salient; Representation (politics); Artificial intelligence; Graphics; Computer graphics; Perception; Visual analytics; Computer graphics (images); Computer vision; Pattern recognition (psychology)","score_opus":0.032841803156640634,"score_gpt":0.30822155397119533,"score_spread":0.2753797508145547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2014848270","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004555253,0.000008577009,0.99732023,0.0011947026,0.00024976028,0.0002455015,0.00016455716,0.00027722566,0.00008391485],"genre_scores_gemma":[0.85344666,0.00009844939,0.14037082,0.0054739635,0.000051110506,0.000088948065,0.00028025132,0.00004134196,0.00014847638],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99878323,0.00003452561,0.00026490874,0.00036755102,0.0003172239,0.00023253866],"domain_scores_gemma":[0.9986767,0.00016195387,0.000075287775,0.0007699018,0.00019995373,0.00011615589],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017789289,0.00016749086,0.00014397193,0.00035774248,0.00034627333,0.00018613315,0.000768602,0.00009668029,0.000031911928],"category_scores_gemma":[0.000084936044,0.00017072026,0.00015004649,0.0008597311,0.000069328606,0.00036690925,0.000006974932,0.00010465336,0.000016156679],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004936594,0.0013446969,0.00009659852,0.00012513189,0.00009546625,0.000006158268,0.00092595886,0.048011806,0.000758011,0.93475425,0.0009353855,0.012897178],"study_design_scores_gemma":[0.0060980096,0.0013992487,0.0016834054,0.0002230708,0.00022542181,0.000015095058,0.00029664297,0.8311252,0.011430729,0.12097492,0.025129229,0.0013990139],"about_ca_topic_score_codex":0.000035345245,"about_ca_topic_score_gemma":0.00013023328,"teacher_disagreement_score":0.8569494,"about_ca_system_score_codex":0.000051153907,"about_ca_system_score_gemma":0.00015822105,"threshold_uncertainty_score":0.696177},"labels":[],"label_agreement":null},{"id":"W2015277797","doi":"10.1145/2507288.2507291","title":"Presentation patterns","year":2013,"lang":"en","type":"article","venue":"ACM SIGSOFT Software Engineering Notes","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Presentation (obstetrics); Software engineering; Medicine","score_opus":0.016925181516834267,"score_gpt":0.2557837749532833,"score_spread":0.23885859343644905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015277797","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.057722054,0.00003637535,0.9407224,0.00037124872,0.00025758528,0.00010638666,0.0000075054736,0.00077317754,0.0000032456542],"genre_scores_gemma":[0.91565984,0.000010612011,0.08379798,0.0002774038,0.00007250191,0.00002295444,0.000049450155,0.000016423193,0.00009283374],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999188,0.000010876146,0.00016470463,0.00022827127,0.00019584932,0.00021228615],"domain_scores_gemma":[0.9941486,0.004971823,0.00004296469,0.0006530261,0.00008599491,0.000097577584],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.000058611182,0.00012373846,0.00009894231,0.00010255044,0.00004634618,0.00026518537,0.00081922737,0.000043640695,0.000109742716],"category_scores_gemma":[0.02119177,0.000122066594,0.000038993992,0.00025810095,0.0000068786076,0.00084640336,0.0002911556,0.00007632176,0.00030748014],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.3029406e-7,0.000104738516,0.9131792,0.00017958581,0.000054390777,0.000013632842,0.0008781849,0.004269247,0.0027418197,0.013193716,0.008433749,0.056950986],"study_design_scores_gemma":[0.00036174108,0.00005628355,0.907636,0.000091158945,0.000012388491,0.000013522133,0.000017309616,0.077244915,0.007857717,0.00033484967,0.0057292595,0.0006448819],"about_ca_topic_score_codex":0.000058480575,"about_ca_topic_score_gemma":0.000001254967,"teacher_disagreement_score":0.8579378,"about_ca_system_score_codex":0.000017747509,"about_ca_system_score_gemma":0.000014790213,"threshold_uncertainty_score":0.98705316},"labels":[],"label_agreement":null},{"id":"W2015755066","doi":"10.1109/tvcg.2013.153","title":"Empirical Guidance on Scatterplot and Dimension Reduction Technique Choices","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":183,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria; University of British Columbia","funders":"","keywords":"Computer science; Usability; Workflow; Dimensionality reduction; Data visualization; Data mining; Visualization; Dimension (graph theory); Set (abstract data type); Artificial intelligence; Machine learning; Human–computer interaction; Database","score_opus":0.02519876842752377,"score_gpt":0.30963438750978706,"score_spread":0.2844356190822633,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015755066","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011544016,0.000026149737,0.9869322,0.00038555497,0.00038386657,0.00034967216,0.0000049548185,0.0003247929,0.000048757087],"genre_scores_gemma":[0.9899724,0.000395344,0.005181266,0.004087198,0.00007720659,0.00008236049,0.000014149194,0.00002709522,0.00016294079],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99848485,0.00014268585,0.00032236284,0.00054864807,0.00030282838,0.0001986431],"domain_scores_gemma":[0.9991288,0.00006923597,0.00010705251,0.00036831957,0.00016525056,0.0001613211],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017378997,0.00022658102,0.00018274279,0.0004488298,0.00036849445,0.0004155804,0.00022546433,0.00012673865,0.000016608838],"category_scores_gemma":[0.000003198315,0.00021045103,0.000051674575,0.0007656299,0.00011338215,0.0007320634,0.000010712959,0.0001697648,0.000024817278],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044606106,0.0018013053,0.0011161405,0.00020936744,0.00014895955,0.0000070961532,0.0020986446,0.0014026461,0.0018614379,0.9055211,0.011923634,0.073865086],"study_design_scores_gemma":[0.00046431957,0.00047318503,0.001996983,0.00013036774,0.000018143366,0.0000472649,0.00002216205,0.98369443,0.008695516,0.0015273213,0.0025509435,0.00037933522],"about_ca_topic_score_codex":0.000022005068,"about_ca_topic_score_gemma":0.0000038063818,"teacher_disagreement_score":0.9822918,"about_ca_system_score_codex":0.000020312329,"about_ca_system_score_gemma":0.00002212574,"threshold_uncertainty_score":0.8581945},"labels":[],"label_agreement":null},{"id":"W2018064988","doi":"10.1145/1268517.1268554","title":"Progressive multiples for communication-minded visualization","year":2007,"lang":"en","type":"article","venue":"Proceedings","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Timeline; Computer science; Visualization; Event (particle physics); Data visualization; Multiple; Data science; Visual analytics; World Wide Web; Human–computer interaction; Data mining","score_opus":0.027634633250463007,"score_gpt":0.34266492931360565,"score_spread":0.31503029606314265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018064988","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0048182863,0.00008748352,0.9918428,0.00041871885,0.00006334194,0.00033247963,0.0000034222696,0.00025169327,0.0021817572],"genre_scores_gemma":[0.87741995,0.000014268087,0.12154091,0.00049374404,0.00006481548,0.000034063367,0.000055334378,0.000013658844,0.00036328196],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99921596,0.0000032112882,0.00021464538,0.00020554518,0.00017033756,0.00019031265],"domain_scores_gemma":[0.99908197,0.00006941164,0.00015599477,0.00015278636,0.0004716091,0.00006820016],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004815981,0.000084159954,0.000085439904,0.000114449096,0.00018537631,0.00024586808,0.0006190472,0.00004680133,0.0000058597966],"category_scores_gemma":[0.0002732922,0.000080972204,0.000032398955,0.00042090358,0.000036876314,0.0006780325,0.00013585742,0.00003962191,0.000011539064],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000761816,0.00008987117,0.0022855555,0.00004408029,0.000011387132,4.238042e-7,0.0018249195,0.000001435877,0.0008299193,0.9777902,0.004787767,0.012326872],"study_design_scores_gemma":[0.0020332243,0.00022291795,0.0047906972,0.00018702328,0.00003627011,0.00002705903,0.0013297974,0.7014963,0.07830902,0.023673072,0.18710567,0.0007889485],"about_ca_topic_score_codex":0.0000016064374,"about_ca_topic_score_gemma":0.0000014599806,"teacher_disagreement_score":0.95411706,"about_ca_system_score_codex":0.00002485573,"about_ca_system_score_gemma":0.000022471208,"threshold_uncertainty_score":0.33019507},"labels":[],"label_agreement":null},{"id":"W2018885424","doi":"10.1002/meet.14504201177","title":"Towards a research agenda for visual informatics","year":2005,"lang":"en","type":"article","venue":"Proceedings of the American Society for Information Science and Technology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Informatics; Computer science; Engineering informatics; Data science; Visualization; Visual analytics; Health informatics; Human–computer interaction; Knowledge management; Artificial intelligence; Engineering; Political science","score_opus":0.04013249442407557,"score_gpt":0.3783642424931723,"score_spread":0.3382317480690967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018885424","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.42324227,0.00004419194,0.5128318,0.055739343,0.00021630808,0.0024231635,0.00008043212,0.00052017224,0.004902308],"genre_scores_gemma":[0.7648658,0.00009478776,0.23182131,0.003019387,0.000031000927,0.00010012979,0.0000026811988,0.0000045290085,0.000060364735],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99860066,0.0000012043778,0.00035767155,0.000114137125,0.00057569315,0.0003506591],"domain_scores_gemma":[0.9966554,0.000049084567,0.0004262622,0.00014208193,0.00267935,0.000047832487],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023438204,0.00007564674,0.0001395969,0.0003828466,0.00057632005,0.00028193716,0.0014490037,0.000042196687,3.1036083e-7],"category_scores_gemma":[0.001024722,0.000055429347,0.00007787058,0.0046363026,0.0019164013,0.003749459,0.0006554626,0.00010364437,0.0000020940647],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005338759,0.000025767411,0.00021289024,0.00009865281,0.0000139516205,1.2751527e-9,0.0041493867,0.0000045425877,0.0021803263,0.62080044,0.021919983,0.3505887],"study_design_scores_gemma":[0.00048733866,0.0003882226,0.00018871491,0.000025903151,0.000010383214,0.000008208696,0.016463049,0.45751938,0.039009415,0.007260762,0.47845876,0.00017983273],"about_ca_topic_score_codex":0.0000030818014,"about_ca_topic_score_gemma":3.1909184e-7,"teacher_disagreement_score":0.6135397,"about_ca_system_score_codex":0.000081085906,"about_ca_system_score_gemma":0.00030154974,"threshold_uncertainty_score":0.70610607},"labels":[],"label_agreement":null},{"id":"W2019215553","doi":"10.1109/hicss.2014.176","title":"Studying Animation for Real-Time Visual Analytics: A Design Study of Social Media Analytics in Emergency Management","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Visual analytics; Computer science; Analytics; Animation; Social media analytics; Cultural analytics; Data science; Visualization; Social media; Interactive visual analysis; Emergency management; Data visualization; Big data; Information visualization; Human–computer interaction; Semantic analytics; World Wide Web; Artificial intelligence; Data mining; The Internet; Computer graphics (images)","score_opus":0.06246409507180954,"score_gpt":0.3475030349951246,"score_spread":0.285038939923315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019215553","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022795204,0.0000014290453,0.9748583,0.00006564674,0.00008861498,0.00054527394,0.0000026761616,0.00007130008,0.0015715959],"genre_scores_gemma":[0.9636572,0.000020047077,0.03570248,0.00003305109,0.00005653466,0.00002617519,0.000024194187,0.000014417654,0.00046590078],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99811417,0.0001758535,0.00068728934,0.0003562949,0.00043480904,0.00023159568],"domain_scores_gemma":[0.99908626,0.00015930897,0.0002395842,0.00029089628,0.00017053568,0.00005342647],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012898013,0.00014551617,0.0002985308,0.0004393235,0.00009421793,0.00007217062,0.00055935484,0.000040303228,0.000048624952],"category_scores_gemma":[0.000118313,0.00013980249,0.000058363315,0.0010641213,0.000014883767,0.00031488365,0.00020715565,0.00004072914,0.000014282634],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016088496,0.012821596,0.017035048,0.0005784901,0.0009949247,0.000017617753,0.046845727,0.02401957,0.0013340202,0.8082511,0.020836638,0.06710443],"study_design_scores_gemma":[0.0011118999,0.00028865394,0.0076539563,0.000008190357,0.00006565997,1.2750088e-7,0.001986146,0.98681617,0.000069069276,0.0017400184,0.00008718525,0.00017292594],"about_ca_topic_score_codex":0.000016776923,"about_ca_topic_score_gemma":0.00009171595,"teacher_disagreement_score":0.9627966,"about_ca_system_score_codex":0.000045828503,"about_ca_system_score_gemma":0.000021035197,"threshold_uncertainty_score":0.57009804},"labels":[],"label_agreement":null},{"id":"W2019617939","doi":"10.1145/1569901.1569908","title":"VISPLORE","year":2009,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Visualization; Particle swarm optimization; Data visualization; Data exploration; Human–computer interaction; Range (aeronautics); Population; Interactive visual analysis; Interactive visualization; Artificial intelligence; Machine learning","score_opus":0.021986718933980447,"score_gpt":0.3068461844839032,"score_spread":0.28485946554992275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019617939","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00014490717,0.0000039624383,0.9466435,0.0020277062,0.000028868211,0.00000836657,1.296513e-7,0.00012930215,0.05101329],"genre_scores_gemma":[0.93464994,0.0000069562143,0.048671197,0.012193212,0.000028604565,1.6115749e-7,0.0000034925827,0.0000011036195,0.004445325],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99977934,0.0000034262675,0.00003881592,0.00006814863,0.000059964248,0.000050273484],"domain_scores_gemma":[0.99979174,0.0000028335037,0.0000070897404,0.00015795116,0.000013589212,0.000026801921],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000027404692,0.000020674164,0.000021922364,0.00002041269,0.000018245611,0.00006863122,0.00024419057,0.0000069310345,0.00004247625],"category_scores_gemma":[0.000005792361,0.000016207447,0.000009528818,0.00014175968,0.0000025893835,0.0001959174,0.000021414822,0.000011178021,0.00018056478],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.402459e-8,0.000011226396,0.0000177028,1.4539366e-7,3.7573884e-7,0.0000010769287,0.000029189669,0.0000030567999,0.00003042092,0.9609558,0.012741677,0.026209218],"study_design_scores_gemma":[0.0002778772,0.0001547967,0.0044044503,0.000004944958,0.0000019405254,0.000008203769,0.00002422301,0.6736238,0.002455529,0.06324017,0.25558898,0.00021509484],"about_ca_topic_score_codex":5.129774e-7,"about_ca_topic_score_gemma":2.9936092e-7,"teacher_disagreement_score":0.93450505,"about_ca_system_score_codex":0.000002233036,"about_ca_system_score_gemma":0.0000074791774,"threshold_uncertainty_score":0.23208551},"labels":[],"label_agreement":null},{"id":"W2019944300","doi":"10.1007/978-3-642-31454-4_23","title":"Towards Adaptive Information Visualization: On the Influence of User Characteristics","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":110,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Visualization; Information visualization; Human–computer interaction; Adaptation (eye); Context (archaeology); Bar chart; Perception; Visual analytics; Preference; Task (project management); Artificial intelligence","score_opus":0.022580442224785523,"score_gpt":0.27201706650679996,"score_spread":0.24943662428201444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019944300","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0003004889,0.000026980477,0.9968729,0.00040270045,0.00049516134,0.00026346318,0.000030027957,0.00006088329,0.0015473855],"genre_scores_gemma":[0.9423098,0.00015587246,0.048609424,0.008271339,0.00036573794,0.000010431096,0.0000640726,0.000030005594,0.00018329755],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975184,0.000042375443,0.0006221007,0.0004134659,0.0010659641,0.00033765298],"domain_scores_gemma":[0.99734694,0.0002963798,0.00060854584,0.0010474802,0.00059829024,0.000102382575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081623864,0.00032741082,0.00033723676,0.0005346599,0.00017293474,0.00036988937,0.0024172342,0.00018281068,0.000032311455],"category_scores_gemma":[0.00025069955,0.00023802136,0.000073089206,0.00073324994,0.0004937151,0.0016323013,0.00081307936,0.00035566033,0.00008080012],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000052312516,0.00002840279,0.00006594159,0.000031358923,0.000011081884,0.0000022048084,0.0012043874,0.012869258,0.000016254886,0.80916417,0.00005362157,0.1765481],"study_design_scores_gemma":[0.00034610665,0.00042692234,0.006071249,0.0010576049,0.00003008672,0.000024386352,0.0000015865927,0.91559845,0.0017390014,0.050826218,0.022753622,0.0011247476],"about_ca_topic_score_codex":0.000008531225,"about_ca_topic_score_gemma":0.000003651659,"teacher_disagreement_score":0.94826347,"about_ca_system_score_codex":0.0001300907,"about_ca_system_score_gemma":0.00040230787,"threshold_uncertainty_score":0.9706229},"labels":[],"label_agreement":null},{"id":"W2020209128","doi":"10.1057/ivs.2010.9","title":"Accommodating IPv6 Addresses in Security Visualization Tools","year":2010,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; IPv6; IPv4; Visualization; Network security; The Internet; Computer security; Data science; World Wide Web; Data mining","score_opus":0.022057581375386118,"score_gpt":0.3239579858245105,"score_spread":0.3019004044491244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020209128","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.040589467,0.0000064777505,0.951739,0.0001906525,0.0006712034,0.00035929668,0.000028429567,0.0004828685,0.0059325895],"genre_scores_gemma":[0.994264,0.00002909318,0.002786012,0.0013273451,0.00008514705,0.000030307852,0.0014348674,0.00001371003,0.000029482399],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99796283,0.00010101856,0.00086802884,0.00023944819,0.0005351692,0.00029349513],"domain_scores_gemma":[0.998425,0.00011044289,0.00042792363,0.00051279354,0.0004192146,0.00010463718],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00073439896,0.00020078727,0.00019410899,0.0006564715,0.00018965133,0.0012122149,0.00070131774,0.0001717099,0.00014221994],"category_scores_gemma":[0.0009916885,0.00021405701,0.00004588908,0.0018324495,0.000037978243,0.013354389,0.00022613634,0.000204024,0.00020305607],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004704067,0.00010596482,0.0070913276,0.00006517735,0.0000063783423,9.800352e-7,0.0033759319,0.00069436914,0.00034997403,0.9697815,0.0018149524,0.016708726],"study_design_scores_gemma":[0.0007514841,0.00003622167,0.007881093,0.00005170492,0.0000057595216,0.000009001124,0.00029267112,0.9364627,0.0032001785,0.0037276272,0.047178183,0.00040340488],"about_ca_topic_score_codex":0.000038457085,"about_ca_topic_score_gemma":0.00010800682,"teacher_disagreement_score":0.9660539,"about_ca_system_score_codex":0.000053745123,"about_ca_system_score_gemma":0.00012538918,"threshold_uncertainty_score":0.99982464},"labels":[],"label_agreement":null},{"id":"W2020235040","doi":"10.1145/1145581.1145619","title":"Taking the community's pulse","year":2006,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Marketing buzz; Surprise; Reputation; Social media; Public opinion; Internet privacy; Microblogging; Computer science; World Wide Web; Order (exchange); Opinion leadership; Power (physics); Phenomenon; Advertising; Public relations; Political science; Sociology; Business","score_opus":0.04001432250805144,"score_gpt":0.3067538005999206,"score_spread":0.26673947809186915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020235040","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014193335,0.000008756119,0.83205485,0.0014717114,0.000052350373,0.000019722076,5.4617624e-7,0.00009736071,0.16487536],"genre_scores_gemma":[0.99122417,0.0000011975496,0.0039807754,0.0019826011,0.000026498337,6.423595e-7,0.0000058714363,0.0000016721293,0.0027765569],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99966383,0.00006443562,0.00006912707,0.000044890643,0.00008619304,0.00007153074],"domain_scores_gemma":[0.99948597,0.000050715513,0.000030456527,0.00039976204,0.00002193079,0.0000111477475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020654945,0.00003073695,0.000027620328,0.00001858244,0.00021824383,0.00020345097,0.000716982,0.000008909375,0.000110226814],"category_scores_gemma":[0.000017402886,0.000018400087,0.000014538393,0.00020997689,0.00001963243,0.00016968194,0.00018597906,0.000064196676,0.000074607255],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.7731672e-8,0.00002401405,0.0003694083,8.480329e-7,0.0000011348528,5.6060327e-7,0.00007297399,0.00005924325,0.00004067981,0.981278,0.01008564,0.008067466],"study_design_scores_gemma":[0.00029193572,0.00003114798,0.040831268,0.000011541683,0.000006546399,0.000016094978,0.00030238347,0.70855564,0.002178493,0.034841567,0.21266697,0.00026641277],"about_ca_topic_score_codex":0.00063225836,"about_ca_topic_score_gemma":0.00017123189,"teacher_disagreement_score":0.98980486,"about_ca_system_score_codex":0.0000046543955,"about_ca_system_score_gemma":0.000008164013,"threshold_uncertainty_score":0.19618824},"labels":[],"label_agreement":null},{"id":"W2022951468","doi":"10.1145/2009916.2010162","title":"The Meta-Dex Suite","year":2011,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Suite; Computer science; Index (typography); Scalability; Domain (mathematical analysis); Information retrieval; Software; Data mining; World Wide Web; Programming language; Database; Mathematics","score_opus":0.1389501655515393,"score_gpt":0.30536742710074416,"score_spread":0.16641726154920486,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022951468","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00002590229,0.000050295504,0.8821674,0.00048299116,0.00009259201,0.000022062868,5.126993e-7,0.00009138714,0.11706687],"genre_scores_gemma":[0.62199163,0.000279819,0.15181625,0.016797803,0.00012104353,0.000023781009,0.000008505288,0.000022510654,0.20893863],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99965405,0.000018747769,0.000070985705,0.00008407494,0.00008938752,0.000082735394],"domain_scores_gemma":[0.99955213,0.000026621432,0.000012302079,0.0003486105,0.000029507359,0.00003080448],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001762658,0.000034104032,0.000042008716,0.000013508061,0.000085203625,0.00011098444,0.0006259912,0.000007973359,0.00021635718],"category_scores_gemma":[0.00001833801,0.00001649583,0.00003863865,0.00014212368,0.000018503933,0.00019952934,0.00013192398,0.000018579181,0.0002658044],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.187621e-7,0.000007170962,0.000041695555,2.5114707e-7,0.0000353127,6.3041864e-7,0.00009096404,2.2142507e-7,0.00000391973,0.98636734,0.010905435,0.0025469111],"study_design_scores_gemma":[0.00009931057,0.00003039853,0.0009287693,6.7882826e-7,0.000073066454,0.0000043474233,0.00006025745,0.080078214,0.0030500325,0.023651669,0.89187384,0.00014941278],"about_ca_topic_score_codex":0.000016970414,"about_ca_topic_score_gemma":0.000016939888,"teacher_disagreement_score":0.9627157,"about_ca_system_score_codex":0.0000018564825,"about_ca_system_score_gemma":0.000010081836,"threshold_uncertainty_score":0.34164667},"labels":[],"label_agreement":null},{"id":"W2023356304","doi":"10.5539/cis.v1n4p3","title":"An Alternative Analysis of Two Circular Variables via Graphical Representation","year":2008,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Plot (graphics); Box plot; Computer science; Variable (mathematics); Representation (politics); Exploratory data analysis; Statistics; Variables; Linear regression; Principal component analysis; Mathematics; Data mining; Mathematical analysis","score_opus":0.027342434565759063,"score_gpt":0.3272245358614048,"score_spread":0.29988210129564574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2023356304","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.066487566,0.0000039878714,0.9329101,0.00003799072,0.00010015459,0.000046537207,0.0000046535656,0.000037215723,0.0003717846],"genre_scores_gemma":[0.9595637,0.000039328082,0.039843228,0.0005001538,0.000015640597,0.0000012140013,0.00003439346,8.8652007e-7,0.0000015050599],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99883074,0.000035903642,0.00032200033,0.00019474077,0.0004953588,0.000121264035],"domain_scores_gemma":[0.9989019,0.000033818,0.00017228904,0.0003854397,0.00039781016,0.00010875107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045629722,0.00006856294,0.00014204916,0.0009466564,0.00022379933,0.00021871833,0.0006665672,0.000016880133,0.000006180982],"category_scores_gemma":[0.000024895922,0.00006128209,0.000038435745,0.0040642484,0.00030007068,0.011115546,0.00016944611,0.000038838865,0.0000037951734],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000046227387,0.00013152615,0.034276225,0.000019136955,0.00014549296,0.0000036465335,0.012062531,0.08225303,0.0012441269,0.8206586,0.00016237347,0.049038645],"study_design_scores_gemma":[0.00015227201,0.000035933623,0.042892393,0.0000026105017,0.000016971828,0.000009721698,0.000015844289,0.9551275,0.00072623236,0.0007729888,0.00017351726,0.00007405323],"about_ca_topic_score_codex":0.000042268282,"about_ca_topic_score_gemma":6.8221715e-7,"teacher_disagreement_score":0.89307606,"about_ca_system_score_codex":0.000012275608,"about_ca_system_score_gemma":0.000063590596,"threshold_uncertainty_score":0.80585027},"labels":[],"label_agreement":null},{"id":"W2023357311","doi":"10.1109/tvcg.2013.214","title":"Variant View: Visualizing Sequence Variants in their Gene Context","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research; Canada's Michael Smith Genome Sciences Centre","keywords":"Computer science; Visualization; Workflow; Context (archaeology); Sequence (biology); Task (project management); Data visualization; Encoding (memory); Information retrieval; Data science; Human–computer interaction; Data mining; Artificial intelligence; Database; Biology; Genetics","score_opus":0.03505998007357396,"score_gpt":0.28724645938030113,"score_spread":0.25218647930672716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2023357311","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0052094166,0.00006386263,0.99337304,0.00015384238,0.0005446505,0.00034450463,0.000022175867,0.00024150014,0.000047020152],"genre_scores_gemma":[0.9915636,0.00075517385,0.002267511,0.005199821,0.000044287448,0.00004728228,0.000023982026,0.00002805442,0.00007028081],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978587,0.0002879514,0.00055544515,0.0006276487,0.0003185838,0.00035166665],"domain_scores_gemma":[0.9988164,0.00014627611,0.00013930498,0.00049186737,0.00021176816,0.00019443267],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00038182517,0.00030357324,0.0003076296,0.00062498,0.00027604992,0.00057725154,0.00051725016,0.00014248709,0.000053271968],"category_scores_gemma":[0.00000600395,0.00028568605,0.000083268824,0.0015181351,0.00009287607,0.0011505734,0.000015552021,0.00021353876,0.000051842766],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000063513207,0.00052711245,0.0001377147,0.00004652449,0.000058866834,0.000020789226,0.0020958201,0.0006723896,0.0002510333,0.9395597,0.0004589274,0.056164786],"study_design_scores_gemma":[0.00061948533,0.00011217181,0.0005115502,0.00008508112,0.000009038974,0.00004497044,0.00007136732,0.9933936,0.0014755861,0.00202563,0.0013017714,0.0003497216],"about_ca_topic_score_codex":0.00013382707,"about_ca_topic_score_gemma":0.000058148333,"teacher_disagreement_score":0.99272126,"about_ca_system_score_codex":0.000040689858,"about_ca_system_score_gemma":0.00006989535,"threshold_uncertainty_score":0.9999595},"labels":[],"label_agreement":null},{"id":"W2023451127","doi":"10.1109/hicss.2013.57","title":"A Qualitative Methodology for the Design of Visual Analytic Tools for Emergency Operation Centers","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Visual analytics; Workflow; Cultural analytics; Computer science; Analytics; Domain (mathematical analysis); Data science; Multidisciplinary approach; Argument (complex analysis); Qualitative research; Knowledge management; Human–computer interaction; Visualization; Management science; Semantic analytics; World Wide Web; Artificial intelligence; Engineering; Database","score_opus":0.3401342301655841,"score_gpt":0.49224903710159346,"score_spread":0.15211480693600937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2023451127","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00016940427,0.000017896451,0.9972639,0.0014715829,0.00016775943,0.00082714896,0.000010640405,0.000023122599,0.000048530073],"genre_scores_gemma":[0.113191135,0.000040682862,0.884063,0.000884399,0.00004486141,0.0002851909,0.000045472316,0.00000970636,0.001435525],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989712,0.00029223732,0.00031390847,0.00018266815,0.00009876689,0.00014119828],"domain_scores_gemma":[0.99714285,0.002193742,0.00011441279,0.00020605727,0.00031084355,0.000032106112],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012495476,0.00007506725,0.00014256424,0.00006135739,0.00008990736,0.00009496187,0.00042407983,0.000028196633,0.00011801066],"category_scores_gemma":[0.0008742176,0.000047358375,0.00007549087,0.00019848521,0.000030034345,0.0006315453,0.000055416465,0.000019841313,0.000010731061],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023725308,0.00014243732,0.00002067925,0.000051329487,0.00017557286,4.99098e-8,0.009103048,0.0035653736,0.0064739524,0.91510844,0.03899422,0.026341181],"study_design_scores_gemma":[0.00026560505,0.0002322087,0.000042773885,0.000002559524,0.000020200445,2.6780498e-7,0.0023757808,0.9853709,0.002945434,0.007992375,0.000677706,0.000074191106],"about_ca_topic_score_codex":0.000037957503,"about_ca_topic_score_gemma":0.000007152762,"teacher_disagreement_score":0.9818055,"about_ca_system_score_codex":0.000010862206,"about_ca_system_score_gemma":0.000041843552,"threshold_uncertainty_score":0.19312185},"labels":[],"label_agreement":null},{"id":"W2024157150","doi":"10.1145/2788940.2794366","title":"Differences in Perspective and Software Scaling","year":2015,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Scaling; Perspective (graphical); Software; Computer science; Quantization (signal processing); Scale (ratio); Artificial intelligence; Mathematics; Algorithm; Physics; Geometry; Programming language","score_opus":0.06050453893054082,"score_gpt":0.3172917261337463,"score_spread":0.2567871872032055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024157150","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021587024,0.00007948683,0.9745249,0.0005710542,0.00004562705,0.000022463706,6.4090597e-7,0.000065541055,0.003103258],"genre_scores_gemma":[0.973947,0.000008470586,0.02537284,0.00029297228,0.000009373333,5.471524e-7,6.045384e-7,0.0000011682855,0.00036704633],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996888,0.000014014873,0.000049252267,0.00011259337,0.000077790304,0.00005751583],"domain_scores_gemma":[0.9997963,0.000018481425,0.000010294969,0.0000810078,0.0000441108,0.000049807823],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008506593,0.000030041858,0.00004617374,0.00004778488,0.000013479516,0.0000940022,0.00014067326,0.000011103689,0.000004298935],"category_scores_gemma":[0.00009434606,0.000023239952,0.000004385164,0.0001566862,0.000015517075,0.00022220293,0.00009988876,0.000021715516,0.00000852585],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.5825724e-7,0.000036157806,0.11631111,0.000002606655,0.0000031235795,0.00000473571,0.004261019,0.000009138767,0.0000028070283,0.87244284,0.00086193613,0.006063642],"study_design_scores_gemma":[0.0009984777,0.00009239033,0.07236262,0.000039801347,0.0000037317386,0.00001172301,0.010130585,0.8136355,0.00020225806,0.10049184,0.0016473022,0.00038377498],"about_ca_topic_score_codex":0.000086738684,"about_ca_topic_score_gemma":0.000032603773,"teacher_disagreement_score":0.95236,"about_ca_system_score_codex":0.000014187824,"about_ca_system_score_gemma":0.000023962994,"threshold_uncertainty_score":0.094769776},"labels":[],"label_agreement":null},{"id":"W2024288733","doi":"10.1167/13.9.432","title":"Enumeration of Illusory Contour Figures","year":2013,"lang":"fr","type":"article","venue":"Journal of Vision","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Enumeration; Task (project management); Artificial intelligence; Line (geometry); Computer vision; Computer science; Visual search; Object (grammar); Simple (philosophy); Contour line; Visual Objects; Computer graphics (images); Pattern recognition (psychology); Mathematics; Geometry; Combinatorics; Psychology; Geography; Cartography; Perception","score_opus":0.029075766016119203,"score_gpt":0.3254458549568148,"score_spread":0.29637008894069555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024288733","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.058448143,0.012074963,0.9016114,0.019301567,0.0049768323,0.00020470329,0.000017859005,0.000015001872,0.0033495405],"genre_scores_gemma":[0.9684541,0.0022233366,0.015589194,0.0010374807,0.0007141222,3.9835433e-7,0.0000055681367,0.000012889403,0.011962905],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99847984,0.00014367363,0.0006945598,0.00009540969,0.00045760054,0.00012890468],"domain_scores_gemma":[0.9978048,0.000090569,0.0008162076,0.0001920035,0.0009749363,0.00012143528],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005164445,0.000092559756,0.00023118586,0.00016000534,0.000051575444,0.00021758335,0.00038994531,0.00008030073,0.0007540286],"category_scores_gemma":[0.00023228898,0.00007681663,0.00012318706,0.00023984957,0.000062773535,0.0018845515,0.00008036912,0.00014619768,0.00012133864],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021970429,0.0010244976,0.00065642287,0.0002468656,0.000111946676,0.000040505434,0.0025057467,0.0016263544,0.034275007,0.07679918,0.5177572,0.36493433],"study_design_scores_gemma":[0.001967964,0.0023417287,0.038692392,0.002173101,0.00011143605,0.00023985474,0.00042099415,0.61316806,0.009270516,0.009997176,0.3212348,0.00038199616],"about_ca_topic_score_codex":0.000050499322,"about_ca_topic_score_gemma":0.0000035927453,"teacher_disagreement_score":0.910006,"about_ca_system_score_codex":0.00003249706,"about_ca_system_score_gemma":0.00013909144,"threshold_uncertainty_score":0.82560843},"labels":[],"label_agreement":null},{"id":"W2024290096","doi":"10.1109/tvcg.2009.167","title":"MizBee: A Multiscale Synteny Browser","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":160,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Synteny; Computer science; Visualization; Data visualization; Comparative genomics; Similarity (geometry); Data science; Abstraction; Genomics; Human–computer interaction; Genome; Information retrieval; Data mining; Artificial intelligence; Biology","score_opus":0.01787192504938046,"score_gpt":0.28145648305157456,"score_spread":0.2635845580021941,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024290096","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012799372,0.000032095188,0.99725634,0.00027774356,0.00044622418,0.00015267251,0.0000117775035,0.00041648926,0.00012674491],"genre_scores_gemma":[0.98549,0.0003534018,0.0049047037,0.008798949,0.00007010432,0.000007930581,0.000018632394,0.000018367455,0.00033790062],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985159,0.000095247946,0.00033110147,0.00047855216,0.00033275448,0.00024643829],"domain_scores_gemma":[0.9990963,0.00005672477,0.00008738336,0.0004211659,0.00015349152,0.00018497412],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000150354,0.00022396626,0.00020141258,0.0004092319,0.00032731515,0.0003690899,0.000383122,0.000112626,0.000019686666],"category_scores_gemma":[0.0000030022256,0.00022076075,0.00009956751,0.0010236229,0.000060770268,0.0005973926,0.000004812655,0.00015336492,0.000025549074],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000099192775,0.0004936518,0.000031290947,0.000015306743,0.000032047894,0.000007302775,0.00053538,0.00053329667,0.000038596667,0.9613879,0.0015546893,0.03536063],"study_design_scores_gemma":[0.0005794609,0.00026447125,0.0005092889,0.000041089264,0.000018254357,0.000023375484,0.000014204778,0.99150044,0.0010413772,0.0013157092,0.004404199,0.00028814358],"about_ca_topic_score_codex":0.0000063350512,"about_ca_topic_score_gemma":0.0000086074915,"teacher_disagreement_score":0.9923516,"about_ca_system_score_codex":0.0000167081,"about_ca_system_score_gemma":0.000030203142,"threshold_uncertainty_score":0.9002362},"labels":[],"label_agreement":null},{"id":"W2024806371","doi":"10.1145/2470654.2470696","title":"Individual user characteristics and information visualization","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":136,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Visualization; Human–computer interaction; Information visualization; Eye tracking; Bar chart; Perception; Relation (database); Cognition; Gaze; Task (project management); User interface; User modeling; Data visualization; Visual analytics; Creative visualization; Artificial intelligence; Data mining; Psychology","score_opus":0.014625997919173711,"score_gpt":0.2644998251327063,"score_spread":0.2498738272135326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024806371","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010946777,0.000002322653,0.98638123,0.00040262594,0.00007909847,0.000085731015,0.0000050683225,0.000121216945,0.0019759284],"genre_scores_gemma":[0.96981746,0.000064978725,0.020102896,0.00867357,0.00004723141,0.000012136526,0.00037193496,0.000005931458,0.0009038877],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995239,0.000014345585,0.00015862336,0.00007459963,0.0001454241,0.00008310356],"domain_scores_gemma":[0.9996323,0.000013898757,0.000058015496,0.00013758424,0.000102704624,0.000055523506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008023229,0.000052927044,0.000051897416,0.00008838628,0.000052499177,0.0007027269,0.00018554939,0.000027941607,0.000119868266],"category_scores_gemma":[0.000042411077,0.000045236804,0.000007380474,0.0001936498,0.0000134937545,0.0048475577,0.00014109613,0.00002252751,0.00031321624],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.7619769e-7,0.000014612256,0.005016632,0.000009592571,0.000005518554,1.13415204e-7,0.00038283164,0.000001188828,0.000023076662,0.943078,0.011369588,0.040098704],"study_design_scores_gemma":[0.0003854228,0.00005343888,0.2339247,0.000012106087,0.000008683845,0.000007915176,0.00012175438,0.5856489,0.00037328052,0.0018266325,0.17733668,0.00030046783],"about_ca_topic_score_codex":0.000011232085,"about_ca_topic_score_gemma":5.077226e-7,"teacher_disagreement_score":0.9662783,"about_ca_system_score_codex":0.000004810514,"about_ca_system_score_gemma":0.000013680386,"threshold_uncertainty_score":0.67764115},"labels":[],"label_agreement":null},{"id":"W2025019158","doi":"10.3138/carto.46.4.252","title":"Toward Appropriate Representations of Quantitative Data in Virtual Environments","year":2011,"lang":"en","type":"article","venue":"Cartographica The International Journal for Geographic Information and Geovisualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"McGill University; Northwestern University","keywords":"Symbol (formal); Computer science; Task (project management); Value (mathematics); Human–computer interaction; Artificial intelligence; Machine learning; Engineering","score_opus":0.06350346723356445,"score_gpt":0.3344164561839822,"score_spread":0.2709129889504177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2025019158","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0113168,0.00007987433,0.986563,0.00065762096,0.0006636542,0.00028815755,0.000110559486,0.000022488342,0.00029779537],"genre_scores_gemma":[0.9889965,0.0017073916,0.0076722936,0.0007583089,0.00004338163,0.000023853469,0.0007555612,0.000008736108,0.000033969354],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982966,0.00008803228,0.0007651468,0.00017769854,0.0005186343,0.00015385925],"domain_scores_gemma":[0.99850297,0.00011006621,0.00056794804,0.00039304097,0.00036003994,0.00006593522],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011712753,0.00012220474,0.00014172269,0.00086352136,0.00016533074,0.0002540388,0.0014634925,0.000060965373,0.000014372169],"category_scores_gemma":[0.0003171305,0.00009620705,0.00007763318,0.0006599277,0.00015094828,0.0030954105,0.00034776298,0.00012440709,0.000002477078],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000080907026,0.00012996182,0.013149774,0.000017717095,0.00016450204,0.0000016968206,0.007914371,0.00033516518,0.000057450412,0.96568495,0.00037846377,0.012085014],"study_design_scores_gemma":[0.004762373,0.00064363267,0.062059313,0.00018990651,0.00012599876,0.00016847925,0.010495785,0.77216923,0.000720164,0.0853737,0.06258752,0.00070391677],"about_ca_topic_score_codex":0.00006850485,"about_ca_topic_score_gemma":0.000027729344,"teacher_disagreement_score":0.9788908,"about_ca_system_score_codex":0.00001312647,"about_ca_system_score_gemma":0.00005592435,"threshold_uncertainty_score":0.39232096},"labels":[],"label_agreement":null},{"id":"W2025087771","doi":"10.1016/j.cose.2006.10.001","title":"SVision: A novel visual network-anomaly identification technique","year":2006,"lang":"en","type":"article","venue":"Computers & Security","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"Defense Advanced Research Projects Agency","keywords":"Computer science; Denial-of-service attack; Intrusion detection system; Roaming; Network security; Data mining; Identification (biology); Visualization; Anomaly detection; Set (abstract data type); Computer network; Computer security; The Internet; World Wide Web","score_opus":0.01084682031874227,"score_gpt":0.2745660951248051,"score_spread":0.26371927480606283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2025087771","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0022070752,0.000074156385,0.9951088,0.0005033668,0.0006086629,0.00022556685,0.0000075196363,0.00043924025,0.0008256061],"genre_scores_gemma":[0.93519783,0.000008765668,0.0633035,0.0006877332,0.0004840415,0.000016810447,0.00012768802,0.0000147905,0.0001588433],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983016,0.0000695029,0.00043597832,0.0005323813,0.00033836634,0.00032217527],"domain_scores_gemma":[0.9988715,0.00006160549,0.00019602002,0.00062743016,0.00014935764,0.000094053634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047058958,0.00018224132,0.00019341205,0.00012357639,0.00020770503,0.00049742544,0.0010174443,0.00009163287,0.00001169778],"category_scores_gemma":[0.000014750792,0.00018963925,0.00009506434,0.0008393945,0.000058128673,0.0006433487,0.0004748287,0.0001419176,0.00007148884],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000072822772,0.0008828216,0.0017487714,0.00005378624,0.000032909873,0.000030698902,0.00028668685,0.0028473472,0.003189026,0.8529083,0.13028432,0.0077280067],"study_design_scores_gemma":[0.00042650005,0.00006498479,0.009889774,0.000055148717,0.000013292692,0.00004085197,0.0000055866503,0.8983686,0.0014348106,0.023987826,0.06526233,0.00045027566],"about_ca_topic_score_codex":0.000067930596,"about_ca_topic_score_gemma":0.000022583254,"teacher_disagreement_score":0.93299073,"about_ca_system_score_codex":0.00005352109,"about_ca_system_score_gemma":0.000059670147,"threshold_uncertainty_score":0.77332646},"labels":[],"label_agreement":null},{"id":"W2025394193","doi":"10.1111/j.1467-8659.2009.01475.x","title":"iPCA: An Interactive System for PCA‐based Visual Analytics","year":2009,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":222,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Interactivity; Principal component analysis; Visual analytics; Dimensionality reduction; Human–computer interaction; Visualization; Set (abstract data type); Interface (matter); Interactive visual analysis; User interface; Data mining; Component (thermodynamics); Machine learning; Artificial intelligence; Multimedia","score_opus":0.024198623112862163,"score_gpt":0.3157650869119379,"score_spread":0.29156646379907575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2025394193","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012077808,0.00001891428,0.99605656,0.0009811897,0.00076759607,0.00027555585,0.00002920974,0.00048454123,0.00017866938],"genre_scores_gemma":[0.93275666,0.0000041409376,0.06073433,0.0059935367,0.00023298118,0.000009740491,0.00019892889,0.000021585976,0.000048062182],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980841,0.00007936853,0.00042157108,0.0006039507,0.00033445188,0.00047652575],"domain_scores_gemma":[0.99832183,0.00012398354,0.00020655399,0.00073975156,0.00036922967,0.00023865292],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003161233,0.00026322145,0.0003133665,0.00046505322,0.00026627607,0.0005690384,0.0011972314,0.000110504545,0.000001919576],"category_scores_gemma":[0.000017903609,0.0002547116,0.00020919503,0.00090747385,0.000048371727,0.00095041085,0.00015238427,0.0001557651,0.00001473537],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022357492,0.00039579166,0.00027589052,0.000043336175,0.00005169866,0.000015473544,0.00014006704,0.000925212,0.000039137907,0.9696814,0.008876735,0.019532936],"study_design_scores_gemma":[0.00070361525,0.0007851049,0.00042254187,0.000060577757,0.000023653569,0.000009539969,0.000050517006,0.98629147,0.0004818847,0.0030622266,0.007788254,0.0003205891],"about_ca_topic_score_codex":0.0000041877265,"about_ca_topic_score_gemma":0.000009726227,"teacher_disagreement_score":0.9853663,"about_ca_system_score_codex":0.00006301917,"about_ca_system_score_gemma":0.00009756838,"threshold_uncertainty_score":0.9999905},"labels":[],"label_agreement":null},{"id":"W2025904186","doi":"10.1145/503376.503388","title":"Acquisition of expanding targets","year":2002,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":210,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"University of Toronto","keywords":"Fitts's law; Computer science; Selection (genetic algorithm); Task (project management); Focus (optics); Target acquisition; Human–computer interaction; Space (punctuation); Artificial intelligence; Operating system; Engineering","score_opus":0.03281730917383631,"score_gpt":0.29295066961425065,"score_spread":0.26013336044041435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2025904186","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00069284486,0.000029918416,0.97772264,0.00023799045,0.00005066582,0.000012754951,7.7564545e-7,0.000047194557,0.021205185],"genre_scores_gemma":[0.9814725,0.00001804226,0.016576808,0.00035066984,0.000012215736,3.0393937e-7,0.0000024109888,0.0000012283787,0.001565822],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99972105,0.0000072289577,0.00007448869,0.00006610363,0.00008139747,0.00004971242],"domain_scores_gemma":[0.99979293,0.000008369502,0.000024702984,0.00013137015,0.000022672442,0.000019978872],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000421874,0.000023041499,0.000036272064,0.00004029561,0.000018598535,0.00002498618,0.00016405183,0.000009419998,0.00049782934],"category_scores_gemma":[0.000006688136,0.000019767433,0.000013697661,0.00015338173,0.000006858554,0.00024026376,0.000046154004,0.0000094193765,0.00007268612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.3652254e-7,0.000081871425,0.0006541698,0.000009637231,0.000006141889,0.0000021306198,0.00043268627,0.00004326577,0.002611033,0.9502097,0.032181423,0.013767712],"study_design_scores_gemma":[0.00018409191,0.00003344368,0.00048918667,0.0000102605345,0.0000020978553,0.0000026362907,0.000031218366,0.9643746,0.024065979,0.0024646611,0.008247425,0.000094404335],"about_ca_topic_score_codex":0.0000016235768,"about_ca_topic_score_gemma":2.515572e-7,"teacher_disagreement_score":0.98077965,"about_ca_system_score_codex":0.000003549979,"about_ca_system_score_gemma":0.0000014261338,"threshold_uncertainty_score":0.54508823},"labels":[],"label_agreement":null},{"id":"W2026404479","doi":"10.1167/14.10.881","title":"Plinko: A spatial probability task to measure learning and updating.","year":2014,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Task (project management); Probability distribution; Computer science; Statistics; Ball (mathematics); Event (particle physics); Artificial intelligence; Matching (statistics); Mathematics; Engineering","score_opus":0.017302577041362753,"score_gpt":0.3062568750239014,"score_spread":0.2889542979825387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026404479","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04500174,0.000019834511,0.9533459,0.0011832762,0.00013164934,0.000037955582,3.2524986e-7,0.000014595813,0.00026473563],"genre_scores_gemma":[0.9627696,0.000008179238,0.036820304,0.0002498462,0.00011129226,1.5027007e-7,6.188176e-7,0.0000033813358,0.00003662067],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991153,0.00011438618,0.00026025274,0.000115641444,0.00030979232,0.000084659674],"domain_scores_gemma":[0.999295,0.00005634711,0.00019763575,0.00011652385,0.0002112485,0.00012325849],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012080641,0.00005586563,0.00012218037,0.00008283158,0.000077096876,0.00016342854,0.00023694886,0.000027382815,0.000007501022],"category_scores_gemma":[0.0007202711,0.00004235057,0.000031078496,0.00015881493,0.000011929812,0.00029873382,0.00014236532,0.00013569162,0.000008671809],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058686583,0.00028278318,0.016033977,0.000071058945,0.000028200277,0.000011017736,0.0016173034,0.002012971,0.016251713,0.015768798,0.0050445837,0.9428189],"study_design_scores_gemma":[0.0015108954,0.0029072887,0.056436494,0.00050190114,0.000029895542,0.00011794297,0.00009335536,0.78143543,0.00094070815,0.0061406977,0.14950956,0.0003758177],"about_ca_topic_score_codex":0.0000033098413,"about_ca_topic_score_gemma":0.000003594807,"teacher_disagreement_score":0.9424431,"about_ca_system_score_codex":0.000016198328,"about_ca_system_score_gemma":0.00003146887,"threshold_uncertainty_score":0.1727006},"labels":[],"label_agreement":null},{"id":"W2026568547","doi":"10.1109/iv.2013.94","title":"Visual Clustering for Large Scale Commercial Enterprises","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Imperial Bank of Commerce (Canada)","funders":"","keywords":"Cluster analysis; Computer science; Interpretation (philosophy); Data mining; Scale (ratio); Representation (politics); Cluster (spacecraft); Data science; Artificial intelligence","score_opus":0.0213457743656423,"score_gpt":0.3194586458572124,"score_spread":0.2981128714915701,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026568547","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0025084247,0.000003844946,0.9940208,0.00064593536,0.00018407723,0.00013612298,0.00000585633,0.00012247628,0.002372439],"genre_scores_gemma":[0.8949638,0.0000065736035,0.09385866,0.006655365,0.00016009079,0.000039151877,0.000042652166,0.0000123415475,0.004261349],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994267,0.000012633158,0.00012843698,0.00015510453,0.00009422272,0.00018285036],"domain_scores_gemma":[0.9996344,0.00003349844,0.00002809409,0.00017480606,0.00006375089,0.00006548993],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000086202665,0.00006249497,0.00007794515,0.000045256922,0.000095772375,0.00027501697,0.0003769427,0.000022549972,0.00019562212],"category_scores_gemma":[0.000016325599,0.000053523876,0.000039393846,0.00010595967,0.000008018653,0.00052472256,0.00025979523,0.000023043987,0.00020387156],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012823755,0.0012366233,0.019828625,0.00013930979,0.00006997904,0.0000025365255,0.0030516959,0.000101943515,0.0015379137,0.23218359,0.5760314,0.1658036],"study_design_scores_gemma":[0.00032672015,0.000042692987,0.0015811132,0.0000062628233,0.0000022510599,0.0000010628312,0.000072452734,0.95367146,0.00052343035,0.00036653204,0.04329935,0.00010666483],"about_ca_topic_score_codex":0.000017726208,"about_ca_topic_score_gemma":0.000048666247,"teacher_disagreement_score":0.95356953,"about_ca_system_score_codex":0.000008575126,"about_ca_system_score_gemma":0.00001248307,"threshold_uncertainty_score":0.26519948},"labels":[],"label_agreement":null},{"id":"W2028428362","doi":"10.1080/13614568.2013.856093","title":"Introduction to the special issue on advances in the convergence of multimedia, communications, and social web technology","year":2013,"lang":"en","type":"article","venue":"New Review of Hypermedia and Multimedia","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Convergence (economics); Multimedia; Computer science; World Wide Web; Telecommunications; Economics","score_opus":0.014608166286780693,"score_gpt":0.3078224754918939,"score_spread":0.2932143092051132,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028428362","genre_codex":"commentary","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010972567,0.17936161,0.003816067,0.7967504,0.0027100015,0.004484532,0.0000791037,0.00010057115,0.0017251296],"genre_scores_gemma":[0.061045125,0.8744625,0.04465397,0.013135478,0.006087623,0.00019405532,0.00010082132,0.000022077042,0.00029833496],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990628,0.000117175616,0.0003227227,0.000184293,0.00020033216,0.00011270727],"domain_scores_gemma":[0.9989807,0.00021004005,0.0001448688,0.0005276952,0.00009755521,0.000039147086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036882638,0.00009251857,0.00023560166,0.00009862053,0.0000628265,0.000018484023,0.000824883,0.000042301206,0.00007922672],"category_scores_gemma":[0.0003654839,0.00005509217,0.000024340463,0.0004870607,0.0002698902,0.0002166023,0.00019992494,0.00012475257,0.0000460016],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000017736319,0.000055293727,0.00041808165,0.00025225588,0.0000049162704,2.482677e-7,0.0017352917,3.045983e-7,0.00019630557,0.0034048362,0.07321345,0.92071724],"study_design_scores_gemma":[0.00026698282,0.000078659985,0.0014772494,0.00027905405,0.000015201553,0.0000047181497,0.00038410613,0.0062311883,0.00014811121,0.00017981045,0.99085015,0.00008474777],"about_ca_topic_score_codex":0.000019778887,"about_ca_topic_score_gemma":0.000043648488,"teacher_disagreement_score":0.9206325,"about_ca_system_score_codex":0.0000062112567,"about_ca_system_score_gemma":0.000046303143,"threshold_uncertainty_score":0.22465934},"labels":[],"label_agreement":null},{"id":"W2028634151","doi":"10.1109/mcg.2012.37","title":"In Color Perception, Size Matters","year":2012,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Visualization; Perception; Data visualization; Information visualization; Computer graphics (images); Human–computer interaction; Artificial intelligence; Computer vision","score_opus":0.017174952515296882,"score_gpt":0.28557223562139994,"score_spread":0.26839728310610306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028634151","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0070546744,0.000037489324,0.9896848,0.0027355992,0.00015865949,0.00016172323,0.000007030771,0.00006438658,0.00009562036],"genre_scores_gemma":[0.93015677,0.00026115193,0.046222173,0.022530349,0.0004982255,0.00013740273,0.000018031944,0.000014385564,0.00016148818],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99931115,0.000024634199,0.00017111753,0.00020251959,0.00010259418,0.00018798061],"domain_scores_gemma":[0.9994274,0.00007319844,0.00004522611,0.00029998817,0.000040693718,0.00011349335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016330446,0.000087287444,0.00009183227,0.00011237326,0.00010726862,0.00012244083,0.00031518316,0.00003972732,0.0000107207825],"category_scores_gemma":[0.0000016147069,0.00008639691,0.00002716015,0.00048580414,0.000052727744,0.0004481385,0.00008969483,0.000074200776,0.000052264713],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.497847e-7,0.00017101181,0.004325351,0.000014150076,0.000007190942,4.5533002e-7,0.00037951831,0.000027109789,0.00016835508,0.97142094,0.018138515,0.0053469664],"study_design_scores_gemma":[0.0005731744,0.000038337374,0.08485924,0.000019436438,0.000014173442,0.000033397104,0.000043735396,0.3174148,0.000075356984,0.015288484,0.58113205,0.00050785544],"about_ca_topic_score_codex":0.000011012914,"about_ca_topic_score_gemma":0.0000045706565,"teacher_disagreement_score":0.9561324,"about_ca_system_score_codex":0.000010876862,"about_ca_system_score_gemma":0.0000111808895,"threshold_uncertainty_score":0.35231638},"labels":[],"label_agreement":null},{"id":"W2028822613","doi":"10.1109/tvcg.2014.2346292","title":"Constructing Visual Representations: Investigating the Use of Tangible Tokens","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":140,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures","keywords":"Computer science; Visualization; Human–computer interaction; Data visualization; Computer graphics (images); Artificial intelligence; Multimedia","score_opus":0.05256574381991955,"score_gpt":0.30938542724989126,"score_spread":0.25681968342997175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028822613","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0072481497,0.00000771172,0.99188864,0.0001497102,0.00035521676,0.00014709713,0.000010571323,0.0001492813,0.00004364706],"genre_scores_gemma":[0.9824482,0.000096198,0.014522701,0.0027434959,0.000062337574,0.000011834502,0.000022704797,0.000020319932,0.00007216259],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984481,0.00026874035,0.00044667488,0.00033329905,0.0003322881,0.00017092301],"domain_scores_gemma":[0.99857867,0.00048097837,0.00022021071,0.00038951254,0.00023403963,0.000096603195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029942617,0.00016050646,0.00018092788,0.00030282556,0.00040127235,0.0003644966,0.00029022366,0.000069377624,0.000007200548],"category_scores_gemma":[0.000035255638,0.00013461363,0.000077721015,0.0011821319,0.00022226742,0.00066060846,0.000013181283,0.00014163338,0.000003016907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021214432,0.00008308053,0.0005375651,0.000025055884,0.000034673416,3.3651773e-7,0.00065401045,0.0029992901,0.00002643839,0.9806973,0.0003130104,0.014627136],"study_design_scores_gemma":[0.00027676806,0.00010124224,0.00017374518,0.00005265407,0.000022983866,0.0000126946425,0.000093535986,0.9943953,0.0023455906,0.0008702238,0.0015044162,0.00015085922],"about_ca_topic_score_codex":0.000035045534,"about_ca_topic_score_gemma":0.00002676501,"teacher_disagreement_score":0.991396,"about_ca_system_score_codex":0.000012041724,"about_ca_system_score_gemma":0.00003644537,"threshold_uncertainty_score":0.54893845},"labels":[],"label_agreement":null},{"id":"W2029143245","doi":"10.1109/tvcg.2013.160","title":"GPLOM: The Generalized Plot Matrix for Visualizing Multidimensional Multivariate Data","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Systems, Applications & Products in Data Processing (Canada); École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Categorical variable; Computer science; Multivariate statistics; Plot (graphics); Data Matrix; Variable (mathematics); Matrix (chemical analysis); Visualization; Continuous variable; Design matrix; Data mining; Data visualization; Parallel coordinates; Feature (linguistics); Artificial intelligence; Pattern recognition (psychology); Mathematics; Statistics; Regression analysis; Machine learning","score_opus":0.05670578463631569,"score_gpt":0.3408862254024929,"score_spread":0.2841804407661772,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029143245","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001574182,0.000052818712,0.99602747,0.00044491672,0.0007718721,0.0007036949,0.00009483603,0.00032257073,0.0000076131587],"genre_scores_gemma":[0.8667502,0.0008820242,0.11329508,0.016382065,0.00049746956,0.0003715136,0.00076418935,0.00016328,0.0008942259],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978383,0.00020856387,0.0004991254,0.0007186711,0.0004082024,0.00032711806],"domain_scores_gemma":[0.99796534,0.00035204727,0.00017281585,0.0010140158,0.0003308008,0.00016499186],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043188865,0.0002891318,0.00024971314,0.00029808813,0.0008016675,0.000618025,0.00097384554,0.00011771918,0.000030678202],"category_scores_gemma":[0.000012991441,0.00022403123,0.00010133419,0.0007838583,0.0001100208,0.0010978543,0.000045889174,0.00015735607,0.000032109172],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013985459,0.00032635432,0.000016864054,0.000038165523,0.0001167187,8.920931e-7,0.00055011484,0.001422625,0.00016853379,0.98496765,0.0050031412,0.0073749726],"study_design_scores_gemma":[0.0010612651,0.00011046853,0.00010820673,0.00003289242,0.00004156199,0.000010029644,0.000032129934,0.98650813,0.00062240474,0.0011254714,0.010050804,0.00029661242],"about_ca_topic_score_codex":0.00008869046,"about_ca_topic_score_gemma":0.000019563955,"teacher_disagreement_score":0.98508555,"about_ca_system_score_codex":0.00001803384,"about_ca_system_score_gemma":0.00006247665,"threshold_uncertainty_score":0.91357285},"labels":[],"label_agreement":null},{"id":"W2030831602","doi":"10.1145/2663887.2663902","title":"ACH Walkthrough","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Software walkthrough; Computer science; JavaScript; HTML5; Software deployment; Cognitive walkthrough; Flexibility (engineering); Software; Visualization; Reflection (computer programming); Human–computer interaction; Usability; World Wide Web; Software engineering; Software development; Pluralistic walkthrough; Software construction; Artificial intelligence; Operating system","score_opus":0.019978610534271152,"score_gpt":0.29290824025693246,"score_spread":0.2729296297226613,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030831602","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000078436606,0.0000017607115,0.90327513,0.0011268075,0.00007507713,0.000008901186,1.5625467e-7,0.00011556088,0.09531817],"genre_scores_gemma":[0.82723224,0.000008228745,0.1414087,0.011237152,0.00010254387,0.0000012949923,0.000008993277,0.00000529719,0.019995559],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996852,0.00001346817,0.000054589156,0.000096966956,0.000081102335,0.00006866825],"domain_scores_gemma":[0.99966615,0.0000146986695,0.000011682935,0.00025719032,0.000019572974,0.00003067975],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000088995264,0.000028419063,0.00003394188,0.00001813301,0.00002884855,0.00008728084,0.00034932958,0.000010865587,0.00008291771],"category_scores_gemma":[0.000023924336,0.000022239663,0.000012217847,0.0001367804,0.0000073664696,0.00022135982,0.000094371164,0.000015730764,0.00047204932],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.580612e-8,0.000008204309,0.00009194462,8.04635e-7,8.6431965e-7,1.3936646e-7,0.000027022044,0.000005730653,0.000019846226,0.96363103,0.019611003,0.016603356],"study_design_scores_gemma":[0.00007543942,0.000013508966,0.00025422077,0.0000012165242,6.8947963e-7,0.0000012756083,0.0000042041665,0.47026822,0.0006497707,0.0072965184,0.5213763,0.000058651356],"about_ca_topic_score_codex":0.0000046702808,"about_ca_topic_score_gemma":0.000001976864,"teacher_disagreement_score":0.95633453,"about_ca_system_score_codex":0.0000028362206,"about_ca_system_score_gemma":0.000006011826,"threshold_uncertainty_score":0.60673964},"labels":[],"label_agreement":null},{"id":"W2031128418","doi":"10.1117/12.703654","title":"A user-driven interface for exploring visualizations","year":2007,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Human–computer interaction; Visualization; Interface (matter); User interface; Variety (cybernetics); Representation (politics); Data visualization; Programming language; Software engineering; Artificial intelligence; Operating system","score_opus":0.030821451455362903,"score_gpt":0.29008375057955876,"score_spread":0.25926229912419585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031128418","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85111225,0.000040609437,0.1453472,0.0015173462,0.00038437993,0.00052547874,0.000046284335,0.00016763632,0.00085880613],"genre_scores_gemma":[0.2909678,0.00012928591,0.7069805,0.00032935277,0.0006100791,0.000233559,0.000027548684,0.00009191557,0.0006299199],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977701,1.0856173e-8,0.0007564378,0.00043204683,0.0006025193,0.00043891673],"domain_scores_gemma":[0.9971495,0.00022365426,0.00038133105,0.00009272045,0.0020014883,0.000151301],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085907173,0.0002674934,0.00032837607,0.00017673694,0.00013011307,0.00026142114,0.0017725138,0.00012237794,0.0000051378647],"category_scores_gemma":[0.00072965206,0.000238938,0.00048871717,0.00062645884,0.00012416011,0.0013769947,0.000345604,0.00017337006,0.0000018723246],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024318837,0.00011193505,0.00020958483,0.00023768413,0.0001946236,4.4329347e-8,0.00036518247,0.00024685403,0.12801322,0.8662593,0.0039182804,0.00041898276],"study_design_scores_gemma":[0.0020790999,0.0005931818,0.0006975916,0.00056959083,0.000185791,0.00001750943,0.0026950762,0.5798032,0.3435825,0.0038037633,0.06514281,0.00082986784],"about_ca_topic_score_codex":0.0000038863027,"about_ca_topic_score_gemma":3.4090468e-7,"teacher_disagreement_score":0.86245555,"about_ca_system_score_codex":0.00013334875,"about_ca_system_score_gemma":0.00003831847,"threshold_uncertainty_score":0.9743609},"labels":[],"label_agreement":null},{"id":"W2031366103","doi":"10.1007/s10115-002-8192-7","title":"Knowledge Discovery Through Self-Organizing Maps: Data Visualization and Query Processing","year":2002,"lang":"en","type":"article","venue":"Knowledge and Information Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Knowledge extraction; Visualization; Data mining; Set (abstract data type); Information retrieval; Heuristic; Premise; Data visualization; Information visualization; Data science; Artificial intelligence","score_opus":0.047145981158898155,"score_gpt":0.3028134019006688,"score_spread":0.2556674207417706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031366103","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009806429,0.007853058,0.95494956,0.00009662916,0.00061650795,0.00032996078,0.000055750963,0.0004517989,0.03466608],"genre_scores_gemma":[0.993314,0.0021663478,0.0018975823,0.00033699724,0.0003044466,0.000014609232,0.0005873268,0.000020734316,0.0013579236],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99875003,0.0000783987,0.0005331711,0.0002655942,0.00017850792,0.00019429676],"domain_scores_gemma":[0.9989105,0.000045531655,0.00023046882,0.0004997357,0.00023219449,0.00008156337],"candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.00040021748,0.0001681894,0.00020025506,0.0001784791,0.0003156508,0.0019212022,0.00048373186,0.000083730745,0.0000042089414],"category_scores_gemma":[0.00006984765,0.00015015312,0.000013800777,0.0006752092,0.00003586432,0.025069382,0.0005709207,0.000072108625,0.00015760405],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000028091067,0.00024994047,0.0013528952,0.0025948125,0.00006417793,0.000001599066,0.06997391,0.00001712391,0.000035418798,0.7880519,0.08302036,0.054635078],"study_design_scores_gemma":[0.00025006806,0.000017275306,0.00006408594,0.00013981576,0.000010912067,0.000024719178,0.00064502965,0.5940569,0.000025767527,0.000035748584,0.40456277,0.00016692458],"about_ca_topic_score_codex":0.000010475106,"about_ca_topic_score_gemma":0.0000042410993,"teacher_disagreement_score":0.9923334,"about_ca_system_score_codex":0.000036642796,"about_ca_system_score_gemma":0.000054003336,"threshold_uncertainty_score":0.9991149},"labels":[],"label_agreement":null},{"id":"W2031530648","doi":"10.1016/j.autcon.2012.08.004","title":"Comparative visualization of construction schedules","year":2012,"lang":"en","type":"article","venue":"Automation in Construction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of British Columbia; University of Victoria","funders":"","keywords":"Gantt chart; Schedule; Computer science; Visualization; Flexibility (engineering); Project management; Software; Operations research; Software engineering; Systems engineering; Data mining; Engineering","score_opus":0.03226052099126875,"score_gpt":0.3339316170395943,"score_spread":0.30167109604832554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031530648","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13884906,0.000043090975,0.8583372,0.000060413324,0.00066898245,0.00012265798,0.0000039748584,0.00014752624,0.0017670682],"genre_scores_gemma":[0.9020604,0.000017961067,0.097786404,0.000030489995,0.000042818167,0.0000068244763,0.000044145356,0.000003832994,0.0000071130353],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998885,0.00012884068,0.00044235814,0.00015446398,0.00023555092,0.00015379087],"domain_scores_gemma":[0.99920475,0.000055085005,0.00031634938,0.00021429737,0.00015962053,0.000049906343],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003104677,0.00009679321,0.00017507086,0.00037861895,0.000061101666,0.00004983547,0.0001599474,0.000069598755,0.000042831616],"category_scores_gemma":[0.00006217295,0.00010364889,0.00003105517,0.0009411549,0.000116854586,0.0019105081,0.00004721343,0.000053443102,0.000029498247],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000020433731,0.000054207398,0.0541976,0.000019162702,0.000008490271,6.844096e-8,0.00067632925,0.00023316231,0.00070669677,0.9341999,0.00004218367,0.009860159],"study_design_scores_gemma":[0.001311528,0.00007370125,0.1522204,0.00015625339,0.000027927019,0.00009361262,0.0022174264,0.768467,0.059907913,0.012788223,0.002234477,0.00050149614],"about_ca_topic_score_codex":0.000013021896,"about_ca_topic_score_gemma":0.0000041192266,"teacher_disagreement_score":0.9214117,"about_ca_system_score_codex":0.00004366232,"about_ca_system_score_gemma":0.00004969269,"threshold_uncertainty_score":0.42266792},"labels":[],"label_agreement":null},{"id":"W2031574677","doi":"10.1016/s0893-9659(01)80023-9","title":"Using table lens to interactively build classifiers","year":2001,"lang":"en","type":"article","venue":"Applied Mathematics Letters","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Categorical variable; Table (database); Computer science; Visualization; Domain (mathematical analysis); Data mining; Machine learning; Artificial intelligence; Pattern recognition (psychology); Mathematics","score_opus":0.06255615583782155,"score_gpt":0.3120231126463782,"score_spread":0.24946695680855668,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031574677","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0126260705,0.0000014360687,0.9683447,0.0020030376,0.00009412215,0.00016979736,0.000003024857,0.00013583853,0.016621957],"genre_scores_gemma":[0.12486737,0.000008452259,0.8551061,0.019425867,0.00010361981,0.000019521149,0.000009507465,0.00003965954,0.00041988984],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99884945,0.000009141001,0.00026359406,0.0003024318,0.00027006655,0.00030529033],"domain_scores_gemma":[0.9991476,0.00007033066,0.00011548706,0.0005233944,0.000035890916,0.000107305736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017729499,0.0001563032,0.00018597704,0.00016261257,0.00011046492,0.00025162907,0.00067458546,0.000035432495,0.000026871658],"category_scores_gemma":[0.00003131219,0.00015157716,0.00003789738,0.0006281653,0.00002855175,0.0003540174,0.00024958805,0.00009974924,0.00022344677],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005790482,0.0002040997,0.00007016066,0.000053172884,0.00006258621,0.000022459451,0.0024652858,0.0029910682,0.19606596,0.7489302,0.04720494,0.001924295],"study_design_scores_gemma":[0.00083467417,0.000041145147,0.0000671072,0.00014513779,0.000060592844,0.00007087752,0.0010875998,0.8304292,0.020008149,0.007800602,0.13832816,0.0011267606],"about_ca_topic_score_codex":0.000007771922,"about_ca_topic_score_gemma":0.0000014628523,"teacher_disagreement_score":0.8274381,"about_ca_system_score_codex":0.00007539092,"about_ca_system_score_gemma":0.000026120853,"threshold_uncertainty_score":0.6181137},"labels":[],"label_agreement":null},{"id":"W2032107533","doi":"10.1145/1958824.1958912","title":"Privacy and sharing information on spherical and large flat displays","year":2011,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Limiting; Internet privacy; Information sharing; Information privacy; Privacy software; Factor (programming language); Computer security; Human–computer interaction; World Wide Web; Engineering","score_opus":0.032406963626465064,"score_gpt":0.2713455831736251,"score_spread":0.23893861954716006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032107533","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023333993,0.000004037599,0.95975196,0.0000911561,0.00003196485,0.00003435904,0.0000015495871,0.000057963334,0.016693033],"genre_scores_gemma":[0.97325784,0.00002426823,0.02483343,0.0014953009,0.000010066243,0.0000010036962,0.000008950946,0.0000021399562,0.00036701237],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996904,0.0000041763356,0.00008018875,0.00008415861,0.00006670455,0.000074340656],"domain_scores_gemma":[0.99977183,0.0000072939238,0.000021143278,0.00013680488,0.000012598197,0.00005034106],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006863277,0.000039825394,0.000039629573,0.000024402641,0.000046487083,0.00013117585,0.00013915251,0.000015740981,0.000039766895],"category_scores_gemma":[0.000018007422,0.000031033524,0.000005379442,0.000078183475,0.00000904152,0.0009893057,0.00025287096,0.000025688758,0.00003651301],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000019681338,0.000017917962,0.012684475,0.000010005729,0.0000032336045,8.688267e-7,0.001659636,4.6602588e-7,0.000009427404,0.9736829,0.0009932964,0.010935796],"study_design_scores_gemma":[0.00051494275,0.0001022364,0.04826905,0.000017949027,0.0000043418245,0.00000818361,0.00011017603,0.8980543,0.000598323,0.0041550025,0.047971036,0.00019446237],"about_ca_topic_score_codex":0.0000065435856,"about_ca_topic_score_gemma":0.0000017842973,"teacher_disagreement_score":0.9695279,"about_ca_system_score_codex":0.0000033109047,"about_ca_system_score_gemma":0.000003747584,"threshold_uncertainty_score":0.12655103},"labels":[],"label_agreement":null},{"id":"W2032161135","doi":"10.1109/tvcg.2013.149","title":"DiffAni: Visualizing Dynamic Graphs with a Hybrid of Difference Maps and Animation","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":84,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Animation; Visualization; Graph; Graph drawing; Data visualization; Interval (graph theory); Theoretical computer science; Sequence (biology); Computer graphics (images); Data mining; Mathematics","score_opus":0.012184989118129775,"score_gpt":0.2528745847747128,"score_spread":0.24068959565658304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032161135","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09585093,0.000034896897,0.90351355,0.000053517153,0.000106481544,0.00025291526,0.000017635133,0.00015053978,0.000019522819],"genre_scores_gemma":[0.9964481,0.00042645412,0.002483145,0.00051781425,0.0000069439775,0.000022137394,0.00002464551,0.00001916804,0.000051616193],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985638,0.00010543544,0.00036933535,0.0004351161,0.00032848594,0.00019778092],"domain_scores_gemma":[0.9990495,0.00008614814,0.00017957992,0.00031391348,0.00023055247,0.00014029478],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011374593,0.00023402453,0.00025050092,0.000500279,0.00022985268,0.0002884498,0.00024166508,0.00006505507,0.000009502301],"category_scores_gemma":[0.000002319425,0.0002047978,0.000048541442,0.00080104015,0.00015405663,0.000658242,0.000010786331,0.00011762625,0.0000031935497],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014725107,0.00034484162,0.00053746504,0.00017327028,0.00009159264,0.0000028361997,0.0013437731,0.00018914175,0.0004367492,0.9744688,0.000104810715,0.022291956],"study_design_scores_gemma":[0.00059322896,0.00039672616,0.0027787278,0.00011191483,0.000029399029,0.000030414254,0.00006031014,0.99070364,0.0017687455,0.0031705596,0.00008184813,0.00027449158],"about_ca_topic_score_codex":0.00004038815,"about_ca_topic_score_gemma":0.000022502067,"teacher_disagreement_score":0.9905145,"about_ca_system_score_codex":0.000012705934,"about_ca_system_score_gemma":0.000031139196,"threshold_uncertainty_score":0.8351412},"labels":[],"label_agreement":null},{"id":"W2032892927","doi":"10.1057/palgrave.ivs.9500015","title":"Representing High-Dimensional Data Sets as Closed Surfaces","year":2002,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Visualization; Information visualization; Set (abstract data type); ENCODE; Data visualization; Similarity (geometry); Scientific visualization; Surface (topology); Measure (data warehouse); Data set; Data mining; Interactive visualization; Theoretical computer science; Artificial intelligence; Image (mathematics); Geometry","score_opus":0.052377802726807504,"score_gpt":0.3275444828299672,"score_spread":0.2751666801031597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032892927","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014263896,0.000045526947,0.97682977,0.0010414872,0.0006292117,0.00026189326,0.000081121136,0.0006383883,0.0062087122],"genre_scores_gemma":[0.98000246,0.00007633736,0.01062845,0.0033331048,0.000076514065,0.0000058886653,0.0051817484,0.000014281524,0.0006812357],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981902,0.00008536556,0.0005795474,0.00026954294,0.0006632378,0.00021206374],"domain_scores_gemma":[0.99819666,0.00006138742,0.00034700925,0.0010080453,0.00029408344,0.00009281742],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004602969,0.00014084067,0.00013219843,0.00024904808,0.0002476117,0.00069456233,0.0010171059,0.000076190925,0.0004025073],"category_scores_gemma":[0.00044892207,0.00014126065,0.00002510391,0.00087285764,0.000027958118,0.009992023,0.00058531505,0.00006815748,0.0015700927],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000076133065,0.00023136321,0.0015787308,0.000095427895,0.00006574581,0.00000620456,0.0031010034,0.014634893,0.00015303255,0.70671374,0.19887292,0.0745393],"study_design_scores_gemma":[0.0003497427,0.000020085561,0.00064647105,0.000019651827,0.000006761833,0.000009240845,0.000041031275,0.95590883,0.00035605906,0.0006609508,0.041805275,0.00017587883],"about_ca_topic_score_codex":0.0000495569,"about_ca_topic_score_gemma":0.0000034772213,"teacher_disagreement_score":0.9662013,"about_ca_system_score_codex":0.000030591844,"about_ca_system_score_gemma":0.00003647919,"threshold_uncertainty_score":0.9992073},"labels":[],"label_agreement":null},{"id":"W2033029648","doi":"10.1109/mnet.2012.6375888","title":"Alertwheel: radial bipartite graph visualization applied to intrusion detection system alerts","year":2012,"lang":"en","type":"article","venue":"IEEE Network","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Visualization; Intrusion detection system; Workflow; Parsing; Enhanced Data Rates for GSM Evolution; Data visualization; Bipartite graph; Graph; Data mining; Network security; Information visualization; Theoretical computer science; Artificial intelligence; Computer network; Database","score_opus":0.017450577554544964,"score_gpt":0.265375012158662,"score_spread":0.24792443460411703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033029648","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0053671715,0.000051955933,0.98487633,0.000044064534,0.0075796857,0.00026505705,0.0000022083286,0.00048298537,0.0013305257],"genre_scores_gemma":[0.99250734,0.000015702239,0.0020393266,0.0008713373,0.0044019893,0.000030579475,0.000022985361,0.000023170667,0.00008754877],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984569,0.00009646394,0.00031857606,0.00031450216,0.00033357937,0.00048000476],"domain_scores_gemma":[0.99902713,0.000040563427,0.0001272475,0.0004502259,0.000067968256,0.00028684843],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047367087,0.00016806697,0.00018108594,0.00016901159,0.00025296412,0.0001860685,0.00038272023,0.00009551613,0.000006265494],"category_scores_gemma":[0.000014499551,0.00016338663,0.000052330408,0.0014810342,0.000017623155,0.000491991,0.0001148994,0.00007168659,0.00032273258],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020449671,0.0005675714,0.006579227,0.00027187596,0.00018581637,0.000012345953,0.0044449405,0.15479696,0.015380702,0.36053634,0.30975214,0.14726758],"study_design_scores_gemma":[0.0014427343,0.00025630696,0.007426267,0.00032380054,0.00010302108,0.00005268205,0.00013321759,0.4822706,0.03518883,0.0010655823,0.4700737,0.0016632408],"about_ca_topic_score_codex":0.000011228561,"about_ca_topic_score_gemma":0.000019115389,"teacher_disagreement_score":0.9871402,"about_ca_system_score_codex":0.00007866314,"about_ca_system_score_gemma":0.000018880226,"threshold_uncertainty_score":0.6662713},"labels":[],"label_agreement":null},{"id":"W2033341439","doi":"10.1145/2786567.2793693","title":"The Infinite Canvas","year":2015,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario College of Art and Design","funders":"","keywords":"Popularity; Computer science; Information retrieval; Order (exchange); Test (biology); Human–computer interaction; World Wide Web; Multimedia; Psychology","score_opus":0.0628021312359636,"score_gpt":0.3171737358909653,"score_spread":0.2543716046550017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033341439","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00011767059,0.000027285105,0.90720195,0.0036677266,0.00020222199,0.000017881539,4.2817615e-7,0.00008836018,0.08867648],"genre_scores_gemma":[0.76049596,0.000127083,0.056282166,0.023635844,0.00031263728,0.000008553866,0.000017813407,0.000015947913,0.159104],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997058,0.000013394609,0.00005189963,0.00005503224,0.000108729706,0.00006513772],"domain_scores_gemma":[0.9996123,0.000026320842,0.000012644118,0.00024027334,0.000051067454,0.000057422003],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001695133,0.000022139766,0.000019542813,0.000011379216,0.000051223167,0.00019276964,0.00041643417,0.000006712345,0.0000055659525],"category_scores_gemma":[0.000060714417,0.000012239766,0.000007721809,0.00015993911,0.000013603679,0.00014516155,0.00011689379,0.000016639557,0.00024734435],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.106242e-7,0.000002902402,0.00015437893,1.3150337e-7,0.0000012690377,5.4467114e-7,0.00007548683,0.000012818975,9.950897e-7,0.9008752,0.09267915,0.0061970027],"study_design_scores_gemma":[0.00005760664,0.000008063262,0.00007459418,4.8741924e-7,4.2474025e-7,0.0000013426212,0.000040060775,0.14323679,0.000054726956,0.0051880223,0.85130864,0.000029217259],"about_ca_topic_score_codex":0.00002417002,"about_ca_topic_score_gemma":0.000044903052,"teacher_disagreement_score":0.89568716,"about_ca_system_score_codex":0.00000580729,"about_ca_system_score_gemma":0.000053662672,"threshold_uncertainty_score":0.31791937},"labels":[],"label_agreement":null},{"id":"W2033650322","doi":"10.1109/infovis.2004.53","title":"PhylloTrees: Harnessing Nature&#146;s Phyllotactic Patterns for Tree Layout","year":2004,"lang":"en","type":"article","venue":"IEEE Symposium on Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Tree (set theory); A priori and a posteriori; Theoretical computer science; Mathematics; Combinatorics","score_opus":0.014351242053106172,"score_gpt":0.30041828943848414,"score_spread":0.28606704738537797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033650322","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005003412,0.0000072754183,0.98944545,0.00085529184,0.0014367007,0.00052925886,0.00006789985,0.00048668322,0.002168038],"genre_scores_gemma":[0.9896238,0.00003584442,0.003241882,0.0056107803,0.00024127547,0.00008283918,0.0009788332,0.000031600754,0.00015315656],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99791306,0.00005385991,0.0007070171,0.00033418473,0.0006268056,0.00036508875],"domain_scores_gemma":[0.9982555,0.000076368815,0.00050331006,0.0005695577,0.00045490518,0.00014038832],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003379349,0.0002933088,0.00023477954,0.000538584,0.0003781226,0.0010003888,0.0006619163,0.00022805714,0.000010457355],"category_scores_gemma":[0.00012287764,0.0002888042,0.00012622835,0.0008102928,0.000030022407,0.005464015,0.000060089387,0.00016394045,0.00017808579],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052105934,0.00037235548,0.00046405446,0.00034176305,0.00006416851,0.0000018212885,0.004988942,0.048011202,0.0015083073,0.93240327,0.0031495958,0.008642423],"study_design_scores_gemma":[0.0059442776,0.00079479814,0.0014839577,0.00052023743,0.0000759592,0.000022794133,0.0004967786,0.86799645,0.055025075,0.0048589087,0.061363928,0.0014168044],"about_ca_topic_score_codex":0.000014545071,"about_ca_topic_score_gemma":0.000011050888,"teacher_disagreement_score":0.98620355,"about_ca_system_score_codex":0.00021758459,"about_ca_system_score_gemma":0.0001618133,"threshold_uncertainty_score":0.9999564},"labels":[],"label_agreement":null},{"id":"W2033663663","doi":"10.1145/1358628.1358816","title":"Intelligent object group selection","year":2008,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Selection (genetic algorithm); Gestalt psychology; Rectangle; Object (grammar); Computer science; Group (periodic table); Artificial intelligence; Pattern recognition (psychology); Mathematics; Perception; Geometry","score_opus":0.036688993559326005,"score_gpt":0.2923847887614091,"score_spread":0.2556957952020831,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033663663","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002670494,0.0000067454016,0.9921632,0.00015259058,0.00009730631,0.000023754794,2.0349835e-7,0.00018338865,0.0047023506],"genre_scores_gemma":[0.96529585,0.000045624634,0.028644832,0.0011274904,0.00003718192,0.0000015225335,0.0000049496134,0.0000034235966,0.004839098],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995785,0.000021798893,0.00008166723,0.00012412536,0.00011205708,0.000081901635],"domain_scores_gemma":[0.99976885,0.000014037598,0.000017314924,0.00013039616,0.000031546002,0.000037854432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008745357,0.00003979588,0.000039719132,0.000052698117,0.00007908527,0.000040269002,0.0002164749,0.0000148095905,0.00009198958],"category_scores_gemma":[0.000016557891,0.000033620614,0.000020369489,0.00033582305,0.000011392381,0.0002460527,0.00005966111,0.000026967504,0.00024773873],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007689918,0.00028371284,0.0071166893,0.000007253855,0.000025749898,0.000018605137,0.0011747939,0.00031621012,0.001954207,0.87290776,0.08533379,0.030853534],"study_design_scores_gemma":[0.00017573623,0.00015577559,0.005940021,0.0000044944286,0.000002538179,0.00010349013,0.0000348793,0.79273117,0.014121301,0.0011094571,0.18539122,0.00022994619],"about_ca_topic_score_codex":0.000013568205,"about_ca_topic_score_gemma":0.0000068944532,"teacher_disagreement_score":0.9635183,"about_ca_system_score_codex":0.000016937975,"about_ca_system_score_gemma":0.00001977544,"threshold_uncertainty_score":0.31842625},"labels":[],"label_agreement":null},{"id":"W2033750982","doi":"10.1109/ldav.2013.6675175","title":"Visualization of residents in long-term care centres through mobile natural user interfaces (NUI)","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario College of Art and Design","funders":"","keywords":"Computer science; Workflow; Visualization; Visual analytics; Human–computer interaction; Analytics; Set (abstract data type); Interactive visual analysis; Data visualization; Data science; Natural (archaeology); Mobile device; Multimedia; World Wide Web; Artificial intelligence; Database","score_opus":0.013375068712984795,"score_gpt":0.32161958695984083,"score_spread":0.30824451824685606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033750982","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7730104,0.0006560277,0.22361343,0.00010762814,0.00040788125,0.00045227376,0.000005727616,0.00013723796,0.0016094559],"genre_scores_gemma":[0.9969824,0.00009124549,0.0015981732,0.0001978948,0.0000129538475,0.000008143996,0.000055480654,0.0000064772457,0.0010472246],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990288,0.00005179999,0.00029125644,0.0002334212,0.00023494777,0.00015977725],"domain_scores_gemma":[0.99936324,0.000025545041,0.000094913274,0.00030741896,0.00017707997,0.00003182521],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004260526,0.000099362,0.00013232333,0.000105925814,0.00002800543,0.00017589019,0.00056337984,0.000040287658,0.00024845335],"category_scores_gemma":[0.000024480812,0.00008204876,0.000027802427,0.00041632858,0.000032561333,0.001423552,0.00027030415,0.000045620953,0.0000729366],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010031209,0.00041954312,0.8536318,0.00041520174,0.00004978555,0.000011419566,0.017475437,0.0006948024,0.0031504706,0.094275706,0.014143476,0.015722346],"study_design_scores_gemma":[0.0013974458,0.00018638534,0.8180758,0.00042736335,0.000013798679,0.0000043266764,0.0024949652,0.080761544,0.09453965,0.00087333674,0.0006106206,0.0006147844],"about_ca_topic_score_codex":0.0005892092,"about_ca_topic_score_gemma":0.0003971069,"teacher_disagreement_score":0.22397207,"about_ca_system_score_codex":0.000032915876,"about_ca_system_score_gemma":0.000025292318,"threshold_uncertainty_score":0.33458516},"labels":[],"label_agreement":null},{"id":"W2033951552","doi":"10.1109/geoinformatics.2009.5293552","title":"Quantitative visualizations of hierarchically organized data in a geographic context","year":2009,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Visualization; Context (archaeology); Tree (set theory); Data visualization; Geographic information system; Data mining; Hierarchical database model; Topology (electrical circuits); Theoretical computer science; Geography; Mathematics; Cartography","score_opus":0.05098683389696238,"score_gpt":0.36147572140216494,"score_spread":0.31048888750520254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033951552","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004861639,0.000042917236,0.9916665,0.0014149518,0.000029053877,0.000089235946,0.000024743591,0.000070354305,0.0018006088],"genre_scores_gemma":[0.94592786,0.000057523725,0.05209459,0.0016279892,0.0000047715766,5.811102e-7,0.0001495503,0.0000036643823,0.00013345148],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990101,0.000077547535,0.00031741103,0.0002726057,0.00019696968,0.00012537302],"domain_scores_gemma":[0.9988781,0.00009869042,0.00008025622,0.0007678615,0.00012296683,0.000052092866],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002915772,0.00007332657,0.00015703082,0.0002745654,0.000032228778,0.0000673092,0.0012496731,0.000029181057,0.000057530167],"category_scores_gemma":[0.0003072074,0.00006473947,0.000019026975,0.0015272495,0.00004621693,0.00057881995,0.00024031318,0.000055589782,0.00001558367],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000035763167,0.0001839061,0.0014627097,0.000003288788,0.000006708363,0.0000029846678,0.00026464567,0.000011310133,0.00038841102,0.9938588,0.0005233021,0.0032903254],"study_design_scores_gemma":[0.0012932436,0.000321893,0.025035163,0.000054896776,0.000010454558,0.000004492882,0.0002949166,0.9432553,0.0006726933,0.025834186,0.0029459056,0.0002768361],"about_ca_topic_score_codex":0.000054679553,"about_ca_topic_score_gemma":0.00019653604,"teacher_disagreement_score":0.9680247,"about_ca_system_score_codex":0.0000051777447,"about_ca_system_score_gemma":0.00007790273,"threshold_uncertainty_score":0.2639999},"labels":[],"label_agreement":null},{"id":"W2033991989","doi":"10.1007/s10758-006-0001-z","title":"Characterizing Interaction with Visual Mathematical Representations","year":2006,"lang":"en","type":"article","venue":"International Journal of Computers for Mathematical Learning","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":92,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Visualization; Set (abstract data type); Representation (politics); Human–computer interaction; Context (archaeology); Selection (genetic algorithm); Visual reasoning; ENCODE; Cognition; Artificial intelligence","score_opus":0.0189776168736553,"score_gpt":0.3373142329662818,"score_spread":0.31833661609262653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033991989","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011293099,0.000005841808,0.9851516,0.0018283334,0.0003671803,0.00009324454,0.0000016141306,0.000056797464,0.0012023253],"genre_scores_gemma":[0.7319465,0.0000034375882,0.26704803,0.00022027238,0.00047987362,0.0000052571936,0.000023364018,0.000018686624,0.00025456256],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982843,0.000058839945,0.0006905851,0.00017139052,0.0006264483,0.00016845483],"domain_scores_gemma":[0.9979676,0.00057333685,0.00061126647,0.00012207571,0.00064673903,0.0000790056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043988484,0.00013385278,0.00024871432,0.00029361367,0.000089629284,0.00050841796,0.0006902093,0.000039286657,0.000040135394],"category_scores_gemma":[0.00022275277,0.000105628365,0.00014937656,0.000168993,0.000043996468,0.0009813434,0.00011507584,0.00020644016,0.000025709316],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011253769,0.0007862096,0.0004187336,0.00008107718,0.00032412264,0.00009923946,0.0009343534,0.011632639,0.0020017119,0.96670187,0.001462209,0.015445313],"study_design_scores_gemma":[0.0012781299,0.0003986347,0.0003666295,0.00046150584,0.000045410387,0.0009381871,0.00022524477,0.93022984,0.0018267232,0.053729936,0.010252546,0.0002472064],"about_ca_topic_score_codex":0.0000011348216,"about_ca_topic_score_gemma":2.993264e-7,"teacher_disagreement_score":0.9185972,"about_ca_system_score_codex":0.00006696008,"about_ca_system_score_gemma":0.00005341085,"threshold_uncertainty_score":0.49026862},"labels":[],"label_agreement":null},{"id":"W2037205988","doi":"10.1109/tvcg.2012.204","title":"Beyond Mouse and Keyboard: Expanding Design Considerations for Information Visualization Interactions","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":210,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Interactivity; Human–computer interaction; Visualization; Pointer (user interface); Data science; Interaction design; Data visualization; Information visualization; World Wide Web; Artificial intelligence","score_opus":0.04117507242616682,"score_gpt":0.31341944338234373,"score_spread":0.27224437095617693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2037205988","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011282999,0.000032115033,0.9969446,0.00010522212,0.0008352812,0.00053819444,0.000051601844,0.00031585505,0.0000488082],"genre_scores_gemma":[0.97015464,0.0003610461,0.025222607,0.0037599076,0.00013207167,0.00012516281,0.000112145,0.000032087562,0.00010034077],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984487,0.00016416884,0.0005083962,0.00030052417,0.0002697708,0.00030842607],"domain_scores_gemma":[0.9985504,0.00043456702,0.00019591925,0.00027663427,0.00030704128,0.00023539457],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00042939774,0.00025678356,0.00021786295,0.0007665313,0.0008275752,0.00072982523,0.00013928355,0.00011600905,0.000015786447],"category_scores_gemma":[0.000028491446,0.0002703908,0.000073382114,0.00065622333,0.00007991947,0.0036670996,0.000010847793,0.00012350753,0.000009129191],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013688262,0.00020999789,0.00005776967,0.000047283975,0.000055423687,2.107035e-7,0.002950637,0.0009768786,0.0000541227,0.9908313,0.001344834,0.0034578375],"study_design_scores_gemma":[0.0008309058,0.00017537948,0.00008069405,0.00003161118,0.00005503173,0.000034906894,0.00015455122,0.98781776,0.0042287144,0.0025578227,0.0036802068,0.0003524369],"about_ca_topic_score_codex":0.0000064417804,"about_ca_topic_score_gemma":0.000007531385,"teacher_disagreement_score":0.9882735,"about_ca_system_score_codex":0.000038428272,"about_ca_system_score_gemma":0.000048860744,"threshold_uncertainty_score":0.99997485},"labels":[],"label_agreement":null},{"id":"W2037845592","doi":"10.1016/s0933-3657(00)00102-0","title":"Exploring presentation methods for tomographic medical image viewing","year":2001,"lang":"en","type":"article","venue":"Artificial Intelligence in Medicine","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Simon Fraser University","funders":"","keywords":"Computer science; Presentation (obstetrics); Context (archaeology); Computer vision; Artificial intelligence; Medical imaging; Multimedia; Human–computer interaction; Radiology; Medicine","score_opus":0.36694768515871706,"score_gpt":0.50488732119163,"score_spread":0.13793963603291298,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2037845592","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027708109,0.00014161516,0.9883491,0.0074213785,0.0006976966,0.00020559804,4.946246e-7,0.00008936772,0.00032396795],"genre_scores_gemma":[0.49086,0.0033048568,0.50119895,0.003108337,0.0011042111,0.00024816947,0.000053375305,0.000035954006,0.00008617561],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981436,0.00016160021,0.00063976576,0.000361187,0.00039694327,0.00029686262],"domain_scores_gemma":[0.9986324,0.00065316464,0.00009176244,0.00033095104,0.00014103751,0.00015070397],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025637136,0.00012291785,0.00022977397,0.00039192158,0.00009179992,0.00006767067,0.0007074393,0.000049703285,0.00015406274],"category_scores_gemma":[0.0024239183,0.000105974774,0.00004866205,0.0015499503,0.00014141125,0.00086533575,0.000104775405,0.00014093923,0.000021829223],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008379,0.00006032275,0.00021212838,0.000016637736,0.0000062299946,0.000018453982,0.0017527894,0.00006426038,0.0009450287,0.13730912,0.00014821322,0.85945845],"study_design_scores_gemma":[0.000085222,0.00012310491,0.00016497864,0.00018772294,0.000010075034,0.000013915809,0.001348094,0.9152763,0.0067161745,0.06742272,0.008481574,0.00017011099],"about_ca_topic_score_codex":0.00012940029,"about_ca_topic_score_gemma":0.00008274129,"teacher_disagreement_score":0.91521204,"about_ca_system_score_codex":0.000025235408,"about_ca_system_score_gemma":0.000044766137,"threshold_uncertainty_score":0.43215257},"labels":[],"label_agreement":null},{"id":"W2038457881","doi":"10.1109/vissof.2007.4290693","title":"Requirements of Software Visualization Tools: A Literature Survey","year":2007,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":57,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Visualization; Software engineering; Software visualization; Usability; Requirements analysis; Interoperability; Software development; Software; Software construction; World Wide Web; Human–computer interaction; Programming language; Data mining","score_opus":0.06679035873182436,"score_gpt":0.3618710456864382,"score_spread":0.2950806869546138,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038457881","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020834254,0.000038281716,0.996629,0.000014805687,0.00012606848,0.0000531507,0.000019155823,0.00009852392,0.0009375866],"genre_scores_gemma":[0.8878069,0.00006395282,0.10611849,0.0017461781,0.000062877385,0.0000013909996,0.0009544993,0.000018356788,0.0032273605],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99908715,0.00005065422,0.00027344146,0.00017896066,0.00027263508,0.00013712756],"domain_scores_gemma":[0.9991207,0.000093566676,0.00009928782,0.00032518568,0.00030529394,0.000055930403],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089982944,0.000071703165,0.00009504041,0.0001293389,0.000035675293,0.00015858839,0.00041216088,0.00004653023,0.000034964705],"category_scores_gemma":[0.00038263676,0.00006179764,0.000026748163,0.0010432511,0.000015547303,0.00078894396,0.00012507885,0.000030465151,0.000015511807],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002640144,0.00053523586,0.1381665,0.00014331733,0.00006597778,0.000020599451,0.001960302,0.000052887277,0.0014250829,0.7318005,0.024389632,0.101413585],"study_design_scores_gemma":[0.0033052582,0.0006988328,0.72764254,0.00068207824,0.000038110287,0.00002757491,0.00022814753,0.13601932,0.084022224,0.0073988833,0.038078275,0.0018587327],"about_ca_topic_score_codex":0.000012302854,"about_ca_topic_score_gemma":0.00004525578,"teacher_disagreement_score":0.8905105,"about_ca_system_score_codex":0.000013938325,"about_ca_system_score_gemma":0.000028825003,"threshold_uncertainty_score":0.25200346},"labels":[],"label_agreement":null},{"id":"W2038651474","doi":"10.1117/12.643631","title":"Theoretical analysis of uncertainty visualizations","year":2006,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":130,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Visualization; Artificial intelligence","score_opus":0.00985648724964216,"score_gpt":0.2571819687450688,"score_spread":0.24732548149542666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038651474","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9809745,0.000040649138,0.012222042,0.00163512,0.00012505529,0.00025359556,0.000106537664,0.00009687462,0.0045456565],"genre_scores_gemma":[0.88783884,0.000051531115,0.111422315,0.00015684777,0.00017928508,0.00004169083,0.0000663304,0.00003263805,0.00021054712],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99766016,2.578283e-8,0.0008502095,0.0003819992,0.000805692,0.00030189304],"domain_scores_gemma":[0.9970482,0.00018470314,0.00046711284,0.0001059656,0.0021028754,0.00009112693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006308573,0.00023659298,0.00047558342,0.00029103973,0.00007706648,0.00015687894,0.0015786308,0.00013522228,0.00004391376],"category_scores_gemma":[0.0004524214,0.00019539124,0.0007842536,0.001770623,0.00036256548,0.0005623194,0.00027170172,0.00014577899,9.3322916e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012287553,0.00018276295,0.0005216697,0.000117744225,0.0007326954,4.02286e-8,0.00010270896,0.002824949,0.047711708,0.94589335,0.0017987792,0.000101322155],"study_design_scores_gemma":[0.0005183476,0.00013344674,0.0014126817,0.00009056214,0.0006124073,0.0000027326964,0.0003240099,0.95992625,0.020019365,0.014693701,0.0019842763,0.00028224383],"about_ca_topic_score_codex":0.00001842692,"about_ca_topic_score_gemma":4.6395095e-7,"teacher_disagreement_score":0.9571013,"about_ca_system_score_codex":0.000082914514,"about_ca_system_score_gemma":0.000042194733,"threshold_uncertainty_score":0.7967824},"labels":[],"label_agreement":null},{"id":"W2038881214","doi":"10.3138/carto.46.4.227","title":"Development of an Open-Source Toolbox for the Analysis and Visualization of Remotely Sensed Time Series","year":2011,"lang":"en","type":"article","venue":"Cartographica The International Journal for Geographic Information and Geovisualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Toolbox; Visualization; Slicing; Animation; Human–computer interaction; Data visualization; Construct (python library); Data mining; Data science; Computer graphics (images)","score_opus":0.023507849438468943,"score_gpt":0.29567690431302596,"score_spread":0.272169054874557,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038881214","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034052007,0.000054028973,0.9647989,0.0002567281,0.00020448116,0.00049314764,0.00004531799,0.000027849044,0.00006749903],"genre_scores_gemma":[0.92098093,0.0007766743,0.07569848,0.0012320923,0.00009234163,0.00007163915,0.0009970461,0.000025359364,0.0001254436],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983747,0.00007312773,0.0008701204,0.00014986603,0.00039117277,0.00014101074],"domain_scores_gemma":[0.9970282,0.00015520187,0.0009055238,0.00024613086,0.0015919652,0.00007303213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001492227,0.00014375754,0.00021599077,0.00086052506,0.000533876,0.00055435614,0.0010115945,0.00006923122,0.000011836082],"category_scores_gemma":[0.00018951055,0.00009695126,0.000120332195,0.0011297232,0.00016602945,0.002433042,0.00018777356,0.00005878397,2.9504363e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00083101774,0.00037345418,0.00902051,0.00018373055,0.003692226,5.1440423e-7,0.04242552,0.0010966166,0.0013166666,0.7150897,0.00064111874,0.22532897],"study_design_scores_gemma":[0.0028211013,0.0006026553,0.04858536,0.00010848066,0.00083122146,0.00009609324,0.003995818,0.83857626,0.005515172,0.009527282,0.08878924,0.0005513019],"about_ca_topic_score_codex":0.0000357519,"about_ca_topic_score_gemma":0.000058596037,"teacher_disagreement_score":0.8891005,"about_ca_system_score_codex":0.000009535707,"about_ca_system_score_gemma":0.00008954142,"threshold_uncertainty_score":0.53456694},"labels":[],"label_agreement":null},{"id":"W2039488353","doi":"10.1109/vast.2010.5650854","title":"ALIDA: Using machine learning for intent discernment in visual analytics interfaces","year":2010,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Visual analytics; Human–computer interaction; Visualization; Data visualization; Analytics; Rendering (computer graphics); Process (computing); User interface; Information visualization; User experience design; Data science; World Wide Web; Artificial intelligence","score_opus":0.04021053278247524,"score_gpt":0.34516135086574895,"score_spread":0.30495081808327373,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039488353","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1045533,0.0000074321188,0.89445,0.00034188942,0.00023662658,0.00009464538,0.0000023529487,0.000057028334,0.0002566901],"genre_scores_gemma":[0.96193624,0.0000061881324,0.036921483,0.00022540225,0.000032541768,0.000002738219,0.000014581443,0.0000082683855,0.0008525847],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991326,0.00002254574,0.00024401669,0.00024246673,0.00016768592,0.00019072255],"domain_scores_gemma":[0.9995859,0.00004888642,0.000072251794,0.00018100638,0.000048722886,0.000063218584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029452462,0.00010125603,0.00012867012,0.00013047621,0.00006620171,0.0002196174,0.00040124723,0.000036205292,0.000051590338],"category_scores_gemma":[0.00009920593,0.00008328904,0.000038693688,0.00025579453,0.000025906553,0.00028828575,0.0002919977,0.00015354696,0.0000082272445],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056792327,0.0016757061,0.20476927,0.00017562996,0.00018693433,0.000028679562,0.0035103296,0.027885891,0.11783568,0.5628977,0.0011972821,0.07978009],"study_design_scores_gemma":[0.0002462213,0.000052755313,0.00022362138,0.00001140083,0.000005425442,0.0000026582086,0.00011844373,0.98671126,0.007740713,0.00023310633,0.0045353826,0.00011903201],"about_ca_topic_score_codex":0.00009039394,"about_ca_topic_score_gemma":0.00048764228,"teacher_disagreement_score":0.95882535,"about_ca_system_score_codex":0.000037549416,"about_ca_system_score_gemma":0.000028286599,"threshold_uncertainty_score":0.33964285},"labels":[],"label_agreement":null},{"id":"W2040355224","doi":"10.1111/j.1467-8659.2008.01204.x","title":"Animating Causal Overlays","year":2008,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Public Safety Canada","keywords":"Causality (physics); Computer science; Perception; Context (archaeology); Visualization; Causal model; Dimension (graph theory); Cognitive psychology; Human–computer interaction; Artificial intelligence; Psychology; Mathematics","score_opus":0.028978387480187804,"score_gpt":0.2691838588696616,"score_spread":0.24020547138947382,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040355224","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0048225196,0.000052317704,0.992786,0.00054922287,0.0005131263,0.0000624037,0.0000051153297,0.00032859182,0.00088069757],"genre_scores_gemma":[0.87300515,0.00011085947,0.11868876,0.007582488,0.00026741892,0.0000050358058,0.000046907684,0.000026969308,0.0002663833],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987319,0.000036916455,0.0002499731,0.00033904723,0.00030359003,0.0003385706],"domain_scores_gemma":[0.99907994,0.00005179807,0.00009286294,0.0005515799,0.000099984645,0.00012383323],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013294564,0.00014505794,0.0001550339,0.00018883494,0.000335036,0.00015031395,0.000854789,0.0000569471,0.000008405388],"category_scores_gemma":[0.00001299597,0.00014201258,0.00009059824,0.00073213264,0.00007347096,0.0005852399,0.00051250245,0.00013165743,0.00006835133],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.794453e-7,0.0000559523,0.007253967,0.000008132796,0.000016827818,0.00004876647,0.00023729849,0.00006238892,0.000021800077,0.9539021,0.03519233,0.0031997152],"study_design_scores_gemma":[0.00026218873,0.0000822284,0.0043214783,0.000017103774,0.0000032794972,0.00012003385,0.0000068585828,0.9536606,0.00012319004,0.0051481966,0.036006324,0.00024852832],"about_ca_topic_score_codex":0.000009611949,"about_ca_topic_score_gemma":0.0000057942448,"teacher_disagreement_score":0.9535982,"about_ca_system_score_codex":0.00001317472,"about_ca_system_score_gemma":0.000051119398,"threshold_uncertainty_score":0.57911044},"labels":[],"label_agreement":null},{"id":"W2040517636","doi":"10.1145/2630099.2630108","title":"Spirograph inspired visualization of ecological networks","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Networks of Centres of Excellence of Canada; Natural Sciences and Engineering Research Council of Canada; Singapore-MIT Alliance for Research and Technology Centre","keywords":"Visualization; Computer science; Ecological network; Enhanced Data Rates for GSM Evolution; Ecosystem; Ecology; Graph drawing; Complex network; Distributed computing; Artificial intelligence; World Wide Web; Biology","score_opus":0.01827104781648575,"score_gpt":0.2868803542275883,"score_spread":0.26860930641110253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040517636","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023381368,0.000005865321,0.9901786,0.00007746176,0.00009455879,0.00003780004,2.8896514e-7,0.00012280578,0.007144505],"genre_scores_gemma":[0.9886566,0.00001484342,0.010173386,0.000955055,0.000028708224,0.0000013373076,0.000015871616,0.0000029974221,0.00015121987],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993657,0.000056081873,0.00019234711,0.00015165201,0.00012792418,0.00010633456],"domain_scores_gemma":[0.9995129,0.00004255462,0.00007592144,0.00024935842,0.00006974145,0.000049493934],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022320717,0.000056603323,0.00010009551,0.00007585473,0.0000348699,0.00005254723,0.00037511162,0.000045954355,0.000059983002],"category_scores_gemma":[0.000061383995,0.00004506061,0.000037083897,0.0005279713,0.00003289106,0.00018521854,0.000118623044,0.00002312153,0.000012348356],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.235357e-7,0.000062217856,0.0042141126,0.0000034076688,0.000003980033,2.043009e-7,0.00001750536,0.0015095997,0.00003216151,0.9843611,0.0013868542,0.008408321],"study_design_scores_gemma":[0.00013746468,0.00008495386,0.0074297185,0.0000035645653,0.0000026566327,5.629904e-7,0.0000031505806,0.98163354,0.00022780642,0.0015026153,0.008906297,0.000067690555],"about_ca_topic_score_codex":0.0000045743013,"about_ca_topic_score_gemma":0.000005608206,"teacher_disagreement_score":0.98631847,"about_ca_system_score_codex":0.0000057561206,"about_ca_system_score_gemma":0.000010875533,"threshold_uncertainty_score":0.18375182},"labels":[],"label_agreement":null},{"id":"W2040991761","doi":"10.1117/12.2041318","title":"The CZSaw notes case study","year":2013,"lang":"pl","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Workspace; Visual analytics; Data science; Process (computing); Data visualization; Analytics; Visualization; Data analysis; Cultural analytics; Information retrieval; World Wide Web; Data mining; Semantic analytics; Artificial intelligence; Programming language; The Internet","score_opus":0.01991635218569851,"score_gpt":0.2685776013563171,"score_spread":0.24866124917061858,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040991761","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98895323,0.00019318677,0.00045330834,0.0071770134,0.00069347257,0.0014110005,0.000055493456,0.00011480833,0.00094848016],"genre_scores_gemma":[0.9427654,0.000298808,0.054017972,0.00039354528,0.0008719749,0.00030748697,0.000009260846,0.00010806507,0.001227451],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.995862,5.1405532e-8,0.0013327083,0.00072142674,0.0013578909,0.0007258997],"domain_scores_gemma":[0.9939103,0.00064298994,0.00080871134,0.00020113672,0.004165014,0.00027182174],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001449734,0.000545988,0.0005729454,0.00013146499,0.00047533103,0.001519024,0.003200117,0.00022743226,0.000031367377],"category_scores_gemma":[0.0015215374,0.00038734073,0.0008008601,0.000874246,0.00047588392,0.0016226658,0.00091913366,0.0005319502,0.000020087327],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036451496,0.00091297546,0.0016553503,0.000536131,0.001501349,0.0000034223633,0.0023993717,0.0001786171,0.036533616,0.9313537,0.021770678,0.0031183315],"study_design_scores_gemma":[0.00328633,0.001847976,0.0017134423,0.00066185807,0.0007697599,0.00049213803,0.031811927,0.91738427,0.020343006,0.0033548763,0.016834496,0.0014999347],"about_ca_topic_score_codex":0.00016160877,"about_ca_topic_score_gemma":0.0000020056011,"teacher_disagreement_score":0.92799884,"about_ca_system_score_codex":0.00017128924,"about_ca_system_score_gemma":0.00009006851,"threshold_uncertainty_score":0.99985784},"labels":[],"label_agreement":null},{"id":"W2041676769","doi":"10.1142/s0218843008001932","title":"EVOLVING A SOCIAL VISUALIZATION DESIGN AIMED AT INCREASING PARTICIPATION IN A CLASS-BASED ONLINE COMMUNITY","year":2008,"lang":"en","type":"article","venue":"International Journal of Cooperative Information Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Telus (Canada); University of Saskatchewan","funders":"","keywords":"Visualization; Computer science; Cluster analysis; Personalization; Class (philosophy); Human–computer interaction; Information visualization; Online community; Visual analytics; World Wide Web; Data science; Artificial intelligence","score_opus":0.07463535164154282,"score_gpt":0.36934639032016797,"score_spread":0.29471103867862514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041676769","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17546964,0.000022047478,0.8232962,0.00026298242,0.0004726432,0.00015464166,0.000020847116,0.00003063608,0.00027037764],"genre_scores_gemma":[0.9965753,0.000014949915,0.0024554955,0.00064091996,0.000113092006,0.0000069271528,0.0001627588,0.0000060156035,0.00002454546],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99654436,0.001103571,0.0012499099,0.00007240598,0.00088651496,0.00014321422],"domain_scores_gemma":[0.99563044,0.00034521346,0.001045184,0.00012938929,0.0027776314,0.0000721558],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016900024,0.00013563246,0.00024722566,0.0006908654,0.0003017981,0.0003667444,0.00068641244,0.00006291105,0.000017193575],"category_scores_gemma":[0.0009509509,0.00012534183,0.000063399886,0.0005569591,0.000056000496,0.004476134,0.000111262154,0.00022444174,0.00002018625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010209653,0.002272078,0.040044464,0.00013896183,0.0004875828,0.00015136332,0.08109375,0.79163146,0.0033089505,0.06208217,0.011976306,0.0057919463],"study_design_scores_gemma":[0.0017347822,0.00012911041,0.016103663,0.00015894284,0.0000066657553,0.000159895,0.0005984001,0.97720236,0.00073538016,0.000021579808,0.0029939313,0.0001553107],"about_ca_topic_score_codex":0.000089810215,"about_ca_topic_score_gemma":0.000027628095,"teacher_disagreement_score":0.82110566,"about_ca_system_score_codex":0.00057810225,"about_ca_system_score_gemma":0.000383779,"threshold_uncertainty_score":0.51112914},"labels":[],"label_agreement":null},{"id":"W2042044826","doi":"10.1109/vast.2009.5333020","title":"Capturing and supporting the analysis process","year":2009,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":77,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Boeing","keywords":"Computer science; Visual analytics; Analytics; Scripting language; Process (computing); Visualization; Human–computer interaction; Cultural analytics; Timeline; Interactive visual analysis; Data visualization; Process mining; Undo; Data science; Reuse; Process modeling; Work in process; Programming language; World Wide Web; Artificial intelligence; Semantic analytics; Business process modeling; Web page","score_opus":0.015509453554631413,"score_gpt":0.3221305469962769,"score_spread":0.3066210934416455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042044826","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021575693,0.000018568438,0.96983516,0.0036360533,0.000010859813,0.000026348864,3.6391745e-7,0.00007920639,0.004817734],"genre_scores_gemma":[0.99627316,0.000003303069,0.0018212697,0.0014800637,0.000008909484,2.410065e-7,0.000001661525,6.158608e-7,0.0004108045],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99962455,0.000008643522,0.00008626455,0.00011052971,0.000089621324,0.0000803869],"domain_scores_gemma":[0.99974006,0.000012230488,0.000033773948,0.00016143604,0.000024633033,0.000027841616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015267766,0.000032904933,0.00004936033,0.000050869614,0.00007593592,0.00019278176,0.00024287603,0.000007832594,0.000013375454],"category_scores_gemma":[0.00002043646,0.000019322422,0.000018354429,0.0005709824,0.000008478516,0.00020513465,0.00003518638,0.000022762693,0.000003034688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000011373432,0.00008546102,0.024312522,0.000015265949,0.00020545941,0.000014310001,0.0069812415,0.0021806112,0.00012497691,0.7828986,0.0019198413,0.18126059],"study_design_scores_gemma":[0.00005204657,0.000008832867,0.017170357,0.0000017163865,0.000044602508,0.0000029568535,0.00022482923,0.97693884,0.0004871565,0.004317831,0.0006725378,0.00007830342],"about_ca_topic_score_codex":0.000004907493,"about_ca_topic_score_gemma":0.0000083084215,"teacher_disagreement_score":0.9747582,"about_ca_system_score_codex":0.0000019794845,"about_ca_system_score_gemma":0.0000080611235,"threshold_uncertainty_score":0.1858999},"labels":[],"label_agreement":null},{"id":"W2042635584","doi":"10.1108/13673270010315957","title":"Network Map: visualizing telecommunications service","year":2000,"lang":"en","type":"article","venue":"Journal of Knowledge Management","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Peter's Hospital","funders":"","keywords":"Computer science; Telecommunications service; Telecommunications; Relation (database); Service provider; Service (business); Order (exchange); Path (computing); Knowledge management; Telecommunications network; World Wide Web; Business; Database; Computer network; Marketing","score_opus":0.030266752621583307,"score_gpt":0.3152555174567208,"score_spread":0.2849887648351375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042635584","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005702043,0.0029553347,0.7074846,0.006787646,0.0009140446,0.00020504784,0.0000017898069,0.00012289463,0.28095847],"genre_scores_gemma":[0.33998206,0.006519427,0.57686985,0.017006794,0.0021424743,0.00001822053,0.000035718065,0.00009100011,0.05733442],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989332,0.00010308842,0.0004531315,0.00011483031,0.00020680166,0.00018894575],"domain_scores_gemma":[0.9989434,0.00004255838,0.00019431803,0.0005187229,0.00020395582,0.00009703246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058070506,0.00009605522,0.00015355163,0.00014219209,0.00015438556,0.00018441824,0.0015251383,0.000023662287,0.00020235652],"category_scores_gemma":[0.0000061900364,0.00008675098,0.00006869605,0.0008379737,0.000013124609,0.00044444628,0.00031095702,0.00011768577,0.00049128104],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010440111,0.0006480697,0.0002311625,0.00012573741,0.00024354942,0.00004394351,0.0013587173,0.0050369943,0.0000074952413,0.3710528,0.26374033,0.35750073],"study_design_scores_gemma":[0.00035514182,0.00004375056,0.00057328533,0.00013629388,0.0000383871,0.000017020504,0.000093452094,0.045083985,0.00000890592,0.002495439,0.9510308,0.00012354644],"about_ca_topic_score_codex":0.0000011103979,"about_ca_topic_score_gemma":0.000008934033,"teacher_disagreement_score":0.68729043,"about_ca_system_score_codex":0.000048771417,"about_ca_system_score_gemma":0.000031858075,"threshold_uncertainty_score":0.6314588},"labels":[],"label_agreement":null},{"id":"W2043623491","doi":"10.1145/2480362.2480528","title":"Reducing data transfer for charts on adaptive web sites","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Automatic summarization; Visualization; JavaScript; Data visualization; Data mining; Data extraction; Web application; Client-side; Transfer (computing); Data compression; Data transmission; Database; Information retrieval; Artificial intelligence; World Wide Web; Computer hardware","score_opus":0.11059305951057682,"score_gpt":0.32392686652383607,"score_spread":0.21333380701325924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043623491","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011612653,0.000007838294,0.99298096,0.001841269,0.00008372579,0.00018226894,0.000052828225,0.00010374573,0.0035860955],"genre_scores_gemma":[0.94515705,0.000018080267,0.045858044,0.0037632827,0.00011550206,0.00001888964,0.00025269552,0.000011312697,0.0048051556],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993598,0.000012441826,0.00010480876,0.00028873576,0.000106799744,0.00012745611],"domain_scores_gemma":[0.99917346,0.000060073984,0.000011129303,0.00064424454,0.000056659635,0.00005440201],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000109035216,0.00006344346,0.00006821517,0.000046395475,0.000059727034,0.00016515363,0.0007661523,0.000019210858,0.00018712934],"category_scores_gemma":[0.00002894261,0.00004958885,0.000017957185,0.00012436642,0.0000118866055,0.0007888311,0.0001133297,0.000027005737,0.00024376732],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000030204544,0.000111485926,0.00002952815,0.000011623264,0.000022804148,7.2157127e-7,0.00034988817,0.00005775377,0.0031978365,0.63706404,0.3272723,0.031879004],"study_design_scores_gemma":[0.00015510856,0.00006439794,0.000043178494,0.000009483076,0.0000029848416,5.402134e-7,0.000027438435,0.9782878,0.0015243216,0.0008982571,0.018896773,0.00008970967],"about_ca_topic_score_codex":0.000014658174,"about_ca_topic_score_gemma":0.00000684874,"teacher_disagreement_score":0.97823006,"about_ca_system_score_codex":0.000005938961,"about_ca_system_score_gemma":0.00002702923,"threshold_uncertainty_score":0.3133217},"labels":[],"label_agreement":null},{"id":"W2046425758","doi":"10.1177/0093854806290161","title":"It’s no Riddle, Choose the Middle","year":2007,"lang":"en","type":"article","venue":"Criminal Justice and Behavior","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland; Carleton University","funders":"","keywords":"Profiling (computer programming); Officer; Offender profiling; Crime scene; Applied psychology; Psychology; Computer science; Geography; Artificial intelligence; Criminology; Visualization; Archaeology","score_opus":0.09169539738640287,"score_gpt":0.34241394170874395,"score_spread":0.2507185443223411,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046425758","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.37455553,0.0004710141,0.60779595,0.0015577722,0.0022167342,0.0003808106,0.000024707446,0.0002479091,0.012749553],"genre_scores_gemma":[0.95787823,0.00031131072,0.016016083,0.017031677,0.0008348323,0.000019515688,0.00003726448,0.000027155367,0.007843902],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991516,0.000018315308,0.00017627551,0.00021627086,0.00020814671,0.00022938031],"domain_scores_gemma":[0.99930507,0.00007842426,0.000051734976,0.00033738394,0.00011236208,0.00011502804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033894856,0.00010082465,0.00008081269,0.000052147367,0.00023410194,0.0002144618,0.0004877315,0.000040072075,0.000036716985],"category_scores_gemma":[0.00006363312,0.00006996014,0.000032023243,0.00018694795,0.00007857073,0.00028150398,0.00017793861,0.000106833395,0.00018039579],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010076797,0.00305169,0.0040140226,0.0022367097,0.000044966735,0.001227058,0.03770869,0.000012816779,0.0072563635,0.24256,0.09578302,0.6060039],"study_design_scores_gemma":[0.0045128046,0.0016078877,0.31201965,0.00053446146,0.029826375,0.00135831,0.069173306,0.043129906,0.0150797395,0.0006069394,0.51840967,0.003740924],"about_ca_topic_score_codex":0.00001532126,"about_ca_topic_score_gemma":0.000015593134,"teacher_disagreement_score":0.602263,"about_ca_system_score_codex":0.000011158891,"about_ca_system_score_gemma":0.000026872667,"threshold_uncertainty_score":0.28528917},"labels":[],"label_agreement":null},{"id":"W2047148641","doi":"10.3138/carto.44.3.201","title":"Issues of Change Detection in Animated Choropleth Maps","year":2009,"lang":"en","type":"article","venue":"Cartographica The International Journal for Geographic Information and Geovisualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Graphics; Animation; Foveal; Change detection; Cartography; Computer graphics (images); Artificial intelligence; Geography","score_opus":0.026700539574668093,"score_gpt":0.3202383230490318,"score_spread":0.2935377834743637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047148641","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.099483505,0.0008362229,0.8827817,0.013306879,0.0019803124,0.0010402609,0.000087562126,0.00017108789,0.00031248736],"genre_scores_gemma":[0.99450886,0.002377528,0.00072521425,0.0020806568,0.000112589325,0.00001740691,0.00016218144,0.000004475891,0.000011097828],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99853355,0.000062291736,0.0006418148,0.000119264754,0.0004730607,0.00017002338],"domain_scores_gemma":[0.99843454,0.000049111837,0.00044753388,0.00016262555,0.00084485864,0.00006133053],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008872924,0.00012896836,0.00014762823,0.0011760276,0.00019272522,0.00044834518,0.0005904327,0.000079767684,0.0000052476116],"category_scores_gemma":[0.00014615234,0.00010086956,0.00010765015,0.0011137554,0.000059366906,0.0024079569,0.000055564444,0.00012704442,0.0000012116594],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017352104,0.0002206328,0.015354198,0.000059710244,0.00014043108,0.0000031685556,0.0065874136,0.00027892538,0.0009289516,0.6559042,0.0011974697,0.3191514],"study_design_scores_gemma":[0.0055404967,0.001245773,0.19776326,0.00037769345,0.00008496004,0.00034277342,0.0020329778,0.46762705,0.0037739335,0.09049224,0.2298121,0.0009067211],"about_ca_topic_score_codex":0.000051979587,"about_ca_topic_score_gemma":0.000043874606,"teacher_disagreement_score":0.8950254,"about_ca_system_score_codex":0.000019721723,"about_ca_system_score_gemma":0.000026426846,"threshold_uncertainty_score":0.4323403},"labels":[],"label_agreement":null},{"id":"W2047348798","doi":"10.1145/2213836.2213970","title":"Towards scalable summarization and visualization of large text corpora (abstract only)","year":2012,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Automatic summarization; Scalability; Information retrieval; NoSQL; World Wide Web; Visualization; Analytics; Full text search; Data visualization; Data science; Search engine; Database; Artificial intelligence","score_opus":0.02637914321600676,"score_gpt":0.31252712637317137,"score_spread":0.2861479831571646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047348798","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008397089,0.000066290915,0.97755843,0.000094285395,0.00013371978,0.0000748244,0.000010749557,0.000088718865,0.013575916],"genre_scores_gemma":[0.9914952,0.00005689271,0.0070892167,0.00031781627,0.00003348282,8.9460576e-7,0.00009417741,0.0000069154385,0.00090539776],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991973,0.000026271739,0.00022979651,0.00014444748,0.00021837346,0.00018381514],"domain_scores_gemma":[0.9994099,0.000021951948,0.00012988524,0.00022110049,0.00011775238,0.00009942451],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036251522,0.00008148528,0.000112702925,0.00011179888,0.000059496455,0.00008603255,0.00019306496,0.00004955241,0.00014807716],"category_scores_gemma":[0.00006419129,0.00007245269,0.000019616788,0.00047345902,0.000024823381,0.0012093536,0.00014931774,0.000027736318,0.000026254253],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012464674,0.00017776914,0.048183274,0.000030936986,0.000007523663,2.472456e-7,0.0002170017,0.000007989442,0.00041090426,0.9418017,0.0019458538,0.0072155115],"study_design_scores_gemma":[0.0017349493,0.0001722793,0.30539888,0.00009917508,0.000053556007,0.000031741016,0.00031373184,0.5807362,0.030073414,0.004202755,0.076328926,0.00085434277],"about_ca_topic_score_codex":0.000027870854,"about_ca_topic_score_gemma":0.000006851819,"teacher_disagreement_score":0.9830981,"about_ca_system_score_codex":0.000011880964,"about_ca_system_score_gemma":0.000049858267,"threshold_uncertainty_score":0.2954535},"labels":[],"label_agreement":null},{"id":"W2048308612","doi":"10.1007/s11432-012-4692-6","title":"An IconMap-based exploratory analytical approach for multivariate geospatial data","year":2012,"lang":"en","type":"article","venue":"Science China Information Sciences","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Geospatial analysis; Multivariate statistics; Visualization; Computer science; Geographic information system; Spatial analysis; Data mining; Raster graphics; Soil fertility; Software; Exploratory data analysis; Soil nutrients; Organic matter; Environmental science; Remote sensing; Geography; Soil science; Soil water; Artificial intelligence; Machine learning; Ecology","score_opus":0.10591367325524026,"score_gpt":0.3828487265029075,"score_spread":0.27693505324766726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048308612","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00451959,0.000008025866,0.99228805,0.0002614593,0.000489842,0.00026557638,0.000078401965,0.000158535,0.0019304876],"genre_scores_gemma":[0.78559196,0.0000013020564,0.21313806,0.0009578203,0.00008821568,0.000015769838,0.00019729286,0.0000027586307,0.000006810978],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970985,0.00006026711,0.00046203696,0.00047282325,0.0012302327,0.00067614083],"domain_scores_gemma":[0.9977688,0.000068851325,0.00026656064,0.0012260997,0.00026214673,0.0004075153],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.006929067,0.00016354716,0.00015709174,0.00057221117,0.0012202297,0.0018503605,0.0056784563,0.00004744281,0.000015818221],"category_scores_gemma":[0.00073828205,0.00012749106,0.000036003097,0.0027922383,0.0009799865,0.04509662,0.0005605781,0.00008550002,0.00004787025],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023906923,0.0008705822,0.010455633,0.000093143295,0.00001288062,2.492772e-7,0.0122949965,0.031702787,0.00049834664,0.86109316,0.003906946,0.07904739],"study_design_scores_gemma":[0.00025120497,0.000084625804,0.0032495293,0.000004621595,0.00000482595,0.0000017347638,0.000591524,0.9917577,0.0005675328,0.0002155394,0.003059596,0.00021157718],"about_ca_topic_score_codex":0.000027543436,"about_ca_topic_score_gemma":0.0000017928742,"teacher_disagreement_score":0.9600549,"about_ca_system_score_codex":0.000051638184,"about_ca_system_score_gemma":0.0008005642,"threshold_uncertainty_score":0.9997013},"labels":[],"label_agreement":null},{"id":"W2048389037","doi":"10.1109/tvcg.2013.210","title":"Using Concrete Scales: A Practical Framework for Effective Visual Depiction of Complex Measures","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario College of Art and Design; University of Toronto","funders":"","keywords":"Computer science; GRASP; Depiction; Scale (ratio); Data science; Visualization; Cognition; Visual approach; Human–computer interaction; Artificial intelligence; Psychology; Software engineering","score_opus":0.060984848746516565,"score_gpt":0.3664249008108995,"score_spread":0.30544005206438296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048389037","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0049662953,0.000013350311,0.99360436,0.000080951584,0.00040871455,0.0007342094,0.000021326321,0.00016072567,0.000010037328],"genre_scores_gemma":[0.909415,0.00008733678,0.0892203,0.001082765,0.00007271859,0.000068508736,0.000019206465,0.000026437221,0.000007734922],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983039,0.00021555793,0.0004512113,0.00043528932,0.00036187095,0.00023217971],"domain_scores_gemma":[0.9983599,0.00050554547,0.00022446475,0.0002748543,0.0004849649,0.00015024384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002552678,0.00022700772,0.00030432965,0.00039544638,0.0003242185,0.00026576334,0.00020075873,0.0001727141,0.000014107056],"category_scores_gemma":[0.000025400808,0.00022509211,0.0001353764,0.00082403753,0.00015381475,0.00071227615,0.0000084932,0.0001572522,0.0000041903572],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030154872,0.00018811293,0.00008440369,0.00010074558,0.00012886626,6.8217054e-7,0.0004779077,0.00076159375,0.00042103924,0.98458534,0.0002145026,0.01300667],"study_design_scores_gemma":[0.00058388524,0.00043227017,0.00030293068,0.00008181485,0.000049955088,0.000014953389,0.000053972773,0.9894056,0.0033868828,0.005130791,0.0003181577,0.00023879984],"about_ca_topic_score_codex":0.00002692676,"about_ca_topic_score_gemma":0.0000051942434,"teacher_disagreement_score":0.988644,"about_ca_system_score_codex":0.00002936279,"about_ca_system_score_gemma":0.00005074597,"threshold_uncertainty_score":0.917899},"labels":[],"label_agreement":null},{"id":"W2050995286","doi":"10.1117/12.872578","title":"EdgeMaps: visualizing explicit and implicit relations","year":2011,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"University of Calgary","keywords":"Computer science; Visualization; Graph drawing; Focus (optics); Theoretical computer science; GRASP; Graph; Spatialization; Node (physics); Similarity (geometry); Data visualization; Information visualization; Human–computer interaction; Artificial intelligence; Programming language","score_opus":0.02375671249526078,"score_gpt":0.26066390135992534,"score_spread":0.23690718886466455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050995286","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9867037,0.000075998854,0.005548552,0.0010981231,0.00016983235,0.00030028448,0.000024074336,0.00013716686,0.005942279],"genre_scores_gemma":[0.50525606,0.00019194359,0.49300718,0.00042780102,0.000323499,0.000114724004,0.00001333228,0.00006985852,0.00059561507],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982208,1.3232826e-8,0.00059166475,0.00040174078,0.00047355334,0.000312204],"domain_scores_gemma":[0.99825156,0.00009401723,0.0003278012,0.000084955595,0.0011024997,0.00013918466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050980854,0.00023817712,0.00029348698,0.0001337522,0.00011951326,0.00018522638,0.0012309285,0.00012896111,0.0000133676],"category_scores_gemma":[0.00037979288,0.00020544727,0.00029675214,0.0004626869,0.00012932919,0.0011711244,0.00039563724,0.00019069857,0.0000032976932],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009345527,0.000080794016,0.0005622496,0.00012694969,0.00015327077,5.919383e-8,0.00068729534,0.0000064748306,0.075445,0.91970193,0.0029106732,0.00031598378],"study_design_scores_gemma":[0.0037069984,0.0011834131,0.01042114,0.0011553445,0.0005238786,0.00010917415,0.006900869,0.6386173,0.25602493,0.050169367,0.02910914,0.002078446],"about_ca_topic_score_codex":0.000010141491,"about_ca_topic_score_gemma":1.3016641e-7,"teacher_disagreement_score":0.8695325,"about_ca_system_score_codex":0.00006443482,"about_ca_system_score_gemma":0.000028437455,"threshold_uncertainty_score":0.83778965},"labels":[],"label_agreement":null},{"id":"W2051302141","doi":"10.1504/ijitst.2011.041299","title":"Exploring visualisation in web information retrieval","year":2011,"lang":"en","type":"article","venue":"International Journal of Internet Technology and Secured Transactions","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Information retrieval; Visualization; World Wide Web; Information visualization; Rendering (computer graphics); Search engine; Web search query; Scroll; Web page; Process (computing); Data mining; Artificial intelligence","score_opus":0.05726337935187113,"score_gpt":0.27862084930705994,"score_spread":0.2213574699551888,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2051302141","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12007006,0.000037712696,0.87750757,0.0010015261,0.0008520721,0.0000396811,0.000005666597,0.00005089816,0.00043480084],"genre_scores_gemma":[0.99441344,0.000316116,0.0050937687,0.00012337991,0.000021070775,0.0000016520148,0.0000033263543,0.0000029297842,0.00002434747],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991318,0.000024432207,0.00046409937,0.00008486888,0.00020444459,0.0000903333],"domain_scores_gemma":[0.99932367,0.000021196156,0.00021355302,0.000089429355,0.00031437151,0.000037783324],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002251254,0.000076473065,0.00011000142,0.0016288254,0.000020061278,0.00006821262,0.0005552659,0.00007733954,0.000047185593],"category_scores_gemma":[0.00006046591,0.000073077106,0.000042673713,0.00048631482,0.00005463042,0.0029317753,0.000027715909,0.00024267481,0.000009193068],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032145547,0.000538801,0.004548041,0.000023656266,0.00042257548,0.00016184404,0.02293804,0.00017821093,0.0015260915,0.8392243,0.00026310634,0.12985389],"study_design_scores_gemma":[0.016557757,0.0029320924,0.030946521,0.0016391901,0.00020071285,0.0067323344,0.015145021,0.5441303,0.17413422,0.10887621,0.09659882,0.002106764],"about_ca_topic_score_codex":0.000008890486,"about_ca_topic_score_gemma":0.00002456179,"teacher_disagreement_score":0.87434334,"about_ca_system_score_codex":0.000050959683,"about_ca_system_score_gemma":0.000050153383,"threshold_uncertainty_score":0.2979998},"labels":[],"label_agreement":null},{"id":"W2051526144","doi":"10.1145/1377966.1377969","title":"Increasing the utility of quantitative empirical studies for meta-analysis","year":2008,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Quantitative analysis (chemistry); Visualization; Interface (matter); Empirical research; Task (project management); Data visualization; Information visualization; Visual analytics; User interface; Task analysis; Human–computer interaction; Data mining; Data science; Statistics; Engineering; Systems engineering","score_opus":0.584447370374735,"score_gpt":0.5006277537113519,"score_spread":0.08381961666338311,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2051526144","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003860779,0.000501157,0.993364,0.0016269422,0.000015573729,0.00007315098,0.000015455289,0.000024823745,0.0005181162],"genre_scores_gemma":[0.8968032,0.00002821216,0.10198441,0.00079082325,0.000004266968,0.000009682751,0.0000046380624,0.000001701274,0.0003730422],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991835,0.0001544514,0.00023816367,0.00016645943,0.00017756052,0.000079880934],"domain_scores_gemma":[0.99829,0.000941856,0.00009599567,0.0003589392,0.000291465,0.000021745584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061368407,0.000060818744,0.00037907745,0.000071233466,0.00014181074,0.000019510886,0.00037061932,0.000012279899,0.000048436505],"category_scores_gemma":[0.0005384289,0.00003056189,0.00041307276,0.0008591728,0.00013081428,0.00016071164,0.00012461335,0.000022065358,0.0000025565607],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030371366,0.00041883177,0.014965133,0.000046579324,0.23117524,0.000003869439,0.013310868,0.00039156483,0.00003898781,0.6657181,0.07338657,0.0005139166],"study_design_scores_gemma":[0.00012760467,0.00006135899,0.005600583,5.510365e-7,0.026041495,0.0000033733932,0.0009950672,0.9586845,0.0005562594,0.004098246,0.0037125382,0.000118422635],"about_ca_topic_score_codex":0.000033996927,"about_ca_topic_score_gemma":0.00003828629,"teacher_disagreement_score":0.95829296,"about_ca_system_score_codex":0.0000038405065,"about_ca_system_score_gemma":0.000028804854,"threshold_uncertainty_score":0.12462776},"labels":[],"label_agreement":null},{"id":"W2052398640","doi":"10.1109/mcg.2005.102","title":"Evaluating visualizations: do expert reviews work?","year":2005,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":217,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"","keywords":"Usability; Computer science; Visualization; Heuristics; Human–computer interaction; Set (abstract data type); Expert system; Data visualization; Data science; Information visualization; Focus (optics); User interface; Heuristic evaluation; Interactive visualization; Artificial intelligence","score_opus":0.08895323162627967,"score_gpt":0.4014014550314654,"score_spread":0.31244822340518574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2052398640","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00018526534,0.0022013613,0.9957892,0.0009334435,0.00009445976,0.0003830521,0.000003830332,0.00016062704,0.0002488102],"genre_scores_gemma":[0.074850954,0.018051755,0.8811923,0.021388095,0.0026794835,0.0010592768,0.00015215027,0.00006412919,0.00056184706],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99865717,0.00007526954,0.0004062701,0.00045597937,0.00021400342,0.00019132509],"domain_scores_gemma":[0.9988461,0.000076557124,0.0001482834,0.0006530163,0.00014210204,0.00013389792],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043236764,0.00015672088,0.00017957458,0.00017065633,0.0003373162,0.00044449608,0.00059754285,0.000054875785,0.000011291113],"category_scores_gemma":[0.000009094403,0.00014673098,0.000067056724,0.0010243336,0.00006229338,0.00038818273,0.00015989985,0.00009617514,0.000084314626],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.0471574e-7,0.00008465265,0.00009481419,0.000009552246,0.000008713074,1.5215092e-7,0.00020866405,0.00015177217,0.000035307832,0.5681306,0.010409443,0.42086604],"study_design_scores_gemma":[0.00014975842,0.000020020076,0.00014914853,0.00003509589,0.0000075236985,0.000004511132,0.0000035546018,0.4247343,0.0000429403,0.0028990288,0.5717647,0.00018940138],"about_ca_topic_score_codex":0.0000020777918,"about_ca_topic_score_gemma":0.000002963603,"teacher_disagreement_score":0.56523156,"about_ca_system_score_codex":0.000013481406,"about_ca_system_score_gemma":0.000027726912,"threshold_uncertainty_score":0.59835154},"labels":[],"label_agreement":null},{"id":"W2053479348","doi":"10.1145/2669485.2669555","title":"Bancada","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Zoom; Geospatial analysis; Computer graphics (images); Human–computer interaction; Computer science; Affordance; Physics; Lens (geology); Cartography; Optics","score_opus":0.015006677823594588,"score_gpt":0.27369192419002236,"score_spread":0.25868524636642776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053479348","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000059411894,0.0000012328848,0.89812154,0.0005307075,0.00005883435,0.000005265805,8.383522e-8,0.000083049825,0.1011399],"genre_scores_gemma":[0.87348056,0.0000037792104,0.100947656,0.009202214,0.000069712005,6.930271e-7,0.0000039442098,0.0000031092836,0.01628835],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99978536,0.000008443287,0.000037013993,0.000066058274,0.00005703955,0.000046058783],"domain_scores_gemma":[0.9997638,0.00001070186,0.000007672352,0.00017973366,0.000012756941,0.000025339865],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006586439,0.000018517243,0.000022154534,0.000015407139,0.000017996106,0.000058664,0.00024532585,0.000006339924,0.00006393518],"category_scores_gemma":[0.000017587405,0.000014521011,0.0000077297755,0.0000966546,0.0000040124705,0.00013607035,0.0000556266,0.000010052638,0.00031981204],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.6737857e-8,0.0000035246,0.00009391048,4.3393598e-7,3.9925766e-7,7.9108894e-8,0.000007825114,0.000003941908,0.00001541218,0.96983004,0.016514143,0.013530302],"study_design_scores_gemma":[0.000043601092,0.000006970384,0.00029336146,7.32137e-7,2.901092e-7,6.3091034e-7,0.0000013897867,0.510537,0.0004745156,0.0046107913,0.48399526,0.0000354446],"about_ca_topic_score_codex":0.0000025624363,"about_ca_topic_score_gemma":0.0000018360115,"teacher_disagreement_score":0.9652192,"about_ca_system_score_codex":0.000001589197,"about_ca_system_score_gemma":0.0000043779514,"threshold_uncertainty_score":0.41106433},"labels":[],"label_agreement":null},{"id":"W2054054049","doi":"10.1109/tvcg.2014.2346573","title":"Supporting Communication and Coordination in Collaborative Sensemaking","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":110,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; Division 29: Society for the Advancement of Psychotherapy; University of Victoria","keywords":"Sensemaking; Computer science; Set (abstract data type); Task (project management); Baseline (sea); Human–computer interaction; Visual analytics; Work (physics); Collaborative software; Information sharing; Analytics; Shared space; Knowledge management; Space (punctuation); World Wide Web; Data science; Visualization; Artificial intelligence","score_opus":0.014658041340122878,"score_gpt":0.30954970947868016,"score_spread":0.2948916681385573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2054054049","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0067544347,0.000031534026,0.9924592,0.00025410947,0.00012189781,0.00015106078,0.0000041714025,0.00012517867,0.000098464065],"genre_scores_gemma":[0.99528575,0.00017662472,0.0032095865,0.0012187322,0.0000146344955,0.000009806715,0.000016988757,0.00001136107,0.000056510555],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99871355,0.00027318278,0.00033709517,0.00032351413,0.00019158509,0.00016108819],"domain_scores_gemma":[0.99916863,0.00017522574,0.0001464432,0.00027003145,0.0001635973,0.00007606551],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050360727,0.00014470454,0.00016465511,0.00045344877,0.00028200395,0.00030799818,0.00017362315,0.00008056233,0.00000331851],"category_scores_gemma":[0.000011619744,0.00015554462,0.00002369651,0.0010707929,0.00007432278,0.0005755984,0.000009964035,0.00012904593,0.0000020113866],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000464118,0.00010472955,0.00036022518,0.000025744914,0.0000115113035,8.4662133e-7,0.0017674965,0.0005765004,0.000017157554,0.9773304,0.00014502053,0.01965575],"study_design_scores_gemma":[0.00051607384,0.00009525167,0.0006765287,0.00005997066,0.000007865686,0.000007239549,0.00009312702,0.9940283,0.00036140977,0.0020596301,0.0019215023,0.00017310315],"about_ca_topic_score_codex":0.000014771025,"about_ca_topic_score_gemma":0.000075682336,"teacher_disagreement_score":0.9934518,"about_ca_system_score_codex":0.000018848566,"about_ca_system_score_gemma":0.000023786293,"threshold_uncertainty_score":0.63429254},"labels":[],"label_agreement":null},{"id":"W2054160847","doi":"10.1177/1473871611413099","title":"Information visualization evaluation in large companies: Challenges, experiences and recommendations","year":2011,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visualization; Computer science; Information visualization; Set (abstract data type); Data science; Plan (archaeology); Context (archaeology); Work (physics); Focus (optics); Creative visualization; Data visualization; Automotive industry; Knowledge management; Data mining; Engineering","score_opus":0.07048500596307443,"score_gpt":0.3476712538339281,"score_spread":0.27718624787085366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2054160847","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0096655395,0.00013859088,0.98048604,0.00027687027,0.00048737167,0.00075029174,0.000026512025,0.00032378442,0.0078449845],"genre_scores_gemma":[0.99297845,0.000849632,0.0028417662,0.0011024259,0.000027959562,0.00018512867,0.0019922096,0.000010073562,0.000012367089],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99749374,0.00026851872,0.0010599337,0.00020220487,0.00067357457,0.0003019959],"domain_scores_gemma":[0.998253,0.000049103222,0.0005435847,0.00037511234,0.00066355855,0.000115634706],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0016265826,0.00022323421,0.00020823635,0.0010229462,0.0002530929,0.00045631736,0.00040371815,0.00014822035,0.00021945525],"category_scores_gemma":[0.00040243514,0.00023679939,0.00003411299,0.0012645831,0.00004506136,0.019510759,0.0001785371,0.000093789524,0.0001249101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010991491,0.00013344345,0.0008922473,0.000065992834,0.000011990371,1.8543957e-7,0.1801272,0.00012414539,0.0000024451103,0.76806194,0.00083313585,0.049736265],"study_design_scores_gemma":[0.0014224537,0.000106515356,0.009838672,0.00009080242,0.0000155732,0.000007797147,0.029190859,0.9274022,0.00020290745,0.002627823,0.028686296,0.00040808364],"about_ca_topic_score_codex":0.000049272185,"about_ca_topic_score_gemma":0.0000611364,"teacher_disagreement_score":0.9833129,"about_ca_system_score_codex":0.00013540113,"about_ca_system_score_gemma":0.00012290372,"threshold_uncertainty_score":0.99420285},"labels":[],"label_agreement":null},{"id":"W2056543697","doi":"10.1145/1879211.1879244","title":"ImpactViz","year":2010,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Code reuse; Reuse; Programming language; Software engineering; Modular design; Code (set theory); Software; Object-oriented programming; Class (philosophy); Software development; Engineering; Artificial intelligence","score_opus":0.015197816222813213,"score_gpt":0.30999682100499215,"score_spread":0.29479900478217896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2056543697","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002534967,7.318112e-7,0.9288492,0.00080729334,0.00021031858,0.000010350141,4.5157407e-7,0.00012865594,0.06745799],"genre_scores_gemma":[0.93081886,0.0000014692629,0.06147913,0.00213113,0.000046856825,3.6608068e-7,0.0000026242235,0.0000020216628,0.0055175717],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997842,0.0000024987057,0.00003706707,0.000063475716,0.000056537025,0.000056225792],"domain_scores_gemma":[0.99969804,0.0000069562166,0.00000831274,0.00022662868,0.000016972186,0.000043076714],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005278017,0.000021087988,0.000020460848,0.000021390813,0.000020545012,0.000095870404,0.00030049327,0.00001143068,0.00025642902],"category_scores_gemma":[0.00001943539,0.000015842556,0.000010109816,0.00011196465,0.000006979589,0.0002162546,0.00006169579,0.000034488916,0.0003120643],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.162308e-8,0.000008356176,0.00028470572,2.8977217e-7,7.086318e-7,5.839671e-7,0.0000198051,3.840958e-7,0.0018416168,0.97665644,0.013800728,0.007386333],"study_design_scores_gemma":[0.00017660129,0.000020594185,0.0039848285,0.0000010776414,0.0000014246923,0.000014506504,0.000010823254,0.3605299,0.011202414,0.012241724,0.6116459,0.00017024881],"about_ca_topic_score_codex":0.0000045776374,"about_ca_topic_score_gemma":0.000011272413,"teacher_disagreement_score":0.9644147,"about_ca_system_score_codex":8.89281e-7,"about_ca_system_score_gemma":0.000013546628,"threshold_uncertainty_score":0.40110594},"labels":[],"label_agreement":null},{"id":"W2057444996","doi":"10.1109/tvcg.2013.167","title":"Interactive Exploration of Implicit and Explicit Relations in Faceted Datasets","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":97,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University; University of Toronto","funders":"","keywords":"Computer science; Sensemaking; Visualization; Semantics (computer science); Data visualization; Construct (python library); Information visualization; Visual analytics; Information retrieval; Data science; Focus (optics); Process (computing); Metaphor; Resource (disambiguation); Interactive visual analysis; Human–computer interaction; Data mining; Programming language","score_opus":0.026885834734593272,"score_gpt":0.2989290787614324,"score_spread":0.2720432440268391,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057444996","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014672976,0.000015298909,0.9846207,0.00013066102,0.00013123419,0.0002764171,0.00004617568,0.00007709122,0.000029483344],"genre_scores_gemma":[0.997278,0.0002441911,0.0017652415,0.0005444748,0.000010172617,0.000035446028,0.00008516207,0.000011305263,0.000026006754],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988109,0.00011034414,0.00040238674,0.00034874582,0.00018834393,0.00013928479],"domain_scores_gemma":[0.9992372,0.00011528457,0.00013442093,0.00028710748,0.0001358026,0.00009020727],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012287729,0.00015538311,0.00018714898,0.00060434715,0.00012556421,0.00018276366,0.00018299579,0.000081362596,0.000021571059],"category_scores_gemma":[0.0000055059645,0.00015847737,0.000032750548,0.00096031174,0.000053649117,0.0020674076,0.000011529636,0.00012717939,0.0000092470345],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011818514,0.00048725403,0.0004932716,0.00004993246,0.000053785607,0.0000015179891,0.0039569507,0.001562913,0.00022744924,0.97514534,0.0007935468,0.01721622],"study_design_scores_gemma":[0.0005182529,0.00013592976,0.002016881,0.000059165985,0.000010573112,0.000004677801,0.00015397069,0.99296755,0.0011657989,0.0025185128,0.0002747896,0.00017389994],"about_ca_topic_score_codex":0.00008332386,"about_ca_topic_score_gemma":0.000054989607,"teacher_disagreement_score":0.99140465,"about_ca_system_score_codex":0.00001651861,"about_ca_system_score_gemma":0.000023076553,"threshold_uncertainty_score":0.646252},"labels":[],"label_agreement":null},{"id":"W2057792061","doi":"10.1145/1621995.1622036","title":"Probing the use of charts and graphs in technical documentation through analysis and pragmatic collaboration","year":2009,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Documentation; Computer science; Terminology; Graphics; Comprehension; Technical documentation; Software documentation; User analysis; Search engine indexing; Technical writing; World Wide Web; Information retrieval; Visualization; Multimedia; Human–computer interaction; Artificial intelligence; Software; Software development; Programming language; Linguistics","score_opus":0.02604512500146801,"score_gpt":0.3209403146490181,"score_spread":0.2948951896475501,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057792061","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09365315,0.000028497336,0.9028434,0.00303337,0.000010438045,0.00023221025,0.0000027304056,0.00003323526,0.00016296716],"genre_scores_gemma":[0.9716545,0.00008610236,0.027702954,0.0005100106,0.0000014809289,0.000002329375,0.000011880953,8.5776094e-7,0.000029925084],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995255,0.00004402022,0.00016674698,0.000113326154,0.00010175797,0.00004865037],"domain_scores_gemma":[0.99969614,0.000046340487,0.00006777708,0.0001374379,0.000039823633,0.00001246721],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013697632,0.000039246857,0.00008046382,0.000114264854,0.000035244262,0.0001896221,0.00007549561,0.000016445652,0.0000032993178],"category_scores_gemma":[0.000036170106,0.000026490214,0.000010225244,0.0014521917,0.000025450072,0.001019069,0.000029694922,0.000021716913,2.089408e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003865049,0.000094511764,0.007810795,0.000016972106,0.000036489713,0.000001094883,0.0035704046,0.0006658515,0.00207202,0.9719506,0.0004511803,0.013326201],"study_design_scores_gemma":[0.0006107574,0.00014841257,0.12465442,0.000043126412,0.0001435108,0.000004986889,0.0004852208,0.8421521,0.0026440753,0.028222706,0.00068613025,0.00020452382],"about_ca_topic_score_codex":0.000027928783,"about_ca_topic_score_gemma":0.00016549102,"teacher_disagreement_score":0.9437279,"about_ca_system_score_codex":0.000005826384,"about_ca_system_score_gemma":0.000010283577,"threshold_uncertainty_score":0.18285303},"labels":[],"label_agreement":null},{"id":"W2058203255","doi":"10.1109/tvcg.2011.279","title":"Empirical Studies in Information Visualization: Seven Scenarios","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":628,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Visualization; Computer science; Information visualization; Data visualization; Visual analytics; Data science; Creative visualization; Empirical research; Human–computer interaction; Information retrieval; Data mining","score_opus":0.08538256592749338,"score_gpt":0.34837626729025245,"score_spread":0.26299370136275907,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058203255","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0032236418,0.000041379903,0.9953687,0.00005445843,0.0006718439,0.0002226606,0.000009102617,0.00028141454,0.00012675278],"genre_scores_gemma":[0.99033916,0.00095992273,0.003144947,0.0053526815,0.000045661985,0.00003543221,0.000035885558,0.000021225258,0.000065089334],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99822426,0.00018151788,0.000599477,0.00036904478,0.00037343128,0.00025224927],"domain_scores_gemma":[0.99898875,0.0000771616,0.00015415867,0.00035641837,0.00029072983,0.00013279115],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032900667,0.00024875053,0.00026377014,0.00092281983,0.00025022993,0.00019730616,0.0003556386,0.00013637358,0.00002184548],"category_scores_gemma":[0.000010891805,0.00024488164,0.00007175597,0.0018385923,0.0001280248,0.0018332241,0.000015749098,0.0001630479,0.000030227084],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029018713,0.000600701,0.0011694719,0.00011963566,0.00009656881,0.000010780388,0.025391532,0.0007962908,0.0000014882149,0.9617701,0.0013212612,0.008693129],"study_design_scores_gemma":[0.00078959693,0.0002430693,0.0010085921,0.000098070086,0.000020098614,0.000022404427,0.00036799122,0.99231577,0.00037443728,0.0017509878,0.0026520814,0.00035689463],"about_ca_topic_score_codex":0.000016232148,"about_ca_topic_score_gemma":0.000037067304,"teacher_disagreement_score":0.9922238,"about_ca_system_score_codex":0.000046216544,"about_ca_system_score_gemma":0.00006334124,"threshold_uncertainty_score":0.99859834},"labels":[],"label_agreement":null},{"id":"W2058318782","doi":"10.1111/j.1467-8659.2009.01441.x","title":"Visualization Techniques for Schedule Comparison","year":2009,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of Victoria","funders":"","keywords":"Gantt chart; Computer science; Visualization; Schedule; ENCODE; Information retrieval; Scheduling (production processes); Data mining; Systems engineering","score_opus":0.02696178369461354,"score_gpt":0.33502976516343547,"score_spread":0.3080679814688219,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058318782","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00012118191,0.000059945938,0.99664736,0.0017102542,0.00029898153,0.00027955277,0.00000756057,0.00064654055,0.00022861421],"genre_scores_gemma":[0.357541,0.000051900708,0.62802744,0.013630944,0.0003065965,0.000024972416,0.00027598336,0.000026254611,0.000114910996],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986708,0.000034749104,0.0003491052,0.0003861118,0.00023376662,0.00032545094],"domain_scores_gemma":[0.99896526,0.00004745857,0.0001435579,0.0005166147,0.00022490331,0.00010217835],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024550615,0.00016900423,0.00021440435,0.00030000028,0.00022129326,0.0003605257,0.000860004,0.000096444135,0.0000022333986],"category_scores_gemma":[0.000018821134,0.00016851458,0.00011768693,0.0007584215,0.000034677036,0.0005826323,0.00014350889,0.00008388424,0.000008893701],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021615958,0.00012959531,0.00047910266,0.00000873712,0.000008453755,5.9131423e-7,0.00006166859,0.00001629583,0.000058024652,0.93950516,0.03174684,0.027983388],"study_design_scores_gemma":[0.00022924846,0.00032604655,0.00027472666,0.000025273668,0.000006777335,0.0000031836855,0.000006153657,0.8646365,0.0022564617,0.03564079,0.096373804,0.00022102194],"about_ca_topic_score_codex":0.0000011540395,"about_ca_topic_score_gemma":0.0000029643725,"teacher_disagreement_score":0.9038643,"about_ca_system_score_codex":0.000017977713,"about_ca_system_score_gemma":0.0000354469,"threshold_uncertainty_score":0.6871825},"labels":[],"label_agreement":null},{"id":"W2059122500","doi":"10.1109/icdmw.2011.86","title":"FpMapViz: A Space-Filling Visualization for Frequent Patterns","year":2011,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Visualization; Computer science; Space (punctuation); Data visualization; Computer graphics (images); Artificial intelligence","score_opus":0.07326598480306931,"score_gpt":0.3143182927222915,"score_spread":0.2410523079192222,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059122500","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00071936124,0.000007996154,0.99477875,0.0001179175,0.00019178574,0.00013247841,0.0000093939,0.00019424933,0.0038480703],"genre_scores_gemma":[0.8275997,0.00003932597,0.16764362,0.002045153,0.00010262942,0.000017654407,0.00009621033,0.000022235212,0.0024334947],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992771,0.000018100065,0.00017305069,0.00023310629,0.00013156778,0.00016703189],"domain_scores_gemma":[0.9994414,0.000021410395,0.0000649328,0.00029594416,0.000105721614,0.00007059437],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015289722,0.000083824954,0.00008387447,0.000088131535,0.00007286217,0.000109076245,0.00038867732,0.000033248143,0.00015440912],"category_scores_gemma":[0.00003303204,0.000073369556,0.000045528355,0.00019701142,0.000009343292,0.00041519004,0.00008635454,0.000021339405,0.000048343452],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001203985,0.00006139797,0.0015911347,0.000016086027,0.000009201977,0.0000010687478,0.00079660496,0.000009895518,0.00010428611,0.99333674,0.001838824,0.0022335593],"study_design_scores_gemma":[0.000538642,0.00014215554,0.0010710846,0.00003396631,0.0000152415505,0.000004035176,0.00020325033,0.9413353,0.020255592,0.013209409,0.022828951,0.0003623453],"about_ca_topic_score_codex":0.000045340585,"about_ca_topic_score_gemma":0.00002238531,"teacher_disagreement_score":0.98012733,"about_ca_system_score_codex":0.000016216918,"about_ca_system_score_gemma":0.000024085939,"threshold_uncertainty_score":0.29919234},"labels":[],"label_agreement":null},{"id":"W2060381149","doi":"10.1109/pacificvis.2013.6596149","title":"A generative layout approach for rooted tree drawings","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Generative grammar; Tree (set theory); Generative Design; Computer graphics (images); Engineering drawing; Theoretical computer science; Artificial intelligence; Mathematics; Combinatorics; Engineering","score_opus":0.031698141777737124,"score_gpt":0.28303185886069654,"score_spread":0.25133371708295943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060381149","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002928954,0.0000062405393,0.9789822,0.00074088585,0.000038232363,0.00020005442,0.0000028604911,0.00012356478,0.01961304],"genre_scores_gemma":[0.084204875,0.0000013364553,0.89757836,0.0031306746,0.00006973006,0.00006719386,0.000074208125,0.000008012478,0.014865622],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99941707,0.000015033188,0.0001153733,0.00021225259,0.00010096862,0.00013931865],"domain_scores_gemma":[0.999528,0.000021345879,0.000032884873,0.00024649428,0.00010984683,0.000061432074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000074224205,0.00006993549,0.00008215678,0.00004787404,0.0000727867,0.0003069252,0.0004060868,0.000027220653,0.000053214735],"category_scores_gemma":[0.00002877761,0.00005326799,0.000036894548,0.00020504605,0.000015538031,0.0005002701,0.00009320095,0.000024588036,0.000074258474],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.6643084e-7,0.00010810935,0.00013574946,0.000010566066,0.000022137488,2.64942e-7,0.000742799,0.00015666471,0.00076983514,0.8571852,0.12440936,0.01645857],"study_design_scores_gemma":[0.00021034255,0.000026002712,0.00013516514,0.0000011309464,0.0000024123665,8.1099745e-7,0.000056140787,0.98987687,0.00097451353,0.0031523725,0.0054696244,0.00009459278],"about_ca_topic_score_codex":0.000029678802,"about_ca_topic_score_gemma":0.000004495572,"teacher_disagreement_score":0.9897202,"about_ca_system_score_codex":0.000009465859,"about_ca_system_score_gemma":0.00002436229,"threshold_uncertainty_score":0.29596868},"labels":[],"label_agreement":null},{"id":"W2060438784","doi":"10.1109/cscwd.2014.6846915","title":"Designing portable solutions to support collaborative workflow in long-term care: A five point strategy","year":2014,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; Ontario College of Art and Design; University of Toronto","funders":"","keywords":"Workflow; Documentation; Context (archaeology); Computer science; Analytics; Interface (matter); Information sharing; Health care; Long-term care; Process management; Knowledge management; Nursing; World Wide Web; Data science; Medicine; Business; Database","score_opus":0.03545778115799653,"score_gpt":0.3250883611348909,"score_spread":0.2896305799768944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060438784","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00059179956,0.00008241527,0.99037904,0.00045712016,0.0003787523,0.00062235235,0.00007557295,0.00018736742,0.0072256136],"genre_scores_gemma":[0.78459173,0.000113747934,0.20420788,0.0025337422,0.0001914602,0.00021039754,0.0014480497,0.00005518807,0.006647799],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973946,0.00016423901,0.00060321396,0.00091177295,0.00038525707,0.00054089347],"domain_scores_gemma":[0.9979168,0.000065403125,0.00022321484,0.001019509,0.0005101102,0.000264942],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00051251776,0.00033542237,0.00046147662,0.00043510503,0.00013455215,0.0008499196,0.0013326224,0.00021488489,0.00017678279],"category_scores_gemma":[0.00008663399,0.00033768814,0.00008299104,0.0010764694,0.000038550395,0.0003982497,0.00183537,0.0003623816,0.00016553058],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004293589,0.0008883624,0.014603275,0.00090288214,0.00035066405,0.0007100898,0.026842253,0.45740876,0.00024250294,0.27511686,0.16615014,0.0567413],"study_design_scores_gemma":[0.0047209132,0.002399762,0.032669492,0.0040255478,0.00030304163,0.0000670123,0.0080481125,0.8984601,0.0056929286,0.025152521,0.009844112,0.008616482],"about_ca_topic_score_codex":0.00019468422,"about_ca_topic_score_gemma":0.0016470223,"teacher_disagreement_score":0.78617114,"about_ca_system_score_codex":0.00023975412,"about_ca_system_score_gemma":0.0012919125,"threshold_uncertainty_score":0.9999075},"labels":[],"label_agreement":null},{"id":"W2062065656","doi":"10.1145/1385569.1385602","title":"Exploring the role of individual differences in information visualization","year":2008,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":99,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visualization; Computer science; Information visualization; Data visualization; Data science; Human–computer interaction; Artificial intelligence","score_opus":0.09278469560417973,"score_gpt":0.2767681242395295,"score_spread":0.18398342863534978,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062065656","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.45699283,0.000014435627,0.53924406,0.0001043126,0.0000830735,0.00007878031,0.000002791705,0.000058648562,0.003421076],"genre_scores_gemma":[0.99904245,0.00006553014,0.0007124003,0.00013695544,0.0000065553827,0.000004477559,0.00001229082,9.2387387e-7,0.000018395009],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99943197,0.000027853677,0.00019016358,0.00005153521,0.0002321545,0.0000663015],"domain_scores_gemma":[0.9997148,0.00003106676,0.00006137939,0.00013645587,0.00004173239,0.000014597509],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014037348,0.000038632596,0.000055483146,0.00012044123,0.000049852602,0.000051590283,0.00040614596,0.000010083701,0.000008240906],"category_scores_gemma":[0.00003795733,0.000025519174,0.000011943471,0.00050116034,0.000023644454,0.001946838,0.00010873247,0.000025750942,0.000011152657],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001191,0.000049771268,0.067951284,0.0000063187254,0.000006182406,3.1779012e-7,0.013846353,0.00011647096,0.00003402571,0.8793901,0.00016203648,0.03843596],"study_design_scores_gemma":[0.0003348211,0.000057799523,0.4883937,0.00002380907,0.000003615091,0.0000057224265,0.0024793902,0.49351755,0.0070672464,0.0026658776,0.0052757906,0.00017470046],"about_ca_topic_score_codex":0.000030552746,"about_ca_topic_score_gemma":0.000007857488,"teacher_disagreement_score":0.87672424,"about_ca_system_score_codex":0.0000051927445,"about_ca_system_score_gemma":0.00002411669,"threshold_uncertainty_score":0.14114106},"labels":[],"label_agreement":null},{"id":"W2062196104","doi":"10.1016/j.displa.2005.02.002","title":"Compressed file length predicts search time and errors on visual displays","year":2005,"lang":"en","type":"article","venue":"Displays","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":66,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada; McGill University","funders":"","keywords":"Computer science; Bitmap; Lossless compression; File size; Chart; Visual search; Overlay; Measure (data warehouse); Computer graphics (images); Algorithm; Artificial intelligence; Data compression; Mathematics; Data mining; Statistics","score_opus":0.015483533462355637,"score_gpt":0.28925874921557915,"score_spread":0.2737752157532235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062196104","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5445105,0.0002542528,0.37337407,0.007389677,0.00070011185,0.0012821777,0.0040486967,0.0015002678,0.06694024],"genre_scores_gemma":[0.9914606,0.00002312775,0.0023418218,0.0012417517,0.0001564292,0.0000088429115,0.0006351205,0.000020608706,0.004111699],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986876,0.00006012695,0.00018878559,0.00039115656,0.00037395096,0.000298376],"domain_scores_gemma":[0.9992,0.00014075833,0.000047855614,0.0003747186,0.00004543859,0.00019121755],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00015335302,0.00015528542,0.00015782323,0.00011093671,0.00016333484,0.00020851058,0.0005023646,0.000058461857,0.00058596104],"category_scores_gemma":[0.00004459722,0.00013843579,0.000037219124,0.00026351493,0.0000675929,0.0004657006,0.00027258915,0.00013127063,0.00084354565],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009684281,0.002224027,0.003407129,0.00014813367,0.00017777554,0.000098494704,0.004216178,0.011038849,0.0043470464,0.20192768,0.70271903,0.06959885],"study_design_scores_gemma":[0.00040904272,0.00012167878,0.0068726055,0.000037983213,0.0000066106736,0.0000061331175,0.000018400206,0.966024,0.00093982334,0.00004174581,0.02533436,0.00018763808],"about_ca_topic_score_codex":0.0000100542875,"about_ca_topic_score_gemma":0.000007545542,"teacher_disagreement_score":0.95498514,"about_ca_system_score_codex":0.000025667614,"about_ca_system_score_gemma":0.00003817607,"threshold_uncertainty_score":0.99993443},"labels":[],"label_agreement":null},{"id":"W2062422175","doi":"10.1109/hicss.2012.57","title":"A Focus + Context Technique for Visualizing a Document Collection","year":2012,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Zoom; Computer science; Focus (optics); Visualization; Context (archaeology); Visibility; Visual analytics; Information retrieval; Data visualization; Data collection; World Wide Web; Data science; Artificial intelligence","score_opus":0.03192516991094233,"score_gpt":0.34059943193741,"score_spread":0.30867426202646764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062422175","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00004172899,0.000044536147,0.99571717,0.00042809354,0.00015699395,0.00033021628,0.0000014241376,0.00014997716,0.003129866],"genre_scores_gemma":[0.8650193,0.000011536043,0.12983945,0.0011942731,0.00009112962,0.00019104479,0.000007541161,0.000009087366,0.0036366433],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994021,0.000024057994,0.00014139057,0.00012820338,0.00010748801,0.00019676358],"domain_scores_gemma":[0.9995785,0.00004577889,0.00004759602,0.00018564865,0.00006459774,0.00007787632],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034404531,0.00006650119,0.00007840469,0.00008705701,0.000105722946,0.00011813311,0.00020947827,0.000032113312,0.000036031073],"category_scores_gemma":[0.000041347525,0.000057566525,0.000040397597,0.00030056573,0.00000917479,0.00060773327,0.000083189465,0.000024612702,0.000027910886],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000024824276,0.000068504036,0.00017181112,0.000008943306,0.000009628213,1.3387165e-7,0.00032878487,7.8814145e-7,0.0016564694,0.9650038,0.023963094,0.008785557],"study_design_scores_gemma":[0.0010929474,0.00028620535,0.00013769366,0.00004128622,0.000021609565,0.000031070307,0.0003638455,0.06489383,0.32206216,0.01623968,0.59431213,0.00051750155],"about_ca_topic_score_codex":0.000031007792,"about_ca_topic_score_gemma":0.000012771676,"teacher_disagreement_score":0.94876415,"about_ca_system_score_codex":0.0000461297,"about_ca_system_score_gemma":0.000027123375,"threshold_uncertainty_score":0.23474947},"labels":[],"label_agreement":null},{"id":"W2063177175","doi":"10.1177/1473871611433710","title":"Exploring how and why people use visualizations in casual contexts: Modeling user goals and regulated motivations","year":2012,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Casual; Artifact (error); Visualization; Computer science; Human–computer interaction; Duration (music); Data visualization; Usability; Data science; Cognition; Artificial intelligence; Psychology","score_opus":0.09451377455360013,"score_gpt":0.30287932840523496,"score_spread":0.20836555385163483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063177175","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21672307,0.000037829006,0.7823254,0.00029055946,0.0001403892,0.00024899992,0.000015287766,0.00016989496,0.000048565227],"genre_scores_gemma":[0.9956765,0.00029230607,0.0026436446,0.0007902362,0.000038117014,0.000042185646,0.00045611104,0.000015021357,0.000045846806],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99848783,0.00011970996,0.00055401505,0.00019470295,0.00032969634,0.00031401988],"domain_scores_gemma":[0.99891174,0.000100797995,0.00021864011,0.00026711586,0.00033542997,0.00016629999],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00046421835,0.00019442142,0.00020165503,0.00071302755,0.00025976487,0.0010311162,0.00016509803,0.00008979305,0.000007768441],"category_scores_gemma":[0.0005399427,0.00020701635,0.000022963226,0.0013909078,0.00003227571,0.028793406,0.00017892646,0.0000822882,0.000009231204],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007709013,0.00012609363,0.090659454,0.00010333235,0.000025761696,3.8560378e-7,0.023817472,0.012161268,0.0001346528,0.8695067,0.0007109661,0.0027462153],"study_design_scores_gemma":[0.0005661586,0.00001936481,0.027984325,0.000066834786,0.000011480096,0.000008593876,0.0009746879,0.96521443,0.00015191919,0.00015269282,0.004580819,0.000268685],"about_ca_topic_score_codex":0.00010348984,"about_ca_topic_score_gemma":0.000065194086,"teacher_disagreement_score":0.9530532,"about_ca_system_score_codex":0.00006873353,"about_ca_system_score_gemma":0.000038095823,"threshold_uncertainty_score":0.9943077},"labels":[],"label_agreement":null},{"id":"W2063763232","doi":"10.1177/154193120304701314","title":"Judgments of Proportion with Graphs: Object-Based Advantages","year":2003,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Bar (unit); Object (grammar); Bar chart; Graph; Error bar; Mathematics; Computer science; Artificial intelligence; Statistics; Geology; Combinatorics","score_opus":0.013534949805159796,"score_gpt":0.24371734817919705,"score_spread":0.23018239837403726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063763232","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9982745,0.000026371927,0.0010037682,0.000026504944,0.000038294766,0.00011074006,0.000011769268,0.00002556628,0.00048249456],"genre_scores_gemma":[0.9940114,0.00002098218,0.005850336,0.000058615988,0.0000059850313,0.0000019099223,0.000002580605,0.000007296959,0.000040902934],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991942,0.000006784044,0.00026694467,0.0002094308,0.00017420945,0.0001483979],"domain_scores_gemma":[0.9991968,0.000020741345,0.00044510604,0.00009608447,0.00019820615,0.0000430183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031528386,0.00012434674,0.00017208704,0.000034095538,0.00022894675,0.00006696626,0.0003224222,0.000044104676,0.0000012599256],"category_scores_gemma":[0.000043476277,0.00008288448,0.000095911026,0.00022029903,0.00013411183,0.00040439537,0.0000974855,0.00007994505,8.5488224e-8],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018324923,0.0002557702,0.77668434,0.0005422794,0.00013569205,7.632554e-8,0.010483804,0.00021683816,0.017595658,0.19283216,0.0010126807,0.00022240025],"study_design_scores_gemma":[0.0035403976,0.0011319086,0.14999646,0.0014414621,0.00027920966,0.000007575234,0.04202223,0.019323211,0.7683925,0.009034072,0.0032377127,0.0015932894],"about_ca_topic_score_codex":0.000014456942,"about_ca_topic_score_gemma":0.0000017389598,"teacher_disagreement_score":0.75079685,"about_ca_system_score_codex":0.00002026425,"about_ca_system_score_gemma":0.00003410081,"threshold_uncertainty_score":0.3379931},"labels":[],"label_agreement":null},{"id":"W2064468319","doi":"10.1177/154193120204602103","title":"Human-Computer Interaction as Cognitive Science","year":2002,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Cognition; Cognitive science; Computer science; Human–computer interaction; Data science; Psychology; Neuroscience","score_opus":0.028240759440191786,"score_gpt":0.2824295005622129,"score_spread":0.2541887411220211,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064468319","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9965528,0.000018335706,0.00050239,0.00008925042,0.00016135318,0.00008906753,0.00000708593,0.000053956428,0.0025257652],"genre_scores_gemma":[0.9982862,0.000020997833,0.0011743789,0.00022447617,0.0000862974,0.0000015294745,0.0000011360537,0.000007347541,0.00019765017],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989084,0.0000051803436,0.00027127913,0.00035917404,0.00022085769,0.00023512566],"domain_scores_gemma":[0.99915284,0.000036039095,0.00031833677,0.00009452443,0.00031788333,0.000080396785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037639693,0.00014770988,0.00015870905,0.000058839527,0.0009438497,0.0004212672,0.00074735936,0.000050822422,0.000009240628],"category_scores_gemma":[0.00006703711,0.000114107126,0.00011767001,0.00034084643,0.00034606125,0.0014319721,0.0007511269,0.00016496131,0.0000034014029],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014597379,0.0008294923,0.10912734,0.00049438066,0.00034573983,5.954067e-7,0.22043855,0.00016028622,0.07889228,0.5551231,0.023914235,0.010659404],"study_design_scores_gemma":[0.0034600717,0.0012575964,0.12713218,0.0022730546,0.00029205845,0.000058883303,0.08983815,0.532402,0.21991955,0.012175118,0.007891289,0.0033000757],"about_ca_topic_score_codex":0.00003292757,"about_ca_topic_score_gemma":0.0000010576928,"teacher_disagreement_score":0.54294795,"about_ca_system_score_codex":0.00005564866,"about_ca_system_score_gemma":0.000013262189,"threshold_uncertainty_score":0.72594243},"labels":[],"label_agreement":null},{"id":"W2064858495","doi":"10.1145/1368044.1368053","title":"A syntactic analysis of accessibility to a corpus of statistical graphs","year":2008,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Statistics Canada; Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Object (grammar); Field (mathematics); Artificial intelligence; Natural language processing; Theoretical computer science; Mathematics","score_opus":0.03925609958547774,"score_gpt":0.34775825977793584,"score_spread":0.30850216019245813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064858495","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10658001,0.0000035691119,0.8925542,0.000048037557,0.000019420504,0.00003638561,0.0000359588,0.00002082442,0.00070159836],"genre_scores_gemma":[0.9605591,0.0000060004386,0.039173078,0.00016258501,0.0000011851075,8.3584854e-7,0.000010605997,0.0000013660346,0.00008522737],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991501,0.00004047006,0.0002868947,0.00019045781,0.00024671236,0.000085350664],"domain_scores_gemma":[0.99911,0.00012901158,0.00008521769,0.00045070428,0.00014031208,0.00008474625],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014653946,0.000050345247,0.00022740084,0.00031186454,0.000023026898,0.000014041102,0.000422699,0.00001635883,0.00014252914],"category_scores_gemma":[0.00018534598,0.00004125492,0.000064389475,0.0025010626,0.000052052066,0.00016050682,0.00013571717,0.000021756658,0.000005703946],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012801985,0.0004963156,0.18589011,0.00002915508,0.0004298059,0.000012148855,0.00062378054,0.00045860233,0.0006657642,0.80660766,0.0014934418,0.0032803928],"study_design_scores_gemma":[0.0001726537,0.00011978415,0.4891155,0.0000064226206,0.00021926903,0.0000028751413,0.000030475034,0.504776,0.0030247788,0.002222997,0.00017209639,0.0001371513],"about_ca_topic_score_codex":0.00014261849,"about_ca_topic_score_gemma":0.00005411787,"teacher_disagreement_score":0.8539791,"about_ca_system_score_codex":0.000007777019,"about_ca_system_score_gemma":0.000051272105,"threshold_uncertainty_score":0.16823268},"labels":[],"label_agreement":null},{"id":"W2065140130","doi":"10.1109/hicss.2012.583","title":"The Role of Social Interaction Filter and Visualization in Casual Browsing","year":2012,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; MacEwan University","funders":"","keywords":"Visualization; Casual; Filter (signal processing); Computer science; Information visualization; Human–computer interaction; Social relation; Feature (linguistics); Data visualization; World Wide Web; Multimedia; Artificial intelligence; Psychology; Computer vision; Social psychology","score_opus":0.024740211478249414,"score_gpt":0.330273304372709,"score_spread":0.3055330928944596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065140130","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17564844,0.00018019977,0.80983794,0.0004921456,0.00038646406,0.00011898958,0.000002224316,0.00006763723,0.01326598],"genre_scores_gemma":[0.99934745,0.000008520935,0.0003978785,0.0000861477,0.000032541917,6.515927e-7,0.0000033037365,0.0000018644316,0.0001216366],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996326,0.00003861764,0.00011326358,0.000054105898,0.00007870988,0.000082681756],"domain_scores_gemma":[0.99981636,0.000037348782,0.000045274806,0.0000595283,0.000024935925,0.000016565706],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018769821,0.000030858533,0.000038850598,0.000042869327,0.0000629142,0.00006828484,0.000087664914,0.000016715167,0.000009816287],"category_scores_gemma":[0.000023979886,0.00002233506,0.000008814146,0.00015739228,0.000017712162,0.00056666427,0.00007179714,0.000023234717,0.0000033450199],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002814896,0.000053868807,0.014655088,0.0000045109546,0.000004400087,8.176785e-8,0.0038995622,0.0000054512,0.0012380466,0.930532,0.0004613379,0.049142882],"study_design_scores_gemma":[0.00039035873,0.000037460708,0.04331909,0.00001887437,0.00000726506,0.00000889399,0.0034282827,0.85249174,0.016853692,0.0028649205,0.08037885,0.00020058246],"about_ca_topic_score_codex":0.000022241045,"about_ca_topic_score_gemma":0.00002736056,"teacher_disagreement_score":0.927667,"about_ca_system_score_codex":0.000010195659,"about_ca_system_score_gemma":0.0000067566134,"threshold_uncertainty_score":0.091079734},"labels":[],"label_agreement":null},{"id":"W2065488074","doi":"10.1109/tvcg.2014.2346250","title":"DimpVis: Exploring Time-varying Information Visualizations by Direct Manipulation","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":75,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Visualization; Dimension (graph theory); Data visualization; Variety (cybernetics); Path (computing); Human–computer interaction; Artificial intelligence; Computer vision","score_opus":0.02677131602771091,"score_gpt":0.26381687341725346,"score_spread":0.23704555738954255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065488074","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011240585,0.000014563395,0.9969433,0.00007826469,0.00054688967,0.00021505918,0.000026153955,0.0006601285,0.0003916036],"genre_scores_gemma":[0.9927186,0.00044312383,0.0024774605,0.003617512,0.00009949043,0.000068847046,0.00035029475,0.000043338096,0.00018138433],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980497,0.00020752674,0.0005605012,0.00042462916,0.00047622903,0.0002814167],"domain_scores_gemma":[0.9988018,0.00014045667,0.00020235321,0.00043544592,0.0002317205,0.0001882155],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00034505545,0.00028900258,0.00024999032,0.0006607465,0.00062913215,0.0007385265,0.0003570821,0.00011983844,0.00002567653],"category_scores_gemma":[0.000010782733,0.00030896513,0.000089242705,0.0013616758,0.00005859969,0.0031115904,0.000013437324,0.00014395124,0.00007343546],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013822362,0.00034530487,0.0000987399,0.000084378116,0.00010039409,6.3517257e-7,0.0016508787,0.008589239,0.00008034708,0.94799614,0.0030057032,0.038034443],"study_design_scores_gemma":[0.00052478164,0.00015350929,0.00008044169,0.000056035697,0.00003250367,0.000005392642,0.000014785726,0.9831691,0.001518571,0.0003851501,0.01370278,0.00035698572],"about_ca_topic_score_codex":0.000014301346,"about_ca_topic_score_gemma":0.0000029439648,"teacher_disagreement_score":0.9944658,"about_ca_system_score_codex":0.00003717377,"about_ca_system_score_gemma":0.000027682036,"threshold_uncertainty_score":0.9999362},"labels":[],"label_agreement":null},{"id":"W2065598197","doi":"10.1177/0272989x0002000208","title":"Perception of Quantitative Information for Treatment Decisions","year":2000,"lang":"en","type":"article","venue":"Medical Decision Making","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":186,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Context (archaeology); Task (project management); Computer science; Perception; Statistics; Artificial intelligence; Mathematics; Psychology; Engineering","score_opus":0.05602459499976107,"score_gpt":0.40357311940104107,"score_spread":0.34754852440128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065598197","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013397969,0.000012920591,0.98519766,0.0002479816,0.0001132214,0.00012589166,0.00001499156,0.000038102262,0.00085128576],"genre_scores_gemma":[0.5622453,0.00023820011,0.4364512,0.0008331921,0.0000339519,0.000015792471,0.00005128346,0.000005167935,0.00012591363],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99870896,0.000031667485,0.00041756665,0.0001355913,0.00058937917,0.00011681166],"domain_scores_gemma":[0.9986587,0.0007968929,0.00008579639,0.00025119566,0.00012404699,0.00008337075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039933212,0.00007422993,0.00014722554,0.00013955629,0.000091394504,0.00007143749,0.00038183157,0.00006124837,0.00084038626],"category_scores_gemma":[0.0011684254,0.00005490231,0.00007561613,0.00032109453,0.000031613028,0.00062701904,0.000047115434,0.000025564163,0.00015029417],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020423735,0.0000479037,0.000025712068,0.000002380937,0.000004683886,6.8319156e-7,0.0004951944,0.00019298418,0.0000060336183,0.029321117,0.0012756223,0.96860725],"study_design_scores_gemma":[0.00075848517,0.00034534265,0.0010359553,0.00019808768,0.000008217024,0.0000055470864,0.0002130796,0.9123156,0.000019817826,0.011521142,0.073482916,0.0000957883],"about_ca_topic_score_codex":0.00000430837,"about_ca_topic_score_gemma":0.0000036666272,"teacher_disagreement_score":0.96851146,"about_ca_system_score_codex":0.000039222068,"about_ca_system_score_gemma":0.00007471088,"threshold_uncertainty_score":0.92016405},"labels":[],"label_agreement":null},{"id":"W2066568783","doi":"10.1145/2732158.2732160","title":"Visual Text Analytics for Asynchronous Online Conversations","year":2015,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Asynchronous communication; Visual analytics; Analytics; Visualization; Human–computer interaction; World Wide Web; Data science; Artificial intelligence","score_opus":0.0649670839174645,"score_gpt":0.353723982909995,"score_spread":0.28875689899253054,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066568783","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004163642,0.000014393225,0.9956169,0.0016422732,0.00018618474,0.00009724366,0.000027935883,0.00014871125,0.0018499611],"genre_scores_gemma":[0.61765844,0.000021421198,0.365796,0.006987783,0.0003189839,0.000010816895,0.00058978033,0.000022633922,0.008594123],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999296,0.000015273758,0.00017444127,0.00018998486,0.00017289862,0.00015141837],"domain_scores_gemma":[0.9992131,0.00005637256,0.000051693332,0.0002611865,0.0002589653,0.0001586778],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016118538,0.000076171425,0.000098948316,0.00009217116,0.00005494672,0.00014561025,0.0003837388,0.000032649048,0.00003189521],"category_scores_gemma":[0.00014298028,0.000067938665,0.000040922838,0.00033579496,0.000026684063,0.0003467938,0.00010880857,0.000031438267,0.00010276957],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000056691106,0.00058695767,0.0011551252,0.000021721673,0.000062133004,0.0000037122659,0.00061289006,0.0017515637,0.000036215,0.8412416,0.13339311,0.021129334],"study_design_scores_gemma":[0.00045734475,0.00010067757,0.000096889875,0.000002242325,0.000009949633,0.0000022495278,0.00018083764,0.92533726,0.00013694543,0.0017344152,0.07183414,0.00010708025],"about_ca_topic_score_codex":0.000018591521,"about_ca_topic_score_gemma":0.000045464152,"teacher_disagreement_score":0.92358565,"about_ca_system_score_codex":0.000042511947,"about_ca_system_score_gemma":0.00018803262,"threshold_uncertainty_score":0.27704585},"labels":[],"label_agreement":null},{"id":"W2068562326","doi":"10.1109/tvcg.2012.229","title":"Graphical Overlays: Using Layered Elements to Aid Chart Reading","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":102,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Overlay; Computer science; Bitmap; Bar chart; Pie chart; Visualization; Chart; Context (archaeology); Data visualization; Reading (process); Graphical user interface; Data mining; Information retrieval; Artificial intelligence; Programming language","score_opus":0.0414411278657241,"score_gpt":0.322433338182983,"score_spread":0.28099221031725885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068562326","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011506343,0.000018305711,0.98690796,0.000068969486,0.0009777248,0.0002090145,0.000019033258,0.00025170113,0.000040925457],"genre_scores_gemma":[0.98449045,0.000116882125,0.010366383,0.004764822,0.00014668982,0.000012521981,0.000017901066,0.00002986082,0.000054503736],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981631,0.00013069186,0.00042886785,0.00042450058,0.00043428948,0.00041857202],"domain_scores_gemma":[0.99890566,0.00005557771,0.00010706424,0.00039933826,0.00013399475,0.00039839427],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00034992018,0.00024786018,0.0002229953,0.0006900052,0.00042077314,0.000302369,0.00033738528,0.00011197874,0.000023877652],"category_scores_gemma":[0.000004681712,0.00025764626,0.00009418073,0.0016010375,0.000045179873,0.0009095379,0.000015969417,0.00015138042,0.000024409437],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015633812,0.0005706231,0.0015335704,0.000036189747,0.00008685751,0.0000023969862,0.0014479422,0.0008639983,0.00021667051,0.9891412,0.0007751939,0.0053097107],"study_design_scores_gemma":[0.00049187907,0.00014406172,0.00044554085,0.000060668546,0.00002852126,0.000020112406,0.000037444002,0.9901781,0.0015055707,0.00023575142,0.0064888885,0.00036347372],"about_ca_topic_score_codex":0.000011676092,"about_ca_topic_score_gemma":0.000004807304,"teacher_disagreement_score":0.9893141,"about_ca_system_score_codex":0.000036122296,"about_ca_system_score_gemma":0.00002990437,"threshold_uncertainty_score":0.9999876},"labels":[],"label_agreement":null},{"id":"W2068589268","doi":"10.5210/ojphi.v5i3.4933","title":"The Challenge of Big Data in Public Helth: An Opportunity for Visual Analytics","year":2014,"lang":"en","type":"article","venue":"Online Journal of Public Health Informatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":77,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Big data; Variety (cybernetics); Data science; Computer science; Analytics; Visual analytics; Cognition; Work (physics); Cultural analytics; Visualization; Knowledge management; World Wide Web; Artificial intelligence; Psychology; The Internet; Data mining; Engineering; Semantic analytics","score_opus":0.3574789185532871,"score_gpt":0.43813273868802366,"score_spread":0.08065382013473654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068589268","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015496215,0.00008606604,0.95843095,0.038880315,0.00049702305,0.00016038802,0.0001435548,0.000017423532,0.00023466835],"genre_scores_gemma":[0.73874,0.007918829,0.2345875,0.015165536,0.0017800666,0.0000049821438,0.0016168249,0.000056645924,0.00012957078],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9955068,0.0003548038,0.0027719804,0.000111410736,0.0007389585,0.0005160109],"domain_scores_gemma":[0.99392915,0.00045593735,0.0026626466,0.0011552594,0.0010520192,0.000745013],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.016756792,0.00014679227,0.00045474098,0.0005569953,0.00019219423,0.00038279092,0.0031584075,0.00007679951,0.000003240699],"category_scores_gemma":[0.0047838013,0.000102242026,0.0000669511,0.0008667788,0.00008456674,0.0029451575,0.00050285977,0.0003323546,9.760994e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000049895584,0.0008554445,0.000471182,0.00029766292,0.00004144501,6.3558554e-7,0.0015421588,0.00007736511,2.7457872e-7,0.11051636,0.003883373,0.8823091],"study_design_scores_gemma":[0.00055175374,0.0006001628,0.00024656768,0.000037467966,0.000003349878,0.000011422733,0.00095525733,0.6755628,5.4719555e-7,0.001279033,0.32067186,0.000079813704],"about_ca_topic_score_codex":0.0000109268485,"about_ca_topic_score_gemma":0.00029560376,"teacher_disagreement_score":0.88222927,"about_ca_system_score_codex":0.000093986964,"about_ca_system_score_gemma":0.0033413644,"threshold_uncertainty_score":0.5927437},"labels":[],"label_agreement":null},{"id":"W2068805774","doi":"10.1007/s00180-009-0170-z","title":"Commemorating William Playfair’s 250th birthday","year":2009,"lang":"en","type":"article","venue":"Computational Statistics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"University of Toronto; University of Missouri","keywords":"Statistician; Classics; Philosophy; Art; Mathematics; Statistics","score_opus":0.022327088015431755,"score_gpt":0.3074991009383399,"score_spread":0.2851720129229081,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068805774","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00013265264,0.000028189497,0.99677545,0.0009504773,0.00018902436,0.00007293343,0.00016950024,0.00018616798,0.0014956318],"genre_scores_gemma":[0.2769439,0.000008531365,0.71779776,0.0042978595,0.00009427531,0.000001499472,0.0005664213,0.000008637947,0.00028112813],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99871415,0.000053680422,0.0003248121,0.00027063815,0.00042207743,0.00021466598],"domain_scores_gemma":[0.99900186,0.0002492282,0.00013672537,0.00023767288,0.00024966442,0.00012483509],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016526322,0.00013961205,0.0001480282,0.00010155562,0.00022621195,0.00031424008,0.00053035165,0.000034840035,0.000037397844],"category_scores_gemma":[0.00014393179,0.00014264182,0.000028229833,0.0004268024,0.00003998074,0.00034135266,0.000085302854,0.00010426806,0.00014924971],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001311521,0.00007634817,0.00019529503,0.000005852143,0.00000819579,0.000017775417,0.00017554256,0.03231336,0.0000065356835,0.88091767,0.052778065,0.033504054],"study_design_scores_gemma":[0.00026717802,0.00007891194,0.0061665447,0.000011449423,0.0000045100205,0.000011722741,0.000010849475,0.83136034,0.000012557648,0.14970404,0.012190833,0.00018107455],"about_ca_topic_score_codex":0.0000022703473,"about_ca_topic_score_gemma":0.000002291092,"teacher_disagreement_score":0.799047,"about_ca_system_score_codex":0.000040508407,"about_ca_system_score_gemma":0.00011084569,"threshold_uncertainty_score":0.5816764},"labels":[],"label_agreement":null},{"id":"W2068963126","doi":"10.1109/tvcg.2014.2346922","title":"#FluxFlow: Visual Analysis of Anomalous Information Spreading on Social Media","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":182,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Social media; Misinformation; Interactive visual analysis; Data science; Visualization; Set (abstract data type); Data visualization; Visual analytics; Information visualization; Domain (mathematical analysis); Anomaly detection; World Wide Web; Microblogging; Crowd psychology; Information retrieval; Human–computer interaction; Data mining; Artificial intelligence; Computer security","score_opus":0.0176954374738774,"score_gpt":0.278173029808617,"score_spread":0.2604775923347396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068963126","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01671804,0.0000028396748,0.9824526,0.000039749488,0.00039912295,0.0000882498,0.000031641244,0.00016835348,0.00009940769],"genre_scores_gemma":[0.99762887,0.000052530388,0.00064957404,0.001493774,0.000050141083,0.0000054430516,0.00010058867,0.0000103471275,0.00000871409],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983566,0.00016091026,0.00051181903,0.00029663992,0.0004835219,0.00019050798],"domain_scores_gemma":[0.99893063,0.00023492902,0.00023027373,0.00026483083,0.00022971908,0.000109640925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031291618,0.00020506959,0.00033712192,0.001670115,0.00029682467,0.00024233342,0.00030262265,0.00012599102,0.000016757096],"category_scores_gemma":[0.00001233309,0.00020777527,0.00017164633,0.0028408475,0.00008230514,0.0007516071,0.000007801509,0.00012466077,0.000010600871],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018387065,0.00029009255,0.00014279905,0.000034172335,0.00028556495,4.5763042e-7,0.0024867845,0.0035563447,0.00000825189,0.9503454,0.0002462893,0.04258548],"study_design_scores_gemma":[0.0004366185,0.00016689327,0.002354359,0.000020338286,0.00017773002,0.0000012083404,0.00003891137,0.99471366,0.00058203225,0.00024036308,0.0010536032,0.00021425971],"about_ca_topic_score_codex":0.000009332436,"about_ca_topic_score_gemma":0.00001564857,"teacher_disagreement_score":0.99115735,"about_ca_system_score_codex":0.00002064532,"about_ca_system_score_gemma":0.000026695932,"threshold_uncertainty_score":0.847283},"labels":[],"label_agreement":null},{"id":"W2070528321","doi":"10.1145/1723028.1723083","title":"User interfaces for visual analysis and monitoring in business intelligence","year":2009,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Human–computer interaction; Business intelligence; Intelligence analysis; Knowledge management; Computer security","score_opus":0.029860481402326357,"score_gpt":0.35447883035153577,"score_spread":0.32461834894920943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070528321","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037374325,0.000026516236,0.9619156,0.00044211413,0.000048180966,0.00004384811,6.714207e-7,0.00003786209,0.000110899666],"genre_scores_gemma":[0.9678275,0.000053438045,0.031640768,0.00016120377,0.000017676228,0.0000015263956,0.0000027467772,0.0000015493663,0.00029362334],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994567,0.000010139464,0.00014922132,0.00019774275,0.00007740245,0.00010878232],"domain_scores_gemma":[0.999698,0.000038893886,0.000029005483,0.00012939206,0.00007123005,0.000033502904],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012923057,0.000060957187,0.00010786121,0.00026360078,0.000029019295,0.00019895918,0.00024853583,0.000020469904,0.000005166237],"category_scores_gemma":[0.00004129355,0.0000524302,0.000018262606,0.001448409,0.000010798128,0.00043105168,0.00006458536,0.000022479173,0.000002392392],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000195245,0.0004232281,0.15704581,0.00004496463,0.00016124123,0.000008617296,0.0015529711,0.006194457,0.0017665009,0.24027891,0.00036239988,0.5921414],"study_design_scores_gemma":[0.00011786096,0.00005609676,0.107465245,0.000020162044,0.000029544906,8.09685e-7,0.00015266963,0.8740066,0.015687607,0.0015003924,0.00078258157,0.00018041384],"about_ca_topic_score_codex":0.00003112441,"about_ca_topic_score_gemma":0.00002931842,"teacher_disagreement_score":0.9304531,"about_ca_system_score_codex":0.000009678259,"about_ca_system_score_gemma":0.000009923328,"threshold_uncertainty_score":0.21380416},"labels":[],"label_agreement":null},{"id":"W2070664725","doi":"10.1109/tvcg.2014.2346320","title":"Four Experiments on the Perception of Bar Charts","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":132,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"McGill University","keywords":"Bar chart; Bar (unit); Computer science; Chart; Pie chart; Perception; Ranking (information retrieval); Visualization; Artificial intelligence; Statistics; Mathematics; Psychology","score_opus":0.03604497504253758,"score_gpt":0.2931317659053733,"score_spread":0.25708679086283576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070664725","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010560929,0.000003714479,0.98845494,0.00019610873,0.0003931148,0.0001364342,0.0000060509064,0.00010370895,0.00014499611],"genre_scores_gemma":[0.99608713,0.000101846796,0.00058407045,0.0030746858,0.00004772881,0.000010953727,0.0000063839443,0.000012441818,0.00007477585],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99875134,0.00019172777,0.0002723336,0.00030143955,0.00034480664,0.00013834634],"domain_scores_gemma":[0.9991638,0.00011471191,0.000108607295,0.00041565511,0.00012016491,0.00007705504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027281357,0.00015596344,0.00014734945,0.00023895886,0.0002746147,0.00013953759,0.0003261676,0.000067664114,0.00003700961],"category_scores_gemma":[0.0000044743724,0.00012152031,0.00007649636,0.00048685164,0.00007964743,0.00023623416,0.000006119132,0.0001010744,0.00001971871],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006455241,0.00020751434,0.000031749845,0.000014309876,0.000023258193,2.9365953e-7,0.0008115731,0.0003970138,0.00008221692,0.9896407,0.0005939023,0.008190996],"study_design_scores_gemma":[0.00031866322,0.0002920632,0.00038915995,0.00004537632,0.000011215551,0.0000035524417,0.000047238365,0.9934875,0.002402916,0.00073854445,0.002114844,0.00014891944],"about_ca_topic_score_codex":0.0000052314253,"about_ca_topic_score_gemma":0.0000015610343,"teacher_disagreement_score":0.9930905,"about_ca_system_score_codex":0.000011288278,"about_ca_system_score_gemma":0.000014942941,"threshold_uncertainty_score":0.49554545},"labels":[],"label_agreement":null},{"id":"W2071947880","doi":"10.1145/1923947.1923963","title":"Left or right?","year":2010,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Visual field; Dashboard; Interface (matter); Field (mathematics); Human–computer interaction; Process (computing); Information processing; Computer vision; Artificial intelligence; Data science; Cognitive psychology; Psychology","score_opus":0.01875408630229577,"score_gpt":0.3065722550872553,"score_spread":0.2878181687849595,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071947880","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00085315463,6.121061e-7,0.933159,0.0009978235,0.00033868774,0.000017755394,7.880713e-7,0.00016304158,0.064469166],"genre_scores_gemma":[0.5754055,0.0000075568173,0.25460184,0.0076901284,0.00018489838,9.4868363e-7,0.000011565133,0.000008388973,0.16208917],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996934,0.0000043105715,0.000056726876,0.00009727224,0.00007902701,0.00006926109],"domain_scores_gemma":[0.99962497,0.000014308015,0.000011844643,0.0002787017,0.00002435058,0.000045818582],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000060290386,0.000030405923,0.000031326155,0.000026703394,0.000035999215,0.000121110905,0.0004180589,0.00001704927,0.0018840578],"category_scores_gemma":[0.00002427895,0.000018624332,0.000011005735,0.00009823041,0.000011975851,0.00024531552,0.00008803992,0.00004222289,0.00050297665],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.9951455e-7,0.000017308023,0.00018106736,8.9662757e-7,0.0000013973201,0.0000036982365,0.000032497006,4.9300843e-7,0.0005213108,0.96598685,0.02953165,0.003722607],"study_design_scores_gemma":[0.00009663426,0.0000136291355,0.0004174638,9.840761e-7,9.861113e-7,0.000015394735,0.0000041261974,0.12602659,0.004504448,0.0030138863,0.8658208,0.00008506331],"about_ca_topic_score_codex":0.000003927275,"about_ca_topic_score_gemma":0.00010298014,"teacher_disagreement_score":0.962973,"about_ca_system_score_codex":0.0000011962643,"about_ca_system_score_gemma":0.000025180707,"threshold_uncertainty_score":0.9990284},"labels":[],"label_agreement":null},{"id":"W2072566697","doi":"10.1109/vast.2010.5652879","title":"A closer look at note taking in the co-located collaborative visual analytics process","year":2010,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Visual analytics; Computer science; Analytics; Scope (computer science); Process (computing); Domain (mathematical analysis); Data science; Data analysis; Cultural analytics; Human–computer interaction; Visualization; World Wide Web; Semantic analytics; Data mining","score_opus":0.020559164561743438,"score_gpt":0.36352559518159633,"score_spread":0.3429664306198529,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072566697","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2246183,0.000018406994,0.73292387,0.003273686,0.00039409974,0.00063702377,0.000026943404,0.00029901296,0.03780868],"genre_scores_gemma":[0.9946033,0.000004417717,0.0020961454,0.0025542348,0.00004309543,0.0000073372466,0.000031304382,0.0000071381055,0.0006530417],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99880725,0.000071367715,0.00024176507,0.0002891674,0.00036613538,0.00022433804],"domain_scores_gemma":[0.9990924,0.00010290529,0.00013729854,0.0003840434,0.0002258403,0.00005750528],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045041388,0.00012483331,0.00013116273,0.00012819014,0.00014098875,0.00032939314,0.0009163035,0.00006847937,0.000114493436],"category_scores_gemma":[0.0001560263,0.000082980696,0.00002494001,0.0017213013,0.000077645396,0.0004257798,0.00013412787,0.00019688078,0.00012050675],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006437562,0.0017668355,0.07932355,0.00012433594,0.0000960603,0.00022884078,0.03652512,0.002092684,0.0106770415,0.8179064,0.03716669,0.014028066],"study_design_scores_gemma":[0.00052450213,0.00006504895,0.003441284,0.000013138101,0.0000103665325,0.000011549205,0.0006500855,0.97280765,0.0076623224,0.0009270603,0.013612946,0.00027402834],"about_ca_topic_score_codex":0.00001995352,"about_ca_topic_score_gemma":0.00088980346,"teacher_disagreement_score":0.970715,"about_ca_system_score_codex":0.000026117794,"about_ca_system_score_gemma":0.000178755,"threshold_uncertainty_score":0.33838546},"labels":[],"label_agreement":null},{"id":"W2072589092","doi":"10.1111/j.1467-8659.2008.01233.x","title":"Interactive Exploratory Visualization of 2D Vector Fields","year":2008,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Glyph (data visualization); Computer science; Visualization; Computer graphics (images); Animation; Set (abstract data type); Field (mathematics); Computer animation; Euclidean vector; Vector field; Artificial intelligence; Computer vision; Mathematics","score_opus":0.029469747615883286,"score_gpt":0.28776881194031645,"score_spread":0.25829906432443317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072589092","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006906149,0.000047757563,0.9917087,0.00024284255,0.00065334333,0.0000816055,0.000005908474,0.00013626527,0.00021743873],"genre_scores_gemma":[0.9921434,0.000105717205,0.006028823,0.001543728,0.000075396885,0.00000441394,0.000037640693,0.000011810219,0.00004905687],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99887943,0.000067097106,0.00030659774,0.00028071305,0.0002702607,0.00019590119],"domain_scores_gemma":[0.99896044,0.000073062336,0.00016838286,0.0004722643,0.00024494602,0.00008091686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011048449,0.0001319435,0.0001855131,0.0002803776,0.00012510661,0.000050090857,0.0006578925,0.00007368603,0.000010073797],"category_scores_gemma":[0.000021021558,0.00013063845,0.00009792144,0.0007955267,0.00008677664,0.00073849224,0.00034438292,0.00009964535,0.000017005414],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006486814,0.00022321897,0.004921182,0.000028468281,0.00005459894,0.000019006007,0.0023470074,0.00013337958,0.00006558048,0.9628703,0.0268654,0.002465346],"study_design_scores_gemma":[0.0006041531,0.00034681687,0.0040680766,0.00007329578,0.00001156705,0.00003318617,0.000071931914,0.96663,0.0042634886,0.0062178345,0.017283084,0.00039656257],"about_ca_topic_score_codex":0.0000064068413,"about_ca_topic_score_gemma":0.000007781761,"teacher_disagreement_score":0.98567986,"about_ca_system_score_codex":0.000013533396,"about_ca_system_score_gemma":0.00006378445,"threshold_uncertainty_score":0.53272814},"labels":[],"label_agreement":null},{"id":"W2073800769","doi":"10.1109/tvcg.2013.124","title":"A Multi-Level Typology of Abstract Visualization Tasks","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":756,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Visualization; Typology; Task (project management); Human–computer interaction; Domain (mathematical analysis); Information visualization; Data visualization; Interdependence; Data science; Scope (computer science); Task analysis; Artificial intelligence","score_opus":0.04654491311054944,"score_gpt":0.31370795271711455,"score_spread":0.2671630396065651,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2073800769","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004662497,0.00002340733,0.99421567,0.000064974505,0.00047015506,0.00027248045,0.000028615263,0.00020397874,0.00005823128],"genre_scores_gemma":[0.9902353,0.00028770385,0.007729546,0.0014731879,0.000035972684,0.000025457091,0.000042104315,0.000026245933,0.00014445081],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983369,0.00010788808,0.00054952275,0.00044756217,0.00031873005,0.0002393875],"domain_scores_gemma":[0.99871176,0.00009841492,0.00022855522,0.00041786185,0.0003896923,0.0001536951],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017987046,0.0002375738,0.0002707332,0.0005971082,0.00021075689,0.00020030612,0.00039222676,0.0001673912,0.00009451968],"category_scores_gemma":[0.0000069873695,0.00023537841,0.000097441196,0.0010594915,0.00013751027,0.00072728307,0.000011165218,0.00013488292,0.000039870534],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008116483,0.00090876257,0.00021441568,0.00009623218,0.0000965198,0.0000021298226,0.00097115745,0.0006732002,0.0003730213,0.9768182,0.0011708239,0.018667404],"study_design_scores_gemma":[0.00070274173,0.00019850086,0.0038447764,0.000045537636,0.000020924987,0.000010953781,0.000048775622,0.9909793,0.0027034122,0.0006157099,0.0005572788,0.00027205562],"about_ca_topic_score_codex":0.00006490198,"about_ca_topic_score_gemma":0.000025495276,"teacher_disagreement_score":0.99030614,"about_ca_system_score_codex":0.0000171422,"about_ca_system_score_gemma":0.000053864478,"threshold_uncertainty_score":0.9598453},"labels":[],"label_agreement":null},{"id":"W2073955455","doi":"10.1145/2460625.2460672","title":"C4","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Networks of Centres of Excellence of Canada; Natural Sciences and Engineering Research Council of Canada; Singapore-MIT Alliance for Research and Technology Centre; Alberta Innovates - Technology Futures","keywords":"Computer science; Interactivity; Human–computer interaction; Architecture; Multimedia; Graphics; Coding (social sciences); Class (philosophy); Programming language; Space (punctuation); Computer graphics (images); Artificial intelligence; Operating system","score_opus":0.019614551152414648,"score_gpt":0.27846661063619566,"score_spread":0.258852059483781,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2073955455","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00025540177,0.0000021878575,0.9264522,0.0011738606,0.000042511467,0.000015613696,8.166432e-8,0.00008984895,0.07196828],"genre_scores_gemma":[0.77692664,0.000008965928,0.14869231,0.012680064,0.00005110588,0.000005253604,0.0000054375505,0.0000041234407,0.06162607],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999811,0.0000037019897,0.000035361012,0.00005550448,0.00004820654,0.00004620333],"domain_scores_gemma":[0.99978817,0.0000049953765,0.0000062295567,0.00015076765,0.000022329716,0.00002749762],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000019109075,0.000016790706,0.000017474222,0.000015483061,0.000014461203,0.00011927013,0.00023098118,0.000005759945,0.00067660207],"category_scores_gemma":[0.000006222573,0.0000124830485,0.000006885286,0.0000966534,0.0000039503393,0.00032262682,0.00006349253,0.000008708498,0.0030067584],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.4061005e-9,0.0000076171386,0.00017912369,4.8525243e-7,8.5832306e-7,1.9699335e-7,0.000020174777,0.0000017386083,0.00006446348,0.8512022,0.13151112,0.017012015],"study_design_scores_gemma":[0.000087666165,0.000012531194,0.0030258044,0.0000015645835,5.706187e-7,0.0000020133666,0.000018291552,0.77089673,0.0011333732,0.015697652,0.20902468,0.000099109224],"about_ca_topic_score_codex":0.000014460607,"about_ca_topic_score_gemma":7.2664335e-7,"teacher_disagreement_score":0.83550453,"about_ca_system_score_codex":0.000001682057,"about_ca_system_score_gemma":0.0000051017696,"threshold_uncertainty_score":0.99776953},"labels":[],"label_agreement":null},{"id":"W2076425358","doi":"10.1109/tvcg.2014.2363828","title":"A Topologically-Informed Hyperstreamline Seeding Method for Alignment Tensor Fields","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Shared Hierarchical Academic Research Computing Network","keywords":"Visualization; Seeding; Glyph (data visualization); Tensor (intrinsic definition); Computer science; Degenerate energy levels; Domain (mathematical analysis); Liquid crystal; Orientation (vector space); Structure tensor; Field (mathematics); Algorithm; Physics; Artificial intelligence; Geometry; Mathematics; Optics; Image (mathematics); Mathematical analysis","score_opus":0.03088924450323353,"score_gpt":0.3260195099282029,"score_spread":0.29513026542496934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076425358","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0003045989,0.0000059958975,0.99827635,0.00033060779,0.0004727989,0.00023386502,0.0000143510715,0.00024304754,0.000118407836],"genre_scores_gemma":[0.8020065,0.0003427743,0.18002333,0.016717682,0.00024435125,0.000089100104,0.000067788045,0.000037812373,0.00047066834],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99870276,0.000089621855,0.00034101307,0.00040261733,0.00023459291,0.00022936214],"domain_scores_gemma":[0.9989746,0.00033168012,0.00010304902,0.00028871774,0.00015934094,0.00014259554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032821824,0.00019453157,0.00021952526,0.0002734125,0.00033141125,0.00024094239,0.00029780864,0.00013138488,0.000010565765],"category_scores_gemma":[0.000014735125,0.00017371024,0.00011113389,0.00047505816,0.000045798304,0.00027609846,0.000007907893,0.00009693557,0.0000039577744],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012130058,0.00015884945,0.000017016668,0.000039955554,0.000040165032,4.5781275e-7,0.0003945714,0.0017998043,0.000013131348,0.9672502,0.00068882544,0.02958484],"study_design_scores_gemma":[0.0007000222,0.00043070893,0.000028236753,0.000027136599,0.000027556722,0.000009331466,0.00003190437,0.98027253,0.0010577133,0.0017926955,0.015402131,0.00022005275],"about_ca_topic_score_codex":0.0000074994477,"about_ca_topic_score_gemma":0.000012845666,"teacher_disagreement_score":0.9784727,"about_ca_system_score_codex":0.000019751826,"about_ca_system_score_gemma":0.000029193983,"threshold_uncertainty_score":0.7083698},"labels":[],"label_agreement":null},{"id":"W2076489690","doi":"10.1117/12.704612","title":"Supporting interactive graph exploration using edge plucking","year":2007,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Enhanced Data Rates for GSM Evolution; Plucking; Readability; Graph drawing; Graph; Theoretical computer science; Human–computer interaction; Artificial intelligence; Programming language","score_opus":0.02532217844942639,"score_gpt":0.2967873761535007,"score_spread":0.2714651977040743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076489690","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92771286,0.00002879381,0.069407664,0.00078995543,0.00036428636,0.00031507039,0.000014448603,0.00012106707,0.0012458788],"genre_scores_gemma":[0.62128603,0.000038111964,0.37774715,0.00025737475,0.00046071678,0.00002568179,0.0000158903,0.00005160871,0.00011742055],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99753636,1.6258683e-8,0.0008665403,0.00042213075,0.00072026136,0.0004546871],"domain_scores_gemma":[0.997102,0.00016080309,0.0006864952,0.00007822265,0.0018408052,0.0001316436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013320246,0.00026583974,0.0003177593,0.00021958647,0.00013354351,0.00029797477,0.0013318375,0.00013264913,0.000005557249],"category_scores_gemma":[0.0006749587,0.00023784945,0.0004453961,0.0007230023,0.00012753684,0.0024280238,0.00033653236,0.00026286676,0.0000013930218],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025974594,0.00009560322,0.0003835911,0.00016489453,0.00019283133,2.0280133e-7,0.0007275931,0.00023543605,0.3005599,0.6958608,0.0009075329,0.000845621],"study_design_scores_gemma":[0.0011320964,0.00026247159,0.000496649,0.0005269638,0.00013955419,0.000032251177,0.0050901785,0.6371235,0.34308544,0.0077862325,0.0036670757,0.00065758335],"about_ca_topic_score_codex":0.000008262995,"about_ca_topic_score_gemma":2.6224527e-7,"teacher_disagreement_score":0.6880746,"about_ca_system_score_codex":0.00017059558,"about_ca_system_score_gemma":0.000042017815,"threshold_uncertainty_score":0.9699219},"labels":[],"label_agreement":null},{"id":"W2076538271","doi":"10.1145/2702613.2732840","title":"Atypical Visual Display for Monitoring Multiple CCTV Feeds","year":2015,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Workload; Human–computer interaction; Cognition; Key (lock); Visual search; Computer security; Artificial intelligence; Psychology","score_opus":0.06753360546717804,"score_gpt":0.361964095487697,"score_spread":0.2944304900205189,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076538271","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009474898,0.000010611045,0.9888015,0.00030878183,0.0004886449,0.00007952487,0.000003092873,0.00021117336,0.0006217683],"genre_scores_gemma":[0.93025905,0.0000018108854,0.06767383,0.00020456508,0.00021975918,0.000008579901,0.000013428806,0.0000068279205,0.001612116],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931616,0.000014358363,0.00013080495,0.00018925728,0.00017975579,0.00016968207],"domain_scores_gemma":[0.9994246,0.00006978716,0.00002699684,0.00020580346,0.000104559695,0.00016828183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001703043,0.0000711644,0.00008330689,0.000045524685,0.00005711407,0.00017180984,0.00038395563,0.000033658875,0.000003289134],"category_scores_gemma":[0.00016527776,0.000058552574,0.000035022807,0.00018470362,0.000014252762,0.00036948832,0.0001685795,0.00003294336,0.000079844605],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000076973156,0.0006793536,0.116449945,0.000041317166,0.000060198105,0.000009810698,0.0013479079,0.00056298944,0.001097594,0.72875935,0.10903574,0.041878853],"study_design_scores_gemma":[0.00072003173,0.000095591924,0.0022463745,0.0000072568155,0.000004113722,0.0000016708171,0.00010014603,0.941537,0.002759981,0.0005318098,0.051847998,0.00014801914],"about_ca_topic_score_codex":0.000007269354,"about_ca_topic_score_gemma":0.0000037543512,"teacher_disagreement_score":0.940974,"about_ca_system_score_codex":0.000023323448,"about_ca_system_score_gemma":0.00004323848,"threshold_uncertainty_score":0.23877047},"labels":[],"label_agreement":null},{"id":"W2078018431","doi":"10.1068/p5023","title":"Search of Jumping Items: Visual Marking and Discrete Motion","year":2003,"lang":"en","type":"article","venue":"Perception","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Jumping; Motion (physics); Psychology; Computer science; Artificial intelligence; Computer vision; Cognitive psychology; Geology","score_opus":0.030805051754999316,"score_gpt":0.33232338632803915,"score_spread":0.30151833457303984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078018431","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23532674,0.000013247793,0.7637552,0.00005372748,0.00005073267,0.000036123834,0.0000010207305,0.000025876681,0.00073733716],"genre_scores_gemma":[0.99412644,0.000060683902,0.005617382,0.000055161603,0.000018381723,7.833771e-7,0.000010484264,0.0000033846466,0.00010729607],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99940705,0.00007565777,0.00012055809,0.00015415523,0.00015263191,0.000089937465],"domain_scores_gemma":[0.99975795,0.00001485921,0.000034398065,0.00011301088,0.000045427932,0.0000343579],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031506005,0.00004692112,0.00006203111,0.000089084526,0.000061060025,0.0000718657,0.00008374664,0.000024771096,0.000041018782],"category_scores_gemma":[0.000032990163,0.000045472425,0.000017461993,0.0001982936,0.000025826726,0.00037764345,0.000046356825,0.000037907037,0.000012977442],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013074465,0.00027854857,0.12329665,0.00037675272,0.00004347937,0.000004790702,0.013021366,0.000815411,0.17724778,0.22892353,0.0007531762,0.45522544],"study_design_scores_gemma":[0.00032533114,0.00007914162,0.08674206,0.00006614023,0.000009245691,0.000012104071,0.00079041556,0.90695095,0.0023628138,0.0007111904,0.0017664293,0.00018415833],"about_ca_topic_score_codex":0.00001236356,"about_ca_topic_score_gemma":0.000001915214,"teacher_disagreement_score":0.90613556,"about_ca_system_score_codex":0.000016921087,"about_ca_system_score_gemma":0.000010646141,"threshold_uncertainty_score":0.18543117},"labels":[],"label_agreement":null},{"id":"W2078099210","doi":"10.1145/1176617.1176658","title":"VET3D","year":2006,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Visualization; Software visualization; Software; Software engineering; Software evolution; World Wide Web; Software construction; Programming language; Software development","score_opus":0.01478758564787105,"score_gpt":0.2749189915379536,"score_spread":0.2601314058900826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078099210","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00017356733,0.0000044783524,0.8729358,0.00038729663,0.000039014776,0.0000063046073,2.398037e-7,0.00009525733,0.12635806],"genre_scores_gemma":[0.87984836,0.0000030134338,0.069516085,0.002706889,0.00009974083,8.628595e-7,0.000014749697,0.0000034587304,0.047806837],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997958,0.0000035382764,0.000040792936,0.000059473845,0.00005477126,0.00004565146],"domain_scores_gemma":[0.9998331,0.000004419863,0.0000072616003,0.00013160567,0.000012099992,0.000011499215],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000027193068,0.000017653341,0.000018045945,0.000017962337,0.000017362716,0.0000666998,0.00018568616,0.000006027826,0.000057221874],"category_scores_gemma":[0.0000023945224,0.000014308971,0.000008086752,0.000120261124,0.0000041803673,0.00013619412,0.000041925563,0.000007903412,0.0002549432],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.6987794e-8,0.000008306424,0.00019662862,2.8388962e-7,2.5585427e-7,7.3953936e-7,0.0000026057548,0.00001248468,0.00004323985,0.9521884,0.045986217,0.0015608488],"study_design_scores_gemma":[0.0001287548,0.0000108677705,0.0025589967,0.000001487748,9.242273e-7,0.0000033127073,0.0000044447647,0.35770696,0.002551184,0.024037527,0.6128919,0.00010359673],"about_ca_topic_score_codex":0.000019310353,"about_ca_topic_score_gemma":0.000005375103,"teacher_disagreement_score":0.92815083,"about_ca_system_score_codex":0.0000024157773,"about_ca_system_score_gemma":0.0000061001874,"threshold_uncertainty_score":0.32768643},"labels":[],"label_agreement":null},{"id":"W2078452098","doi":"10.1016/j.matcom.2010.04.020","title":"The geometry and dynamics of binary trees","year":2010,"lang":"en","type":"article","venue":"Mathematics and Computers in Simulation","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Geometry; Dynamics (music); Mathematics; Binary expression tree; Binary number; Binary tree; Physics; Combinatorics; Arithmetic","score_opus":0.013124200431695049,"score_gpt":0.2825952291347539,"score_spread":0.26947102870305883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078452098","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32093778,0.000021023747,0.67861074,0.00017774166,0.00009588828,0.00005080188,0.0000013188103,0.000013470001,0.00009122111],"genre_scores_gemma":[0.93765587,0.000025259451,0.062261455,0.000028540244,0.000008679675,5.953467e-7,0.000003139162,0.0000027976143,0.000013695254],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99954945,0.000010390091,0.00018222467,0.000094539806,0.00009773164,0.00006564559],"domain_scores_gemma":[0.9993137,0.00035904514,0.00008082271,0.0001934859,0.000030666488,0.0000222851],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025728432,0.000052849387,0.000082733655,0.00007749326,0.000063445856,0.00010624982,0.0001777872,0.000028815435,6.514591e-7],"category_scores_gemma":[0.00004007615,0.00003874693,0.000011193074,0.00019444824,0.0000547295,0.00012310961,0.00014609731,0.00005699783,3.491696e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000013042189,0.000068436406,0.0025608416,0.000046667985,0.000007254284,8.957241e-7,0.0008444253,0.0081971185,0.00013566356,0.9306341,0.000023688432,0.057479598],"study_design_scores_gemma":[0.0001144448,0.0000167725,0.004131872,0.000015155727,0.0000018891479,0.0000015301991,0.000047203328,0.97020966,0.000009625825,0.025303708,0.000103905884,0.000044226963],"about_ca_topic_score_codex":0.000002424665,"about_ca_topic_score_gemma":0.000024244247,"teacher_disagreement_score":0.9620125,"about_ca_system_score_codex":0.000004011348,"about_ca_system_score_gemma":0.0000065204226,"threshold_uncertainty_score":0.1580054},"labels":[],"label_agreement":null},{"id":"W207853804","doi":"","title":"CoMoVA - A comprehension measurement framework for visualization systems","year":2009,"lang":"en","type":"dissertation","venue":"Spectrum Research Repository (Concordia University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Visualization; Comprehension; Computer science; Information visualization; Set (abstract data type); Human–computer interaction; Visual analytics; Creative visualization; Perception; Data science; Artificial intelligence; Psychology","score_opus":0.06774438260924652,"score_gpt":0.34135257729668433,"score_spread":0.2736081946874378,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W207853804","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007968871,0.0007456279,0.95350766,0.00038480104,0.003954362,0.0023460072,0.00003600297,0.00061536586,0.030441282],"genre_scores_gemma":[0.9459303,0.0004991651,0.0021471218,0.000073359304,0.0010268936,0.000021802667,0.0012652079,0.00011779438,0.04891836],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9951461,0.000692161,0.00045619995,0.0010199271,0.0019551907,0.0007303977],"domain_scores_gemma":[0.99621314,0.00027534727,0.00039066607,0.0011117688,0.0016704988,0.00033857228],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010878298,0.00036219222,0.00051326165,0.001505253,0.0010690163,0.0009235078,0.0019030881,0.0004887156,0.000005890977],"category_scores_gemma":[0.00024167333,0.00041531958,0.00023349945,0.0020219404,0.000081222235,0.0006253592,0.0001865886,0.0006549866,0.00002999186],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023367052,0.00032714466,0.00033942796,0.0005804469,0.00020259275,0.00019735044,0.00057358254,0.00016556884,0.0014965863,0.9856285,0.008438814,0.0018163221],"study_design_scores_gemma":[0.0033978827,0.002941954,0.014867402,0.0042097215,0.00037301955,0.000054481206,0.0049277437,0.22330701,0.020958113,0.027858479,0.694056,0.00304819],"about_ca_topic_score_codex":0.0014369793,"about_ca_topic_score_gemma":0.0014805383,"teacher_disagreement_score":0.95777,"about_ca_system_score_codex":0.0013615814,"about_ca_system_score_gemma":0.0016771441,"threshold_uncertainty_score":0.9998299},"labels":[],"label_agreement":null},{"id":"W2079069819","doi":"10.3828/comma.2012.2.6","title":"Using information visualization and visual analytics to achieve a more sustainable future for archives: A survey and critical analysis of some developments","year":2012,"lang":"en","type":"article","venue":"Comma","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Australian Academy of Science","keywords":"Visual analytics; Visualization; Field (mathematics); Data science; Computer science; Information visualization; Cultural analytics; Analytics; Reflection (computer programming); Relation (database); Critical reflection; World Wide Web; Semantic analytics; Sociology; The Internet; Artificial intelligence; Data mining","score_opus":0.04246037237744122,"score_gpt":0.3737001773782728,"score_spread":0.3312398050008316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079069819","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08546838,0.000043235268,0.91409564,0.00012256864,0.000043909717,0.00014667862,0.000043943775,0.000017645929,0.000017999218],"genre_scores_gemma":[0.97572047,0.00002003203,0.023334917,0.00058142224,0.000032336604,0.0000048791794,0.00027481272,0.0000057203056,0.000025441019],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991061,0.00007604859,0.00028766302,0.0001255205,0.00016445441,0.00024022166],"domain_scores_gemma":[0.9991964,0.00019790216,0.00009081279,0.0001438672,0.00021055005,0.00016044787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047050175,0.00010102673,0.00021395662,0.0005765377,0.00014397058,0.00017750054,0.00015833604,0.00004330641,0.0000014225008],"category_scores_gemma":[0.00034165534,0.00009844283,0.000029870482,0.0011425331,0.00004810486,0.001495259,0.00027800942,0.00003377007,3.9726126e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007711085,0.00023485236,0.1771168,0.00041296138,0.00042043874,7.055618e-7,0.014937828,0.0004511246,0.00007647311,0.7966617,0.00039072876,0.009219286],"study_design_scores_gemma":[0.00022587547,0.000065293694,0.12138708,0.000012570062,0.00012956154,0.0000014119212,0.0012429161,0.87507796,0.00007339936,0.00037272018,0.0012534907,0.00015770171],"about_ca_topic_score_codex":0.000021690243,"about_ca_topic_score_gemma":0.000008269265,"teacher_disagreement_score":0.8907607,"about_ca_system_score_codex":0.000022917286,"about_ca_system_score_gemma":0.000056310757,"threshold_uncertainty_score":0.40143824},"labels":[],"label_agreement":null},{"id":"W2079128191","doi":"10.1145/1370114.1370140","title":"Towards a framework for software navigation techniques","year":2008,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Exploit; Software; Process (computing); Context (archaeology); Software framework; Human–computer interaction; Software development; Software system; Component-based software engineering; Programming language","score_opus":0.04104540732004085,"score_gpt":0.34060607142631655,"score_spread":0.2995606641062757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079128191","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00012316505,0.000009042934,0.9979998,0.00040631424,0.00006524227,0.000097773016,0.0000052225882,0.000525802,0.00076762267],"genre_scores_gemma":[0.014411545,0.000016861008,0.9836812,0.001200257,0.00005465147,0.000016384764,0.000030043493,0.000004508044,0.00058454793],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99953395,0.000007741933,0.00010121385,0.00014563445,0.000117658725,0.0000938074],"domain_scores_gemma":[0.9995572,0.000041930172,0.000032031632,0.00023846769,0.00009302504,0.000037361704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007469312,0.00005147313,0.000059920916,0.00003838994,0.00009948348,0.000053909727,0.00032697894,0.0000452376,0.00001669206],"category_scores_gemma":[0.0001214883,0.00004428018,0.000033636712,0.00022126477,0.00001867761,0.0002915522,0.00006823797,0.000034354172,0.000016709497],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.675052e-7,0.000024661598,0.00012389926,0.000008433093,0.0000031122704,0.0000019514555,0.00016837695,0.0000017197774,0.00001753166,0.94414794,0.009747348,0.045754354],"study_design_scores_gemma":[0.00029320607,0.00024494747,0.00046643207,0.000098591896,0.000009092428,0.00008020901,0.00003755636,0.108517915,0.05445986,0.52296036,0.31225905,0.0005727296],"about_ca_topic_score_codex":0.0000035691894,"about_ca_topic_score_gemma":2.6824986e-7,"teacher_disagreement_score":0.42118755,"about_ca_system_score_codex":0.000011741353,"about_ca_system_score_gemma":0.00004689082,"threshold_uncertainty_score":0.18056932},"labels":[],"label_agreement":null},{"id":"W2079540665","doi":"10.1155/2014/274803","title":"The Bifixation Field as a Function of Viewing Distance","year":2014,"lang":"en","type":"article","venue":"Journal of Ophthalmology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Medicine; Function (biology); Field (mathematics); Evolutionary biology; Pure mathematics","score_opus":0.023767245118470243,"score_gpt":0.31632974920594165,"score_spread":0.2925625040874714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079540665","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04787626,0.00013482744,0.94601625,0.0013055457,0.0007112934,0.000019766041,2.2774474e-7,0.0000037257366,0.003932107],"genre_scores_gemma":[0.99811625,0.000021685715,0.0013494154,0.00015137943,0.00007264112,2.5340006e-7,3.636073e-7,0.000001876426,0.00028612037],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99933267,0.00010652282,0.00029021106,0.000056064167,0.00014294563,0.00007160376],"domain_scores_gemma":[0.9989429,0.00027857925,0.00041804413,0.00016447391,0.00016857393,0.000027408249],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064245873,0.00003834152,0.00010185262,0.00005327282,0.000062267056,0.00003596206,0.0003590624,0.000029295086,0.000023399332],"category_scores_gemma":[0.00045448027,0.000024778266,0.00004790367,0.00016152537,0.000023737775,0.00021466553,0.000041473908,0.000073969946,0.00000615447],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013618814,0.00018963704,0.012515671,0.00005053904,0.00011301769,0.000098526994,0.00065718254,0.00063670205,0.0029907476,0.8725286,0.0087670395,0.10131612],"study_design_scores_gemma":[0.0027554168,0.009571143,0.08115408,0.00036199263,0.00014959314,0.017273132,0.00031584594,0.19026229,0.009583408,0.24908067,0.4388539,0.00063856266],"about_ca_topic_score_codex":0.000001894679,"about_ca_topic_score_gemma":1.6714164e-7,"teacher_disagreement_score":0.95024,"about_ca_system_score_codex":0.000008532516,"about_ca_system_score_gemma":0.000032407956,"threshold_uncertainty_score":0.10104284},"labels":[],"label_agreement":null},{"id":"W2080618601","doi":"10.1145/1629826.1629834","title":"Visualisation hybride des liens hiérarchiques incorporant des treemaps dans une matrice d'adjacence","year":2009,"lang":"fr","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Visualization; Adjacency matrix; Hierarchy; Graph drawing; Theoretical computer science; Node (physics); Software; Adjacency list; Graph; Data mining; Programming language; Algorithm","score_opus":0.05985672478760438,"score_gpt":0.3245118280256289,"score_spread":0.2646551032380245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080618601","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02460719,0.0009852693,0.950648,0.0042194044,0.00035970786,0.00020931462,0.000048074817,0.0003801478,0.018542893],"genre_scores_gemma":[0.7550394,0.003151634,0.20216593,0.00402097,0.00039197181,0.000005828896,0.00015411532,0.000038364135,0.035031818],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.996992,0.00033600276,0.0007132018,0.0007039508,0.00056433806,0.0006905299],"domain_scores_gemma":[0.99805236,0.00015928507,0.00028175523,0.00071613566,0.00040488565,0.0003855633],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007116659,0.00037765235,0.00034874878,0.00028328382,0.0005089084,0.00089115516,0.0010401441,0.00011645966,0.00013114327],"category_scores_gemma":[0.00024056011,0.00036821663,0.00013793394,0.0022628866,0.00069497805,0.0026555867,0.00022571451,0.00019472507,0.00028668533],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013859065,0.0006772246,0.002590573,0.0001229613,0.000028409495,0.00011906908,0.00925786,0.00075202424,0.0016014918,0.7469906,0.008123186,0.22972275],"study_design_scores_gemma":[0.0008486825,0.0010217432,0.036345426,0.00061926583,0.00012413945,0.000312333,0.001415093,0.66289437,0.015493024,0.24795897,0.03174717,0.001219749],"about_ca_topic_score_codex":0.0013706741,"about_ca_topic_score_gemma":0.0009185206,"teacher_disagreement_score":0.74848205,"about_ca_system_score_codex":0.00022199562,"about_ca_system_score_gemma":0.00024610266,"threshold_uncertainty_score":0.999877},"labels":[],"label_agreement":null},{"id":"W2080702463","doi":"10.1145/2396636.2396673","title":"Branch-explore-merge","year":2012,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"National Science Foundation","keywords":"Merge (version control); Computer science; Leverage (statistics); Collaborative software; Mobile device; Human–computer interaction; Task (project management); Multimedia; World Wide Web; Information retrieval; Artificial intelligence","score_opus":0.05473432110430791,"score_gpt":0.3200023533593323,"score_spread":0.2652680322550244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080702463","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010430051,0.00003831262,0.96334356,0.0004317686,0.00027660455,0.0000162907,5.2830273e-7,0.0001471235,0.03470279],"genre_scores_gemma":[0.9789692,0.000015286834,0.013700984,0.0024450389,0.000107533604,0.0000013351637,0.000006090005,0.0000035273777,0.004750966],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996001,0.000010922704,0.00006949557,0.00007280409,0.00010035005,0.00014633326],"domain_scores_gemma":[0.99963635,0.000009395362,0.0000149053,0.00023750741,0.000016819613,0.0000849908],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009893947,0.000038328,0.000039720155,0.000031327778,0.000031962958,0.00005004058,0.0002879688,0.000012900609,0.00024170925],"category_scores_gemma":[0.000013133859,0.000030601877,0.000018450044,0.00019462543,0.000007834641,0.00072393357,0.00010337758,0.000020147385,0.000985597],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.2264906e-7,0.000049225073,0.0031896387,0.0000019768506,0.0000033854217,2.0690335e-7,0.0002872458,0.0000020263178,0.00012692716,0.9394802,0.047526125,0.009332938],"study_design_scores_gemma":[0.0002007136,0.000017160042,0.0053372504,0.0000041652775,0.0000037022332,0.0000059518866,0.000051047242,0.044953927,0.004997134,0.0024781218,0.94171655,0.00023429988],"about_ca_topic_score_codex":0.0000033738165,"about_ca_topic_score_gemma":7.0404764e-7,"teacher_disagreement_score":0.97792625,"about_ca_system_score_codex":0.0000044997832,"about_ca_system_score_gemma":0.0000070598126,"threshold_uncertainty_score":0.9997923},"labels":[],"label_agreement":null},{"id":"W2080752813","doi":"10.1109/vast.2011.6102435","title":"Visual analytic roadblocks for novice investigators","year":2011,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Visual analytics; Computer science; Visualization; Data science; Cognition; Coding (social sciences); Analytics; Data visualization; Human–computer interaction; Psychology; Artificial intelligence","score_opus":0.0528054952958675,"score_gpt":0.3066845106245686,"score_spread":0.2538790153287011,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080752813","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0025443558,0.0000068520185,0.98418945,0.00018043943,0.00012668928,0.00009488274,0.0000028057218,0.00018969375,0.012664855],"genre_scores_gemma":[0.8315506,0.000004531178,0.15793686,0.0058948207,0.00007835354,0.000013796086,0.000021818103,0.000015571,0.00448365],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99922615,0.000015336753,0.00018182772,0.000256739,0.00013306325,0.00018686018],"domain_scores_gemma":[0.9993599,0.00003096994,0.000054470558,0.00031151142,0.00009397531,0.00014917835],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017148294,0.00009067413,0.00010342545,0.00011085576,0.000070712515,0.000088821864,0.0005721747,0.00003632323,0.00010835468],"category_scores_gemma":[0.000074463554,0.00007745783,0.000052094267,0.00043412723,0.000033955428,0.00039038213,0.00012905247,0.000033482385,0.00010750572],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000031736586,0.00015040982,0.0033192434,0.00001923956,0.000036508587,0.0000031979491,0.0007453211,0.000010655126,0.00013355065,0.9683973,0.02011295,0.0070684273],"study_design_scores_gemma":[0.0004699308,0.00017373255,0.001380015,0.000010395639,0.0000232791,0.0000050178205,0.00010433841,0.9444705,0.008642483,0.010987467,0.033393897,0.0003389235],"about_ca_topic_score_codex":0.000039500894,"about_ca_topic_score_gemma":0.000019265795,"teacher_disagreement_score":0.95740986,"about_ca_system_score_codex":0.000011986313,"about_ca_system_score_gemma":0.000068980706,"threshold_uncertainty_score":0.31586385},"labels":[],"label_agreement":null},{"id":"W2081373777","doi":"10.1117/12.771680","title":"Evaluation of information visualization approaches for an enhanced recognized maritime picture","year":2008,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Visualization; Computer science; Domain (mathematical analysis); Data visualization; Information visualization; Creative visualization; Human–computer interaction; Data science; Data mining","score_opus":0.03849991864267232,"score_gpt":0.278093275399814,"score_spread":0.23959335675714166,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081373777","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92939687,0.00002594358,0.06778513,0.0003903176,0.0001657741,0.0008801315,0.000065486536,0.00008411598,0.001206245],"genre_scores_gemma":[0.69698316,0.00007062886,0.3020663,0.00014411754,0.00021517057,0.00024349189,0.00017776691,0.000034166627,0.00006519219],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99753135,6.905736e-8,0.0007802448,0.00028762495,0.0011674841,0.00023322146],"domain_scores_gemma":[0.9939451,0.000091133865,0.0006313763,0.00008439325,0.005162873,0.00008510035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016376782,0.00021660517,0.00031880662,0.00016143224,0.00010393119,0.00012029502,0.001019086,0.00016427283,0.00000638415],"category_scores_gemma":[0.0012345178,0.00019086181,0.00032524727,0.00049380836,0.00012287246,0.0024735434,0.00012701603,0.000109870416,7.5523224e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006185096,0.00021176605,0.000071241026,0.00044021258,0.0002753277,6.190348e-9,0.0012659471,0.0011262945,0.08878573,0.90198153,0.0018601465,0.0039199633],"study_design_scores_gemma":[0.001483646,0.0003039283,0.0003464721,0.00010873138,0.00015042892,0.0000051744964,0.00065300276,0.8833696,0.10859117,0.003959607,0.00079804333,0.00023016185],"about_ca_topic_score_codex":0.0000032872279,"about_ca_topic_score_gemma":1.6478425e-7,"teacher_disagreement_score":0.89802194,"about_ca_system_score_codex":0.000116311916,"about_ca_system_score_gemma":0.00009935092,"threshold_uncertainty_score":0.77831185},"labels":[],"label_agreement":null},{"id":"W2081749267","doi":"10.1109/vast.2014.7042543","title":"VACI: Towards visual analytics for criminal investigation","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Visual analytics; Computer science; Visualization; Analytics; Data visualization; Cultural analytics; Interactive visual analysis; Data science; Data analysis; Criminal investigation; Human–computer interaction; Artificial intelligence; Data mining; Semantic analytics","score_opus":0.05187364616846072,"score_gpt":0.3342446115827653,"score_spread":0.28237096541430456,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081749267","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00210621,0.0000026086268,0.99374306,0.0009342247,0.00014610704,0.000069197224,0.0000026574749,0.00013639616,0.002859537],"genre_scores_gemma":[0.75931644,0.0000053240733,0.23021269,0.006617168,0.00024301952,0.000010632222,0.00010067392,0.000013642854,0.0034804253],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999216,0.000028650173,0.00018355377,0.00022463864,0.00018922979,0.00015793291],"domain_scores_gemma":[0.99938494,0.00005231156,0.000057956637,0.00025067854,0.00014696814,0.000107127606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000322736,0.000083625244,0.000099305886,0.00009356933,0.000085922984,0.0002217178,0.00039682383,0.00003719604,0.000021986894],"category_scores_gemma":[0.00018229167,0.00007341011,0.000046603385,0.00026970296,0.00002904854,0.0003775923,0.000096017175,0.000032262895,0.000043423344],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000015382178,0.00003134764,0.00027172995,0.000026675152,0.00000903279,2.2588073e-7,0.00018301143,0.00011976759,0.00020471454,0.9524032,0.010847891,0.03590087],"study_design_scores_gemma":[0.00020786752,0.00010142142,0.0005556376,0.0000046085333,0.000014248708,0.0000013855508,0.000026179501,0.9618578,0.0034643058,0.0093198465,0.024327632,0.000119051656],"about_ca_topic_score_codex":0.000010193899,"about_ca_topic_score_gemma":0.000007499248,"teacher_disagreement_score":0.96173805,"about_ca_system_score_codex":0.000016302325,"about_ca_system_score_gemma":0.000060640185,"threshold_uncertainty_score":0.29935774},"labels":[],"label_agreement":null},{"id":"W2082111181","doi":"10.3138/t91x-1n21-5336-2r73","title":"MapTime: Software for Exploring Spatiotemporal Data Associated with Point Locations","year":2000,"lang":"en","type":"article","venue":"Cartographica The International Journal for Geographic Information and Geovisualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Animation; Frame (networking); Scroll; Relation (database); Point (geometry); Software; Change detection; Bar chart; Computer graphics (images); Data mining; Artificial intelligence; Geography; Mathematics; Programming language","score_opus":0.045894003366047216,"score_gpt":0.30112656561217216,"score_spread":0.25523256224612495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2082111181","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0060678166,0.00007857429,0.98801404,0.004101062,0.000570681,0.0005648479,0.00037311087,0.00014719492,0.000082673934],"genre_scores_gemma":[0.907123,0.0046100146,0.04703049,0.012336627,0.00090850896,0.0006346684,0.026610471,0.0000901293,0.00065605703],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981953,0.000058983787,0.00063738023,0.00024365084,0.00060615095,0.00025851582],"domain_scores_gemma":[0.99709,0.00024185846,0.00042826118,0.00046992218,0.0016468492,0.00012315655],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0012129374,0.0001932798,0.00016030867,0.00056795013,0.00085101725,0.0014800164,0.0014565996,0.000075715674,0.00003869203],"category_scores_gemma":[0.0004800944,0.00014361991,0.00009664049,0.00084097293,0.00011654796,0.0054336702,0.00013519237,0.00014132785,0.0000039622237],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004716011,0.00044307343,0.014443821,0.00011624054,0.0017380624,0.0000045764996,0.005006265,0.009922401,0.000015029496,0.41180685,0.042851448,0.5131806],"study_design_scores_gemma":[0.002898758,0.00032284224,0.004984232,0.00018569388,0.00013533463,0.00011874416,0.00057818106,0.6035309,0.000040127048,0.010005997,0.3766929,0.00050629396],"about_ca_topic_score_codex":0.000021115831,"about_ca_topic_score_gemma":0.000054198466,"teacher_disagreement_score":0.94098353,"about_ca_system_score_codex":0.000029732279,"about_ca_system_score_gemma":0.00013437147,"threshold_uncertainty_score":0.99955654},"labels":[],"label_agreement":null},{"id":"W2082634718","doi":"10.1002/meet.14504301315","title":"Spatialized information visualizations: a “BASSTEP” approach to application design","year":2006,"lang":"en","type":"article","venue":"Proceedings of the American Society for Information Science and Technology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Spatialization; Computer science; Visualization; Context (archaeology); Human–computer interaction; Formative assessment; Usability; Information visualization; Process (computing); Hypertext; Domain (mathematical analysis); Information retrieval; World Wide Web; Artificial intelligence","score_opus":0.012242383073454748,"score_gpt":0.27167093195299935,"score_spread":0.2594285488795446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2082634718","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005544551,0.0000040698096,0.99007076,0.0026107896,0.000026393322,0.0007166288,0.000010264731,0.00015731998,0.00085923966],"genre_scores_gemma":[0.61733544,0.000025144727,0.37925363,0.0030697924,0.000015507905,0.00026691903,0.000016080168,0.000004562262,0.00001290441],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987466,0.0000023652233,0.0004017004,0.0001557391,0.00046562558,0.00022802311],"domain_scores_gemma":[0.9975218,0.000022033848,0.00049299485,0.0001881424,0.001730966,0.000044025855],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009560644,0.000098663324,0.00015106177,0.00042864648,0.00039988317,0.00032433306,0.0011109438,0.000042893244,1.3614702e-7],"category_scores_gemma":[0.0003668764,0.00007766179,0.000054496646,0.0064885747,0.0006644662,0.0047530895,0.0003410552,0.00005227656,0.0000039723286],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000044571793,0.000028517861,0.00039558267,0.000043110645,0.0000063985744,5.320863e-10,0.0006892083,0.00016724224,0.002836527,0.9605689,0.0070553822,0.028204663],"study_design_scores_gemma":[0.00055807753,0.00015842955,0.00092869933,0.000019406581,0.000022584083,0.000008185175,0.0031776717,0.84171236,0.02468819,0.01381614,0.11461443,0.0002958485],"about_ca_topic_score_codex":0.00002455006,"about_ca_topic_score_gemma":2.4344988e-7,"teacher_disagreement_score":0.9467528,"about_ca_system_score_codex":0.000072470415,"about_ca_system_score_gemma":0.00014846103,"threshold_uncertainty_score":0.3445875},"labels":[],"label_agreement":null},{"id":"W2083221884","doi":"10.1145/1012551.1012563","title":"Perceptual invariance of nonlinear Focus+Context transformations","year":2004,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Focus (optics); Clutter; Perception; Artificial intelligence; Context (archaeology); Transformation (genetics); Invariant (physics); Visualization; Computer vision; Nonlinear system; Scaling; Visual perception; Pattern recognition (psychology); Mathematics; Psychology; Geometry","score_opus":0.025208771664786724,"score_gpt":0.27887553745551014,"score_spread":0.2536667657907234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2083221884","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013268308,0.000012687285,0.98748994,0.0016362546,0.00004267809,0.000045797537,0.000011130895,0.000061290055,0.009373413],"genre_scores_gemma":[0.8979793,0.000021931193,0.10078343,0.0008537299,0.00001697149,0.0000013463542,0.000012146144,0.0000030734207,0.00032803835],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99948347,0.000009291137,0.000186355,0.000099566394,0.00013438816,0.00008690824],"domain_scores_gemma":[0.99961567,0.000011580414,0.000033656535,0.00022678539,0.000068064895,0.000044269793],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007329507,0.000050563343,0.00007628211,0.00005601923,0.000041289408,0.000042199004,0.00038450028,0.000022311282,0.0000927269],"category_scores_gemma":[0.0000158271,0.000043583703,0.000035157325,0.00029791167,0.000031513402,0.00059862353,0.000036483452,0.000034374985,0.00010993058],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.30164e-7,0.00007205702,0.000019402643,0.000005349653,0.000005094654,5.655336e-7,0.001698738,0.0003066487,0.00021909933,0.9859614,0.00040422168,0.011306889],"study_design_scores_gemma":[0.005361977,0.0005191602,0.0018906158,0.00015665576,0.000039505627,0.000047893267,0.0034757892,0.74140716,0.08308242,0.05652866,0.10640263,0.001087543],"about_ca_topic_score_codex":0.000056484827,"about_ca_topic_score_gemma":0.00008998408,"teacher_disagreement_score":0.92943275,"about_ca_system_score_codex":0.000011490532,"about_ca_system_score_gemma":0.00007770653,"threshold_uncertainty_score":0.17772919},"labels":[],"label_agreement":null},{"id":"W2084253356","doi":"10.1145/1278253.1278260","title":"Visualization of web spaces","year":2007,"lang":"en","type":"article","venue":"ACM SIGMIS Database the DATABASE for Advances in Information Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"World Wide Web; Computer science; Web modeling; Web navigation; Web intelligence; Data Web; Web standards; Social Semantic Web; Web page; Cyberspace; Web mapping; Web design; Web development; Information retrieval; Semantic Web; The Internet","score_opus":0.024211427505561135,"score_gpt":0.3348181446461068,"score_spread":0.31060671714054566,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084253356","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00068179605,0.0007301492,0.9930378,0.00009906207,0.0007432742,0.00073230953,0.0030555427,0.00009593108,0.00082411885],"genre_scores_gemma":[0.88406056,0.0040726773,0.07427697,0.00142742,0.0004248072,0.00028731758,0.035191406,0.000053143012,0.0002056769],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99760276,0.000084879706,0.0011173801,0.00022977902,0.0006304593,0.00033471346],"domain_scores_gemma":[0.9962826,0.0007946184,0.0007236203,0.0017475158,0.00036644103,0.00008520175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034170232,0.00018920712,0.00025732012,0.0004655748,0.0001552272,0.00022393143,0.0018075035,0.00004863376,0.000009038042],"category_scores_gemma":[0.0016405096,0.00014452262,0.000053050666,0.0012527303,0.00008677123,0.011336534,0.00053469546,0.00009696101,0.000033875178],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000085040076,0.000117431766,0.0013802518,0.0010443515,0.000027080718,0.0000023291843,0.0013523143,0.003238851,0.0008570768,0.9705853,0.011979497,0.009330467],"study_design_scores_gemma":[0.0011551464,0.000063337546,0.000059541537,0.00031834526,0.0000149629195,0.000013773593,0.0016858494,0.23972468,0.003325197,0.00026578613,0.7530747,0.00029868857],"about_ca_topic_score_codex":0.000073746094,"about_ca_topic_score_gemma":0.000106143896,"teacher_disagreement_score":0.9703195,"about_ca_system_score_codex":0.00005700295,"about_ca_system_score_gemma":0.000095702635,"threshold_uncertainty_score":0.8218714},"labels":[],"label_agreement":null},{"id":"W2085260377","doi":"10.1145/1166324.1166342","title":"Towards a design attitude for information architecture","year":2006,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Operationalization; Architecture; Computer science; Human–computer interaction; Cognitive science; Epistemology; Psychology; Philosophy; Art; Visual arts","score_opus":0.02258135065188313,"score_gpt":0.28218200275117955,"score_spread":0.2596006520992964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2085260377","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000009842998,0.000003551826,0.9894513,0.0006393329,0.000051204865,0.00011248602,0.0000045347347,0.0001224575,0.009605321],"genre_scores_gemma":[0.04809957,0.0000014945022,0.94849837,0.0021696056,0.00005772338,0.000014473775,0.00007693473,0.000002904936,0.0010789266],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99961853,0.000009528673,0.0001115947,0.00006646752,0.00010274937,0.0000911428],"domain_scores_gemma":[0.9997208,0.000020770172,0.000030860418,0.0001477945,0.00005843083,0.00002134663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011695669,0.0000452769,0.000043615248,0.000065599444,0.000045316927,0.00019628419,0.00026513325,0.000019671696,0.000009917923],"category_scores_gemma":[0.0000160088,0.000035617926,0.000023527322,0.0001620812,0.0000070161504,0.00053314224,0.000042995776,0.000017449542,0.00003570635],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016091963,0.000016592516,0.000014178085,0.000009415856,0.0000029489943,1.4687102e-7,0.00009910619,0.0045200107,0.00003183716,0.9271198,0.036853094,0.031331267],"study_design_scores_gemma":[0.00033929452,0.000049139126,0.00032934867,0.0000042880793,0.000003415078,0.0000032320636,0.000008994554,0.6379089,0.0021947965,0.035606686,0.32342282,0.00012913796],"about_ca_topic_score_codex":0.00002237928,"about_ca_topic_score_gemma":0.000006878871,"teacher_disagreement_score":0.8915131,"about_ca_system_score_codex":0.000009060963,"about_ca_system_score_gemma":0.000037038408,"threshold_uncertainty_score":0.1892773},"labels":[],"label_agreement":null},{"id":"W2086806493","doi":"10.1145/1979742.1979824","title":"DARLS","year":2011,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Storyboard; Animation; Class diagram; Computer graphics (images); Unified Modeling Language; Layering; Visualization; Class (philosophy); Programming language; Engineering drawing; Human–computer interaction; Artificial intelligence; Multimedia; Software","score_opus":0.07304808113205079,"score_gpt":0.29375895275608294,"score_spread":0.22071087162403213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086806493","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000042872398,0.0000017320954,0.7878294,0.0000532478,0.000044834695,0.0000063164616,2.556026e-7,0.00007720701,0.21194413],"genre_scores_gemma":[0.57777995,0.000010787666,0.39281997,0.0058412235,0.000033844033,0.0000013810827,0.000006134958,0.000004860715,0.023501845],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998077,0.0000042622287,0.000037928578,0.00006170834,0.000043702887,0.00004467559],"domain_scores_gemma":[0.99977463,0.0000023742175,0.000007794516,0.00017625482,0.000013606864,0.000025312234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000036376867,0.000017819735,0.00001886409,0.00001820812,0.000014094198,0.000026444417,0.00028470487,0.0000062120407,0.00032820163],"category_scores_gemma":[0.000005050637,0.000013864881,0.000007834949,0.00009829913,0.00000537617,0.000199379,0.000069635294,0.00000890149,0.000418118],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.7310532e-8,0.000010963694,0.00023677538,3.244299e-7,8.8994284e-7,0.0000010340424,0.00012244428,6.898708e-8,0.000008724234,0.9819223,0.013230085,0.004466339],"study_design_scores_gemma":[0.00040130925,0.000099245,0.007894607,0.0000074264904,0.000005616695,0.000014479382,0.00009984325,0.24451849,0.020920694,0.06786705,0.6577327,0.00043851577],"about_ca_topic_score_codex":0.0000070647047,"about_ca_topic_score_gemma":0.0000014474407,"teacher_disagreement_score":0.9140552,"about_ca_system_score_codex":0.0000013481031,"about_ca_system_score_gemma":0.000007071804,"threshold_uncertainty_score":0.53742003},"labels":[],"label_agreement":null},{"id":"W2087459536","doi":"10.3791/2397","title":"Facilitating the Analysis of Immunological Data with Visual Analytic Techniques","year":2011,"lang":"en","type":"article","venue":"Journal of Visualized Experiments","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Child and Family Research Institute; University of British Columbia","funders":"National Institute of Allergy and Infectious Diseases; Canadian Child Health Clinician Scientist Program; Children's Health Research Institute; Women and Children's Health Research Institute; Child and Family Research Institute; Michael Smith Health Research BC; Burroughs Wellcome Fund","keywords":"Computer science; Visual analytics; Visualization; Data analysis; Data visualization; Data exploration; Exploratory data analysis; Exploratory analysis; Software; Domain (mathematical analysis); Data science; Flexibility (engineering); Data mining; Information retrieval","score_opus":0.10310890843737047,"score_gpt":0.45129132458224275,"score_spread":0.3481824161448723,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2087459536","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13251722,0.00047592883,0.8660394,0.000055640747,0.00008536929,0.00012476176,0.000020636056,0.000046176443,0.000634853],"genre_scores_gemma":[0.9063303,0.00008981243,0.093308896,0.00017448023,0.000021369513,0.000002158332,0.00002106292,0.000008562552,0.00004338907],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978769,0.0002395341,0.0008204387,0.00024454264,0.00062659493,0.00019200555],"domain_scores_gemma":[0.99762934,0.00015897147,0.0009395157,0.0008547115,0.00033789393,0.00007956429],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010695282,0.0001564031,0.0005082338,0.00047869302,0.00009124614,0.000090196605,0.0023242298,0.000051266023,0.00010040095],"category_scores_gemma":[0.00020188469,0.00008683589,0.0001547447,0.0016579053,0.00015244358,0.00081857137,0.0005423063,0.00014796808,0.0000026491484],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0038725233,0.018296296,0.08894017,0.00025931405,0.07993966,0.0009234958,0.13543898,0.0004994349,0.25383398,0.15839635,0.008026279,0.2515735],"study_design_scores_gemma":[0.0052583073,0.006052085,0.02937456,0.0004814679,0.0053402972,0.00022040294,0.01894853,0.4779349,0.447267,0.001123836,0.006424135,0.0015744809],"about_ca_topic_score_codex":0.000032951353,"about_ca_topic_score_gemma":0.000002246616,"teacher_disagreement_score":0.77381307,"about_ca_system_score_codex":0.000030854568,"about_ca_system_score_gemma":0.00009061854,"threshold_uncertainty_score":0.43190357},"labels":[],"label_agreement":null},{"id":"W2088290398","doi":"10.1177/1473871613510429","title":"The nested blocks and guidelines model","year":2013,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":92,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Abstraction; Visualization; Domain (mathematical analysis); Task (project management); Process (computing); Block (permutation group theory); Data mining; Theoretical computer science; Software engineering; Programming language; Systems engineering","score_opus":0.02926739136881598,"score_gpt":0.3201169184577522,"score_spread":0.2908495270889362,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088290398","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012063594,0.00003538712,0.9951597,0.0017893979,0.000096441414,0.00017773233,0.000002098426,0.00016673582,0.0013661678],"genre_scores_gemma":[0.9026278,0.001786019,0.059168667,0.030261278,0.00021409993,0.000208718,0.0007372304,0.00003572323,0.0049604657],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991109,0.000024217441,0.00041509594,0.000083052284,0.00024165487,0.00012507966],"domain_scores_gemma":[0.9988521,0.000037770973,0.00016329446,0.00024952524,0.00063873135,0.00005858412],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00025401617,0.000082859195,0.00006025224,0.000092597846,0.00030212576,0.0011002511,0.00029825562,0.00004104442,0.000011228328],"category_scores_gemma":[0.0002477237,0.000058512218,0.000015683901,0.0003634631,0.000030357236,0.004287182,0.00012174156,0.000031467713,0.00011108812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.9383605e-7,0.0000097195,0.00022821431,0.000011245197,0.0000075238136,4.3204313e-8,0.0010081537,0.0071484945,0.000037938004,0.8456556,0.06479204,0.08110011],"study_design_scores_gemma":[0.00012509635,0.000008845647,0.00025364893,0.000008135831,0.0000022008887,0.0000023938558,0.000089982444,0.9662539,0.00009051069,0.0038869043,0.029197501,0.00008090137],"about_ca_topic_score_codex":0.000016109467,"about_ca_topic_score_gemma":0.0000025801878,"teacher_disagreement_score":0.9591054,"about_ca_system_score_codex":0.000013450582,"about_ca_system_score_gemma":0.00004050073,"threshold_uncertainty_score":0.9999367},"labels":[],"label_agreement":null},{"id":"W20884040","doi":"10.1016/j.chemosphere.2010.09.011","title":"A Model-Based Visualization Taxonomy","year":2002,"lang":"en","type":"article","venue":"Chemosphere","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Visualization; Terminology; Computer science; Taxonomy (biology); Data visualization; Information visualization; Set (abstract data type); Data science; Information retrieval; Data mining; Programming language","score_opus":0.05863810070993225,"score_gpt":0.27211975831951174,"score_spread":0.2134816576095795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W20884040","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00030367737,0.000057738296,0.9813833,0.00035118658,0.000054103268,0.00008018776,0.0000021964986,0.00021801097,0.01754956],"genre_scores_gemma":[0.8758231,0.000016930431,0.11389181,0.003692875,0.00005493607,0.000028807466,0.000033931803,0.000017946655,0.006439679],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993053,0.000013057238,0.000140684,0.00023645889,0.00015710315,0.00014736732],"domain_scores_gemma":[0.9993715,0.000012057237,0.00005685648,0.0004151393,0.00006772678,0.00007669122],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000055768367,0.00009224253,0.00008674159,0.000015114704,0.00007002408,0.00014712689,0.0004499145,0.0000440589,0.00044661236],"category_scores_gemma":[0.00002572508,0.00009158033,0.00003891441,0.00039305835,0.000021422487,0.00034050952,0.000065332875,0.000040057494,0.0002790923],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000033514818,0.0007086925,0.0016381582,0.000105686806,0.000030176383,0.00001527969,0.0004633579,0.04871489,0.0005733816,0.42052257,0.41548625,0.111738235],"study_design_scores_gemma":[0.00021274434,0.000009030438,0.000008465094,0.000007730721,0.0000028005747,7.374521e-7,0.000005731424,0.9396652,0.0017319757,0.00032219398,0.05791894,0.00011444378],"about_ca_topic_score_codex":0.0000014339404,"about_ca_topic_score_gemma":0.0000016115248,"teacher_disagreement_score":0.8909503,"about_ca_system_score_codex":0.000026676502,"about_ca_system_score_gemma":0.000024456574,"threshold_uncertainty_score":0.48900923},"labels":[],"label_agreement":null},{"id":"W2088484380","doi":"10.1145/1520340.1520636","title":"AdWiL","year":2009,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Task (project management); Human–computer interaction; Visual analytics; Software; Creativity; Analytics; Software engineering; Task management; Task analysis; Visualization; Data science; Operating system; Artificial intelligence; Engineering; Systems engineering","score_opus":0.020460324945458085,"score_gpt":0.30247305148576664,"score_spread":0.28201272654030857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088484380","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006469466,0.000004676402,0.91043055,0.0020213793,0.00002925263,0.0000069328894,1.2222243e-7,0.00011007876,0.087332286],"genre_scores_gemma":[0.87123895,0.00001240546,0.08887879,0.022953538,0.000044476907,2.129321e-7,0.000004487806,0.0000014535942,0.01686569],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.999794,0.0000035434343,0.000037158905,0.000061775514,0.00005629965,0.00004719788],"domain_scores_gemma":[0.9998004,0.0000029751795,0.0000066673138,0.00015233045,0.0000124627095,0.000025187055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000030637253,0.000018567058,0.00002026902,0.000018403578,0.000016376118,0.0000623672,0.00023278921,0.0000063131356,0.00005309943],"category_scores_gemma":[0.000006327624,0.000014701014,0.000008662766,0.00013026682,0.0000023008613,0.00017777777,0.000019607442,0.000010079748,0.00019406814],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.59232e-8,0.000010488806,0.000020166068,1.1462994e-7,3.0787007e-7,8.076758e-7,0.000014781225,0.000002930315,0.000036835696,0.93965316,0.025148315,0.035112042],"study_design_scores_gemma":[0.00020253692,0.00007740003,0.0041591683,0.0000035489745,0.0000014097399,0.0000061637015,0.000010912564,0.47276634,0.00227241,0.040055096,0.4802767,0.00016828674],"about_ca_topic_score_codex":6.1896355e-7,"about_ca_topic_score_gemma":3.3555128e-7,"teacher_disagreement_score":0.89959806,"about_ca_system_score_codex":0.0000020811194,"about_ca_system_score_gemma":0.000006927512,"threshold_uncertainty_score":0.2494418},"labels":[],"label_agreement":null},{"id":"W2088540292","doi":"10.1109/vast.2014.7042529","title":"The care and condition monitor: Designing a tablet based tool for visualizing informal qualitative healthcare data","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario College of Art and Design","funders":"Mitacs","keywords":"Visualization; Scope (computer science); Health care; Data visualization; Structuring; Computer science; Comprehension; Visual analytics; Analytics; Qualitative research; Human–computer interaction; Data science; Knowledge management; Multimedia; Data mining","score_opus":0.07471421459530998,"score_gpt":0.41624421214260415,"score_spread":0.3415299975472942,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088540292","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00047192827,0.00007662923,0.9980525,0.0006904024,0.00009068755,0.0002048719,0.000104116385,0.000082381295,0.00022652208],"genre_scores_gemma":[0.8412873,0.00002288999,0.15475565,0.002685657,0.000085432,0.000031765547,0.0010211208,0.000011152748,0.00009899165],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999005,0.00016321978,0.00021892325,0.00023447434,0.00018074113,0.0001976043],"domain_scores_gemma":[0.99837196,0.0007604112,0.00009979808,0.0005145644,0.00019257926,0.00006069484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010221021,0.0000885463,0.00009689199,0.000044767043,0.00051465543,0.00051996944,0.0005934645,0.00003213119,0.0000016682129],"category_scores_gemma":[0.00032792406,0.00006384089,0.000016347645,0.00014814027,0.00004257865,0.0010025307,0.00023581792,0.000047667738,0.0000033006697],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019004669,0.000019129566,0.00043166365,0.00025921766,0.000025181938,4.5983862e-7,0.013534963,0.00011415002,0.00010863285,0.8758497,0.0090583,0.10057955],"study_design_scores_gemma":[0.0005096928,0.00016473126,0.00006871088,0.000038560902,0.000007676505,0.0000011395338,0.006836957,0.95443326,0.00072396884,0.00079706864,0.03626306,0.00015516688],"about_ca_topic_score_codex":0.000038421364,"about_ca_topic_score_gemma":0.000034917408,"teacher_disagreement_score":0.9543191,"about_ca_system_score_codex":0.00001570537,"about_ca_system_score_gemma":0.00007535759,"threshold_uncertainty_score":0.50140774},"labels":[],"label_agreement":null},{"id":"W2088558086","doi":"10.1145/2442576.2442590","title":"Evaluating analytic performance","year":2012,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Boeing","keywords":"Computer science; Visual analytics; Analytics; Position paper; Position (finance); Data science; Visualization; Artificial intelligence; World Wide Web","score_opus":0.11375931541617205,"score_gpt":0.40273392929242074,"score_spread":0.2889746138762487,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088558086","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.049622655,0.000036978607,0.9173249,0.00018562286,0.00020121109,0.000033663593,2.8711344e-7,0.0001534308,0.032441255],"genre_scores_gemma":[0.95439094,0.000006099332,0.042233445,0.0006973579,0.000054559816,9.4714136e-7,0.0000023973384,0.0000022280672,0.0026120294],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99946785,0.000017333927,0.000093849354,0.000084006,0.00017068529,0.0001662958],"domain_scores_gemma":[0.99959874,0.000017724538,0.000026561052,0.00025304453,0.00003353133,0.00007038356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039124303,0.00004181088,0.000045349923,0.000045047036,0.00005694618,0.000065522465,0.00029304333,0.000011539806,0.00013745484],"category_scores_gemma":[0.000034850087,0.000033547996,0.00001604467,0.00028942243,0.000007759606,0.00085817045,0.000108374035,0.000026485393,0.00046638935],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.2529615e-7,0.00014361211,0.079152256,0.000027196224,0.00002153555,4.6170624e-7,0.0007749148,0.0005204409,0.0004746752,0.6985291,0.0087105455,0.21164429],"study_design_scores_gemma":[0.000064719374,0.000017599028,0.0072471485,0.0000033048823,0.000003112646,0.000002861494,0.000011050591,0.98660743,0.0007261532,0.0000661119,0.0051812176,0.00006930979],"about_ca_topic_score_codex":0.0000015760032,"about_ca_topic_score_gemma":2.3885735e-7,"teacher_disagreement_score":0.98608696,"about_ca_system_score_codex":0.000010923485,"about_ca_system_score_gemma":0.000016326325,"threshold_uncertainty_score":0.5994647},"labels":[],"label_agreement":null},{"id":"W2088614079","doi":"10.1109/pacificvis.2013.6596122","title":"Exploring entities in text with descriptive non-photorealistic rendering","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Rendering (computer graphics); Computer science; Visualization; Exploit; Data collection; Data visualization; Complaint; Human–computer interaction; Computer graphics (images); Information retrieval; Artificial intelligence","score_opus":0.10132488086074685,"score_gpt":0.25827617297314087,"score_spread":0.156951292112394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088614079","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043451507,0.000005125782,0.93626654,0.00012263862,0.00009529532,0.00010438995,0.0000011356404,0.000103309445,0.019850068],"genre_scores_gemma":[0.98439103,0.000017550237,0.014017208,0.00018172209,0.000014054054,0.00003524938,0.0000041171365,0.0000056109507,0.0013334644],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99941105,0.000011768894,0.000114777016,0.00017329388,0.00013356353,0.00015553883],"domain_scores_gemma":[0.9996414,0.00001971694,0.000025706244,0.00021788948,0.000045931418,0.000049336548],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000058736314,0.00007152528,0.00007902727,0.00011856739,0.000035645113,0.0002554936,0.00028376686,0.0000102364575,0.00008576804],"category_scores_gemma":[0.000014063912,0.000055710658,0.000010746404,0.0003144408,0.00002085967,0.0015558649,0.00010884968,0.000043023807,0.00008258096],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008354184,0.00030213982,0.017138088,0.00013520246,0.00006917102,0.000097731754,0.024455098,0.0016505276,0.0021517065,0.9087383,0.011883906,0.033369787],"study_design_scores_gemma":[0.0008365944,0.00016123087,0.040841486,0.00021897598,0.000007404792,0.000015161761,0.0073753777,0.9371177,0.0067704367,0.0027506636,0.0032532727,0.0006517238],"about_ca_topic_score_codex":0.0013056478,"about_ca_topic_score_gemma":0.00024458327,"teacher_disagreement_score":0.94093955,"about_ca_system_score_codex":0.000033405962,"about_ca_system_score_gemma":0.000023909926,"threshold_uncertainty_score":0.24637306},"labels":[],"label_agreement":null},{"id":"W2089444016","doi":"10.1145/1240624.1240627","title":"Improving recognition and characterization in groupware with rich embodiments","year":2007,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; University of Saskatchewan","funders":"","keywords":"Collaborative software; Computer science; Human–computer interaction; Set (abstract data type); Visualization; Variety (cybernetics); Recall; Face (sociological concept); Multimedia; World Wide Web; Artificial intelligence; Cognitive psychology; Psychology","score_opus":0.02243309668498318,"score_gpt":0.25971959167477426,"score_spread":0.2372864949897911,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089444016","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23224498,0.000001591649,0.76712114,0.000052638283,0.000022052298,0.00004738137,0.0000026589269,0.000039761442,0.00046778243],"genre_scores_gemma":[0.9812765,0.000006375578,0.017600255,0.00065003004,0.000017064505,0.0000016345987,0.00019814425,0.0000046438645,0.00024534046],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99955654,0.000009396396,0.00010328769,0.00014541413,0.000089871886,0.000095497024],"domain_scores_gemma":[0.99979436,0.0000103128095,0.000040620307,0.00008700512,0.00003439317,0.00003327698],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018164163,0.00004522184,0.000043950633,0.000104954546,0.000028173941,0.000091204114,0.000078735284,0.00001901081,0.000009282696],"category_scores_gemma":[0.000008146647,0.000037365342,0.000003164739,0.00029749097,0.0000074567497,0.00060828787,0.000045772307,0.000027437713,0.000011000093],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024637473,0.00024161945,0.12370694,0.0000651674,0.000013234524,0.00003905463,0.0015503159,0.0000034912266,0.021718072,0.017635362,0.00005802765,0.83494407],"study_design_scores_gemma":[0.002699203,0.00035790697,0.6308929,0.00015302854,0.000015643758,0.000046552348,0.00043649683,0.33654234,0.025238726,0.0015048413,0.0013029712,0.0008094266],"about_ca_topic_score_codex":0.000016881619,"about_ca_topic_score_gemma":0.00004575765,"teacher_disagreement_score":0.83413464,"about_ca_system_score_codex":0.000012952939,"about_ca_system_score_gemma":0.00000849204,"threshold_uncertainty_score":0.15237144},"labels":[],"label_agreement":null},{"id":"W2091736440","doi":"10.1109/bigdata.2013.6691710","title":"VisReduce: Fast and responsive incremental information visualization of large datasets","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Visualization; Analytics; Data warehouse; Visual analytics; Data visualization; Exploratory analysis; Data mining; Big data; Information retrieval; Database; Data science","score_opus":0.011085946388020249,"score_gpt":0.3023423460319923,"score_spread":0.29125639964397204,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091736440","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020055316,0.000007940193,0.97788286,0.00023705584,0.000054481643,0.00016387635,0.00013446798,0.00005635456,0.0014076428],"genre_scores_gemma":[0.989138,0.000024640416,0.0076956293,0.0015697074,0.000010224556,0.000005165449,0.0014353411,0.0000031024927,0.00011815818],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993873,0.000035616846,0.00021607877,0.000091729,0.00017610786,0.00009313181],"domain_scores_gemma":[0.9995081,0.000021182881,0.00009762282,0.00020529363,0.000117282114,0.00005051056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016037634,0.000057251047,0.000068723064,0.00013071083,0.00005131083,0.00016157297,0.00020028156,0.000023857445,0.00014028407],"category_scores_gemma":[0.00006818765,0.000050291455,0.000009482544,0.00026766796,0.000020250081,0.0030556123,0.00024629355,0.000019471565,0.00009039183],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006675583,0.00013772733,0.002243522,0.000060982453,0.000024643821,5.071913e-7,0.0019108377,0.00001558038,0.004059622,0.85961556,0.10497545,0.026948916],"study_design_scores_gemma":[0.001159878,0.0001558394,0.021298492,0.00003565732,0.000011437234,0.000009992881,0.0013625642,0.9180433,0.022477714,0.00091350736,0.034223165,0.00030843864],"about_ca_topic_score_codex":0.000044923403,"about_ca_topic_score_gemma":0.000004334579,"teacher_disagreement_score":0.97018725,"about_ca_system_score_codex":0.000009035289,"about_ca_system_score_gemma":0.000024704155,"threshold_uncertainty_score":0.22152452},"labels":[],"label_agreement":null},{"id":"W2092929535","doi":"10.1007/s00180-011-0228-6","title":"Graphs as navigational infrastructure for high dimensional data spaces","year":2011,"lang":"en","type":"article","venue":"Computational Statistics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Morphing; Graph; Computer science; Graph theory; Theoretical computer science; Line graph; Discrete mathematics; Mathematics; Combinatorics; Artificial intelligence","score_opus":0.047595611053445966,"score_gpt":0.3205108999731773,"score_spread":0.2729152889197313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092929535","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007563058,0.000022941373,0.9943289,0.00022534608,0.00041096276,0.00014903721,0.003841088,0.000083038314,0.00018236492],"genre_scores_gemma":[0.12222527,0.0000035896578,0.86616296,0.0009954273,0.00006452663,0.000007019554,0.010403738,0.000012730322,0.00012476684],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985265,0.00003636715,0.0003096431,0.00045004394,0.00048429062,0.00019311362],"domain_scores_gemma":[0.9984571,0.00035391407,0.00016925919,0.00044445673,0.00045361184,0.000121663106],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001823679,0.00015229937,0.00014447178,0.000097186356,0.0002263253,0.00016790067,0.0010863577,0.00005040172,0.00018989643],"category_scores_gemma":[0.00021742204,0.00014919428,0.00002388663,0.0002797907,0.00010081169,0.00052134343,0.0004250253,0.00008287293,0.000065598564],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007326056,0.000054213706,0.00031823863,0.000012884968,0.000033833836,0.000005631079,0.0001227966,0.0043151765,0.000002555593,0.93611574,0.05364984,0.0053617447],"study_design_scores_gemma":[0.000254774,0.000044192337,0.0068295286,0.0000069242515,0.000010977567,0.000010975287,0.000006978285,0.4500637,0.000010342501,0.53999555,0.0026390709,0.00012696888],"about_ca_topic_score_codex":0.000025397549,"about_ca_topic_score_gemma":0.0000046190153,"teacher_disagreement_score":0.44574854,"about_ca_system_score_codex":0.000022469218,"about_ca_system_score_gemma":0.00026931107,"threshold_uncertainty_score":0.60839665},"labels":[],"label_agreement":null},{"id":"W2093017994","doi":"10.1145/1463788.1463808","title":"Building highly-interactive, data-intensive, REST applications","year":2008,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Rest (music); Computer science; Medicine","score_opus":0.06820252729472506,"score_gpt":0.3490065999535233,"score_spread":0.28080407265879825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093017994","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00024150792,0.00001751481,0.9893715,0.001310531,0.000098098964,0.000088938315,0.000021120513,0.00024828955,0.008602504],"genre_scores_gemma":[0.43613207,0.00018208423,0.5459848,0.008738378,0.00023419753,0.00002506503,0.0003294962,0.000022242244,0.008351666],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990648,0.000021478041,0.00017688208,0.00040385727,0.00018189312,0.00015109121],"domain_scores_gemma":[0.99818933,0.00007256579,0.00006369775,0.0013343355,0.00025298976,0.00008705434],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008218589,0.000084078165,0.000098289776,0.00009613124,0.00018364601,0.000104048246,0.0015957325,0.000023727518,0.00004075846],"category_scores_gemma":[0.000087131266,0.00007473419,0.000022051601,0.0004567972,0.00004693076,0.0010587613,0.0007823807,0.00007223499,0.00033719244],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016972592,0.000088981375,0.0003942787,0.0000051232623,0.000023361536,0.000019961426,0.000109434724,0.00004649974,0.0007612453,0.8250869,0.16617353,0.0072890157],"study_design_scores_gemma":[0.00016428348,0.00001317384,0.00079134037,0.000007359042,0.000005358989,0.00006681325,0.000042121974,0.26856136,0.0013979068,0.0011158244,0.72765744,0.00017701641],"about_ca_topic_score_codex":0.00003437939,"about_ca_topic_score_gemma":0.00000806621,"teacher_disagreement_score":0.82397103,"about_ca_system_score_codex":0.00001725275,"about_ca_system_score_gemma":0.000052178355,"threshold_uncertainty_score":0.4334039},"labels":[],"label_agreement":null},{"id":"W2094840417","doi":"10.1109/tvcg.2013.61","title":"ParaGlide: Interactive Parameter Space Partitioning for Computer Simulations","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Parameter space; Workload; Visualization; Process (computing); Domain (mathematical analysis); Set (abstract data type); Task (project management); Data mining; Human–computer interaction; User interface; Interactive visual analysis; Space (punctuation); Interface (matter); Graphical user interface; Data visualization; Systems engineering; Programming language","score_opus":0.026554099843000393,"score_gpt":0.3052135667651903,"score_spread":0.2786594669221899,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2094840417","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0035673603,0.000010602531,0.99449915,0.0002671582,0.0007280515,0.0005633443,0.000039670067,0.00030768273,0.000016983913],"genre_scores_gemma":[0.95663095,0.00006049813,0.038838524,0.0039554886,0.00013333661,0.00011461256,0.000081167105,0.000034471042,0.00015098785],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998347,0.000120295,0.00042587073,0.00055224093,0.00025821882,0.00029639777],"domain_scores_gemma":[0.99836844,0.00049838936,0.00015789476,0.0003897636,0.0004028364,0.00018270318],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001258405,0.00026438612,0.00024371034,0.00042782977,0.0004993369,0.0008022376,0.000299401,0.00011658323,0.00005996304],"category_scores_gemma":[0.000008616702,0.00026507853,0.0001301965,0.0007378593,0.00008467738,0.0012402369,0.000011092931,0.00015556772,0.000036253692],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018498431,0.0006684865,0.00020837592,0.00007251391,0.00019722505,0.0000019700335,0.0016842023,0.03261175,0.000036329664,0.9368012,0.00456841,0.023131011],"study_design_scores_gemma":[0.0006214119,0.00025291447,0.00029413484,0.000051676398,0.000028402314,0.000007752373,0.000023635825,0.99035895,0.00068982755,0.003473973,0.0038812624,0.00031607776],"about_ca_topic_score_codex":0.000017176706,"about_ca_topic_score_gemma":0.000013393585,"teacher_disagreement_score":0.95774716,"about_ca_system_score_codex":0.000028866221,"about_ca_system_score_gemma":0.000035598623,"threshold_uncertainty_score":0.99998015},"labels":[],"label_agreement":null},{"id":"W2095102238","doi":"10.1109/vast.2009.5333469","title":"Comparing two interface tools in performing visual analytics tasks","year":2009,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Visual analytics; Icon; Human–computer interaction; Task (project management); Visualization; Interface (matter); Analytics; Interactive visualization; User interface; Graphical user interface; Interactive visual analysis; Task analysis; Data visualization; Data science; Artificial intelligence; Operating system","score_opus":0.06693119350929941,"score_gpt":0.3721998345281795,"score_spread":0.30526864101888007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095102238","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07456843,0.00001797531,0.9090112,0.000398715,0.00008191267,0.000056930872,5.505161e-7,0.00012863438,0.015735641],"genre_scores_gemma":[0.98764724,0.000007198822,0.010878354,0.0008928252,0.000027229657,4.5583704e-7,0.0000068549243,0.000003464716,0.00053638656],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989895,0.000026475453,0.00028910095,0.00025439382,0.00019669344,0.00024383521],"domain_scores_gemma":[0.9995044,0.00003580684,0.000054146498,0.0002863588,0.00004227445,0.00007700283],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026177993,0.000109379136,0.00016910897,0.00018591667,0.000053868698,0.00039665797,0.000599219,0.0000268629,0.000035419405],"category_scores_gemma":[0.00004718801,0.00010134026,0.000033895307,0.00062168436,0.000014735443,0.00094691024,0.00017602988,0.00011764145,0.00007404842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013691136,0.0006939153,0.04684626,0.000024250852,0.000031170493,0.000056339602,0.0019647924,0.032273367,0.0021851656,0.6804632,0.004067999,0.23137985],"study_design_scores_gemma":[0.0003282308,0.000051165647,0.0044908277,0.000024031191,0.000002585014,0.0000048620777,0.00008301715,0.99112,0.0017812006,0.0004894026,0.0014737083,0.0001510058],"about_ca_topic_score_codex":0.00002121042,"about_ca_topic_score_gemma":0.000053646487,"teacher_disagreement_score":0.95884657,"about_ca_system_score_codex":0.00005076057,"about_ca_system_score_gemma":0.0000343912,"threshold_uncertainty_score":0.41325358},"labels":[],"label_agreement":null},{"id":"W2095459940","doi":"10.1109/tvcg.2013.197","title":"Supporting Awareness through Collaborative Brushing and Linking of Tabular Data","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Systems, Applications & Products in Data Processing (Canada); University of Victoria","funders":"","keywords":"Computer science; Workspace; Set (abstract data type); Visualization; Context (archaeology); Selection (genetic algorithm); Data visualization; Work (physics); Human–computer interaction; Data science; World Wide Web; Artificial intelligence","score_opus":0.039744945721858764,"score_gpt":0.3401051067971721,"score_spread":0.3003601610753133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095459940","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009669923,0.00007850394,0.98952085,0.00008661915,0.0002520149,0.00020764928,0.00004230343,0.000119748875,0.000022397966],"genre_scores_gemma":[0.98542,0.00066761323,0.012540222,0.0011900679,0.000037410733,0.000009235634,0.00009105011,0.000019341152,0.000025076633],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984683,0.00011952155,0.00044157146,0.00049001985,0.00028776526,0.00019281893],"domain_scores_gemma":[0.99870735,0.00012504621,0.00022245766,0.0005456259,0.00030953594,0.000090000365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026848813,0.00017809935,0.00023490361,0.00022511346,0.00032189616,0.00041981178,0.00048811306,0.00008960839,0.000011860426],"category_scores_gemma":[0.000007399481,0.0001760727,0.000028550583,0.0010437275,0.00011057312,0.0017606253,0.00003679261,0.000118359574,0.0000025888548],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000068322233,0.00034997234,0.001690846,0.00022270881,0.00014544552,0.000004047828,0.005563818,0.0010176882,0.00011508841,0.9659986,0.00074667885,0.024138303],"study_design_scores_gemma":[0.00034784953,0.000090520865,0.00024132611,0.000096417265,0.000023771321,0.00000560015,0.00018364117,0.994759,0.0014414965,0.0015843909,0.0010243614,0.00020157271],"about_ca_topic_score_codex":0.00007492144,"about_ca_topic_score_gemma":0.00002779593,"teacher_disagreement_score":0.9937414,"about_ca_system_score_codex":0.0000076040037,"about_ca_system_score_gemma":0.00007162918,"threshold_uncertainty_score":0.7180037},"labels":[],"label_agreement":null},{"id":"W2095995927","doi":"10.1177/1473871612456121","title":"Interactive exploration of movement data: A case study of geovisual analytics for fishing vessel analysis","year":2012,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Analytics; Filter (signal processing); Data mining; Movement (music); Range (aeronautics); Process (computing); Focus (optics); Dimension (graph theory); Path (computing); Visual analytics; Fractal dimension; Fractal; Computer vision; Visualization","score_opus":0.09741630888681105,"score_gpt":0.39537576898704707,"score_spread":0.297959460100236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095995927","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0779313,0.0000062593567,0.9211809,0.000024629035,0.00015163547,0.00048446553,0.00012016766,0.00004455643,0.000056090346],"genre_scores_gemma":[0.99409914,0.000008656104,0.0038252827,0.0001335788,0.00003507385,0.00002258978,0.0018605314,0.000005943501,0.0000092115215],"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981037,0.000099486664,0.0010198164,0.00016010953,0.0004511104,0.00016582086],"domain_scores_gemma":[0.99728674,0.00013380311,0.0010578207,0.0006738544,0.0007780194,0.00006975163],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00095974247,0.00013116038,0.00027884194,0.00082740077,0.000104196384,0.0001620185,0.00047202542,0.000050781815,0.0000092107775],"category_scores_gemma":[0.00032104625,0.00013161487,0.000060650418,0.002034487,0.000018042932,0.017948763,0.00027613735,0.00004120115,0.000002678126],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017636137,0.00891312,0.073404975,0.001089493,0.004642114,0.000007755199,0.3731383,0.17980006,0.00030884024,0.3117949,0.0071048085,0.039619252],"study_design_scores_gemma":[0.00066970394,0.00019324408,0.0007674715,0.000013251652,0.0003537823,0.0000032659912,0.01892257,0.9773654,0.0007775965,0.000087194705,0.0007068552,0.00013968871],"about_ca_topic_score_codex":0.00018924687,"about_ca_topic_score_gemma":0.000064779066,"teacher_disagreement_score":0.9173556,"about_ca_system_score_codex":0.00005050373,"about_ca_system_score_gemma":0.000050878745,"threshold_uncertainty_score":0.99578667},"labels":[],"label_agreement":null},{"id":"W2097156270","doi":"10.1007/978-3-540-33037-0_2","title":"A Brief History of Data Visualization","year":2007,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":316,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Depiction; Graphics; Computer science; Statistical graphics; Visualization; Representation (politics); Data science; Information visualization; Computer graphics; Data visualization; Computer graphics (images); Artificial intelligence; Visual arts; Art","score_opus":0.14189887617215066,"score_gpt":0.34776135040082695,"score_spread":0.2058624742286763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097156270","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[7.2158155e-9,0.00022453547,0.5132701,0.0000145397735,0.00018111985,0.000036225003,0.000027400016,0.00006142077,0.48618466],"genre_scores_gemma":[0.000013641177,0.00023439633,0.014338617,0.0010501605,0.0000755292,1.7431438e-7,0.0011530295,0.000021797574,0.98311263],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99861705,0.000008382398,0.00040488158,0.000447207,0.0004152065,0.000107289976],"domain_scores_gemma":[0.9976834,0.000036310612,0.00030408023,0.0017417114,0.00016828647,0.000066186076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032215737,0.00015644377,0.00022659387,0.000259071,0.000013495101,0.000029442934,0.0018579804,0.00015353385,0.0008289753],"category_scores_gemma":[0.000025856436,0.00015623354,0.000044026325,0.00005280187,0.000068925154,0.00055684225,0.00088826363,0.00007988593,0.00009711891],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.6138174e-7,0.0000117090285,8.774836e-7,0.000023529572,0.000014660047,0.0000034065506,0.000033020828,5.408698e-7,0.0000022927154,0.8166224,0.17258024,0.010706791],"study_design_scores_gemma":[0.00008183795,0.000017956825,0.0000013076748,0.000045523037,0.000016735152,0.0000027104982,9.303501e-7,0.050732996,0.0000074111817,0.0027012043,0.94622517,0.00016624274],"about_ca_topic_score_codex":0.000020127085,"about_ca_topic_score_gemma":0.00002960461,"teacher_disagreement_score":0.81392115,"about_ca_system_score_codex":0.00012369482,"about_ca_system_score_gemma":0.0003131514,"threshold_uncertainty_score":0.9076698},"labels":[],"label_agreement":null},{"id":"W2097709032","doi":"10.1145/1822348.1822349","title":"Gameplay analysis through state projection","year":2010,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":86,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Division of Information and Intelligent Systems; Defense Advanced Research Projects Agency; University of Washington; National Science Foundation","keywords":"Computer science; Confusion; Game design; Human–computer interaction; Multidimensional scaling; Task (project management); Visualization; Representation (politics); Data visualization; Projection (relational algebra); Data science; Artificial intelligence; Machine learning","score_opus":0.018132522980305377,"score_gpt":0.31762303781007484,"score_spread":0.29949051482976946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097709032","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004729388,0.0000011469552,0.97790736,0.00029222478,0.00017293647,0.000032712018,0.0000024150772,0.00016938256,0.016692463],"genre_scores_gemma":[0.8499415,0.000015139879,0.13760173,0.0015021679,0.000051356124,0.000004027903,0.000034359626,0.00000568869,0.010844011],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99944043,0.00001423735,0.000111032714,0.00018965766,0.00014242886,0.00010219379],"domain_scores_gemma":[0.9994772,0.000013672134,0.000039463368,0.00037341987,0.00006267395,0.00003356857],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012121947,0.00005150279,0.00007259246,0.0001119882,0.00005419154,0.00019476615,0.00031368964,0.000020487087,0.0002511433],"category_scores_gemma":[0.000020957064,0.000040709314,0.00004861867,0.0013279923,0.000016075815,0.00058408396,0.00007741106,0.00006712538,0.00011417765],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000022649597,0.00020839945,0.010891689,0.0000085805805,0.00034947623,0.000006900906,0.0016934456,0.00048002112,0.0033871618,0.9233758,0.020055544,0.039540734],"study_design_scores_gemma":[0.00013159386,0.000023302757,0.0037063973,8.3488504e-7,0.00005074626,0.000003192899,0.000026396227,0.89693683,0.005062796,0.0039155,0.08997079,0.00017162364],"about_ca_topic_score_codex":0.000083048864,"about_ca_topic_score_gemma":0.00027733564,"teacher_disagreement_score":0.9194603,"about_ca_system_score_codex":0.0000044409326,"about_ca_system_score_gemma":0.000024296723,"threshold_uncertainty_score":0.2749843},"labels":[],"label_agreement":null},{"id":"W2100108891","doi":"10.1109/tvcg.2009.109","title":"A Comparison of User-Generated and Automatic Graph Layouts","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":99,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Graph; Graph drawing; Graph Layout; Task (project management); Human–computer interaction; Engineering drawing; Theoretical computer science; Computer graphics (images); Engineering","score_opus":0.029941843498478768,"score_gpt":0.32504779157195923,"score_spread":0.29510594807348045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2100108891","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037244834,0.000052573298,0.9620376,0.00008590767,0.00019257706,0.00013547004,0.000010466688,0.00021743291,0.000023131603],"genre_scores_gemma":[0.99539167,0.00019954013,0.00322517,0.0011129148,0.000015276584,0.0000030552037,0.000014538257,0.000009268066,0.000028562245],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986668,0.00010831809,0.00043978522,0.00034077474,0.00027982364,0.0001645026],"domain_scores_gemma":[0.9992102,0.000056991503,0.00015509165,0.00029206884,0.00015472727,0.00013092098],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001489478,0.0001890913,0.00028721293,0.0004856601,0.00021033992,0.00019602114,0.00023233838,0.00009545728,0.0000067839433],"category_scores_gemma":[0.0000026626728,0.00018529223,0.00005932461,0.0011498188,0.0000810298,0.00037307388,0.000004780134,0.00010853123,0.0000019800345],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008396993,0.00072747114,0.00045690686,0.000060344606,0.00005881296,0.0000020167895,0.0016799036,0.0011797387,0.00014583656,0.96211606,0.00051940524,0.03304509],"study_design_scores_gemma":[0.00049639307,0.00039439686,0.0017415681,0.000054324893,0.000028698383,0.00000793358,0.000029481438,0.99323946,0.0025982098,0.00091262953,0.00029618217,0.000200716],"about_ca_topic_score_codex":0.000005550048,"about_ca_topic_score_gemma":0.000007831333,"teacher_disagreement_score":0.9920597,"about_ca_system_score_codex":0.000007532596,"about_ca_system_score_gemma":0.000028053815,"threshold_uncertainty_score":0.7555998},"labels":[],"label_agreement":null},{"id":"W2101359516","doi":"10.3233/sju-2006-23401","title":"Data communication – Emerging international trends and practices of the Australian Bureau of Statistics","year":2007,"lang":"en","type":"article","venue":"Statistical Journal of the United Nations Economic Commission for Europe","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Statistics; Geography; Regional science; Library science; Computer science; Mathematics","score_opus":0.11670170714541203,"score_gpt":0.4368034371275509,"score_spread":0.3201017299821388,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101359516","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006596121,0.000030045037,0.98038816,0.012646123,0.00051690266,0.00009336866,0.0019556612,0.0000064321093,0.003703689],"genre_scores_gemma":[0.61172414,0.00048628682,0.3836029,0.00014558087,0.000097604716,6.7810697e-7,0.00052407756,0.000023030128,0.0033957383],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988638,0.00014716177,0.0006437786,0.00009013987,0.00018137097,0.000073711104],"domain_scores_gemma":[0.9962473,0.0012138009,0.0014936744,0.0005625345,0.00042457256,0.000058116853],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011590787,0.0000645252,0.0001185699,0.00058297307,0.00016121648,0.00006410373,0.0019642885,0.000022084585,0.00003517129],"category_scores_gemma":[0.0024022374,0.000041883184,0.000028151113,0.00070334855,0.00014076066,0.00032668078,0.00058853085,0.00013447371,4.4831106e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002155803,0.00008037641,0.0005294134,0.000014127002,0.000058988702,4.225794e-7,0.00014091577,0.00050821336,0.00013274982,0.9417674,0.040535692,0.016210137],"study_design_scores_gemma":[0.0006930781,0.000069313326,0.009777169,0.00010934182,0.00009925578,0.000035587407,0.00015454176,0.2312671,0.00036262104,0.010046133,0.7472931,0.000092731774],"about_ca_topic_score_codex":0.000029256427,"about_ca_topic_score_gemma":0.00006147712,"teacher_disagreement_score":0.93172127,"about_ca_system_score_codex":0.000024952926,"about_ca_system_score_gemma":0.000094577335,"threshold_uncertainty_score":0.36501694},"labels":[],"label_agreement":null},{"id":"W2101647284","doi":"10.1109/vis.2003.10030","title":"A Parallel Coordinates Interface for Exploratory Volume Visualization","year":2003,"lang":"en","type":"article","venue":"IEEE Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Volume rendering; Visualization; Rendering (computer graphics); Parallel coordinates; Data visualization; Computer graphics (images); Volume (thermodynamics); Undoing; Scientific visualization; Parallel rendering; Human–computer interaction; Computational science; Artificial intelligence","score_opus":0.03501979058141939,"score_gpt":0.3314202639472411,"score_spread":0.2964004733658217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101647284","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012811722,0.000119559765,0.99583673,0.00009897632,0.0013013226,0.00042408024,0.000014299083,0.00043150136,0.00049233215],"genre_scores_gemma":[0.96513367,0.00015264872,0.02897915,0.001075758,0.00020778361,0.00022890058,0.0003663384,0.00010896183,0.003746769],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99809444,0.00021041103,0.00048205673,0.0005428875,0.00032381606,0.00034641416],"domain_scores_gemma":[0.99856067,0.00010305714,0.00025146123,0.00048431597,0.00046847458,0.00013199738],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00054189074,0.00024160784,0.00023232322,0.00027203298,0.0002422931,0.00040072086,0.00050617,0.000121763755,0.00004996031],"category_scores_gemma":[0.0004375061,0.0002552703,0.00008515323,0.0010644738,0.000046434274,0.0013667183,0.000051128223,0.00005248998,0.00012342153],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025607475,0.0002383052,0.00048436446,0.0000704868,0.00004031613,0.0000010919863,0.00094976876,0.0034615933,0.0014294629,0.96140164,0.03079079,0.0011065437],"study_design_scores_gemma":[0.0017724523,0.0002915724,0.00003924714,0.000045060973,0.0000300205,0.0000035252801,0.00020840784,0.80839485,0.02071919,0.004017413,0.16395822,0.0005200533],"about_ca_topic_score_codex":0.0000031696618,"about_ca_topic_score_gemma":0.0000091470165,"teacher_disagreement_score":0.9668576,"about_ca_system_score_codex":0.0000817163,"about_ca_system_score_gemma":0.0001215027,"threshold_uncertainty_score":0.9999899},"labels":[],"label_agreement":null},{"id":"W2101654639","doi":"10.1109/infvis.1996.559220","title":"Minimally-immersive interactive volumetric information visualization","year":2002,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Visualization; Computer science; Information visualization; Human–computer interaction; CLARITY; Stereoscopy; Interactive visualization; Glyph (data visualization); Rendering (computer graphics); Visual analytics; Data visualization; Computer graphics (images); Artificial intelligence; Computer vision","score_opus":0.01873398284890919,"score_gpt":0.2746232690393303,"score_spread":0.2558892861904211,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101654639","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005002954,0.000013952749,0.965072,0.00035433818,0.00017968037,0.000073989395,0.0000032125681,0.00011009501,0.033692457],"genre_scores_gemma":[0.9786453,0.00007988828,0.012126173,0.0042978637,0.00004357281,0.000006233558,0.00009389725,0.0000067340725,0.00470034],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992654,0.00003025183,0.00021852851,0.00012895407,0.00022810604,0.00012880999],"domain_scores_gemma":[0.99936324,0.000043113814,0.000114441464,0.00022120707,0.00019581016,0.0000621708],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000079706835,0.00008015433,0.00007673313,0.000385125,0.0000713657,0.00029336335,0.00037308873,0.000033682372,0.00053368986],"category_scores_gemma":[0.00015186254,0.00007521215,0.000033068485,0.0012746922,0.000014135015,0.0038759338,0.00012581503,0.000042156647,0.0015422397],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005221947,0.00029221154,0.0012194007,0.000029562427,0.00006135826,0.00000458977,0.0069281133,0.00018712533,0.00018319109,0.60739523,0.22833717,0.15535685],"study_design_scores_gemma":[0.00021728927,0.000051553056,0.0003904596,0.000005479937,0.000004093498,0.0000032969253,0.00022413171,0.9177223,0.0008418338,0.00013160205,0.08028372,0.00012427903],"about_ca_topic_score_codex":0.00001010317,"about_ca_topic_score_gemma":0.0000017142733,"teacher_disagreement_score":0.978145,"about_ca_system_score_codex":0.00004237708,"about_ca_system_score_gemma":0.000010013349,"threshold_uncertainty_score":0.99923515},"labels":[],"label_agreement":null},{"id":"W2101792094","doi":"10.7202/502100ar","title":"De l’activité pharmacologique à l’usage des drogues : la construction des connaissances sur les psychotropes","year":2008,"lang":"fr","type":"article","venue":"Santé mentale au Québec","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Humanities; Political science; Art; Philosophy","score_opus":0.07126272512293423,"score_gpt":0.33006338163700893,"score_spread":0.2588006565140747,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101792094","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87364686,0.008781094,0.10952765,0.000883461,0.000739808,0.00019094831,0.000102337726,0.0002038571,0.005923982],"genre_scores_gemma":[0.98282236,0.0064657484,0.007372816,0.0005291682,0.00025801646,0.000018670013,0.00002436781,0.000025123281,0.0024837283],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976562,0.0006350153,0.00037786062,0.00048059307,0.00026707168,0.0005832521],"domain_scores_gemma":[0.99879366,0.00034306018,0.00021542738,0.000274538,0.00013916599,0.00023415087],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.00048310406,0.00030451445,0.0002951983,0.000119398515,0.0010148033,0.00024283526,0.0005455647,0.00014079124,0.00049821736],"category_scores_gemma":[0.0001269712,0.00031045562,0.00012808513,0.00042951305,0.004003956,0.0014756175,0.00016020893,0.0002306958,0.000083543964],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006128165,0.0010502626,0.23659919,0.0003256545,0.00025968946,0.00031074497,0.014042604,0.00012340824,0.011842208,0.0272897,0.008600705,0.69949454],"study_design_scores_gemma":[0.004041698,0.00093283213,0.19400749,0.001336624,0.0003392231,0.0046183188,0.0078073204,0.03878967,0.15168081,0.0041827597,0.5901801,0.002083147],"about_ca_topic_score_codex":0.05149284,"about_ca_topic_score_gemma":0.032399874,"teacher_disagreement_score":0.6974114,"about_ca_system_score_codex":0.00062021293,"about_ca_system_score_gemma":0.0012698679,"threshold_uncertainty_score":0.99993473},"labels":[],"label_agreement":null},{"id":"W2102070657","doi":"10.1190/1.3046455","title":"A visual data-mining methodology for seismic facies analysis: Part 1 — Testing and comparison with other unsupervised clustering methods","year":2009,"lang":"en","type":"article","venue":"Geophysics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":72,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"ConocoPhillips (Canada); Université de Montréal; McGill University; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Cluster analysis; Computer science; Data mining; Pattern recognition (psychology); Unsupervised learning; Partition (number theory); Artificial intelligence; Mathematics","score_opus":0.2344927660496599,"score_gpt":0.4381798834007329,"score_spread":0.20368711735107298,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102070657","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008723818,0.000050405655,0.9906624,0.00016736465,0.000049835937,0.0001196103,0.000031384163,0.00012136606,0.00007384184],"genre_scores_gemma":[0.085337676,0.0000032026967,0.9133664,0.0010641898,0.000075802105,0.0000052898963,0.0000719831,0.000010287668,0.00006517311],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985285,0.00022893309,0.00028644098,0.0005282483,0.00014522977,0.00028268903],"domain_scores_gemma":[0.9982838,0.0007518907,0.00017109665,0.00061051466,0.0001070817,0.00007561982],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008687483,0.00017295811,0.00042803484,0.00012975425,0.00017590343,0.00025124213,0.0006029233,0.000044394637,0.0000022092602],"category_scores_gemma":[0.00019387374,0.00014856746,0.000039889823,0.0010726247,0.000048049387,0.00050256314,0.0002862382,0.00007629259,0.000001612092],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003898782,0.0002041165,0.004989314,0.000080570484,0.0007551625,0.0000036108972,0.003442896,0.02741712,0.002166605,0.0058452124,0.0003511224,0.9547053],"study_design_scores_gemma":[0.00029945988,0.00018685187,0.0017055385,0.00001758259,0.0002553527,0.0000028363477,0.00024772328,0.9939262,0.00022709275,0.0008284242,0.0020974646,0.00020546783],"about_ca_topic_score_codex":0.000027210057,"about_ca_topic_score_gemma":0.000017824541,"teacher_disagreement_score":0.9665091,"about_ca_system_score_codex":0.000009507101,"about_ca_system_score_gemma":0.000042108022,"threshold_uncertainty_score":0.6058405},"labels":[],"label_agreement":null},{"id":"W2103937287","doi":"10.1109/imtc.2011.5944177","title":"An environment for visualizing higher dimensional measured data","year":2011,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Instrumentation (computer programming); Graphics; Curse of dimensionality; Software; Rendering (computer graphics); Dimensionality reduction; Multidimensional data; Raw data; Dimension (graph theory); Data acquisition; Data mining; Computer graphics (images); Artificial intelligence","score_opus":0.20592833549727985,"score_gpt":0.34564201329671695,"score_spread":0.1397136777994371,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103937287","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00014729303,0.000017209832,0.99824125,0.00011878155,0.0001503601,0.00007877926,0.000027083483,0.00009952375,0.0011196976],"genre_scores_gemma":[0.27172711,0.000009629265,0.7223577,0.0028860099,0.000111288544,0.0000098618475,0.00056042324,0.000020056868,0.0023179264],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913305,0.000026828096,0.00013794689,0.00035883268,0.00020413498,0.00013923178],"domain_scores_gemma":[0.99877113,0.000017138962,0.000039525275,0.0010548433,0.000023058818,0.00009428447],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028709805,0.00007408086,0.00007302148,0.000035510024,0.0000747607,0.00006763492,0.0011455861,0.000025298044,0.00035077636],"category_scores_gemma":[0.00000943935,0.00006147202,0.00001734145,0.00006399084,0.00001880285,0.00080531,0.0003596559,0.000021240061,0.00007726241],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010734586,0.00063533674,0.0005785341,0.000011898139,0.000047882044,0.000004102684,0.00034703987,0.00004087416,0.002125914,0.9423825,0.037291545,0.016523618],"study_design_scores_gemma":[0.00048542256,0.00013945295,0.0023989389,0.0000069014613,0.000018023049,0.0000021962428,0.000020424157,0.746398,0.002682958,0.0033284787,0.24421795,0.00030130436],"about_ca_topic_score_codex":0.000016087182,"about_ca_topic_score_gemma":0.00000352268,"teacher_disagreement_score":0.9390541,"about_ca_system_score_codex":0.000009798454,"about_ca_system_score_gemma":0.000019509951,"threshold_uncertainty_score":0.38407552},"labels":[],"label_agreement":null},{"id":"W2104757564","doi":"10.1109/iccv.1990.139620","title":"From uncertainty to visual exploration","year":2002,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Ambiguity; Interpretation (philosophy); Context (archaeology); Representation (politics); Computer science; Perception; Artificial intelligence; Epistemology; Geography; Philosophy","score_opus":0.05623992470097005,"score_gpt":0.31670586928948447,"score_spread":0.2604659445885144,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104757564","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001514338,0.0000045583074,0.9898023,0.0030705489,0.00012817375,0.00003641638,0.0000029807743,0.00014660103,0.005294107],"genre_scores_gemma":[0.93228674,0.000015642438,0.04964992,0.00957306,0.00022794816,0.000007063091,0.000051943895,0.000007206744,0.008180494],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99948514,0.00001702751,0.00009630106,0.00017269478,0.00014271997,0.000086120184],"domain_scores_gemma":[0.9996379,0.000018564917,0.000016422619,0.00021234532,0.00003734164,0.00007742119],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000041838884,0.000047376332,0.000048552967,0.000047611626,0.000039540082,0.00017055114,0.00028301627,0.000015851938,0.00061377],"category_scores_gemma":[0.000027311486,0.000041108597,0.000014813635,0.00030386075,0.0000047761273,0.00055601896,0.00009742011,0.000019390898,0.0017767587],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001972356,0.0002627137,0.00018356467,0.0000026069945,0.000018170342,0.000008509254,0.004623168,0.0035225174,0.0010547003,0.316364,0.48058313,0.19337496],"study_design_scores_gemma":[0.00007928564,0.000027330787,0.000038453098,0.0000024767226,0.000001056199,1.7420862e-7,0.00007417947,0.9281634,0.00064234703,0.0015841551,0.0693078,0.00007932949],"about_ca_topic_score_codex":0.000060042494,"about_ca_topic_score_gemma":0.000022083143,"teacher_disagreement_score":0.94015235,"about_ca_system_score_codex":0.000012437598,"about_ca_system_score_gemma":0.000004292296,"threshold_uncertainty_score":0.9990005},"labels":[],"label_agreement":null},{"id":"W2105893525","doi":"10.1109/tvcg.2007.70521","title":"VisLink: Revealing Relationships Amongst Visualizations","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":198,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Pennsylvania","keywords":"Computer science; Visualization; Bridging (networking); Data visualization; Reuse; Human–computer interaction; Variety (cybernetics); Information visualization; Encoding (memory); Space (punctuation); Theoretical computer science; Information retrieval; Data mining; Artificial intelligence","score_opus":0.03493980262763771,"score_gpt":0.30094535984903653,"score_spread":0.26600555722139885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105893525","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002234552,0.000036710193,0.99564105,0.00010731195,0.0007867506,0.00025611182,0.000016014259,0.0006446398,0.00027683497],"genre_scores_gemma":[0.9891308,0.00026952394,0.007484261,0.0025720296,0.00013291961,0.000012452678,0.00006436954,0.000045702764,0.00028794803],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975157,0.00020598793,0.0007126665,0.00064171024,0.00052209507,0.00040188586],"domain_scores_gemma":[0.9982494,0.0003244351,0.0002114152,0.00056750275,0.000337762,0.00030944767],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010250721,0.00031095126,0.00025616487,0.0009695724,0.001031398,0.00046683138,0.0004652194,0.00021637017,0.00002179016],"category_scores_gemma":[0.000019178007,0.0003314903,0.00012226796,0.0024272928,0.00012677924,0.0008809992,0.000013366036,0.00035250417,0.00003540849],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008040133,0.00026010862,0.00027906612,0.00002565563,0.000042006115,0.0000062640415,0.0008948974,0.0007591797,0.00001874365,0.99168605,0.00044134367,0.0055786776],"study_design_scores_gemma":[0.0005918076,0.00014739663,0.0009929527,0.00006519884,0.000038065675,0.000027361306,0.000101421494,0.98962116,0.0014889666,0.0017280002,0.004745334,0.00045231788],"about_ca_topic_score_codex":0.0000136525605,"about_ca_topic_score_gemma":0.000066587105,"teacher_disagreement_score":0.989958,"about_ca_system_score_codex":0.00004589694,"about_ca_system_score_gemma":0.000054257536,"threshold_uncertainty_score":0.9999137},"labels":[],"label_agreement":null},{"id":"W2106330775","doi":"10.1145/1377966.1377975","title":"Qualitative analysis of visualization","year":2008,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of Victoria","funders":"","keywords":"Visualization; Data visualization; Field (mathematics); Qualitative analysis; Computer science; Quantitative analysis (chemistry); Complement (music); Qualitative research; Data science; Qualitative property; Human–computer interaction; Management science; Artificial intelligence; Engineering; Sociology; Mathematics","score_opus":0.07679500683181842,"score_gpt":0.427493996788126,"score_spread":0.35069898995630755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106330775","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0071270214,0.000010572042,0.9883472,0.00005705417,0.000020209358,0.000018499017,0.0000044447,0.000053910804,0.004361132],"genre_scores_gemma":[0.9827485,0.000037657825,0.01549691,0.00029828682,0.0000043553387,7.418346e-7,0.000052317075,0.0000020311777,0.0013592193],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99938023,0.00006725033,0.00018320969,0.00012231688,0.00018703139,0.000059961065],"domain_scores_gemma":[0.9994715,0.00005752112,0.000077797726,0.0002268675,0.00013596384,0.000030351022],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015685202,0.000040786315,0.00012572632,0.00032130483,0.000038706406,0.0000127351595,0.0002455512,0.0000156831,0.00009574624],"category_scores_gemma":[0.00005308142,0.00003510814,0.00005956114,0.0025922665,0.00003366026,0.0002651691,0.00005429089,0.0000116562005,0.000015301337],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.56962e-7,0.00006107865,0.0012283121,0.0000025232841,0.00018921927,0.0000010172666,0.010717536,0.0004145619,0.00010283102,0.9852479,0.0016639071,0.00037057538],"study_design_scores_gemma":[0.00011241615,0.000028424914,0.0036279773,0.0000017856149,0.00007658444,8.097036e-7,0.00053504365,0.9911111,0.0020117594,0.00070943584,0.0016881602,0.000096499134],"about_ca_topic_score_codex":0.000023293282,"about_ca_topic_score_gemma":0.000007693492,"teacher_disagreement_score":0.99069655,"about_ca_system_score_codex":0.00000554249,"about_ca_system_score_gemma":0.00002411028,"threshold_uncertainty_score":0.14316684},"labels":[],"label_agreement":null},{"id":"W2106669190","doi":"10.1109/tvcg.2006.177","title":"Smashing Peacocks Further: Drawing Quasi-Trees from Biconnected Components","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"","keywords":"Computer science; Biconnected graph; Tree (set theory); Graph; Theoretical computer science; Node (physics); Block graph; Combinatorics; Mathematics; Line graph; Pathwidth","score_opus":0.01948905818129087,"score_gpt":0.26103984502140104,"score_spread":0.24155078684011017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106669190","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.046982903,0.000047680343,0.95136917,0.00011894482,0.00069635554,0.00014478026,0.000042307078,0.00054644624,0.000051411884],"genre_scores_gemma":[0.9956403,0.00010330178,0.0026702357,0.001200359,0.00012989627,0.000008426148,0.0001483708,0.000030285768,0.0000688404],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980076,0.00018788966,0.0004817386,0.00060629164,0.0004315939,0.00028488017],"domain_scores_gemma":[0.9989242,0.00016905332,0.00016032398,0.00045333317,0.00015655336,0.00013651385],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016331678,0.0002938991,0.00026952632,0.00050577824,0.00048498335,0.0006839001,0.00046330225,0.00013945572,0.000027642945],"category_scores_gemma":[0.0000027232588,0.00030378127,0.00011654053,0.0010493153,0.00008070556,0.00071548816,0.000012973643,0.00019461715,0.000020505368],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027460857,0.001673084,0.0018588396,0.000041799296,0.00018164756,0.000021053176,0.0028995587,0.0054059504,0.0006583152,0.97224575,0.0010507206,0.013935797],"study_design_scores_gemma":[0.00075764704,0.00010769608,0.0023646955,0.0000724844,0.000032182536,0.0000064412134,0.000052570944,0.99142116,0.001322751,0.0019446502,0.0015435775,0.00037416586],"about_ca_topic_score_codex":0.00032022962,"about_ca_topic_score_gemma":0.00023750198,"teacher_disagreement_score":0.9860152,"about_ca_system_score_codex":0.00002941335,"about_ca_system_score_gemma":0.000034317356,"threshold_uncertainty_score":0.9999414},"labels":[],"label_agreement":null},{"id":"W2106796612","doi":"10.1111/j.1467-8659.2009.01457.x","title":"Comparing Parameter Manipulation with Mouse, Pen, and Slider User Interfaces","year":2009,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Gaze; Task (project management); Human–computer interaction; Fixation (population genetics); Artificial intelligence; Eye tracking; Slider; Computer vision; Computer graphics (images)","score_opus":0.03312300361996709,"score_gpt":0.27122028456106917,"score_spread":0.23809728094110208,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106796612","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09674425,0.000040546955,0.90179336,0.0009003829,0.00010117989,0.000102916776,0.000001159048,0.00016856832,0.00014766106],"genre_scores_gemma":[0.96272916,0.000022192564,0.03449666,0.0025998435,0.000030396019,0.0000015219156,0.000018333705,0.000008930029,0.000092973416],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988983,0.00003525425,0.00021631696,0.00037515993,0.00021574151,0.00025920972],"domain_scores_gemma":[0.99926686,0.00004143765,0.00009406486,0.00041572735,0.000084743195,0.00009715037],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000116260795,0.00017020229,0.00018467543,0.00019629685,0.0001439404,0.0005606343,0.00045872663,0.00005138714,0.0000024358717],"category_scores_gemma":[0.0000047092853,0.00014132017,0.00003287948,0.00038390543,0.000050764265,0.00080800086,0.0002144876,0.00012381714,0.000007749779],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011867947,0.000121901314,0.06348959,0.00001930758,0.000050072875,0.000011490324,0.00039879078,0.0008107851,0.00004307696,0.91676694,0.0057886993,0.0124874795],"study_design_scores_gemma":[0.00047994958,0.0002648595,0.027315618,0.00004270365,0.000011039493,0.000028398805,0.000016747446,0.9602494,0.00038443712,0.0061549353,0.004757177,0.00029468344],"about_ca_topic_score_codex":0.0000068742297,"about_ca_topic_score_gemma":0.00003093287,"teacher_disagreement_score":0.9594387,"about_ca_system_score_codex":0.000009854166,"about_ca_system_score_gemma":0.000011888517,"threshold_uncertainty_score":0.576287},"labels":[],"label_agreement":null},{"id":"W2107330811","doi":"10.1111/j.1467-8659.2012.03116.x","title":"Vismon: Facilitating Analysis of Trade‐Offs, Uncertainty, and Sensitivity In Fisheries Management Decision Making","year":2012,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":89,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"Simon Fraser University","keywords":"Workflow; Computer science; Abstraction; Sensitivity (control systems); Domain (mathematical analysis); Fisheries management; Visualization; Process (computing); Task (project management); Software deployment; Set (abstract data type); Software; Operations research; Decision support system; Data science; Data mining; Software engineering; Systems engineering; Fishery; Database; Engineering","score_opus":0.02690897417958446,"score_gpt":0.2910131301086708,"score_spread":0.2641041559290863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107330811","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11559318,0.00009470013,0.8837719,0.00019754088,0.00014711937,0.00007769112,0.000012776434,0.000037758895,0.00006733482],"genre_scores_gemma":[0.9514052,0.000051866697,0.048003063,0.0005002552,0.0000121785015,0.0000017376955,0.000018349272,0.000004530769,0.000002789291],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987112,0.0000911106,0.00034065076,0.00028550182,0.0002693027,0.00030218958],"domain_scores_gemma":[0.9991455,0.00026445914,0.00011181873,0.00037624894,0.00003163824,0.000070352646],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068442296,0.00013542648,0.00028420627,0.00072599895,0.000084644635,0.00011019109,0.00021340641,0.000049001243,0.0000022490742],"category_scores_gemma":[0.000014917213,0.00013273365,0.00010089462,0.0020297475,0.000070246555,0.0005566331,0.00051549706,0.0000849258,6.630169e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007133371,0.00014334488,0.51451874,0.000066776774,0.00029016696,0.00001870846,0.00205465,0.0032995117,0.0000044800413,0.3412755,0.00056519907,0.13775575],"study_design_scores_gemma":[0.00014041961,0.0000203904,0.22742742,0.00005000092,0.0000526531,0.0000028282277,0.00013158616,0.7694295,0.000005910687,0.0018594634,0.0007511678,0.00012866975],"about_ca_topic_score_codex":0.000016888966,"about_ca_topic_score_gemma":0.00013843105,"teacher_disagreement_score":0.83581203,"about_ca_system_score_codex":0.000017339287,"about_ca_system_score_gemma":0.000006422476,"threshold_uncertainty_score":0.5412721},"labels":[],"label_agreement":null},{"id":"W2107407906","doi":"10.1109/iv.2005.154","title":"Visualizing time dependent semantics: an application to quantum algorithms","year":2005,"lang":"en","type":"article","venue":"Ninth International Conference on Information Visualisation (IV'05)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Semantics (computer science); Computer science; Syntax; Visualization; Algorithm; Theoretical computer science; Natural language processing; Artificial intelligence; Programming language","score_opus":0.04229939058308692,"score_gpt":0.3504658843972832,"score_spread":0.3081664938141963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107407906","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003561848,0.0000020197524,0.9794582,0.007479389,0.00071629434,0.0005109027,0.00013739175,0.0005062217,0.0076277046],"genre_scores_gemma":[0.9714808,0.000023329983,0.013990612,0.011297266,0.0003962073,0.00011816355,0.0018741385,0.000026463464,0.0007930073],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9963113,0.00015135511,0.0011212269,0.0005311993,0.0014953763,0.00038951958],"domain_scores_gemma":[0.99696124,0.0000759899,0.00061856647,0.0007080892,0.0012849446,0.00035119106],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00097047933,0.0003555315,0.000271613,0.0008980815,0.00029517923,0.0015773821,0.0015662045,0.00016035646,0.00067897065],"category_scores_gemma":[0.00022832035,0.00037343602,0.00008821785,0.00058221427,0.000050438848,0.0077301846,0.0002261901,0.0002422217,0.0049992106],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003789273,0.00023388404,0.00010599491,0.000015737682,0.000045725636,0.0000012222614,0.0031028981,0.0080978945,0.0008425955,0.91006494,0.005908997,0.07154222],"study_design_scores_gemma":[0.00069229293,0.00022643978,0.00040711445,0.0000528464,0.000010707017,0.000013754953,0.00037114858,0.93620366,0.0016160662,0.0013600183,0.058608007,0.00043795045],"about_ca_topic_score_codex":0.000063032196,"about_ca_topic_score_gemma":0.000023443303,"teacher_disagreement_score":0.967919,"about_ca_system_score_codex":0.00036981888,"about_ca_system_score_gemma":0.00020916537,"threshold_uncertainty_score":0.99987173},"labels":[],"label_agreement":null},{"id":"W2108732829","doi":"10.1117/12.840329","title":"Visualizing search results: evaluating an iconic visualization","year":2009,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Visualization; Usability; Task (project management); Sorting; Information retrieval; Process (computing); User satisfaction; Human–computer interaction; Data visualization; Exploratory search; World Wide Web; Data mining","score_opus":0.03335924902147688,"score_gpt":0.32747708624760546,"score_spread":0.2941178372261286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108732829","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9885446,0.00004973792,0.006687854,0.0022724601,0.00017905571,0.00041580733,0.000034533932,0.00021034184,0.0016056101],"genre_scores_gemma":[0.6505607,0.00014042122,0.34734112,0.00078183075,0.0006443551,0.000047129444,0.00008167565,0.00006887739,0.00033394634],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9968051,5.8883643e-8,0.00095435214,0.00058759074,0.0011958302,0.00045711576],"domain_scores_gemma":[0.9965705,0.00013330349,0.00046376375,0.00013000355,0.0025256835,0.00017671754],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0018922375,0.00029961727,0.0003628571,0.00019174286,0.00016561741,0.00048368075,0.0019779152,0.00016333094,0.0000056900108],"category_scores_gemma":[0.0010301967,0.0002646657,0.00037318564,0.00085726805,0.0001168193,0.0019328467,0.0002414816,0.0002475668,0.0000025626118],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003663252,0.00015798194,0.000051053772,0.00010521281,0.00008975827,6.817465e-8,0.00048548877,0.00036258163,0.2401563,0.7558328,0.0010876857,0.0016344222],"study_design_scores_gemma":[0.0012666115,0.00088769704,0.00053795346,0.0002751887,0.00006897084,0.000011305051,0.0009817127,0.9080127,0.08310227,0.003045046,0.0014178358,0.00039270837],"about_ca_topic_score_codex":0.0000063473935,"about_ca_topic_score_gemma":1.0808218e-7,"teacher_disagreement_score":0.9076501,"about_ca_system_score_codex":0.00015829074,"about_ca_system_score_gemma":0.000077245764,"threshold_uncertainty_score":0.99998057},"labels":[],"label_agreement":null},{"id":"W2108749458","doi":"10.1109/iv.2006.84","title":"Plot-polling: Collaborative Knowledge Visualization for Online Discussions","year":2006,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Polling; Plot (graphics); Computer science; Visualization; Construct (python library); Mood; Online discussion; World Wide Web; Human–computer interaction; Multimedia; Data science; Psychology; Artificial intelligence; Social psychology","score_opus":0.02677540801997335,"score_gpt":0.3506192336648707,"score_spread":0.32384382564489733,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108749458","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00020637822,0.00006972633,0.9940822,0.00084537594,0.00018003734,0.00019953588,0.000089749024,0.0002453152,0.004081684],"genre_scores_gemma":[0.48102713,0.000095945405,0.42956942,0.0019702152,0.0010462168,0.00009498719,0.0037617597,0.00007818689,0.082356125],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991866,0.000036478155,0.00023784352,0.00025555276,0.000119997734,0.0001635634],"domain_scores_gemma":[0.999234,0.00007384159,0.00007707807,0.00024675246,0.00031010024,0.000058221045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010736115,0.00010276337,0.00011512552,0.00011488522,0.00017241968,0.00018050356,0.0003448619,0.000041280702,0.00002280192],"category_scores_gemma":[0.00006510247,0.00007586903,0.00004062031,0.00092362694,0.000025281608,0.0004043398,0.0000978349,0.000025636215,0.000031621672],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000013788409,0.00027781466,0.00006613742,0.0000071435466,0.0000049166188,2.480664e-7,0.00012817138,0.00014245459,0.0002104235,0.96114576,0.0359614,0.002054166],"study_design_scores_gemma":[0.00045026976,0.00005875361,0.00026582216,0.000014543332,0.000009056883,5.6038033e-7,0.00012020428,0.706679,0.0022957525,0.007501116,0.28242496,0.00018000537],"about_ca_topic_score_codex":0.000009726027,"about_ca_topic_score_gemma":0.00016785004,"teacher_disagreement_score":0.95364463,"about_ca_system_score_codex":0.000025730516,"about_ca_system_score_gemma":0.000100163226,"threshold_uncertainty_score":0.3093849},"labels":[],"label_agreement":null},{"id":"W2109113588","doi":"10.1145/1133265.1133348","title":"Line graph explorer","year":2006,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":82,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Metadata; Visualization; Graph; Graph database; Data visualization; Scalability; Graph drawing; Cluster analysis; Context (archaeology); Data mining; Information retrieval; Theoretical computer science; Artificial intelligence; World Wide Web; Database","score_opus":0.029451849543532267,"score_gpt":0.2853591389277265,"score_spread":0.25590728938419427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2109113588","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00048519776,0.000011268113,0.9744655,0.00066000066,0.000067846384,0.000013369877,6.535835e-7,0.00015137543,0.024144826],"genre_scores_gemma":[0.87244314,0.000019364226,0.10255727,0.004271908,0.00019581302,0.000003326774,0.00004820623,0.0000083238165,0.020452676],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99965537,0.000006217929,0.000075741315,0.00010072517,0.00008899136,0.00007293367],"domain_scores_gemma":[0.9997313,0.0000066641196,0.00001369149,0.00020117906,0.0000255368,0.000021600574],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000439826,0.000033572927,0.000033675537,0.000045286157,0.000025860734,0.00008288857,0.00025311523,0.000010685301,0.000076817014],"category_scores_gemma":[0.00000383789,0.000026388194,0.000018243543,0.00024976284,0.000008756541,0.00022704169,0.00006250903,0.000015202288,0.00017950953],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.9613984e-8,0.000028657492,0.00024714667,8.0224834e-7,0.0000010292118,0.0000017984511,0.000013231621,0.00006766165,0.00007638827,0.9515635,0.046271525,0.0017282048],"study_design_scores_gemma":[0.0004643949,0.000052651107,0.0027294732,0.000007184479,0.0000047416574,0.0000068413874,0.000030697895,0.48487362,0.011739048,0.105998375,0.39374584,0.00034713576],"about_ca_topic_score_codex":0.000018162555,"about_ca_topic_score_gemma":0.000007949224,"teacher_disagreement_score":0.8719579,"about_ca_system_score_codex":0.0000026868738,"about_ca_system_score_gemma":0.0000068645368,"threshold_uncertainty_score":0.23072916},"labels":[],"label_agreement":null},{"id":"W2109247805","doi":"10.1109/tvcg.2008.197","title":"A Novel Visualization Technique for Electric Power Grid Analytics","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":92,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Office of Electricity Delivery and Energy Reliability; U.S. Department of Energy","keywords":"Visualization; Blackout; Computer science; Usability; Electricity; Data visualization; Grid; Electric power; Electric power industry; Geographic information system; Electric power system; Data science; Strengths and weaknesses; Information visualization; Visual analytics; Systems engineering; Human–computer interaction; Data mining; Power (physics); Electrical engineering; Engineering","score_opus":0.028992174654981603,"score_gpt":0.29331128485384517,"score_spread":0.26431911019886356,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2109247805","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00052442704,0.000024130757,0.99770105,0.000058670867,0.00059338793,0.0006059466,0.000048073125,0.00040748183,0.000036845628],"genre_scores_gemma":[0.9723432,0.0009550109,0.021208124,0.0045967055,0.00018217531,0.00019776731,0.00014103121,0.00009200166,0.0002839883],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979697,0.000080745514,0.0005320334,0.0006399049,0.00043152078,0.0003461116],"domain_scores_gemma":[0.9985494,0.00013903434,0.00019460227,0.000471059,0.00045449683,0.00019141921],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00028038313,0.00032147494,0.00030290516,0.00095349556,0.0006845258,0.00022039104,0.0004399257,0.00019640107,0.000010820493],"category_scores_gemma":[0.000011232184,0.0003343214,0.00016394726,0.0022537427,0.00008982162,0.00063138467,0.000009423609,0.00015867755,0.0000063359307],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026571452,0.00087731454,0.00005380588,0.00005872591,0.000096846794,0.0000043199757,0.00057739485,0.0016938027,0.0010010643,0.99246687,0.0022194032,0.0009238658],"study_design_scores_gemma":[0.0008532159,0.00047722098,0.000121700294,0.000036032463,0.000036126163,0.000098457145,0.000010857577,0.9824973,0.010606006,0.0005036459,0.004337747,0.0004216928],"about_ca_topic_score_codex":0.000007698781,"about_ca_topic_score_gemma":0.0000055230853,"teacher_disagreement_score":0.99196327,"about_ca_system_score_codex":0.000044639186,"about_ca_system_score_gemma":0.00011772456,"threshold_uncertainty_score":0.9999109},"labels":[],"label_agreement":null},{"id":"W2109857088","doi":"10.1109/tvcg.2010.129","title":"A Visual Backchannel for Large-Scale Events","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":203,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Conversation; Popularity; Context (archaeology); Social media; Event (particle physics); Visual analytics; Tag cloud; Visualization; Human–computer interaction; World Wide Web; Scale (ratio); Set (abstract data type); Data science; Multimedia; Artificial intelligence","score_opus":0.016095501594756315,"score_gpt":0.2968375878906359,"score_spread":0.2807420862958796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2109857088","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0054889726,0.0000058408364,0.9921928,0.000106951295,0.0015415396,0.00029953042,0.00005760498,0.0002816883,0.000025077423],"genre_scores_gemma":[0.98340887,0.00011202504,0.011801081,0.0039779106,0.00020224112,0.0000675465,0.00007665146,0.000044396445,0.0003092586],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99850893,0.00005777535,0.00032996078,0.000510028,0.00029013347,0.0003031656],"domain_scores_gemma":[0.999021,0.00009564264,0.000102472375,0.00035406102,0.00023004417,0.00019679645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029276172,0.00022464382,0.00020063663,0.00038597226,0.00046918704,0.00023969574,0.00037658555,0.00015430101,0.000022488022],"category_scores_gemma":[0.0000044547905,0.00022717228,0.00012742187,0.0007441556,0.00004188422,0.00047179192,0.000009516832,0.00019983943,0.00001478571],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001793447,0.0008000872,0.0000928113,0.000048729682,0.00004952871,0.0000010350212,0.00084787834,0.00014733747,0.00009640479,0.990495,0.0009558774,0.006447358],"study_design_scores_gemma":[0.0009589028,0.00022605929,0.00013987358,0.000019443723,0.000021557096,0.000010311073,0.000029266823,0.98513734,0.0014366371,0.0016346123,0.010109431,0.00027656986],"about_ca_topic_score_codex":0.0000033382807,"about_ca_topic_score_gemma":0.00006240618,"teacher_disagreement_score":0.9888604,"about_ca_system_score_codex":0.0000089057185,"about_ca_system_score_gemma":0.00004718191,"threshold_uncertainty_score":0.92638165},"labels":[],"label_agreement":null},{"id":"W2110028027","doi":"10.1109/infovis.2004.47","title":"Metric-Based Network Exploration and Multiscale Scatterplot","year":2004,"lang":"en","type":"article","venue":"IEEE Symposium on Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Computer science; Artificial intelligence; Metric (unit); Image (mathematics); Image segmentation; Segmentation; Process (computing); Pattern recognition (psychology); Image processing; Computer vision; Data mining; Engineering","score_opus":0.01762289522549168,"score_gpt":0.2818441891413416,"score_spread":0.2642212939158499,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110028027","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012077024,0.000008191715,0.99497193,0.0015798854,0.00056930986,0.00029811158,0.000010595722,0.00037398824,0.0009802892],"genre_scores_gemma":[0.9787383,0.00010560472,0.012099587,0.008137405,0.00017397663,0.00005514853,0.0006111644,0.000021825688,0.00005696873],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984193,0.00006830095,0.00053536636,0.00023810714,0.0004965408,0.00024239588],"domain_scores_gemma":[0.9988898,0.00005135273,0.0003054396,0.00037323622,0.00025403427,0.00012614252],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035406195,0.00019329529,0.00015604583,0.00048728235,0.00029072535,0.00066562113,0.00030027516,0.00009919718,0.000007465823],"category_scores_gemma":[0.000059798655,0.00019306861,0.00004145414,0.0013685449,0.000037205515,0.0054273587,0.00004816619,0.00007434841,0.00021109018],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016108244,0.00011537108,0.00029118103,0.000056629564,0.0000133739895,7.75488e-7,0.0012307417,0.63401365,0.00021193006,0.35709918,0.002826064,0.004124994],"study_design_scores_gemma":[0.001739195,0.00025713956,0.0004451991,0.00009602364,0.000014913442,0.0000039424035,0.000055856002,0.97335243,0.009440141,0.0023892238,0.01182034,0.00038562383],"about_ca_topic_score_codex":0.000016568833,"about_ca_topic_score_gemma":0.000005421089,"teacher_disagreement_score":0.98287237,"about_ca_system_score_codex":0.00010757292,"about_ca_system_score_gemma":0.000086462256,"threshold_uncertainty_score":0.78731096},"labels":[],"label_agreement":null},{"id":"W2110576593","doi":"10.2312/vissym/eurovis07/051-058","title":"Visualization of Uncertainty in Lattices to Support Decision-Making","year":2007,"lang":"en","type":"article","venue":"Eurographics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; University of Toronto","funders":"","keywords":"Visualization; Computer science; Lattice (music); Data visualization; Data mining; Theoretical computer science; Artificial intelligence; Machine learning","score_opus":0.029561166881082793,"score_gpt":0.3650959281593256,"score_spread":0.33553476127824283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110576593","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06716674,0.000015940825,0.93123305,0.00005807737,0.00017433887,0.00008503027,0.0000030648334,0.00006113914,0.001202632],"genre_scores_gemma":[0.98073566,0.00001943494,0.018432064,0.0007667053,0.000017952607,6.817917e-7,0.000008381456,0.000007111993,0.000012008236],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882907,0.000032665146,0.00037591145,0.00022430651,0.0003443088,0.00019375635],"domain_scores_gemma":[0.9991336,0.00023089346,0.00010732529,0.0003202107,0.00013568361,0.00007229125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000972972,0.000080292295,0.00011726183,0.00064106873,0.000035814315,0.00006879081,0.0005245622,0.000039192808,0.00001437517],"category_scores_gemma":[0.00029446784,0.000079987105,0.000040400453,0.0029429446,0.000029059516,0.00026107518,0.00016163048,0.000053823172,0.000011252652],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002312973,0.00028929178,0.10998158,0.00003501047,0.00001387509,0.00005089363,0.0019413636,0.0044072126,0.00015947653,0.7255895,0.0010538455,0.1564548],"study_design_scores_gemma":[0.0017914814,0.001353958,0.34342766,0.00079516135,0.000039095175,0.000027691041,0.0007353922,0.48140284,0.0012049646,0.029255187,0.13861515,0.0013514094],"about_ca_topic_score_codex":0.0000080993605,"about_ca_topic_score_gemma":0.00019613784,"teacher_disagreement_score":0.9135689,"about_ca_system_score_codex":0.000011168316,"about_ca_system_score_gemma":0.000033518867,"threshold_uncertainty_score":0.32617795},"labels":[],"label_agreement":null},{"id":"W2110615044","doi":"10.1145/2076354.2076390","title":"<i>\"Point it, split it, peel it, view it\"</i>","year":2011,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Immediacy; Visualization; Flexibility (engineering); Domain (mathematical analysis); Point (geometry); Process (computing); Reservoir engineering; Human–computer interaction; Drilling engineering; Representation (politics); Data visualization; Data science; Drilling; Artificial intelligence; Geology; Engineering; Petroleum","score_opus":0.07709404704964605,"score_gpt":0.3110517060422177,"score_spread":0.23395765899257165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110615044","genre_codex":"methods","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000038140348,0.000040280185,0.70973724,0.010413186,0.00030173134,0.00010560434,0.000008086261,0.00018812063,0.2791676],"genre_scores_gemma":[0.09435396,0.0013625439,0.3023742,0.36475015,0.00044732323,0.000038289207,0.00012672838,0.00008934384,0.23645745],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983993,0.000054458367,0.00040727132,0.0004584339,0.00034517725,0.0003353384],"domain_scores_gemma":[0.99858564,0.000041268657,0.000101444886,0.0009378852,0.0001311828,0.0002025926],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00042440332,0.00018458178,0.00021242966,0.00009363873,0.00010994507,0.00021766245,0.0012812669,0.00006026964,0.0021513968],"category_scores_gemma":[0.00005955981,0.00015252104,0.00009772166,0.00049027574,0.000052496973,0.00076205685,0.0005141841,0.000103763945,0.002540652],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000014692074,0.00013425814,0.00009662885,0.000023859293,0.000015618154,0.000015910138,0.0009010825,0.0000026017294,0.000024403598,0.3291193,0.6644944,0.0051704934],"study_design_scores_gemma":[0.00026182804,0.00006411475,0.00014952479,0.000050801005,0.000014698032,0.000019536777,0.00023230379,0.06082266,0.00087119703,0.0021420966,0.9350463,0.0003249439],"about_ca_topic_score_codex":0.000100802965,"about_ca_topic_score_gemma":0.00011419114,"teacher_disagreement_score":0.40736306,"about_ca_system_score_codex":0.000023434523,"about_ca_system_score_gemma":0.00008786345,"threshold_uncertainty_score":0.99876076},"labels":[],"label_agreement":null},{"id":"W2111384966","doi":"10.1145/2556288.2557141","title":"Highlighting interventions and user differences","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":82,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visualization; Computer science; Variety (cybernetics); Psychological intervention; Human–computer interaction; Task (project management); Process (computing); Intervention (counseling); Information visualization; Data visualization; Psychology; Artificial intelligence; Engineering","score_opus":0.037996097572569554,"score_gpt":0.3063747694616426,"score_spread":0.26837867188907305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111384966","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0046744742,0.000009736728,0.98824203,0.0008045794,0.000059973514,0.000011790144,3.0682764e-7,0.000073382944,0.0061237207],"genre_scores_gemma":[0.9734879,0.000009211799,0.022371065,0.00040419667,0.000017757628,7.2659304e-7,0.0000015067192,0.0000013253815,0.0037063262],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99969524,0.000019928364,0.00007747061,0.00009965335,0.000053015556,0.000054690758],"domain_scores_gemma":[0.99978155,0.000029681727,0.000020813914,0.00011924842,0.000016462473,0.00003222747],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009258423,0.000030352363,0.000042114978,0.00003297809,0.000051090243,0.00016947786,0.00018214634,0.000009179226,0.000038016013],"category_scores_gemma":[0.000030388446,0.000022213067,0.00001710974,0.00008132827,0.000012758455,0.00020527495,0.00012922102,0.000015623995,0.000025814115],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.4013468e-8,0.000009589055,0.003941264,0.000005735607,0.0000020552811,8.4697064e-8,0.00003269645,3.687962e-7,0.000015187698,0.9887321,0.0014189623,0.0058419234],"study_design_scores_gemma":[0.00036080045,0.000101774756,0.070857294,0.0001019242,0.000012444297,0.0000058691126,0.00007743725,0.80323,0.0006085656,0.014591299,0.109754965,0.000297641],"about_ca_topic_score_codex":0.0000059918275,"about_ca_topic_score_gemma":0.000011546504,"teacher_disagreement_score":0.9741408,"about_ca_system_score_codex":0.0000014220715,"about_ca_system_score_gemma":0.0000022975044,"threshold_uncertainty_score":0.16342789},"labels":[],"label_agreement":null},{"id":"W2111648217","doi":"10.1111/j.1745-3992.2010.00181.x","title":"Developing Score Reports for Cognitive Diagnostic Assessments","year":2010,"lang":"en","type":"article","venue":"Educational Measurement Issues and Practice","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":68,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Context (archaeology); Test (biology); Cognition; Diagnostic test; Hierarchy; Sample (material); Knowledge management; Data science; Psychology; Medicine","score_opus":0.16578009314480702,"score_gpt":0.4552123800807414,"score_spread":0.28943228693593437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111648217","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027263619,0.0007574659,0.9029152,0.08679445,0.0027524899,0.0006183059,0.000011813368,0.000059814294,0.00336412],"genre_scores_gemma":[0.6360547,0.00025619456,0.35607436,0.0057919286,0.00071791094,0.00016862419,0.00013816176,0.000016634549,0.0007814888],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99885595,0.00006240166,0.00020968354,0.00028773982,0.00045473906,0.00012947276],"domain_scores_gemma":[0.99661255,0.0017094683,0.00019610551,0.00017723435,0.00122394,0.000080723825],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001502616,0.00009186042,0.000082338025,0.000053845004,0.00020895244,0.0003417542,0.00014051968,0.00003120907,0.000034321027],"category_scores_gemma":[0.016560314,0.000088704575,0.000018180559,0.00014466744,0.00002473697,0.0010105084,0.000058505346,0.00008721004,0.000011322497],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020932446,0.00055297225,0.0069857975,0.00009661648,0.00014170213,0.000008806072,0.0008880873,0.0000029380944,0.00066548644,0.93872,0.025110742,0.026805926],"study_design_scores_gemma":[0.00040953298,0.00010980988,0.02471811,0.00018473367,0.00010837289,0.00020513854,0.00044689325,0.0010914551,0.0010709191,0.035209585,0.9360324,0.00041305108],"about_ca_topic_score_codex":0.000030462796,"about_ca_topic_score_gemma":0.000021000818,"teacher_disagreement_score":0.91092163,"about_ca_system_score_codex":0.000032650678,"about_ca_system_score_gemma":0.0005229164,"threshold_uncertainty_score":0.9917236},"labels":[],"label_agreement":null},{"id":"W2111781385","doi":"10.1109/tvcg.2007.46","title":"TopoLayout: Multilevel Graph Layout by Topological Features","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":149,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"University of British Columbia; Institut national de recherche en informatique et en automatique (INRIA)","keywords":"Computer science; Feature (linguistics); Graph; Topology (electrical circuits); Graph Layout; Visualization; Theoretical computer science; Hierarchy; Topological graph theory; Algorithm; Graph drawing; Pattern recognition (psychology); Data mining; Voltage graph; Artificial intelligence; Mathematics; Line graph; Combinatorics","score_opus":0.0207223979919301,"score_gpt":0.3010794843035148,"score_spread":0.2803570863115847,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111781385","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0030102257,0.00006712736,0.99535805,0.00011288214,0.0007134425,0.00016072966,0.000038168444,0.00039021182,0.00014918519],"genre_scores_gemma":[0.9897958,0.00026183933,0.0036102077,0.005757488,0.000075930024,0.0000068791887,0.000046346355,0.000023276249,0.00042222344],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982,0.000094777766,0.0004007164,0.0005480731,0.0004062649,0.00035016934],"domain_scores_gemma":[0.99896383,0.00014229545,0.00010842183,0.00038739012,0.00015155457,0.00024648831],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000362045,0.00026881037,0.0002244037,0.00044961303,0.00043077843,0.00031678664,0.00045074685,0.00019715507,0.000025169742],"category_scores_gemma":[0.0000051378815,0.00024885288,0.00011434096,0.0009016431,0.00014648928,0.0004312545,0.000011215984,0.00023980987,0.000012362339],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017004195,0.00044090173,0.00012757936,0.000017620607,0.00004723865,0.00000839767,0.0007021516,0.00013621686,0.000044839737,0.978421,0.0034577276,0.016579343],"study_design_scores_gemma":[0.0013479525,0.00048261674,0.001636238,0.000048229114,0.00004258247,0.000060184175,0.00011944292,0.9732316,0.0062329103,0.0035304783,0.012473651,0.00079408626],"about_ca_topic_score_codex":0.00002591933,"about_ca_topic_score_gemma":0.000030828174,"teacher_disagreement_score":0.9917478,"about_ca_system_score_codex":0.000021336788,"about_ca_system_score_gemma":0.0000244305,"threshold_uncertainty_score":0.99999636},"labels":[],"label_agreement":null},{"id":"W2112974919","doi":"10.1111/cgf.12635","title":"An Exploratory Study of Data Sketching for Visual Representation","year":2015,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Representation (politics); Interactive visual analysis; Visual analytics; Computer graphics (images); Exploratory data analysis; Exploratory research; Visualization; Human–computer interaction; Artificial intelligence; Data mining","score_opus":0.15410045714420612,"score_gpt":0.408476920058061,"score_spread":0.2543764629138549,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112974919","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.047371257,0.000018371511,0.9516014,0.00011059496,0.00045568994,0.00029338742,0.000021804528,0.00011629071,0.000011236015],"genre_scores_gemma":[0.9586777,0.0000044230424,0.040401552,0.000431791,0.00012813845,0.000010347087,0.00032566127,0.000014835918,0.0000055360774],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998447,0.00013409989,0.00034805996,0.00051682245,0.00036149917,0.00019249805],"domain_scores_gemma":[0.997822,0.000072517,0.0001774278,0.0014794031,0.00030147922,0.0001472054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00074909773,0.000117498756,0.00018522337,0.00024091829,0.00010078694,0.00020778451,0.0018869307,0.00003889682,4.3308967e-7],"category_scores_gemma":[0.00003397835,0.00011619285,0.000033492317,0.00061544817,0.000030775853,0.0023632948,0.0009142667,0.0000672054,0.0000021129038],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008998374,0.007845636,0.0640796,0.00010965315,0.0003523479,0.00002621267,0.031935576,0.0034495464,0.0001401098,0.6909507,0.07557543,0.1254452],"study_design_scores_gemma":[0.0009308478,0.0008274904,0.00033976877,0.000009161054,0.000014072984,0.0000016430971,0.001546967,0.9896655,0.000063053696,0.004647014,0.0018106998,0.00014377218],"about_ca_topic_score_codex":0.000016513703,"about_ca_topic_score_gemma":0.00009294137,"teacher_disagreement_score":0.98621595,"about_ca_system_score_codex":0.000009149768,"about_ca_system_score_gemma":0.00007814743,"threshold_uncertainty_score":0.4738207},"labels":[],"label_agreement":null},{"id":"W2113374668","doi":"10.1145/332040.332414","title":"Using naming time to evaluate quality predictors for model simplification","year":2000,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Heuristics; Computer science; Quality (philosophy); Measure (data warehouse); Artificial intelligence; Machine learning; Cognition; Data mining; Natural language processing; Psychology","score_opus":0.1383067402434222,"score_gpt":0.41844039555539314,"score_spread":0.28013365531197093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113374668","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012696547,0.0000016866768,0.98377454,0.0003194069,0.000018462255,0.00016430268,0.000016194183,0.0001285845,0.0028802562],"genre_scores_gemma":[0.24852926,0.0000033731844,0.71182686,0.0037222784,0.00008199105,0.000020607538,0.00009995355,0.00002130677,0.035694376],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999197,0.000030666368,0.00020802136,0.00023893312,0.00018701662,0.00013833898],"domain_scores_gemma":[0.99942154,0.00003345142,0.000035477653,0.0003360211,0.000093453884,0.00008006506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046996903,0.000064724496,0.000080707294,0.000049707105,0.000097505064,0.00012803052,0.00034053126,0.000024110383,0.00021810875],"category_scores_gemma":[0.000051166888,0.000060035753,0.000030978405,0.00023228479,0.0000074934724,0.0003645396,0.000044795124,0.00001711239,0.00022025571],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016645581,0.00014924101,0.000110786474,0.00003176792,0.000029474864,1.9773549e-7,0.0010299047,0.73186624,0.009855474,0.12926741,0.011587655,0.11605523],"study_design_scores_gemma":[0.00010837421,0.000012334825,0.00006479067,0.000004359733,0.0000050590047,2.828913e-7,0.000003906662,0.9944894,0.00041823555,0.0012656833,0.0035390002,0.00008862243],"about_ca_topic_score_codex":0.000008455347,"about_ca_topic_score_gemma":0.0000010994373,"teacher_disagreement_score":0.2719477,"about_ca_system_score_codex":0.000034454348,"about_ca_system_score_gemma":0.000051905554,"threshold_uncertainty_score":0.2831015},"labels":[],"label_agreement":null},{"id":"W2113386367","doi":"10.1109/tvcg.2008.109","title":"A Framework of Interaction Costs in Information Visualization","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":134,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Visualization; Usability; Human–computer interaction; Data visualization; Risk analysis (engineering); Artificial intelligence","score_opus":0.023117179612594532,"score_gpt":0.3027173949095378,"score_spread":0.2796002152969433,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113386367","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014622732,0.000013353394,0.9843799,0.000035133675,0.0005103722,0.00019933262,0.000011434061,0.00014890458,0.00007883214],"genre_scores_gemma":[0.9956375,0.0006628744,0.0025026677,0.0010965825,0.000022960026,0.000013652976,0.000038599952,0.000011907063,0.000013289035],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99842024,0.00013808631,0.0006152296,0.00026874113,0.00038314494,0.00017456709],"domain_scores_gemma":[0.9989856,0.00012578933,0.00023698545,0.0003081236,0.0002520089,0.00009150145],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002037878,0.00018780476,0.00022804682,0.0010643972,0.00018394893,0.00011007987,0.00025729398,0.00014995426,0.00001410071],"category_scores_gemma":[0.000014396211,0.00020098979,0.00006887842,0.0018855243,0.0000864266,0.0017746978,0.000008301123,0.00017519148,0.000010985472],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024073854,0.0003468087,0.0006610886,0.0000496445,0.000022885972,0.0000025509364,0.0027629666,0.0020048295,0.000008847723,0.9858146,0.00017123632,0.008130482],"study_design_scores_gemma":[0.00056864996,0.00019854508,0.0014200156,0.00013922351,0.000008842499,0.000026022533,0.00007489255,0.9941509,0.0015208109,0.0007342441,0.00093986525,0.00021801842],"about_ca_topic_score_codex":0.00004042722,"about_ca_topic_score_gemma":0.000019758025,"teacher_disagreement_score":0.992146,"about_ca_system_score_codex":0.000051730953,"about_ca_system_score_gemma":0.000059103335,"threshold_uncertainty_score":0.8196126},"labels":[],"label_agreement":null},{"id":"W2113805302","doi":"10.3115/v1/w14-3107","title":"Interactive Exploration of Asynchronous Conversations: Applying a User-centered Approach to Design a Visual Text Analytic System","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Asynchronous communication; Visualization; Human–computer interaction; Thread (computing); Conversation; Interactive visualization; Data visualization; Artificial intelligence; Programming language","score_opus":0.055739150543033994,"score_gpt":0.303825398224764,"score_spread":0.24808624768173002,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113805302","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0003687102,0.000002805018,0.99622506,0.00007661238,0.00009540935,0.00048064286,0.0000025071504,0.00015369248,0.0025945744],"genre_scores_gemma":[0.8896466,0.0000011994241,0.1099023,0.0002203606,0.0000263927,0.00005943453,0.00002301438,0.000008755172,0.00011198609],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99860585,0.00020338543,0.00038386384,0.00035809173,0.00028081873,0.00016799278],"domain_scores_gemma":[0.9989636,0.00013298013,0.00018768272,0.00039158782,0.00021579642,0.00010834196],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045158685,0.00013288355,0.00022961377,0.000298732,0.00007477773,0.00020282838,0.00047607961,0.000038350125,0.000008059622],"category_scores_gemma":[0.00011628951,0.00012147532,0.00005193019,0.00071111764,0.000021661708,0.0012524913,0.00015887812,0.00005171445,0.00009758151],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000070191236,0.0011299419,0.00047718044,0.000382938,0.00025008887,0.0000023385085,0.013246378,0.042728964,0.0021368677,0.9067941,0.0030023064,0.02977873],"study_design_scores_gemma":[0.00034997065,0.00013482447,0.00005098582,0.00005877716,0.000016586908,0.000003188513,0.0021737218,0.9946528,0.0019755044,0.000082314684,0.00036201577,0.00013930812],"about_ca_topic_score_codex":0.000037705257,"about_ca_topic_score_gemma":0.0000038858366,"teacher_disagreement_score":0.95192385,"about_ca_system_score_codex":0.00010929695,"about_ca_system_score_gemma":0.00006160074,"threshold_uncertainty_score":0.49536198},"labels":[],"label_agreement":null},{"id":"W2114039576","doi":"10.1109/visual.2003.1250400","title":"Using deformations for browsing volumetric data","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":175,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Context (archaeology); Situated; Human–computer interaction; Volume (thermodynamics); Visualization; Deformation (meteorology); Artificial intelligence; Geology","score_opus":0.06524414232029742,"score_gpt":0.3102276656195208,"score_spread":0.2449835232992234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114039576","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00067515153,0.00031062443,0.9973288,0.0003822797,0.00033784047,0.00038181563,0.00035814705,0.00013797694,0.000087330605],"genre_scores_gemma":[0.9156079,0.0002373332,0.08341684,0.00060489035,0.000033945733,0.000016177235,0.000039277234,0.000019684867,0.000023937067],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984444,0.00003651003,0.00038165096,0.00047560362,0.0002653842,0.00039648594],"domain_scores_gemma":[0.9985376,0.00022991376,0.0001310789,0.0007553743,0.00019244295,0.00015360252],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037692222,0.00019881982,0.00022634707,0.00048170565,0.0006053789,0.00036924772,0.00079118885,0.00010346992,0.0000046026157],"category_scores_gemma":[0.00008134094,0.00020035742,0.00007857203,0.0014335432,0.000041559302,0.0011971194,0.0000032580476,0.00021292116,0.000005617838],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000077824894,0.0023745303,0.0001453323,0.00019769216,0.0006733722,0.000018207465,0.0009498323,0.28465676,0.012736094,0.35973436,0.00032734592,0.33810866],"study_design_scores_gemma":[0.001796737,0.00021028152,0.000011922314,0.000021665832,0.00009906086,0.000040628176,0.000013303105,0.9908051,0.0007616678,0.005588766,0.00038411102,0.00026674912],"about_ca_topic_score_codex":0.000091447444,"about_ca_topic_score_gemma":0.00006729059,"teacher_disagreement_score":0.9149328,"about_ca_system_score_codex":0.0001528809,"about_ca_system_score_gemma":0.00031416578,"threshold_uncertainty_score":0.8170338},"labels":[],"label_agreement":null},{"id":"W2114570145","doi":"10.1109/hicss.2013.599","title":"Visual Analytics for Public Health: Supporting Knowledge Construction and Decision-Making","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"Virginia Agricultural Experiment Station, Virginia Polytechnic Institute and State University","keywords":"Visual analytics; Exploit; Computer science; Analytics; Data science; Process (computing); Knowledge management; Visualization; Artificial intelligence; Computer security","score_opus":0.0556098623957771,"score_gpt":0.3843485862432115,"score_spread":0.3287387238474344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114570145","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0046861623,0.00003873401,0.9927974,0.0013422675,0.00018834058,0.00018402045,0.000002574689,0.00011530292,0.00064520095],"genre_scores_gemma":[0.5411629,0.000019729307,0.45748737,0.0010973408,0.000060284834,0.000009003044,0.0000122513,0.000007953135,0.00014312394],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989353,0.000023488361,0.00035852432,0.00027421676,0.0001236143,0.00028490048],"domain_scores_gemma":[0.99898946,0.00026289796,0.00015345294,0.00019158548,0.000240773,0.00016179973],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000475502,0.00008989958,0.00014410788,0.00018118585,0.00021271037,0.0006463944,0.00023808755,0.00003598184,0.000075727796],"category_scores_gemma":[0.00026006356,0.00007888874,0.00003419494,0.00040177073,0.000042320626,0.0008842258,0.00018922777,0.0000429224,0.00003589958],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.0095023e-7,0.000030462108,0.0009776126,0.000017500031,0.0000075685643,1.4033027e-7,0.0001567969,0.0000038694566,0.000007725894,0.19750506,0.0058724275,0.7954205],"study_design_scores_gemma":[0.00020077117,0.000062565865,0.0005226178,0.000022756118,0.0000024350456,0.000013572453,0.00030465567,0.96932286,0.000016692982,0.01694265,0.012465786,0.00012266505],"about_ca_topic_score_codex":0.0000070663305,"about_ca_topic_score_gemma":0.00001735782,"teacher_disagreement_score":0.969319,"about_ca_system_score_codex":0.000032689913,"about_ca_system_score_gemma":0.00015241257,"threshold_uncertainty_score":0.6233196},"labels":[],"label_agreement":null},{"id":"W2114580372","doi":"10.2307/3250969","title":"The Effect of Multimedia on Perceived Equivocality and Perceived Usefulness of Information Systems1","year":2000,"lang":"en","type":"article","venue":"MIS Quarterly","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":305,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Multimedia; Psychology; Knowledge management; Information system; Computer science; Engineering","score_opus":0.01060783306232817,"score_gpt":0.2554968389878104,"score_spread":0.2448890059254822,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114580372","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.980877,0.000014073116,0.017999532,0.000092364964,0.000089118206,0.00019638737,0.000021356884,0.00003651658,0.0006736398],"genre_scores_gemma":[0.99967825,0.000005907929,0.0001578088,0.00004126628,0.000011630094,0.000005221001,0.00001372226,0.0000025562344,0.00008361362],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99900967,0.00019423748,0.00032395803,0.000109991386,0.00024720127,0.000114970615],"domain_scores_gemma":[0.9991472,0.00025265734,0.00011809489,0.00036945677,0.000062436775,0.000050155588],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000427132,0.000091218004,0.00017193772,0.0000485686,0.00008479187,0.000099298566,0.00035139697,0.00004015664,0.000021665819],"category_scores_gemma":[0.000037207796,0.000058672376,0.000041414212,0.00014866526,0.0000808494,0.0004230204,0.000010853894,0.00004944398,0.000034335506],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013162871,0.0000814732,0.0018678493,0.00047937295,0.00006366167,0.0000016795352,0.03824883,0.0001149565,0.001751686,0.0028985573,0.0010179041,0.9533424],"study_design_scores_gemma":[0.002722361,0.0039160238,0.20209858,0.00032129826,0.00004459066,0.000010224731,0.0013815007,0.7824921,0.002603622,0.0001397203,0.003908567,0.00036142947],"about_ca_topic_score_codex":0.00009377106,"about_ca_topic_score_gemma":0.000011204149,"teacher_disagreement_score":0.952981,"about_ca_system_score_codex":0.000011591564,"about_ca_system_score_gemma":0.000014790438,"threshold_uncertainty_score":0.239259},"labels":[],"label_agreement":null},{"id":"W2115410320","doi":"10.22230/jem.2005v5n2a294","title":"Computer-based visualization of forest management: A primer for resource managers, communities, and educators","year":2005,"lang":"en","type":"article","venue":"Journal of Ecosystems and Management","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visualization; Resource (disambiguation); Computer science; Perspective (graphical); Resource management (computing); Environmental resource management; Natural resource management; Data science; Knowledge management; Ecology; Natural resource; Environmental science; Artificial intelligence","score_opus":0.018974654115194237,"score_gpt":0.2769437117073281,"score_spread":0.2579690575921339,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115410320","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010294627,0.0003634956,0.98740894,0.00056538574,0.00017964521,0.0003801441,0.00000633662,0.000016707188,0.0007846989],"genre_scores_gemma":[0.9035422,0.0008276067,0.093885206,0.0010232065,0.0001674382,0.000013140989,0.000031907366,0.000022259654,0.0004869896],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989322,0.00006173715,0.00052887277,0.000120795514,0.00021982622,0.00013660558],"domain_scores_gemma":[0.99903035,0.00005178199,0.00049002474,0.00024940827,0.0000969758,0.000081459315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006464929,0.00011590815,0.00023640906,0.00039720166,0.000099586985,0.00015818705,0.00036211667,0.000026889886,0.0000029084624],"category_scores_gemma":[0.0000028130714,0.00010340851,0.000057725723,0.00020022475,0.000027401984,0.0003256287,0.00019175117,0.000037948445,5.3700404e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005089799,0.000550972,0.004657573,0.003233243,0.0005944054,0.000015368727,0.0011809429,0.0050317147,0.0000064087717,0.8490634,0.051855594,0.08375951],"study_design_scores_gemma":[0.0016582819,0.00026589347,0.0013676095,0.000531498,0.0001138682,0.00001621538,0.0007350479,0.391799,0.000028814198,0.00027660237,0.6030351,0.00017208036],"about_ca_topic_score_codex":0.000013389801,"about_ca_topic_score_gemma":0.000049556904,"teacher_disagreement_score":0.89352375,"about_ca_system_score_codex":0.000031433618,"about_ca_system_score_gemma":0.000011738187,"threshold_uncertainty_score":0.42168763},"labels":[],"label_agreement":null},{"id":"W2115413094","doi":"10.5772/33058","title":"Quality Improvement Through Visualization of Software and Systems","year":2012,"lang":"en","type":"book-chapter","venue":"InTech eBooks","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Patient Safety Institute","keywords":"Visualization; Computer science; Software visualization; Process (computing); Software; Information visualization; Quality (philosophy); Data science; Human–computer interaction; Software system; Software engineering; Data mining; Component-based software engineering","score_opus":0.05676258301809815,"score_gpt":0.33222376908158235,"score_spread":0.2754611860634842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115413094","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000009941638,0.0005066221,0.91175634,0.000010234137,0.00034630366,0.00025855828,0.00006220941,0.0001475465,0.08690225],"genre_scores_gemma":[0.23178172,0.0007820825,0.02038938,0.0013342247,0.0006467002,0.000061038605,0.0004288153,0.0002185046,0.7443575],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984564,0.000026840822,0.00060501357,0.00033980765,0.0004055759,0.0001663635],"domain_scores_gemma":[0.99844646,0.000060036484,0.00054016936,0.0006246232,0.0002577437,0.00007097911],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033406768,0.0002344613,0.00037382822,0.000111753616,0.000052767962,0.00011573774,0.00046301095,0.00021647844,0.000019646372],"category_scores_gemma":[0.000038770737,0.00021913247,0.000072412244,0.000022176584,0.0001010717,0.00018812127,0.00043279928,0.000120785684,0.00001745817],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000018961395,0.000012848491,0.000015415215,0.00031474984,0.00004990941,0.0000010663064,0.0003471244,2.497278e-7,0.0011379519,0.9625937,0.00020070878,0.035324425],"study_design_scores_gemma":[0.00072391477,0.0003838524,0.000028202117,0.0013584272,0.00012757386,0.000022544255,0.00010170275,0.001719938,0.030882388,0.0970417,0.8662535,0.0013562553],"about_ca_topic_score_codex":0.0000491247,"about_ca_topic_score_gemma":0.000005166473,"teacher_disagreement_score":0.89136696,"about_ca_system_score_codex":0.000048885195,"about_ca_system_score_gemma":0.00006458141,"threshold_uncertainty_score":0.8935963},"labels":[],"label_agreement":null},{"id":"W2115459739","doi":"10.1145/2145204.2145384","title":"Inflo","year":2012,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Dataflow; Construct (python library); Computer science; Reuse; Computation; Theoretical computer science; Computer network; Programming language; Engineering","score_opus":0.031566408350418934,"score_gpt":0.3134257832227225,"score_spread":0.2818593748723036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115459739","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00025075275,0.000011496877,0.9360839,0.0002363781,0.00010579831,0.000006759391,1.4899886e-7,0.00007799537,0.063226745],"genre_scores_gemma":[0.94886476,0.0000039362835,0.042097982,0.0031593877,0.000069254595,4.811786e-7,0.000002123415,0.0000015384693,0.005800549],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998046,0.000004802834,0.000033636406,0.00003238499,0.000051320396,0.00007324273],"domain_scores_gemma":[0.99979895,0.0000055200926,0.0000067098617,0.0001350035,0.000009103638,0.000044699016],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000060088092,0.000016925369,0.000017065238,0.00001647882,0.000015205743,0.000035873396,0.00016916066,0.000006601837,0.00010923868],"category_scores_gemma":[0.000009149583,0.00001310677,0.000006955591,0.00010558871,0.0000033767208,0.00045083102,0.000069683636,0.000009816916,0.00058884936],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.604774e-8,0.000010943264,0.002474431,3.701242e-7,6.6453947e-7,5.6201795e-8,0.000052877615,4.1505083e-7,0.000017691647,0.97959894,0.013869881,0.003973722],"study_design_scores_gemma":[0.0000901889,0.000007953496,0.0070867613,0.0000014852758,0.000001320364,0.0000039259803,0.000018512934,0.048313394,0.0019986879,0.0019590892,0.94040734,0.00011134659],"about_ca_topic_score_codex":0.0000013944186,"about_ca_topic_score_gemma":2.6976986e-7,"teacher_disagreement_score":0.97763985,"about_ca_system_score_codex":0.0000022900801,"about_ca_system_score_gemma":0.000004084006,"threshold_uncertainty_score":0.75686634},"labels":[],"label_agreement":null},{"id":"W2115517714","doi":"10.1109/tvcg.2007.70568","title":"Interactive Tree Comparison for Co-located Collaborative Information Visualization","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":125,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Workspace; Visualization; Information visualization; Human–computer interaction; Data visualization; Focus (optics); Collaborative software; Computer-supported cooperative work; Data science; World Wide Web; Work (physics); Data mining; Artificial intelligence","score_opus":0.020595387033783632,"score_gpt":0.3356253614782106,"score_spread":0.315029974444427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115517714","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010996131,0.000018103141,0.996757,0.00005912066,0.0007521994,0.000647721,0.00007610251,0.00040716166,0.00018301692],"genre_scores_gemma":[0.99076045,0.00014708402,0.005394587,0.0029776446,0.000085046566,0.000049698363,0.00048779455,0.00003166596,0.00006605259],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979368,0.00012128842,0.0007705818,0.00041709578,0.00043210533,0.00032215842],"domain_scores_gemma":[0.99795586,0.00030657096,0.00036362006,0.00032084048,0.0008614105,0.00019170369],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00055647426,0.00030406046,0.00031083103,0.0009723353,0.00052265805,0.0005721687,0.00034351155,0.00018096938,0.000009892739],"category_scores_gemma":[0.000017594268,0.00031624423,0.0000974992,0.0019076903,0.00009985606,0.0020399431,0.000007350696,0.00015735233,0.000017828304],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013604264,0.0004887133,0.00016407351,0.00007967302,0.00009492048,0.0000010420837,0.00458583,0.0010483176,0.0000314607,0.95713437,0.00240625,0.0338293],"study_design_scores_gemma":[0.0013565148,0.00053083745,0.00038097144,0.00005803303,0.000035981095,0.0000057824477,0.00037298957,0.9727182,0.008931875,0.0004760154,0.014758962,0.00037386877],"about_ca_topic_score_codex":0.000007494194,"about_ca_topic_score_gemma":0.000052184565,"teacher_disagreement_score":0.9913624,"about_ca_system_score_codex":0.00007138257,"about_ca_system_score_gemma":0.00008808192,"threshold_uncertainty_score":0.99992895},"labels":[],"label_agreement":null},{"id":"W2115977463","doi":"10.1109/tvcg.2009.127","title":"Comparing Dot and Landscape Spatializations for Visual Memory Differences","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Visualization; Data visualization; Computer graphics (images); Interactive visual analysis; Information visualization; Human–computer interaction; Artificial intelligence","score_opus":0.02995665320131543,"score_gpt":0.29295504316454696,"score_spread":0.26299838996323155,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115977463","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010164505,0.00005280748,0.9886419,0.00017469443,0.00035481126,0.00026860397,0.000014901454,0.00026699732,0.000060771545],"genre_scores_gemma":[0.995058,0.0003336644,0.0024758338,0.0019215855,0.000070171125,0.00001560187,0.00003733674,0.0000134803395,0.00007430592],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986318,0.00007892575,0.00034622243,0.00047138246,0.00024456717,0.00022712913],"domain_scores_gemma":[0.9992152,0.000118642,0.00011094459,0.00022918008,0.000162281,0.00016374192],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016652628,0.00022983205,0.00026401973,0.0004308434,0.00053148594,0.00050211954,0.00024311664,0.00009842057,0.0000070765254],"category_scores_gemma":[0.000004900195,0.00022389632,0.00006877312,0.0006580874,0.00007146668,0.00048818003,0.0000067244923,0.00009983878,0.0000019888023],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020008227,0.00041936408,0.0006417736,0.00004779361,0.000050004044,0.0000013279051,0.0009824289,0.0007075621,0.000021592656,0.97582126,0.0005454049,0.020741472],"study_design_scores_gemma":[0.00080449984,0.00039720823,0.002293381,0.00004293333,0.000033912827,0.000009540048,0.000041980264,0.9935649,0.0003215529,0.001701627,0.00050903216,0.0002794321],"about_ca_topic_score_codex":0.000006473422,"about_ca_topic_score_gemma":0.000023588067,"teacher_disagreement_score":0.99285734,"about_ca_system_score_codex":0.000009633031,"about_ca_system_score_gemma":0.00003280048,"threshold_uncertainty_score":0.9130227},"labels":[],"label_agreement":null},{"id":"W2116484328","doi":"10.1109/vissof.2009.5336423","title":"Generating visualization-based analysis scenarios from maintenance task descriptions","year":2009,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Visualization; Computer science; Software visualization; Software; Data visualization; Task (project management); Information visualization; Visual analytics; Human–computer interaction; Interactive visualization; Creative visualization; Software engineering; Data mining; Software development; Software construction; Programming language; Systems engineering; Engineering","score_opus":0.020834944704340493,"score_gpt":0.28676770114031597,"score_spread":0.26593275643597547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116484328","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00179005,0.000023553317,0.996078,0.0010446556,0.00007375132,0.000057607598,0.000022436534,0.00027943583,0.00063051714],"genre_scores_gemma":[0.7822752,0.0000087023045,0.20523147,0.011127665,0.000059050773,0.0000028699667,0.00038064984,0.0000057295492,0.0009086329],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987494,0.000062903484,0.00030523527,0.0003951789,0.00027292146,0.00021436505],"domain_scores_gemma":[0.99898654,0.000044060347,0.00010356839,0.0005760618,0.0001771195,0.00011263744],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014584082,0.00012741807,0.00017548873,0.00027519188,0.0002085703,0.00048408686,0.00057698105,0.000043851203,0.00019210328],"category_scores_gemma":[0.0000896727,0.00011426219,0.000113216505,0.0021850036,0.00001957475,0.00046573652,0.00004525415,0.00005145433,0.000066161316],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000040228497,0.00053578586,0.008726484,0.0000048696897,0.00031450333,0.000020087644,0.0006259419,0.32401532,0.0070366478,0.6084868,0.031318843,0.018910734],"study_design_scores_gemma":[0.00018031774,0.000019779809,0.0021040651,0.0000068460895,0.00006603021,2.295261e-7,0.000021300357,0.9930367,0.00035378308,0.00054189796,0.0035053657,0.0001637044],"about_ca_topic_score_codex":0.000102430786,"about_ca_topic_score_gemma":0.00013229484,"teacher_disagreement_score":0.7908465,"about_ca_system_score_codex":0.000040278206,"about_ca_system_score_gemma":0.000076472104,"threshold_uncertainty_score":0.46680608},"labels":[],"label_agreement":null},{"id":"W2117027591","doi":"10.1145/506443.506617","title":"Hunter gatherer","year":2002,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Hunter-gatherer; Computer science; World Wide Web; Human–computer interaction; Archaeology; Geography","score_opus":0.03665220329242286,"score_gpt":0.27241690561667964,"score_spread":0.23576470232425678,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117027591","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00011348527,0.000010739114,0.8216228,0.0009992815,0.00005212134,0.0000095788455,2.012741e-7,0.000092474496,0.17709932],"genre_scores_gemma":[0.7735224,0.000035133868,0.038307726,0.013697713,0.00007152451,0.0000015875243,0.0000022393579,0.0000067276083,0.17435494],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997412,0.000005907692,0.00004667755,0.000080182916,0.000065531465,0.00006047817],"domain_scores_gemma":[0.9997486,0.000005377341,0.000008398541,0.00019704134,0.000013300008,0.00002727908],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000024898034,0.00002551229,0.00002488142,0.00002047011,0.000018834617,0.000079978156,0.00025594942,0.000008838249,0.0021364512],"category_scores_gemma":[0.0000050369927,0.000019590472,0.000013153791,0.00011217859,0.0000056739846,0.00019729043,0.000057767636,0.0000140368575,0.0019557432],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.061584e-8,0.000048957874,0.00058998755,0.0000013464738,0.0000037697398,0.0000031678019,0.00019515165,0.000006491067,0.0000362193,0.7032771,0.27073252,0.025105221],"study_design_scores_gemma":[0.00006856964,0.00000799362,0.00014337146,0.0000013428382,5.6235626e-7,0.0000022717395,0.0000065848653,0.61601686,0.00025819853,0.00060763635,0.38283154,0.00005508901],"about_ca_topic_score_codex":0.0000016116115,"about_ca_topic_score_gemma":0.0000010402478,"teacher_disagreement_score":0.78331506,"about_ca_system_score_codex":0.000002616669,"about_ca_system_score_gemma":0.0000011516674,"threshold_uncertainty_score":0.9988214},"labels":[],"label_agreement":null},{"id":"W2117101792","doi":"10.1007/s00180-011-0229-5","title":"Eulerian tour algorithms for data visualization and the PairViz package","year":2011,"lang":"en","type":"article","venue":"Computational Statistics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Visualization; Eulerian path; R package; Tree traversal; Computer science; Parallel coordinates; Enhanced Data Rates for GSM Evolution; Algorithm; Theoretical computer science; Data visualization; Data mining; Mathematics; Artificial intelligence; Computational science; Lagrangian; Applied mathematics","score_opus":0.11275922288468795,"score_gpt":0.34648431506177846,"score_spread":0.2337250921770905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117101792","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000025689946,0.000046955283,0.99815136,0.00018947816,0.00019155919,0.00022180364,0.0009273457,0.00006299098,0.00018279612],"genre_scores_gemma":[0.035833735,0.000032310956,0.9595406,0.0012428327,0.00009713889,0.000014576485,0.0030443682,0.000016364607,0.00017806796],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989757,0.000080538826,0.0002639116,0.00030716322,0.00023150981,0.00014117255],"domain_scores_gemma":[0.9986514,0.0004953316,0.00013393044,0.00041609988,0.0002343274,0.00006894637],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004582628,0.000105795,0.00012679846,0.000048620568,0.00023404096,0.00022063655,0.0007718504,0.000028235432,0.000028561884],"category_scores_gemma":[0.00031394325,0.000081570404,0.000015635358,0.00018648486,0.00013521964,0.00035768346,0.00037657763,0.000040346386,0.0000136257595],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008874109,0.00003474874,0.00006411259,0.000015213088,0.000021227597,0.0000017294537,0.0005532864,0.000111948815,3.8142917e-7,0.9646827,0.020141065,0.014364689],"study_design_scores_gemma":[0.0007208549,0.00002820093,0.00095254666,0.0000052282303,0.000016521733,0.0000051609736,0.000036267073,0.8323106,0.000004314749,0.15998352,0.0058383057,0.000098486744],"about_ca_topic_score_codex":0.000019178733,"about_ca_topic_score_gemma":0.000009409091,"teacher_disagreement_score":0.8321986,"about_ca_system_score_codex":0.000010315629,"about_ca_system_score_gemma":0.0000724485,"threshold_uncertainty_score":0.33263445},"labels":[],"label_agreement":null},{"id":"W2117424492","doi":"10.1145/1385569.1385578","title":"Exploring blog archives with interactive visualization","year":2008,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Visualization; World Wide Web; Social media; Exploratory research; Human–computer interaction; Usability; Microblogging; Multimedia; Information retrieval; Data mining","score_opus":0.10993796087212782,"score_gpt":0.3045533802121646,"score_spread":0.1946154193400368,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117424492","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015519124,0.000003001141,0.96889627,0.00010006905,0.000054184733,0.000034895133,5.348887e-7,0.00017100743,0.015220923],"genre_scores_gemma":[0.97119856,0.00008401151,0.026779559,0.00042343733,0.00003147546,0.0000076211895,0.00001257222,0.0000066746998,0.0014560616],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99948245,0.00002348159,0.00009147213,0.0001743429,0.00012838861,0.00009984887],"domain_scores_gemma":[0.9996462,0.00004049023,0.00003726384,0.00019685483,0.000031130476,0.000048089914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002518995,0.00006401135,0.00006356193,0.000101533995,0.00009242696,0.000055889508,0.00024859756,0.0000066957095,0.000022218203],"category_scores_gemma":[0.000011472946,0.0000479523,0.000014829311,0.00029994454,0.000035108453,0.0010880688,0.000089368245,0.000032655036,0.000038171966],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012353506,0.00016397306,0.0043100086,0.000008746039,0.00003434579,0.00004532603,0.0068566236,0.00029004217,0.00038239872,0.97908896,0.0006838199,0.008123416],"study_design_scores_gemma":[0.0008883485,0.00032799525,0.010737555,0.00007482995,0.000010261351,0.00016927983,0.0009534224,0.9383799,0.027657162,0.0016902884,0.01854303,0.00056793913],"about_ca_topic_score_codex":0.0000062894687,"about_ca_topic_score_gemma":0.0000035767696,"teacher_disagreement_score":0.97739863,"about_ca_system_score_codex":0.000006395497,"about_ca_system_score_gemma":0.000027573213,"threshold_uncertainty_score":0.19554381},"labels":[],"label_agreement":null},{"id":"W2117616434","doi":"10.1109/tvcg.2012.252","title":"PivotPaths: Strolling through Faceted Information Spaces","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":175,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Microsoft Research","keywords":"Computer science; Tree traversal; Visualization; Interface (matter); Filter (signal processing); Process (computing); Space (punctuation); World Wide Web; Human–computer interaction; Casual; Matching (statistics); Software deployment; Data visualization; Information retrieval; Contrast (vision); Artificial intelligence; Programming language","score_opus":0.025909766185457237,"score_gpt":0.28764612436590203,"score_spread":0.2617363581804448,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117616434","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0031297475,0.00004997461,0.99520946,0.000077537945,0.0008613548,0.0001647865,0.00001937129,0.00036472257,0.00012306978],"genre_scores_gemma":[0.9896017,0.0004536859,0.006497657,0.0032292674,0.00009070172,0.000014151487,0.000045608296,0.000015154411,0.00005209869],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998645,0.00010203413,0.0003683892,0.00021881913,0.00036596454,0.00029981442],"domain_scores_gemma":[0.99916524,0.00006220606,0.00014492517,0.00031355646,0.00015664806,0.00015745623],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023014189,0.00021214683,0.00017783194,0.0003478297,0.00037386504,0.0005180367,0.00027489325,0.00011200371,0.000016826669],"category_scores_gemma":[0.0000039642523,0.000206933,0.000075406686,0.0009884993,0.000056881978,0.0036845198,0.000008179609,0.00014680091,0.000040711868],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000064618253,0.00020517899,0.00017274042,0.0000345111,0.00004191872,3.486755e-7,0.0041088117,0.0011019483,0.0000065018376,0.98608464,0.0004729461,0.007764002],"study_design_scores_gemma":[0.0005295882,0.000117026415,0.00019183647,0.00003541801,0.000023892018,0.000010978597,0.00014643847,0.98136264,0.0011555221,0.0004333818,0.015703479,0.00028977962],"about_ca_topic_score_codex":0.000014788396,"about_ca_topic_score_gemma":0.000003730539,"teacher_disagreement_score":0.9887118,"about_ca_system_score_codex":0.000021551929,"about_ca_system_score_gemma":0.000028623723,"threshold_uncertainty_score":0.8438482},"labels":[],"label_agreement":null},{"id":"W2118312966","doi":"10.1002/sce.21044","title":"Undoing decontextualization or how scientists come to understand their own data/graphs","year":2012,"lang":"en","type":"article","venue":"Science Education","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Undoing; Interpretation (philosophy); Computer science; Objectivity (philosophy); Context (archaeology); Ethnography; Epistemology; Data visualization; Process (computing); Data science; Cognitive science; Visualization; Sociology; Artificial intelligence; Psychology","score_opus":0.10951438885640691,"score_gpt":0.38580105197378517,"score_spread":0.27628666311737826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2118312966","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022256408,0.00010143984,0.9695676,0.0030394504,0.0033875082,0.00026431194,0.000023325838,0.000117064184,0.0012429236],"genre_scores_gemma":[0.9780999,0.000012895024,0.018760048,0.0015207062,0.00012523487,0.0000032989417,0.000080156315,0.0000071553122,0.0013906352],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982536,0.00005248078,0.00017667322,0.00052904355,0.0005499145,0.00043831972],"domain_scores_gemma":[0.99798703,0.0000623628,0.00012063839,0.0012041786,0.00026337165,0.00036241167],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0015976446,0.00011950654,0.00009961492,0.0005350436,0.0005945343,0.0013673626,0.0022870214,0.000026975447,0.00003154042],"category_scores_gemma":[0.0006214261,0.00009351646,0.000016933323,0.00414192,0.0002237899,0.0062157013,0.0005698224,0.000049688242,0.00007846117],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000033915278,0.00034911704,0.0049998704,0.000019631763,0.0000059898052,2.3104697e-7,0.0091389865,0.00003644279,0.001991719,0.881106,0.04415571,0.05819289],"study_design_scores_gemma":[0.0014720638,0.00045107253,0.102787904,0.00060815003,0.00007126654,0.00016948342,0.050087996,0.383098,0.018934827,0.025252579,0.4138329,0.003233753],"about_ca_topic_score_codex":0.000016955219,"about_ca_topic_score_gemma":0.00006606852,"teacher_disagreement_score":0.95584345,"about_ca_system_score_codex":0.00016373009,"about_ca_system_score_gemma":0.0014107517,"threshold_uncertainty_score":0.9996693},"labels":[],"label_agreement":null},{"id":"W2118481978","doi":"10.1145/989863.989890","title":"Temporal Thumbnails","year":2004,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Thumbnail; Computer science; Storyboard; Visualization; Dimension (graph theory); Representation (politics); Data visualization; Computer graphics (images); Human–computer interaction; Information retrieval; Artificial intelligence; Multimedia; Image (mathematics)","score_opus":0.0261895035324059,"score_gpt":0.29978722687399845,"score_spread":0.27359772334159255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2118481978","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005276119,0.0000048032684,0.9726427,0.0013563832,0.000060872517,0.000015632044,4.3052052e-7,0.00014310778,0.02524841],"genre_scores_gemma":[0.9091312,0.0000039858182,0.0848983,0.0029280437,0.00002707755,6.6617093e-7,0.0000051576576,0.0000025204372,0.0030030005],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996917,0.0000041820667,0.000059101218,0.00009112113,0.00008456963,0.00006930412],"domain_scores_gemma":[0.9997274,0.0000032285982,0.000012663522,0.00020331665,0.000016895305,0.000036476376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000050133192,0.00002992399,0.000031301428,0.00002581868,0.000028769466,0.00009185003,0.0003160395,0.00001029664,0.000049102135],"category_scores_gemma":[0.0000072243274,0.00002343395,0.000014661957,0.00016441205,0.000009048398,0.00026971684,0.00007021471,0.000016433753,0.0003593596],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.336786e-8,0.000017648286,0.00020002965,6.4921625e-7,0.0000012557265,0.0000023487398,0.000052690582,0.00004322545,0.000026954138,0.9959305,0.0021088214,0.0016158463],"study_design_scores_gemma":[0.0022993588,0.00019928036,0.0037916978,0.000035727488,0.000007984934,0.000048758124,0.0001615077,0.10663678,0.019694338,0.36168954,0.50456256,0.00087248784],"about_ca_topic_score_codex":0.00002135111,"about_ca_topic_score_gemma":0.000009355595,"teacher_disagreement_score":0.9086036,"about_ca_system_score_codex":0.00000795247,"about_ca_system_score_gemma":0.00002981055,"threshold_uncertainty_score":0.46189606},"labels":[],"label_agreement":null},{"id":"W2119477629","doi":"10.1057/palgrave.ivs.2008.28","title":"Building and applying a human cognition model for visual analytics","year":2009,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":89,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Visual analytics; Computer science; Visualization; Analytics; Cultural analytics; Human–computer interaction; Data science; Cognition; Visual reasoning; Analytic reasoning; Perception; Interactive visual analysis; Artificial intelligence; Semantic analytics; Reasoning system; Psychology","score_opus":0.05619278798790106,"score_gpt":0.3699011569690138,"score_spread":0.31370836898111276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2119477629","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002266904,0.000006588825,0.99649495,0.00019637255,0.000011920666,0.00011882065,0.000002788539,0.0001018633,0.00079982175],"genre_scores_gemma":[0.82329696,0.000004057961,0.17511427,0.0012643022,0.00002335,0.0000043566506,0.000014482153,0.0000030512272,0.00027514217],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99944705,0.0000058816217,0.0001299607,0.00019018802,0.00010111317,0.00012580739],"domain_scores_gemma":[0.99971664,0.00001917148,0.0000384721,0.00010630094,0.000062155676,0.00005727677],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001321712,0.000066066204,0.000079371974,0.00008803734,0.00014610094,0.00021873626,0.00015014416,0.00002594725,0.0000019966767],"category_scores_gemma":[0.000018944907,0.000062897685,0.000023638002,0.00015650224,0.000011559078,0.00034867995,0.000046152276,0.000027115742,0.0000013453873],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010802476,0.000047073518,0.000017575465,0.000008247507,0.000006017241,4.9204425e-7,0.00007661851,0.001070245,0.0033130317,0.9690782,0.00064246886,0.02573897],"study_design_scores_gemma":[0.00022509092,0.000046051744,0.000033832697,0.000007687743,0.00001023854,0.00000147172,0.000011138542,0.95348954,0.00067842996,0.045160465,0.00024544916,0.000090582675],"about_ca_topic_score_codex":8.769289e-7,"about_ca_topic_score_gemma":0.0000018542527,"teacher_disagreement_score":0.95241934,"about_ca_system_score_codex":0.00000807671,"about_ca_system_score_gemma":0.000013084696,"threshold_uncertainty_score":0.25648934},"labels":[],"label_agreement":null},{"id":"W2119595729","doi":"10.1007/s13721-014-0063-0","title":"Visualization of health indicators: utilizing data mining techniques and statistical analysis for effective comparison of user profiles","year":2014,"lang":"en","type":"article","venue":"Network Modeling Analysis in Health Informatics and Bioinformatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Interactivity; Variety (cybernetics); Computer science; Data science; Health informatics; Context (archaeology); Visualization; Health care; Health indicator; Data mining; World Wide Web; Artificial intelligence","score_opus":0.0625554309271082,"score_gpt":0.3961348925971909,"score_spread":0.33357946167008273,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2119595729","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005828189,0.0002467038,0.99319327,0.000057542504,0.00002213487,0.00046058575,0.00011481716,0.000038966195,0.000037795806],"genre_scores_gemma":[0.49711707,0.00038899176,0.50151867,0.00014125842,0.000011633567,0.000008132305,0.00080878404,0.0000048128377,6.510015e-7],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99559903,0.00019127778,0.0032509386,0.00020025327,0.000396832,0.00036169632],"domain_scores_gemma":[0.99638987,0.0005179237,0.0021331478,0.00063680636,0.00018102293,0.00014123421],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005854645,0.00019421926,0.0011933028,0.0014178056,0.00020494105,0.00012259456,0.0004745909,0.00009737365,7.5492665e-7],"category_scores_gemma":[0.00022699016,0.0001733825,0.00007249884,0.0034782884,0.000079912126,0.00066101976,0.00038148847,0.00010822515,8.262258e-8],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017522601,0.00012405166,0.14386651,0.0041659386,0.0009586782,4.098736e-8,0.01139927,0.4381797,9.8934e-8,0.04999028,0.00021417004,0.35108373],"study_design_scores_gemma":[0.00026065166,0.00021397148,0.00062352227,0.00021556136,0.00027538225,3.775916e-7,0.0012336855,0.9965652,0.000003914297,0.00019115795,0.00026810943,0.00014847114],"about_ca_topic_score_codex":0.00010229417,"about_ca_topic_score_gemma":0.000079552745,"teacher_disagreement_score":0.5583855,"about_ca_system_score_codex":0.000039945862,"about_ca_system_score_gemma":0.00013284145,"threshold_uncertainty_score":0.70703334},"labels":[],"label_agreement":null},{"id":"W2120326355","doi":"10.1145/1753326.1753716","title":"Useful junk?","year":2010,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":404,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chart; Recall; Bar chart; Computer science; Presentation (obstetrics); Pie chart; Contrast (vision); Information retrieval; Artificial intelligence; Psychology; Cognitive psychology; Statistics; Mathematics","score_opus":0.01759444065892258,"score_gpt":0.28861543848023313,"score_spread":0.27102099782131056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2120326355","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003093236,9.079705e-7,0.93629456,0.001026745,0.0003421691,0.000014148718,5.1665614e-7,0.0001606389,0.059067074],"genre_scores_gemma":[0.860836,0.0000033813549,0.11330142,0.004616024,0.00009915174,9.839077e-7,0.0000060936513,0.0000045277743,0.021132376],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99971926,0.0000037011898,0.00004939358,0.00009007851,0.00007418481,0.00006337207],"domain_scores_gemma":[0.999631,0.000008987762,0.000010721567,0.00028348994,0.000023898689,0.00004190767],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000614218,0.00002639836,0.000026143813,0.000026551674,0.000026771613,0.00011017623,0.00038761072,0.000014938465,0.0002854789],"category_scores_gemma":[0.000020470232,0.000020867648,0.000011737263,0.00014160108,0.0000100858315,0.0002309468,0.00009058661,0.000041912605,0.0005301603],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.0521776e-8,0.000011853669,0.00078929076,5.016448e-7,9.262715e-7,9.0502556e-7,0.000022231521,6.954278e-7,0.00060230744,0.9724209,0.021924341,0.004226036],"study_design_scores_gemma":[0.00010495538,0.000009392533,0.002458288,8.3898016e-7,0.0000010679519,0.000006278772,0.000005940479,0.15699843,0.0042779855,0.005094511,0.830938,0.000104343504],"about_ca_topic_score_codex":0.000003534357,"about_ca_topic_score_gemma":0.000019728714,"teacher_disagreement_score":0.96732634,"about_ca_system_score_codex":9.945388e-7,"about_ca_system_score_gemma":0.00001419536,"threshold_uncertainty_score":0.68143153},"labels":[],"label_agreement":null},{"id":"W2120857677","doi":"10.1145/2110192.2110204","title":"Evaluating information visualization in large companies","year":2010,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Visualization; Computer science; Set (abstract data type); Information visualization; Context (archaeology); Process (computing); Data science; Focus (optics); Work (physics); Automotive industry; Data visualization; Knowledge management; Engineering; Data mining","score_opus":0.0391547328087585,"score_gpt":0.3849972837720529,"score_spread":0.3458425509632944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2120857677","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03647472,0.000001237575,0.95772284,0.00016154152,0.000202805,0.000066905006,0.0000020481896,0.00012517952,0.005242716],"genre_scores_gemma":[0.974893,0.0000019823908,0.023879543,0.0010177889,0.00001771939,0.00000290884,0.00007077655,0.0000021019987,0.00011418809],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99936736,0.000025317599,0.00021156817,0.00008334139,0.00019760414,0.000114793],"domain_scores_gemma":[0.99959517,0.000024364612,0.00005971831,0.00019838786,0.000092884,0.000029482755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000504474,0.000049235976,0.000056824356,0.00015662305,0.000053182415,0.00023451362,0.0002772009,0.000030267476,0.00010244297],"category_scores_gemma":[0.00016631212,0.000044989985,0.0000118384205,0.0004620551,0.000007783027,0.0019972948,0.00011041511,0.0000650312,0.00013840177],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.3657525e-7,0.00002975419,0.0032671336,0.000005566635,9.756756e-7,1.5596791e-7,0.00065473875,0.00017495928,0.0002999335,0.98804945,0.00044588698,0.007070991],"study_design_scores_gemma":[0.00024623857,0.000012699677,0.006063803,0.0000037067364,6.6612137e-7,0.0000010254306,0.00007168894,0.9846158,0.00036034713,0.0010605897,0.007496474,0.00006698175],"about_ca_topic_score_codex":0.000013564903,"about_ca_topic_score_gemma":0.0001312042,"teacher_disagreement_score":0.9869889,"about_ca_system_score_codex":0.00000802685,"about_ca_system_score_gemma":0.00003368868,"threshold_uncertainty_score":0.22614202},"labels":[],"label_agreement":null},{"id":"W2122138382","doi":"10.1109/ccece.2002.1013099","title":"Scopira - a system for the analysis of biomedical data","year":2003,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Institute for Biodiagnostics","funders":"","keywords":"Computer science; Suite; Software; Software engineering; Architecture; Data science; Computation; Programming language","score_opus":0.08297028659589825,"score_gpt":0.3619952808510997,"score_spread":0.27902499425520144,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122138382","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000037578942,0.000035036595,0.9987336,0.00022737378,0.00008162599,0.00005554187,0.00005841594,0.000027674796,0.0007431924],"genre_scores_gemma":[0.9035627,0.000017762863,0.09444002,0.00070381927,0.000029696843,0.000006912634,0.0002865735,0.0000054742914,0.0009469949],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994277,0.00002695757,0.00015753199,0.00015567726,0.00016024135,0.00007192243],"domain_scores_gemma":[0.9987095,0.00015091822,0.000049712995,0.0010121041,0.000046290643,0.00003146684],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005068057,0.000033706838,0.000102834194,0.00010325328,0.000043795844,0.00005557653,0.0011411243,0.000014807143,0.000027034026],"category_scores_gemma":[0.00011989282,0.000018911467,0.00003833502,0.0012574557,0.000029887275,0.00012836121,0.00015277573,0.000012597328,0.0000044260296],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.692637e-7,0.000035264868,0.00015449162,0.000022318753,0.000327759,3.1446928e-7,0.00004106412,0.000054834087,0.00002403745,0.9863788,0.01021512,0.0027456621],"study_design_scores_gemma":[0.00008295977,0.0000076696315,0.00006612713,0.0000042574875,0.00017514352,4.965165e-7,0.00008144231,0.9462717,0.000121569974,0.0000326905,0.053127028,0.000028875047],"about_ca_topic_score_codex":0.00001481412,"about_ca_topic_score_gemma":0.000012088012,"teacher_disagreement_score":0.98634607,"about_ca_system_score_codex":0.000005044478,"about_ca_system_score_gemma":0.000045570323,"threshold_uncertainty_score":0.2120512},"labels":[],"label_agreement":null},{"id":"W2122753660","doi":"10.1109/wi.2003.1241195","title":"WebKIV: visualizing structure and navigation for Web mining applications","year":2004,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Visualization; Web modeling; Web mining; Web mapping; Web navigation; World Wide Web; Web page; Data Web; Web design; Aggregate (composite); Web intelligence; Data mining; Information retrieval","score_opus":0.019884077983009583,"score_gpt":0.3233100795415554,"score_spread":0.3034260015585458,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122753660","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0099718515,0.000027071785,0.9888737,0.000508282,0.00003549021,0.00015882633,0.000015701959,0.00011126226,0.00029779243],"genre_scores_gemma":[0.7463395,0.000006655562,0.2527034,0.00065210246,0.000055090863,0.000019064682,0.000085583924,0.000006184742,0.00013240014],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999511,0.000005447055,0.0001140834,0.00019027982,0.00008304473,0.0000961562],"domain_scores_gemma":[0.99966216,0.000025254607,0.00004269809,0.00016536405,0.000055565004,0.00004894311],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006322621,0.000058944584,0.00005811762,0.00004820771,0.00013288618,0.00017368462,0.00018130358,0.00002959323,0.0000045973275],"category_scores_gemma":[0.000011271111,0.000053899723,0.000014951748,0.00021994699,0.000017135992,0.00032860914,0.00006119548,0.000022143438,0.0000033165381],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.5092517e-7,0.000013547697,0.00017538761,0.000021383748,0.0000054554926,2.07271e-7,0.0002460839,0.00014421766,0.003168427,0.9827838,0.0003141006,0.013126927],"study_design_scores_gemma":[0.0024521723,0.000140127,0.001145805,0.00009863854,0.000036501144,0.000045634486,0.0006016606,0.69901145,0.022447215,0.11252311,0.1607844,0.00071328477],"about_ca_topic_score_codex":0.0000028423872,"about_ca_topic_score_gemma":0.000006280186,"teacher_disagreement_score":0.8702607,"about_ca_system_score_codex":0.0000146109705,"about_ca_system_score_gemma":0.000040844076,"threshold_uncertainty_score":0.2197967},"labels":[],"label_agreement":null},{"id":"W2122993881","doi":"10.1109/tvcg.2007.70596","title":"Spatialization Design: Comparing Points and Landscapes","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":62,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Spatialization; Grayscale; Computer science; Artificial intelligence; Scale (ratio); Hue; Point (geometry); Spatial analysis; Computer vision; Numerosity adaptation effect; Task (project management); Encoding (memory); Pattern recognition (psychology); Mathematics; Cartography; Geography; Perception; Remote sensing; Pixel","score_opus":0.03246405948961843,"score_gpt":0.2918198199804114,"score_spread":0.25935576049079295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122993881","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0038019253,0.000036628553,0.9952827,0.000057125595,0.00037042997,0.00016850681,0.0000039525526,0.00023289063,0.000045843248],"genre_scores_gemma":[0.9872703,0.00034863697,0.010785633,0.0014650666,0.000053881293,0.0000042625425,0.000020123562,0.000019677012,0.00003241745],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986165,0.00010626219,0.0003505137,0.0004123981,0.00028754497,0.00022679109],"domain_scores_gemma":[0.99920213,0.00013690637,0.00010799032,0.00024748576,0.00013546408,0.00017002608],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005074429,0.00019865064,0.00019327947,0.0004990896,0.00035567814,0.00035972625,0.00020853992,0.00009900826,0.000007142529],"category_scores_gemma":[0.0000044538288,0.00020111632,0.000040357372,0.0008094295,0.000058786696,0.0005250034,0.000009829183,0.000112191134,0.000005724733],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025569629,0.00023274022,0.00079312996,0.000044846372,0.00005075524,0.0000063813513,0.0012061113,0.0013014147,0.000020969723,0.97742623,0.00025039387,0.018641453],"study_design_scores_gemma":[0.00058174785,0.00014429718,0.0009809483,0.000041133124,0.00001945052,0.000020809253,0.000026098436,0.994339,0.0016027344,0.0010507349,0.0009524599,0.00024061576],"about_ca_topic_score_codex":0.000011222438,"about_ca_topic_score_gemma":0.000045706915,"teacher_disagreement_score":0.9930376,"about_ca_system_score_codex":0.00001515049,"about_ca_system_score_gemma":0.000022465485,"threshold_uncertainty_score":0.8201285},"labels":[],"label_agreement":null},{"id":"W2124009048","doi":"10.1145/502348.502358","title":"A framework for unifying presentation space","year":2001,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":160,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Presentation (obstetrics); Computer science; Zoom; Human–computer interaction; Context (archaeology); Interface (matter); Representation (politics); User interface; Scope (computer science); Diagrammatic reasoning; Space (punctuation); Multimedia; Programming language","score_opus":0.06836516142491823,"score_gpt":0.38494074585057714,"score_spread":0.3165755844256589,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124009048","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00019043604,0.0000073884808,0.9927821,0.002433024,0.000094338364,0.00006925855,7.497e-7,0.000106323874,0.0043163747],"genre_scores_gemma":[0.09281563,0.000028100192,0.8990779,0.0015739219,0.000083218285,0.000007718218,0.000013674058,0.0000051297748,0.0063947127],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99963903,0.000008737654,0.00006624749,0.000114711605,0.00008159263,0.000089680674],"domain_scores_gemma":[0.9996458,0.00007268456,0.000024770086,0.00018047719,0.00004267198,0.00003357363],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007202418,0.000034316417,0.00003628392,0.000037263544,0.00005343515,0.00014043071,0.0002249769,0.000020775007,0.000035573856],"category_scores_gemma":[0.000080383405,0.00003057453,0.000018523571,0.00025848302,0.0000058766836,0.00030302233,0.000046821602,0.000020672278,0.000030086592],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.0326485e-7,0.000011691571,0.00037566386,0.0000027890044,0.000002196461,5.539722e-7,0.00009336282,0.00006267342,0.000018362965,0.9911768,0.0036519777,0.0046032546],"study_design_scores_gemma":[0.00016752013,0.000025542136,0.0003114192,0.000010954855,0.0000030474519,0.0000031272884,0.00009799202,0.7482223,0.00064236554,0.1254554,0.12496224,0.000098093886],"about_ca_topic_score_codex":0.000005868658,"about_ca_topic_score_gemma":0.0000035213277,"teacher_disagreement_score":0.8657214,"about_ca_system_score_codex":0.000006541825,"about_ca_system_score_gemma":0.000013115006,"threshold_uncertainty_score":0.13541766},"labels":[],"label_agreement":null},{"id":"W2124079061","doi":"10.1145/1719970.1720062","title":"Workshop on intelligent visual interfaces for text analysis","year":2010,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visual analytics; Computer science; Visualization; Cultural analytics; Analytics; Data science; Point (geometry); Information visualization; Human–computer interaction; Interactive visual analysis; Face (sociological concept); Quality (philosophy); Data visualization; World Wide Web; Semantic analytics; Artificial intelligence; The Internet","score_opus":0.032210641166567584,"score_gpt":0.35978557268525563,"score_spread":0.32757493151868805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124079061","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007227071,0.000004152549,0.98892117,0.00083580636,0.0002798392,0.000072240284,0.0000034237496,0.000104606464,0.002551682],"genre_scores_gemma":[0.96512645,0.000007852628,0.026025658,0.0013944852,0.00006162473,0.000007536008,0.000026787546,0.000005792276,0.007343795],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992564,0.000012054333,0.00017054992,0.0002712729,0.00014440881,0.00014531774],"domain_scores_gemma":[0.99929434,0.00013557608,0.000048552254,0.00036782157,0.00007669942,0.00007703556],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018828423,0.00008682253,0.00012190467,0.00024063252,0.000063222,0.0002789232,0.00059635355,0.00004176596,0.00028336464],"category_scores_gemma":[0.00009807385,0.00006685857,0.00009538358,0.00079213467,0.000023081377,0.00018907759,0.00012314029,0.00008058057,0.00014259286],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010869528,0.00036510985,0.00064740574,0.000008312197,0.00033474562,0.0000012371432,0.0004761476,0.00090375467,0.0010184969,0.7491272,0.022692846,0.22441389],"study_design_scores_gemma":[0.000092466595,0.0000587136,0.00017348443,0.0000039590764,0.000046799338,3.6557202e-7,0.00008851038,0.9317412,0.012624732,0.0007046849,0.054317713,0.00014738821],"about_ca_topic_score_codex":0.000005206662,"about_ca_topic_score_gemma":0.0001569686,"teacher_disagreement_score":0.9628955,"about_ca_system_score_codex":0.000007427105,"about_ca_system_score_gemma":0.000016962977,"threshold_uncertainty_score":0.3102644},"labels":[],"label_agreement":null},{"id":"W2124691415","doi":"10.1037//1076-898x.6.4.336","title":"Illusory correlations in graphological inference.","year":2000,"lang":"en","type":"article","venue":"Journal of Experimental Psychology Applied","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Handwriting; Psychology; Personality; Trait; Big Five personality traits; Cognitive psychology; Set (abstract data type); Correlation; Association (psychology); Inference; Social psychology; Artificial intelligence; Computer science; Mathematics","score_opus":0.04016017632627575,"score_gpt":0.37977323662696993,"score_spread":0.33961306030069416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124691415","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.68059844,0.00064887357,0.18327871,0.0012442891,0.00089816743,0.00020768377,0.0000036054107,0.000071495575,0.13304871],"genre_scores_gemma":[0.99228776,0.00006689406,0.0054012137,0.0020922474,0.00004035884,0.0000027962112,0.0000024048106,0.0000037822904,0.00010256217],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9990478,0.000051646744,0.00043681753,0.00016241033,0.00015275988,0.00014857628],"domain_scores_gemma":[0.9995172,0.00004593299,0.00013156154,0.00020506272,0.00002265569,0.00007761412],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00022905532,0.00008982134,0.00018630727,0.00020158094,0.00004391966,0.00003286837,0.0005472429,0.00008617097,0.0009510279],"category_scores_gemma":[0.000009690686,0.000076115604,0.000058730315,0.000376316,0.00009430114,0.00022465987,0.000038568756,0.00021269555,0.000116659714],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005024585,0.0065247025,0.013573848,0.0000053985527,0.00012824265,0.00045172108,0.005895433,0.0015289818,0.097051695,0.7623784,0.036412574,0.07554654],"study_design_scores_gemma":[0.04472073,0.0065006614,0.43588486,0.00024341779,0.000089676614,0.0036832183,0.0041923695,0.03853648,0.047847215,0.16307326,0.2513886,0.0038394844],"about_ca_topic_score_codex":7.988972e-7,"about_ca_topic_score_gemma":5.9876544e-7,"teacher_disagreement_score":0.59930515,"about_ca_system_score_codex":0.000022681334,"about_ca_system_score_gemma":0.000023352819,"threshold_uncertainty_score":0.9999622},"labels":[],"label_agreement":null},{"id":"W2125811218","doi":"10.3138/carto.44.3.171","title":"Naïve Cartography: How Intuitions about Display Configuration Can Hurt Performance","year":2009,"lang":"en","type":"article","venue":"Cartographica The International Journal for Geographic Information and Geovisualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":112,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Animation; Flexibility (engineering); Salient; Perception; Human–computer interaction; Realism; Computer science; Domain (mathematical analysis); Contrast (vision); Relation (database); Psychology; Multimedia; Artificial intelligence; Computer graphics (images); Visual arts; Art; Mathematics","score_opus":0.01072534208507479,"score_gpt":0.2732278639081946,"score_spread":0.2625025218231198,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2125811218","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028097266,0.00019622811,0.94470304,0.02354835,0.0019004358,0.0006263276,0.00011589736,0.00021000055,0.0006024431],"genre_scores_gemma":[0.989107,0.0023470724,0.0009234269,0.0063697617,0.0002550866,0.00003911997,0.0008699873,0.000009568611,0.00007896838],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99783736,0.00008289788,0.0006723812,0.00023749222,0.000829245,0.00034063015],"domain_scores_gemma":[0.997079,0.000094022354,0.000598072,0.00032779927,0.0017127924,0.00018828777],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0008672296,0.00026577624,0.00020080929,0.0011935094,0.0011333346,0.0026489547,0.0010372986,0.0001281731,0.000012283438],"category_scores_gemma":[0.0001816598,0.00020685025,0.0002439427,0.0011210882,0.00015539872,0.0037282133,0.00007905151,0.00026023743,0.0000037541524],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000061535226,0.000103976796,0.004890181,0.000033456854,0.00023123961,0.0000022414486,0.0025502879,0.00078695494,0.00017873362,0.8848023,0.008045431,0.09831368],"study_design_scores_gemma":[0.0036507442,0.00094180286,0.05950678,0.00027481117,0.00018601488,0.00055381947,0.0015773466,0.4449215,0.0007689621,0.030267732,0.45619088,0.0011596215],"about_ca_topic_score_codex":0.000013276048,"about_ca_topic_score_gemma":0.000022037499,"teacher_disagreement_score":0.96100974,"about_ca_system_score_codex":0.000037190268,"about_ca_system_score_gemma":0.00010999399,"threshold_uncertainty_score":0.9983864},"labels":[],"label_agreement":null},{"id":"W2126296156","doi":"10.1109/vis.2003.10002","title":"Visualization of 2-manifold eversions","year":2003,"lang":"en","type":"article","venue":"IEEE Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Visualization; Computer science; Manifold (fluid mechanics); Data visualization; Artificial intelligence; Engineering","score_opus":0.02747447174667121,"score_gpt":0.3175737950083895,"score_spread":0.2900993232617183,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2126296156","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0033273012,0.000036025067,0.990353,0.000029366398,0.00083616877,0.00013355407,0.00000609937,0.00018338756,0.0050950972],"genre_scores_gemma":[0.9946172,0.00009153741,0.004259483,0.00025477234,0.000039393326,0.0000058487362,0.00008128323,0.000021953321,0.0006284841],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99845845,0.00017737057,0.00042447256,0.00031652613,0.00042446645,0.00019874505],"domain_scores_gemma":[0.9987977,0.000076486824,0.0002509628,0.0004682278,0.00031487748,0.00009175022],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034680183,0.00014478368,0.00017378393,0.00030368028,0.00012361386,0.000093901384,0.00040391544,0.00008707557,0.00009893808],"category_scores_gemma":[0.00027287935,0.00014966853,0.000064982545,0.0015591463,0.00002884488,0.00077473343,0.0000428991,0.00003803472,0.00006893681],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000032957512,0.00013797953,0.0007608896,0.000022083475,0.0000151813765,8.8753933e-7,0.00025453075,0.0004156911,0.0026705973,0.99239165,0.003038003,0.00028923558],"study_design_scores_gemma":[0.0033073628,0.0005346017,0.0010963236,0.0001494556,0.00010061406,0.000015186843,0.0002864966,0.62106115,0.26333752,0.0087495465,0.10026756,0.0010941465],"about_ca_topic_score_codex":0.000008216191,"about_ca_topic_score_gemma":0.0000066246644,"teacher_disagreement_score":0.9912899,"about_ca_system_score_codex":0.000038410566,"about_ca_system_score_gemma":0.00010308398,"threshold_uncertainty_score":0.6103305},"labels":[],"label_agreement":null},{"id":"W2127397139","doi":"10.1111/j.1467-8659.2012.03129.x","title":"Tracing Tuples Across Dimensions: A Comparison of Scatterplots and Parallel Coordinate Plots","year":2012,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"National Research Foundation Singapore; National University of Singapore","keywords":"Curse of dimensionality; Computer science; Visualization; Tuple; Tracing; Baseline (sea); Multivariate statistics; Dimension (graph theory); Dimensionality reduction; Data visualization; Data mining; Information retrieval; Artificial intelligence; Mathematics; Machine learning","score_opus":0.036556236899912754,"score_gpt":0.33478881703422386,"score_spread":0.2982325801343111,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2127397139","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1636201,0.0008682307,0.83438927,0.00045397843,0.00038914444,0.000114329996,0.00001380747,0.00012898259,0.000022142498],"genre_scores_gemma":[0.97614175,0.00006492641,0.022910122,0.00078163226,0.00004996961,0.0000040885366,0.000018345967,0.000014641469,0.000014526365],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984056,0.000068425456,0.0004264594,0.00030883597,0.0002690817,0.00052164536],"domain_scores_gemma":[0.99885124,0.00012382213,0.00020670498,0.00050399883,0.00011038124,0.00020387144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035880815,0.0001909466,0.00033659904,0.00016583859,0.0002442125,0.00016218626,0.0005622167,0.00007913987,0.0000015191822],"category_scores_gemma":[0.00001620002,0.00017679548,0.00008501506,0.0005436648,0.00015551882,0.000825508,0.00074917317,0.0001400543,0.000008661429],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000102722,0.0006493583,0.35768536,0.00013358406,0.00011693775,0.000003780126,0.0058337194,0.0003337639,0.00016026528,0.6032203,0.008456094,0.0233966],"study_design_scores_gemma":[0.0008028204,0.00016759262,0.040623102,0.00017021789,0.000025595753,0.00002522545,0.00024522463,0.9465405,0.000974185,0.0035142198,0.006439934,0.00047137888],"about_ca_topic_score_codex":0.000013181602,"about_ca_topic_score_gemma":0.000013249414,"teacher_disagreement_score":0.94620675,"about_ca_system_score_codex":0.000008676156,"about_ca_system_score_gemma":0.000016462596,"threshold_uncertainty_score":0.7209511},"labels":[],"label_agreement":null},{"id":"W2127760037","doi":"10.5210/ojphi.v4i3.4270","title":"Beyond information access: Support for complex cognitive activities in public health informatics tools","year":2012,"lang":"en","type":"article","venue":"Online Journal of Public Health Informatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Health informatics; Informatics; Computer science; Public health informatics; Variety (cybernetics); Data science; Engineering informatics; Public health; Health informatics tools; Health Administration Informatics; Perception; Knowledge management; Human–computer interaction; Cognition; Artificial intelligence; Medicine; Psychology; Health policy; Engineering; HRHIS","score_opus":0.22760457063556003,"score_gpt":0.4336423978833671,"score_spread":0.2060378272478071,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2127760037","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0035381268,0.000057331265,0.9791533,0.014109005,0.0006297726,0.0006204833,0.0006319616,0.000062302635,0.0011977557],"genre_scores_gemma":[0.31656957,0.0024592408,0.5480208,0.12637535,0.0008153193,0.000042046853,0.005565049,0.000050087016,0.000102581886],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99228185,0.00022249209,0.0051101306,0.00006323568,0.0010465232,0.0012757712],"domain_scores_gemma":[0.99135345,0.00045822756,0.005539672,0.00035088992,0.0011391715,0.0011586115],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.010375933,0.00028981772,0.0007652628,0.0016656523,0.0002931035,0.0017741906,0.0014031222,0.00012317963,0.000039855116],"category_scores_gemma":[0.002072045,0.00025690932,0.00014510157,0.0014177962,0.000083529616,0.04594575,0.00040350115,0.00050411973,0.000017608227],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000150231335,0.0010197749,0.004713387,0.0018679776,0.00011304824,5.224735e-7,0.06648088,0.00014094281,2.6708403e-7,0.060924284,0.04549311,0.8192308],"study_design_scores_gemma":[0.002787371,0.0008690809,0.006804001,0.00019516858,0.00000863717,0.00015718842,0.024156883,0.17503023,0.0000036515519,0.00032334996,0.7892656,0.00039884332],"about_ca_topic_score_codex":0.000010072347,"about_ca_topic_score_gemma":0.000023829409,"teacher_disagreement_score":0.8188319,"about_ca_system_score_codex":0.000595796,"about_ca_system_score_gemma":0.0052497727,"threshold_uncertainty_score":0.9999883},"labels":[],"label_agreement":null},{"id":"W2127964821","doi":"10.3917/i2d.152.0032","title":"Recherche en visualisation d’information ou Dataviz : pourquoi et comment ?","year":2015,"lang":"fr","type":"article","venue":"I2D - Information données & documents","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Musée de la Civilisation","funders":"","keywords":"Humanities; Computer science; Philosophy","score_opus":0.250858938396759,"score_gpt":0.41986738823540415,"score_spread":0.16900844983864516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2127964821","genre_codex":"methods","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00071429764,0.00024585496,0.8868823,0.07555753,0.0039606686,0.0009404888,0.00056367257,0.00037771382,0.03075749],"genre_scores_gemma":[0.19010685,0.009017601,0.2935186,0.3752932,0.002090423,0.00049062684,0.09138212,0.0002084841,0.0378921],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9950357,0.0010275048,0.0016169754,0.00026864588,0.0014509889,0.0006001505],"domain_scores_gemma":[0.9962306,0.00033139883,0.0010223977,0.0009602853,0.0009529059,0.000502427],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.00511548,0.00044295035,0.00034607883,0.00052124134,0.00024860984,0.003733642,0.0014087344,0.00044590762,0.00030359055],"category_scores_gemma":[0.0016340857,0.00047039826,0.0001138248,0.0011323664,0.00009548381,0.056001272,0.00087958685,0.00058053446,0.006548668],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036743993,0.00020035915,0.00049052504,0.00021390655,0.00009512827,0.0000021027638,0.030053407,0.002127068,0.0000028948173,0.4071545,0.43910494,0.12051842],"study_design_scores_gemma":[0.0016022443,0.00015481193,0.0002855552,0.00018588449,0.00004844037,0.000021665666,0.002624802,0.16800345,0.00018481955,0.004640349,0.8218089,0.00043912343],"about_ca_topic_score_codex":0.00047329708,"about_ca_topic_score_gemma":0.000026910448,"teacher_disagreement_score":0.5933637,"about_ca_system_score_codex":0.00095010997,"about_ca_system_score_gemma":0.0007641448,"threshold_uncertainty_score":0.99977475},"labels":[],"label_agreement":null},{"id":"W2130247386","doi":"10.1109/tvcg.2010.194","title":"SparkClouds: Visualizing Trends in Tag Clouds","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":168,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Tag cloud; Computer science; Cloud computing; Visualization; Data visualization; Bar chart; Information retrieval; Data science; World Wide Web; Artificial intelligence","score_opus":0.021222774147279317,"score_gpt":0.3008814098035279,"score_spread":0.2796586356562486,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2130247386","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015794598,0.000010514938,0.982212,0.00012159691,0.0011879695,0.00010154541,0.00001163656,0.0003106091,0.00024954817],"genre_scores_gemma":[0.99500257,0.00017544552,0.0024377443,0.0020510477,0.000098858654,0.000014407747,0.000028253547,0.000029050627,0.00016260879],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99811244,0.00011931848,0.00047278148,0.0005957755,0.00037401568,0.000325642],"domain_scores_gemma":[0.9989755,0.00008341655,0.000117383424,0.00051174045,0.000116781746,0.0001951518],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00035440366,0.000274876,0.00025662046,0.0012752978,0.0002671764,0.00040955882,0.00048823247,0.00018580093,0.00005455057],"category_scores_gemma":[0.0000041794174,0.00028527752,0.00010163578,0.0025672952,0.00010515382,0.0006221366,0.000012275614,0.0003986575,0.000016012516],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008524997,0.00041551917,0.0003082036,0.000017690234,0.00002360176,0.000009112951,0.0008171798,0.00033249773,0.0000945018,0.9597709,0.00046438587,0.037737843],"study_design_scores_gemma":[0.000736727,0.00013662245,0.0010549721,0.00003183763,0.000012773236,0.000023185943,0.000023734246,0.9872137,0.0015050077,0.0007701113,0.008124984,0.00036635084],"about_ca_topic_score_codex":0.00003771817,"about_ca_topic_score_gemma":0.00027756905,"teacher_disagreement_score":0.9868812,"about_ca_system_score_codex":0.000017976323,"about_ca_system_score_gemma":0.000040105766,"threshold_uncertainty_score":0.99995995},"labels":[],"label_agreement":null},{"id":"W2131629051","doi":"10.1002/meet.14504701061","title":"A comparison of a conventional taxonomy with a 3D visualization for use by children","year":2010,"lang":"en","type":"article","venue":"Proceedings of the American Society for Information Science and Technology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University","funders":"","keywords":"Task (project management); Taxonomy (biology); Visualization; Interface (matter); Computer science; Human–computer interaction; User interface; Psychology; Artificial intelligence; Engineering; Ecology; Biology","score_opus":0.017929285370468603,"score_gpt":0.3025646882175236,"score_spread":0.28463540284705496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131629051","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5195325,0.0000031533932,0.4788617,0.00076753355,0.000029014327,0.0006427556,0.00006180882,0.000056878413,0.000044653014],"genre_scores_gemma":[0.880906,0.0000053283466,0.11872762,0.0002690671,0.000003968557,0.00006737017,0.000010526606,0.0000022461077,0.00000788679],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99922836,6.31322e-7,0.00024857666,0.00012282615,0.00026099817,0.00013858551],"domain_scores_gemma":[0.9977263,0.000028768343,0.0007424465,0.000102303406,0.0013724706,0.000027714646],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003997149,0.00006424083,0.00014607648,0.00014577858,0.0002062344,0.00011957679,0.00064375566,0.000032411634,3.13132e-7],"category_scores_gemma":[0.00024223917,0.00004593183,0.000046033587,0.0018697946,0.0014605306,0.002175615,0.00015481004,0.000055095305,1.2784541e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020259042,0.000110758614,0.122056484,0.00008946486,0.000049615708,6.8695644e-10,0.00087804743,0.0000051396446,0.026428381,0.8049698,0.012477695,0.032914355],"study_design_scores_gemma":[0.0017777908,0.0010168878,0.0068332762,0.000051273215,0.00006602501,0.0000149180605,0.0039710915,0.7502206,0.14579313,0.0018462444,0.08802853,0.00038023895],"about_ca_topic_score_codex":0.0000058185633,"about_ca_topic_score_gemma":5.8261475e-7,"teacher_disagreement_score":0.80312353,"about_ca_system_score_codex":0.000012716722,"about_ca_system_score_gemma":0.00011585378,"threshold_uncertainty_score":0.53813857},"labels":[],"label_agreement":null},{"id":"W2131898753","doi":"10.1109/infvis.2003.1249008","title":"Edgelens: an interactive method for managing edge congestion in graphs","year":2004,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":142,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"University of Calgary","keywords":"Computer science; Graph; Theoretical computer science; Enhanced Data Rates for GSM Evolution; Node (physics); Focus (optics); Transparency (behavior); Graph drawing; Data mining; Artificial intelligence","score_opus":0.03626872601459591,"score_gpt":0.3731551114051933,"score_spread":0.3368863853905974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131898753","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000604958,0.000007585221,0.9964657,0.00084203464,0.00014800875,0.0001182929,0.0000023731093,0.000091956106,0.0017190875],"genre_scores_gemma":[0.2670159,0.0000149374955,0.7305856,0.0020316592,0.000030893007,0.000018532653,0.000039183302,0.000008658031,0.00025462502],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99939716,0.00003732205,0.00013431185,0.00023378801,0.00007179545,0.00012560216],"domain_scores_gemma":[0.99958944,0.000055638353,0.000039339597,0.00020744052,0.000064022664,0.000044087636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002745953,0.000065171975,0.00008317998,0.00018331365,0.000037546346,0.00011959718,0.00029937664,0.00002382826,0.0000060312623],"category_scores_gemma":[0.00004594596,0.000060557846,0.000025987618,0.0003257764,0.000010325989,0.0009200849,0.00006271514,0.000045463956,0.000009369948],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000033266547,0.000069142196,0.000055675137,0.0000063361144,0.000004575442,0.0000019046446,0.0005133038,0.0009169268,0.00012712658,0.9573067,0.00016012974,0.04083489],"study_design_scores_gemma":[0.0009723805,0.0001221795,0.0008265533,0.00004164776,0.000005754924,0.0000057837537,0.0003734757,0.7406169,0.0031470337,0.250974,0.0027192296,0.00019502755],"about_ca_topic_score_codex":0.00006863604,"about_ca_topic_score_gemma":0.00016338377,"teacher_disagreement_score":0.7397,"about_ca_system_score_codex":0.0000383863,"about_ca_system_score_gemma":0.000028106784,"threshold_uncertainty_score":0.24694774},"labels":[],"label_agreement":null},{"id":"W2132068130","doi":"10.1109/tvcg.2011.144","title":"A Survey of Visualization Systems for Network Security","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":277,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Visualization; Computer science; Data visualization; Data science; Information visualization; Network security; Visual analytics; Table (database); Creative visualization; Data mining; Computer security","score_opus":0.0549474450495887,"score_gpt":0.3004989653267069,"score_spread":0.24555152027711818,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2132068130","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010708707,0.00012465876,0.9971391,0.000003965857,0.00095766893,0.0003953893,0.0000833983,0.0001810645,0.000043908367],"genre_scores_gemma":[0.9973131,0.0006321354,0.0014056072,0.00040626913,0.000050700663,0.00003441748,0.00009384098,0.000027682616,0.000036262023],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982263,0.00027054892,0.00055652723,0.00042438725,0.00028315381,0.0002390776],"domain_scores_gemma":[0.9984597,0.00017688674,0.0002606151,0.00038882374,0.00058788207,0.00012606663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006699291,0.00021227024,0.0003004374,0.00033037827,0.00024873036,0.00014210182,0.0003626362,0.00013709287,0.000007581022],"category_scores_gemma":[0.00000975621,0.00021693711,0.00008732555,0.0013891713,0.000083110666,0.00042489872,0.000008146394,0.00007933138,0.0000022306112],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002992836,0.00036165875,0.0005661386,0.000114969014,0.000073121824,5.324421e-7,0.0010308826,0.0012539587,0.0000013363206,0.9944712,0.0008605401,0.0012357342],"study_design_scores_gemma":[0.0005265302,0.00034299848,0.0013449107,0.00006382397,0.00002978853,0.0000037805232,0.000016867374,0.9952909,0.00029742654,0.0011581897,0.000687778,0.0002370547],"about_ca_topic_score_codex":0.00014783713,"about_ca_topic_score_gemma":0.000074863696,"teacher_disagreement_score":0.9962422,"about_ca_system_score_codex":0.0000126337445,"about_ca_system_score_gemma":0.00005860746,"threshold_uncertainty_score":0.88464385},"labels":[],"label_agreement":null},{"id":"W2132317457","doi":"10.1109/tvcg.2009.162","title":"Lark: Coordinating Co-located Collaboration with Information Visualization","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":115,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Workspace; Computer science; Visualization; Flexibility (engineering); Human–computer interaction; Representation (politics); Focus (optics); Information visualization; Pipeline (software); Data visualization; Data science; World Wide Web; Data mining; Artificial intelligence","score_opus":0.011654941448717171,"score_gpt":0.28195302086655283,"score_spread":0.2702980794178357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2132317457","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0026970236,0.000011149329,0.99573237,0.00020975244,0.00023748074,0.00033290405,0.000022585067,0.0005576657,0.00019909574],"genre_scores_gemma":[0.9918452,0.00015250183,0.0025400699,0.005087806,0.00004380507,0.0000151917775,0.00024419365,0.000017472124,0.000053787415],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981605,0.00014901627,0.00050970854,0.00038485724,0.0005379205,0.0002580252],"domain_scores_gemma":[0.9985657,0.000057935293,0.00026293923,0.00035438334,0.00059997546,0.00015909682],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00027524977,0.000283249,0.00023019618,0.00074732443,0.00056154,0.00093612797,0.0002921286,0.00014275167,0.000012065852],"category_scores_gemma":[0.0000072836406,0.00026999772,0.000047609497,0.0024915899,0.00006586586,0.0028115094,0.000003659,0.0001485827,0.000018314391],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033754848,0.00028558355,0.00008943787,0.0000336187,0.00003310155,0.000002470708,0.0015480078,0.0034807813,0.000027103788,0.9742741,0.00095191674,0.01924015],"study_design_scores_gemma":[0.0010484156,0.00066814944,0.00045741847,0.0000694384,0.000027114647,0.000018473864,0.00010960496,0.9909654,0.0026976338,0.0004469727,0.0031232978,0.0003680259],"about_ca_topic_score_codex":0.000007474039,"about_ca_topic_score_gemma":0.0000127089215,"teacher_disagreement_score":0.99319226,"about_ca_system_score_codex":0.00004675991,"about_ca_system_score_gemma":0.00009931059,"threshold_uncertainty_score":0.9999752},"labels":[],"label_agreement":null},{"id":"W2132515156","doi":"10.24908/pceea.v0i0.3858","title":"\"RUGPLOT\" VISUALIZATION FOR PRELIMINARY DESIGN","year":2011,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Ontario Centres of Excellence","keywords":"Computer science; Plot (graphics); Visualization; Graph; Software; Class (philosophy); Scatter plot; Software engineering; Systems engineering; Data science; Data mining; Engineering; Theoretical computer science; Artificial intelligence; Programming language; Mathematics; Machine learning","score_opus":0.024977044916806815,"score_gpt":0.24172394519805107,"score_spread":0.21674690028124427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2132515156","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005339616,0.000118567565,0.97752565,0.00413031,0.0039475625,0.0018677805,0.000054544696,0.00048537634,0.0065305983],"genre_scores_gemma":[0.93775827,0.000011694073,0.057725776,0.00077422627,0.00015342303,0.00012755523,0.000023185225,0.00004046529,0.0033854304],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990957,0.0000075825255,0.00025028654,0.00019069802,0.00022737632,0.00022837927],"domain_scores_gemma":[0.9985932,0.000047225665,0.000318505,0.0001294369,0.0007650044,0.00014663434],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005078626,0.00010973512,0.00010950113,0.00027089028,0.00015792905,0.00012648532,0.0006327314,0.00009697025,0.000011171523],"category_scores_gemma":[0.001024338,0.00010871771,0.00006388677,0.00064638274,0.000009083574,0.0005423912,0.00003942062,0.00006434857,0.000006447559],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005636474,0.0001765875,0.01131782,0.00023332547,0.00009221277,4.6400974e-8,0.004505256,0.00062703853,0.0009292509,0.86036503,0.11941485,0.002332954],"study_design_scores_gemma":[0.000840225,0.00026418734,0.10170769,0.00037399007,0.00018326312,0.000008447406,0.0005384964,0.7395231,0.04302419,0.011342828,0.101079546,0.0011140498],"about_ca_topic_score_codex":0.0008444057,"about_ca_topic_score_gemma":0.00022303755,"teacher_disagreement_score":0.93241864,"about_ca_system_score_codex":0.00066807825,"about_ca_system_score_gemma":0.00060602423,"threshold_uncertainty_score":0.44333795},"labels":[],"label_agreement":null},{"id":"W2133414959","doi":"10.3102/10769986027001031","title":"Visions and Re-Visions of Charles Joseph Minard","year":2002,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":75,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Vision; Depiction; Graphics; Visualization; Computer science; Thematic map; Data science; Computer graphics (images); Visual arts; Cartography; Artificial intelligence; Sociology; Art; Geography","score_opus":0.06888977604375794,"score_gpt":0.37290420437207605,"score_spread":0.3040144283283181,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2133414959","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.64992124,0.0033009308,0.32762703,0.015991203,0.0014010298,0.00020384506,0.0009950394,0.000016176637,0.0005435069],"genre_scores_gemma":[0.85929984,0.0011521387,0.13853149,0.00014579218,0.000099340396,7.226973e-7,0.000018749963,0.0000055121404,0.00074644375],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.999222,0.000018217293,0.00034899783,0.00008905803,0.0002405681,0.00008119502],"domain_scores_gemma":[0.9990724,0.00012908735,0.00026598384,0.000095248964,0.00030247832,0.00013481244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000097551776,0.00006921097,0.00014039881,0.00011824543,0.000091479786,0.00007694174,0.00017845609,0.000026049323,0.00026677363],"category_scores_gemma":[0.00007609087,0.000056177236,0.00002552921,0.00014699118,0.00008156075,0.000263158,0.00006370763,0.00007892119,0.0000036317315],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012259299,0.00284658,0.07390199,0.0000800736,0.000053048327,0.000027595084,0.0037959612,0.000023616161,0.0009665581,0.56370324,0.22106285,0.13352624],"study_design_scores_gemma":[0.0031733424,0.0038321924,0.70843476,0.00075234746,0.0006972188,0.0011662198,0.0025403495,0.06330652,0.00067130954,0.093065195,0.121008925,0.0013516172],"about_ca_topic_score_codex":0.000008974054,"about_ca_topic_score_gemma":0.0000053901,"teacher_disagreement_score":0.63453275,"about_ca_system_score_codex":0.000011054348,"about_ca_system_score_gemma":0.00005603484,"threshold_uncertainty_score":0.29209843},"labels":[],"label_agreement":null},{"id":"W2133571633","doi":"10.1109/tvcg.2010.186","title":"Perceptual Guidelines for Creating Rectangular Treemaps","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":111,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Bar chart; Computer science; Rectangle; Pie chart; Luminance; Aspect ratio (aeronautics); Set (abstract data type); Scatter plot; Bar (unit); Tree (set theory); Data mining; Artificial intelligence; Statistics; Mathematics; Machine learning; Geometry","score_opus":0.04870517782880583,"score_gpt":0.34265972246783816,"score_spread":0.2939545446390323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2133571633","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00299571,0.000013411569,0.9950934,0.0002208439,0.0010294964,0.00023159936,0.00003047914,0.00031986798,0.0000651789],"genre_scores_gemma":[0.8355719,0.00040254925,0.14808406,0.0139564965,0.0007525684,0.000111570844,0.00013906918,0.00009836373,0.00088343373],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99857223,0.00005534672,0.00041425327,0.00046661065,0.0002700602,0.00022148227],"domain_scores_gemma":[0.99865586,0.00014156809,0.00010750181,0.00039400827,0.000552304,0.00014875783],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032093312,0.00021226393,0.00019744388,0.00035111967,0.0004988325,0.00036434588,0.00035828215,0.00013751717,0.000023897175],"category_scores_gemma":[0.00002711216,0.00020537213,0.00011657086,0.0006536663,0.000079748665,0.00043503358,0.0000064167743,0.00017059085,0.000006281951],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008202048,0.00016869989,0.000030001673,0.00002928208,0.000035361965,0.0000010916013,0.0007878387,0.00024158329,0.00025320987,0.97392833,0.0022306964,0.022285724],"study_design_scores_gemma":[0.0005271645,0.0001776935,0.000058613707,0.000026796326,0.000023964543,0.000015720121,0.000050026345,0.9829388,0.0015371372,0.0010980587,0.013287421,0.00025858896],"about_ca_topic_score_codex":0.000011179339,"about_ca_topic_score_gemma":0.000061022216,"teacher_disagreement_score":0.98269725,"about_ca_system_score_codex":0.000008519324,"about_ca_system_score_gemma":0.000047449925,"threshold_uncertainty_score":0.8374832},"labels":[],"label_agreement":null},{"id":"W2133784701","doi":"10.2466/pms.2002.95.3.837","title":"A Monte-Carlo Estimation of Effect Size Distortion Due to Significance Testing","year":2002,"lang":"en","type":"article","venue":"Perceptual and Motor Skills","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Monte Carlo method; Distortion (music); Statistics; Statistical physics; Econometrics; Computer science; Mathematics; Physics; Telecommunications","score_opus":0.017911620080773412,"score_gpt":0.2606812713363038,"score_spread":0.2427696512555304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2133784701","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74660033,0.000053577616,0.25231802,0.00015885457,0.0001275259,0.00026254918,0.000021156504,0.000100391655,0.00035757385],"genre_scores_gemma":[0.9812971,0.000008338432,0.017760128,0.00018930883,0.000032693733,0.00001227161,0.0000017306751,0.0000057170364,0.00069273723],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992085,0.000045629546,0.00019332908,0.0002391171,0.00018219749,0.00013124052],"domain_scores_gemma":[0.99931586,0.00024832343,0.00006834688,0.00020281169,0.000062653045,0.00010203193],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001394986,0.00009955974,0.00015772527,0.000053758027,0.000070817,0.0000635187,0.00018898326,0.000031263167,0.000041058724],"category_scores_gemma":[0.0007285807,0.00008655916,0.000029065326,0.00028478104,0.00003649799,0.00026506203,0.00007888084,0.000040340667,0.000035498328],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013669842,0.0004793146,0.0052526486,0.00019843201,0.000028724025,0.000017700015,0.012319045,0.004521483,0.018739255,0.0015745219,0.004392501,0.95246273],"study_design_scores_gemma":[0.0003685449,0.00059052877,0.06041769,0.000105491985,0.000017201524,0.000013312643,0.00004791253,0.9363931,0.00093981664,0.00006651839,0.0007877397,0.00025214776],"about_ca_topic_score_codex":0.000041782496,"about_ca_topic_score_gemma":0.000003911115,"teacher_disagreement_score":0.95221055,"about_ca_system_score_codex":0.000021442529,"about_ca_system_score_gemma":0.0000066078073,"threshold_uncertainty_score":0.35297802},"labels":[],"label_agreement":null},{"id":"W2133860801","doi":"10.1145/1936652.1936673","title":"A set of multi-touch graph interaction techniques","year":2010,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Graph; Set (abstract data type); Theoretical computer science; Human–computer interaction; Programming language","score_opus":0.035386433178103596,"score_gpt":0.35824469986806823,"score_spread":0.32285826668996465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2133860801","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0051199957,8.558186e-7,0.9917726,0.000181611,0.00015316567,0.00003807351,0.0000026972064,0.00015626078,0.0025747742],"genre_scores_gemma":[0.80459154,0.000009993625,0.19437087,0.00029614844,0.000025436775,0.0000025332374,0.000009864184,0.0000031765567,0.00069041713],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99964845,0.00000937429,0.00011030719,0.0001003751,0.000078073725,0.000053389467],"domain_scores_gemma":[0.99959034,0.000014243179,0.000047639962,0.00025212174,0.00006965235,0.000026027785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000808183,0.000038143884,0.000050723567,0.00009533253,0.000018056136,0.000042822303,0.00029644094,0.000026371677,0.00006407792],"category_scores_gemma":[0.000020344474,0.000031160173,0.000024379007,0.0002158153,0.000018576668,0.00032608554,0.000059897626,0.0000622577,0.000015657108],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000034503878,0.0002491389,0.0032180047,0.000035436984,0.000026755435,0.0000035234712,0.001490412,0.0000058742585,0.16886684,0.6632364,0.020600408,0.14226376],"study_design_scores_gemma":[0.00020056008,0.00006604676,0.00056653423,0.000016020429,0.0000050028734,0.000012884749,0.00012850443,0.30443352,0.60055053,0.0021989117,0.09163425,0.00018720175],"about_ca_topic_score_codex":0.000032072072,"about_ca_topic_score_gemma":0.00006462278,"teacher_disagreement_score":0.79947156,"about_ca_system_score_codex":0.0000020980367,"about_ca_system_score_gemma":0.000009909784,"threshold_uncertainty_score":0.12706749},"labels":[],"label_agreement":null},{"id":"W2133882911","doi":"10.1007/978-3-642-02115-2_21","title":"GPSel: A Gestural Perceptual-Based Path Selection Technique","year":2009,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Gestalt psychology; Computer science; Salient; Perception; Selection (genetic algorithm); Path (computing); Artificial intelligence; Closure (psychology); Computer vision","score_opus":0.01749811212321442,"score_gpt":0.2722831060053896,"score_spread":0.2547849938821751,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2133882911","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000010154806,0.00006867728,0.9959447,0.0007304101,0.0004713379,0.00040774283,0.0000063074885,0.00042096726,0.001939712],"genre_scores_gemma":[0.09344575,0.000040397495,0.8968441,0.007913958,0.0005511807,0.00001779435,0.000048894726,0.00005494419,0.0010830091],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9964693,0.000049771515,0.0004953381,0.0013997362,0.0010077031,0.00057815877],"domain_scores_gemma":[0.998034,0.00015593569,0.0002676129,0.0010301772,0.000327955,0.00018429011],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00073500274,0.0005172986,0.00044526538,0.0010014555,0.00028298952,0.00073832524,0.0026547294,0.00035976028,0.00004065563],"category_scores_gemma":[0.0000820571,0.00047357802,0.00014124649,0.0010813464,0.00038729206,0.000647333,0.0004670223,0.00073739485,0.000050527593],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000056972926,0.00009117987,0.000072753275,0.000043254273,0.00000897111,0.0000725489,0.00042110612,0.024952631,0.0006392559,0.03931618,0.00029478013,0.9340816],"study_design_scores_gemma":[0.00024641576,0.0003380615,0.0002053889,0.00037621506,0.000010578579,0.00008248114,1.3100109e-7,0.9461545,0.0016894048,0.042932715,0.0071216165,0.0008424929],"about_ca_topic_score_codex":0.000014276819,"about_ca_topic_score_gemma":0.000038447124,"teacher_disagreement_score":0.93323916,"about_ca_system_score_codex":0.0003548616,"about_ca_system_score_gemma":0.00074413384,"threshold_uncertainty_score":0.9997716},"labels":[],"label_agreement":null},{"id":"W2133934472","doi":"10.1109/tvcg.2010.205","title":"The FlowVizMenu and Parallel Scatterplot Matrix: Hybrid Multidimensional Visualizations for Network Exploration","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":91,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Institute for Cancer Research; Université du Québec à Chicoutimi; École de Technologie Supérieure","funders":"","keywords":"Computer science; Visualization; Parallel coordinates; Data visualization; Data mining; Multidimensional data; Node (physics); Graph drawing; Graph; Theoretical computer science","score_opus":0.020120958359618628,"score_gpt":0.298419829284691,"score_spread":0.2782988709250724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2133934472","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012989937,0.00004889739,0.9959427,0.0006394724,0.0013241525,0.00046598402,0.00003247504,0.00023780021,0.000009494446],"genre_scores_gemma":[0.88992584,0.0035630555,0.09271022,0.010601504,0.0009912561,0.00052556634,0.00036024395,0.0001692905,0.0011530488],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99833745,0.00011206943,0.00043611007,0.00050084846,0.00030767656,0.00030586796],"domain_scores_gemma":[0.99848235,0.00048687521,0.0001501995,0.00041592852,0.00029199585,0.0001726793],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00044123761,0.00024945044,0.00018716995,0.0002075609,0.0016139668,0.0006213528,0.00030013564,0.00009898434,0.0000056259687],"category_scores_gemma":[0.00001477468,0.00021122197,0.000085371736,0.0005937574,0.000172075,0.0007301934,0.00001555399,0.00019361223,0.0000052196947],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017482833,0.00012541769,0.000034505247,0.000017733775,0.000041238047,6.450661e-7,0.00023247619,0.0029894304,0.000025158866,0.98804176,0.0030232903,0.0054508755],"study_design_scores_gemma":[0.00067910226,0.00014385648,0.000081117774,0.000021956928,0.000030084171,0.000018258484,0.000020213673,0.9685261,0.00030336084,0.007076181,0.022841632,0.00025813008],"about_ca_topic_score_codex":0.000004842203,"about_ca_topic_score_gemma":0.000063574145,"teacher_disagreement_score":0.98096555,"about_ca_system_score_codex":0.0000098274095,"about_ca_system_score_gemma":0.000056304576,"threshold_uncertainty_score":0.9996858},"labels":[],"label_agreement":null},{"id":"W2134095301","doi":"10.1109/iv.2005.52","title":"From Form to Content: Using Shape Grammars for Image Visualization","year":2006,"lang":"en","type":"article","venue":"Ninth International Conference on Information Visualisation (IV'05)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Visualization; Computer science; Rule-based machine translation; Algebraic number; Content (measure theory); Identification (biology); Variation (astronomy); Theoretical computer science; Artificial intelligence; Algebra over a field; Computer graphics (images); Mathematics; Pure mathematics","score_opus":0.09215943139414245,"score_gpt":0.35660732408134427,"score_spread":0.2644478926872018,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2134095301","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016480068,0.0000019272857,0.9741827,0.002323343,0.0015688128,0.0007272682,0.0005833351,0.0003101203,0.003822402],"genre_scores_gemma":[0.91855294,0.000014447299,0.061672997,0.007664571,0.00070523063,0.00018265934,0.010334736,0.0000422794,0.00083014776],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99684817,0.00007311132,0.0012018674,0.00045330782,0.0010467012,0.0003768612],"domain_scores_gemma":[0.99651474,0.00013243583,0.000734884,0.0004406289,0.00199738,0.00017996068],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00051082385,0.00034504136,0.0002891187,0.00078180264,0.00030309512,0.0018641757,0.0010473834,0.00015380557,0.0005331184],"category_scores_gemma":[0.00040951092,0.0003591725,0.00013986649,0.00056819525,0.000060494098,0.006264196,0.00019766156,0.00013351745,0.0003505157],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000064227526,0.000105289175,0.00013249142,0.000018543331,0.000036435507,9.552731e-7,0.001210322,0.0008981327,0.0013200582,0.9769498,0.012536888,0.0067268657],"study_design_scores_gemma":[0.0012736327,0.00016306265,0.0005670902,0.00009819815,0.000017511975,0.000004873948,0.0005711301,0.94117266,0.0035357939,0.023884138,0.028269239,0.0004426595],"about_ca_topic_score_codex":0.00044555948,"about_ca_topic_score_gemma":0.00004361202,"teacher_disagreement_score":0.95306563,"about_ca_system_score_codex":0.00036845123,"about_ca_system_score_gemma":0.0002106634,"threshold_uncertainty_score":0.99988604},"labels":[],"label_agreement":null},{"id":"W2134594352","doi":"10.1109/c5.2006.4","title":"A Buffer Framework for Supporting Responsive Interaction in Information Visualization Interfaces","year":2006,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Rendering (computer graphics); Visualization; Human–computer interaction; Information visualization; Coherence (philosophical gambling strategy); Data visualization; Interactive visualization; Distributed computing; User interface; Computer graphics (images); Artificial intelligence; Programming language","score_opus":0.019677516194419712,"score_gpt":0.35742499202292366,"score_spread":0.33774747582850395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2134594352","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010590481,0.0000032626613,0.9872793,0.00054088444,0.00020232606,0.00018236999,0.0000039357797,0.00011225759,0.0010851771],"genre_scores_gemma":[0.9384286,0.0000030065662,0.060234457,0.0008654163,0.000043239856,0.000020938916,0.000151681,0.000005013075,0.00024765977],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913824,0.000037214937,0.00040724984,0.00013691086,0.00013166743,0.00014870612],"domain_scores_gemma":[0.9993263,0.0001586043,0.00018244283,0.00016086544,0.00015080356,0.000021012676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003154092,0.000077482764,0.000087921195,0.0002894494,0.00005221553,0.00032594524,0.00020997073,0.00005678372,0.000030742303],"category_scores_gemma":[0.00039706376,0.00007324296,0.000025245388,0.00047104523,0.000009308944,0.0025445018,0.00007070274,0.000054153676,0.00003479781],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016023112,0.000037836136,0.00071004115,0.000018318675,0.0000026104865,3.5825346e-7,0.00062683807,0.000788954,0.00011739797,0.9869021,0.003103368,0.0076761106],"study_design_scores_gemma":[0.00032424342,0.00006551824,0.0013094889,0.00006409765,0.000003158481,0.0000026761033,0.0005441355,0.9263658,0.007661808,0.046214506,0.017277017,0.00016758006],"about_ca_topic_score_codex":0.00006180311,"about_ca_topic_score_gemma":0.000055380668,"teacher_disagreement_score":0.94068766,"about_ca_system_score_codex":0.00005291109,"about_ca_system_score_gemma":0.00003268547,"threshold_uncertainty_score":0.31430975},"labels":[],"label_agreement":null},{"id":"W2135482287","doi":"10.1109/tvcg.2011.251","title":"Visual Thinking In Action: Visualizations As Used On Whiteboards","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":92,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Microsoft (Canada); Research Canada; University of Calgary","funders":"","keywords":"Visualization; Computer science; Brainstorming; Perspective (graphical); Information visualization; Diagrammatic reasoning; Human–computer interaction; Data visualization; Coding (social sciences); Multimedia; Data science; Artificial intelligence","score_opus":0.052205440549992314,"score_gpt":0.3210782530160777,"score_spread":0.26887281246608535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135482287","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012789199,0.000010687225,0.98483217,0.00007575633,0.00090240577,0.00027834962,0.000009136406,0.00046726016,0.00063502166],"genre_scores_gemma":[0.9934008,0.0002981089,0.0016321042,0.0042164274,0.000074046264,0.00003697121,0.00003180294,0.000047636324,0.00026211597],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99742466,0.00026195642,0.0005831641,0.00073821336,0.0006298293,0.00036219836],"domain_scores_gemma":[0.9988215,0.00011603006,0.00017361826,0.00049123284,0.00018324339,0.0002143855],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00036685372,0.00036202412,0.00030801774,0.0013010148,0.00053715124,0.00038406768,0.0005282141,0.00020868829,0.00009658211],"category_scores_gemma":[0.00000828602,0.0003774035,0.00012062393,0.002291298,0.00010679263,0.0009139961,0.000015759679,0.0003082517,0.00006314268],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028584458,0.0009449204,0.00032671203,0.000026915803,0.000043513955,0.000013971431,0.0036717134,0.0005650971,0.000010085404,0.99009067,0.0001776062,0.004100235],"study_design_scores_gemma":[0.0012599045,0.000803204,0.001174206,0.00014930397,0.0000308808,0.000027281842,0.00018384607,0.98487395,0.0034456863,0.005581352,0.0018721285,0.0005982661],"about_ca_topic_score_codex":0.00005782539,"about_ca_topic_score_gemma":0.00011831637,"teacher_disagreement_score":0.9845093,"about_ca_system_score_codex":0.0000586096,"about_ca_system_score_gemma":0.00009814262,"threshold_uncertainty_score":0.9998678},"labels":[],"label_agreement":null},{"id":"W2136227372","doi":"10.1186/s13040-015-0056-2","title":"The role of visualization and 3-D printing in biological data mining","year":2015,"lang":"en","type":"article","venue":"BioData Mining","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of General Medical Sciences; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; U.S. National Library of Medicine; IXICO; Servier; Eisai; Northern California Institute for Research and Education; University of California, San Diego; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; Synarc; University of Southern California; Medpace; Novartis Pharmaceuticals Corporation; Dartmouth College; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; National Center for Advancing Translational Sciences; Meso Scale Diagnostics; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Visualization; Data science; Computer science; Biological network; Biological data; Data mining; Endophenotype; Data visualization; Artificial intelligence; Machine learning; Bioinformatics; Biology; Neuroscience","score_opus":0.1481506632125918,"score_gpt":0.3576323327334887,"score_spread":0.20948166952089692,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136227372","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.66082215,0.0032795097,0.3322251,0.0004706022,0.00036382294,0.0002570251,0.000100724086,0.00016690222,0.00231413],"genre_scores_gemma":[0.97095925,0.00012575566,0.028594237,0.00007345355,0.000032787306,0.0000013270541,0.00019010752,0.0000044238377,0.00001864554],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991651,0.00007305424,0.00023737407,0.00026034244,0.0001337954,0.00013031787],"domain_scores_gemma":[0.9990768,0.00013280028,0.000114738265,0.0005856568,0.00004200575,0.000048024925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010654032,0.000060306236,0.00008951568,0.00006060499,0.000062419516,0.00015687205,0.0009800876,0.000032150616,9.549539e-7],"category_scores_gemma":[0.0008314543,0.00004291663,0.000005482324,0.00033849222,0.00005735435,0.0005165736,0.0014805039,0.000030220343,0.0000022913896],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012924076,0.000099795456,0.3952276,0.0000179798,0.000022803695,0.0000067269143,0.005399566,0.000013717566,0.0012090281,0.16742767,0.0020057834,0.42855638],"study_design_scores_gemma":[0.0002800441,0.00004452606,0.0037744404,0.000050314786,0.0000033753845,0.000005890909,0.00362853,0.9367109,0.00064960314,0.00026643474,0.054459315,0.00012663567],"about_ca_topic_score_codex":0.0000152099055,"about_ca_topic_score_gemma":0.000017026034,"teacher_disagreement_score":0.9366972,"about_ca_system_score_codex":0.000006276935,"about_ca_system_score_gemma":0.000046746263,"threshold_uncertainty_score":0.18453422},"labels":[],"label_agreement":null},{"id":"W2136731529","doi":"10.1109/i-society18435.2011.5978504","title":"Visual clustering in web search: An effective approach","year":2011,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Cluster analysis; Information retrieval; World Wide Web; Interface (matter); Search engine; Visualization; Exploratory search; Semantic search; Information visualization; User interface; Search analytics; Visual search; Web search query; Data mining; Artificial intelligence","score_opus":0.07780915593579701,"score_gpt":0.3308465174550918,"score_spread":0.2530373615192948,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136731529","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02246063,0.0000026772025,0.93224657,0.000010239426,0.000039579132,0.00010098531,6.436451e-7,0.0001060353,0.04503263],"genre_scores_gemma":[0.9551433,0.0000021635503,0.04438459,0.00021486651,0.000015342452,0.00000532503,0.000005714798,0.0000047126377,0.00022402481],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992873,0.000089843365,0.00010187672,0.00023362334,0.0001278953,0.00015946336],"domain_scores_gemma":[0.999644,0.000014558629,0.000014443418,0.00022628943,0.00002597371,0.00007476906],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030648758,0.00006369777,0.000076246506,0.00013522097,0.000030007364,0.000078904406,0.00043147858,0.000026948102,0.000036945956],"category_scores_gemma":[0.000010722166,0.00005490644,0.000015575046,0.0003746448,0.000020000663,0.0006184815,0.00025662352,0.000063659194,0.000047355625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032049564,0.0023453843,0.023808062,0.000091662434,0.000038168546,0.000059913764,0.024421388,0.00094031624,0.0014543261,0.7277715,0.00053433515,0.21850288],"study_design_scores_gemma":[0.00019172147,0.0000789925,0.005645344,0.000003919821,7.341163e-7,0.000003036481,0.00019424628,0.992744,0.0008264385,0.000096380456,0.0001285251,0.00008665888],"about_ca_topic_score_codex":0.00006478774,"about_ca_topic_score_gemma":0.00008137792,"teacher_disagreement_score":0.9918037,"about_ca_system_score_codex":0.000012483632,"about_ca_system_score_gemma":0.000020663532,"threshold_uncertainty_score":0.22390196},"labels":[],"label_agreement":null},{"id":"W2137090695","doi":"10.1609/icwsm.v2i1.18645","title":"iBlogVis: An Interactive Blog Visualization Tool","year":2021,"lang":"en","type":"article","venue":"Proceedings of the International AAAI Conference on Web and Social Media","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Usability; Visualization; Computer science; World Wide Web; Complement (music); Social media; Human–computer interaction; Information visualization; Multimedia; Data science; Data mining","score_opus":0.03663256425852604,"score_gpt":0.3123833967852382,"score_spread":0.2757508325267122,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137090695","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.954039,0.000021850437,0.0030974033,0.011760429,0.0017382206,0.00015473901,0.00007893697,0.00012642724,0.028983025],"genre_scores_gemma":[0.998027,0.00006558769,0.00050092454,0.000913729,0.00015953774,0.0000049918776,0.000021317814,0.000005347447,0.00030151618],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9990073,0.00001498834,0.000207306,0.0002472437,0.00042328498,0.000099916826],"domain_scores_gemma":[0.99876195,0.0000631921,0.00018449474,0.00006819228,0.00088563946,0.000036532798],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016174994,0.000095714175,0.00012581349,0.00007567774,0.00010694007,0.00030834807,0.000691742,0.00005405182,0.00005988335],"category_scores_gemma":[0.00034762907,0.0000773778,0.000044618257,0.00020971795,0.00007678863,0.0005683907,0.00030506126,0.000102582504,0.000005068455],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008644705,0.00009654044,0.0006793865,0.000009204391,0.000023827575,5.6461516e-7,0.0027522822,2.5450245e-7,0.008255511,0.9835782,0.00052559143,0.004070017],"study_design_scores_gemma":[0.0030676005,0.000306559,0.01764236,0.00065042963,0.00010942745,0.00005410696,0.017639345,0.37983233,0.1535593,0.4025905,0.023292832,0.0012551991],"about_ca_topic_score_codex":0.0000020608338,"about_ca_topic_score_gemma":0.000010403679,"teacher_disagreement_score":0.5809877,"about_ca_system_score_codex":0.000027593776,"about_ca_system_score_gemma":0.00011647305,"threshold_uncertainty_score":0.3155375},"labels":[],"label_agreement":null},{"id":"W2137561086","doi":"10.1109/tvcg.2008.127","title":"EMDialog: Bringing Information Visualization into the Museum","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":158,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Visualization; Exhibition; Computer science; Information visualization; Context (archaeology); Presentation (obstetrics); Human–computer interaction; World Wide Web; Visual analytics; Data visualization; Geovisualization; Data science; Multimedia; Visual arts; Artificial intelligence; Art; Archaeology","score_opus":0.018858624788155014,"score_gpt":0.2657990253389085,"score_spread":0.24694040055075347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137561086","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0032422885,0.000028716307,0.99500877,0.00022096594,0.0007445064,0.00022723294,0.0000059477834,0.00042176785,0.00009983729],"genre_scores_gemma":[0.9921306,0.00086504396,0.0012948482,0.0054541505,0.00008317812,0.000022843697,0.00005512536,0.000020673817,0.000073550626],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982775,0.00016284749,0.0004886384,0.00033183233,0.0004938545,0.00024535262],"domain_scores_gemma":[0.9988465,0.00010737338,0.00018067581,0.00046444483,0.0002697995,0.00013125887],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028892027,0.00024202588,0.00018463944,0.00056832976,0.0011755937,0.00043878664,0.00048525428,0.000115871924,0.000014261682],"category_scores_gemma":[0.000009491817,0.00020660454,0.000094503375,0.0016162517,0.00015308574,0.0017981812,0.00001587984,0.00017422628,0.000037174756],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009172805,0.0001602545,0.00012730304,0.000035590736,0.00005718806,0.000003300682,0.00955384,0.0021214425,0.000008485661,0.9747387,0.0015270544,0.011657665],"study_design_scores_gemma":[0.00044454364,0.00011323157,0.00044770207,0.000029934781,0.000020492598,0.00004048867,0.00006448514,0.9847251,0.00064789574,0.0005277308,0.012671737,0.00026662726],"about_ca_topic_score_codex":0.000044446653,"about_ca_topic_score_gemma":0.00002055934,"teacher_disagreement_score":0.9937139,"about_ca_system_score_codex":0.00003377271,"about_ca_system_score_gemma":0.00007463085,"threshold_uncertainty_score":0.90418357},"labels":[],"label_agreement":null},{"id":"W2137646757","doi":"10.1109/38.946634","title":"Using perceptual syntax to enhance semantic content in diagrams","year":2001,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Leverage (statistics); Theoretical computer science; Story-driven modeling; Data flow diagram; Representation (politics); Construct (python library); Class diagram; Focus (optics); Node (physics); Syntax; Software; Data mining; Artificial intelligence; Programming language; Unified Modeling Language","score_opus":0.06966246396791663,"score_gpt":0.3374914290117499,"score_spread":0.26782896504383324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137646757","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09261865,0.000038345774,0.90644467,0.00047197155,0.00007816226,0.00023586859,0.0000049055875,0.000057490364,0.000049927043],"genre_scores_gemma":[0.97531766,0.00014614049,0.02203632,0.0022641318,0.000119416414,0.000047033915,0.000008207356,0.000008631053,0.00005247363],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990187,0.000027060209,0.00023088335,0.0003836438,0.00014055402,0.00019911728],"domain_scores_gemma":[0.99929595,0.000055436016,0.00004856364,0.0003923405,0.0000725467,0.00013516123],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001331334,0.00011455997,0.00013600348,0.00019593748,0.0001339188,0.00020554398,0.00042637115,0.000039116738,0.0000024960725],"category_scores_gemma":[0.0000035787216,0.00011500923,0.00003413783,0.0008031472,0.00004794579,0.0001489494,0.00014261693,0.00008646402,0.000021800734],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000024205613,0.00034800975,0.020813685,0.000028842958,0.000018069113,0.000012920263,0.0007627203,0.0010654004,0.00095694,0.91365063,0.0008208035,0.061519556],"study_design_scores_gemma":[0.00020865246,0.000054059015,0.01947414,0.000059277336,0.000010230632,0.000038379745,0.000047046327,0.9476788,0.00018445165,0.0045403154,0.027317971,0.00038664465],"about_ca_topic_score_codex":0.0000948871,"about_ca_topic_score_gemma":0.00013398584,"teacher_disagreement_score":0.94661343,"about_ca_system_score_codex":0.000015732825,"about_ca_system_score_gemma":0.000019279985,"threshold_uncertainty_score":0.46899402},"labels":[],"label_agreement":null},{"id":"W2138868843","doi":"10.1198/106186002317375631","title":"A Brief History of the Mosaic Display","year":2002,"lang":"en","type":"article","venue":"Journal of Computational and Graphical Statistics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":92,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Mosaic; Computer science; Computer graphics (images); Artificial intelligence; Geography; Archaeology","score_opus":0.018858655242182307,"score_gpt":0.2492495687104026,"score_spread":0.2303909134682203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138868843","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018487314,0.00040479933,0.99625975,0.0010002849,0.000269962,0.000022294365,0.000051136627,0.0000037812915,0.0001392694],"genre_scores_gemma":[0.8904844,0.00020420416,0.107103534,0.0015639233,0.00007629446,3.47464e-7,0.00000783097,0.0000064264127,0.0005530462],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99905866,0.00005449847,0.0003505974,0.000068023095,0.0004005658,0.000067632645],"domain_scores_gemma":[0.9990362,0.000246294,0.0003066243,0.00008010258,0.00025720947,0.00007359595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013853918,0.000058047244,0.00012734276,0.00007093872,0.000040764964,0.000027213255,0.00028872935,0.000023087898,0.000028387674],"category_scores_gemma":[0.000109990724,0.00003794231,0.000052025996,0.00020034134,0.00015084825,0.00013207161,0.00006285147,0.000112549395,9.291475e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000032903174,0.00012033893,0.0013250855,0.000019032017,0.00003015274,0.000009264965,0.00025531664,0.0016818361,0.0000089024625,0.92307585,0.06520429,0.0082666185],"study_design_scores_gemma":[0.0004732675,0.00012786657,0.02476968,0.000034029268,0.00002595456,0.00011633099,0.000006497917,0.74202216,0.000003413633,0.18166079,0.050670546,0.00008946952],"about_ca_topic_score_codex":0.0000021697874,"about_ca_topic_score_gemma":0.0000011148722,"teacher_disagreement_score":0.8891562,"about_ca_system_score_codex":0.000022243716,"about_ca_system_score_gemma":0.00005511633,"threshold_uncertainty_score":0.15472426},"labels":[],"label_agreement":null},{"id":"W2139478206","doi":"","title":"Procrustes: A Declarative Scene Modelling System","year":2012,"lang":"en","type":"dissertation","venue":"oURspace (University of Regina)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Degree (music); Graduate students; Computer science; Mathematics education; Psychology; Artificial intelligence; Pedagogy","score_opus":0.02600003742826838,"score_gpt":0.24478957615223074,"score_spread":0.21878953872396237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139478206","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016348343,0.00033739538,0.9708817,0.023027765,0.00030507852,0.00019663603,0.000017368147,0.00015924245,0.0034399724],"genre_scores_gemma":[0.05753739,0.0005766188,0.18942386,0.000043418528,0.00017765368,0.0000013495182,0.0010493287,0.000072596195,0.75111777],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99897027,0.000060159757,0.000020289806,0.00034404616,0.0003693452,0.00023588436],"domain_scores_gemma":[0.9985832,0.000024599458,0.0004386244,0.00047834934,0.00034484066,0.00013040945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016269251,0.00019006718,0.00033114853,0.00027831199,0.00019789925,0.00005461479,0.00092191156,0.0002008201,0.0000026693713],"category_scores_gemma":[0.000007916868,0.00023638987,0.0001200026,0.0004991762,0.000037103895,0.0007332024,0.00009364137,0.00016870053,0.00006444342],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007156808,0.00013727731,0.0001552755,0.0026244726,0.00035958126,0.00009161759,0.011740664,0.004355492,0.00015780804,0.5411523,0.4322002,0.006953744],"study_design_scores_gemma":[0.00032956884,0.000049958744,0.000038510094,0.00078080624,0.00013569577,0.0000063060043,0.023573969,0.46922418,0.00011399076,0.000009428086,0.50536054,0.00037703523],"about_ca_topic_score_codex":0.000014068172,"about_ca_topic_score_gemma":0.00011452612,"teacher_disagreement_score":0.78145784,"about_ca_system_score_codex":0.00011885754,"about_ca_system_score_gemma":0.00021700816,"threshold_uncertainty_score":0.9639699},"labels":[],"label_agreement":null},{"id":"W2140064720","doi":"10.1109/achi.2008.29","title":"From Visualization to Visual Mining: Application to Environmental Data","year":2008,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Visualization; Computer science; Data science; Visual analytics; Data visualization; Information visualization; Human–computer interaction; Raw data; Software visualization; Software; Creative visualization; Data mining; Software system; Component-based software engineering","score_opus":0.04061368232625833,"score_gpt":0.3272017456036598,"score_spread":0.28658806327740144,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140064720","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028905282,0.0000046165915,0.96964085,0.00053758,0.000081105216,0.00015909296,0.00008089337,0.0001460281,0.00044455106],"genre_scores_gemma":[0.9035937,0.000011719951,0.08704081,0.0056813415,0.0001785306,0.000012801444,0.0023179073,0.000014867969,0.0011482827],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998746,0.000026454833,0.00020732422,0.0005572646,0.00031422303,0.00014877525],"domain_scores_gemma":[0.9987597,0.000028156677,0.000042379474,0.00096079666,0.000015014306,0.00019395706],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009708048,0.0001003922,0.00009516943,0.00010378687,0.00011340977,0.00008925316,0.0012014587,0.00003224854,0.00010110309],"category_scores_gemma":[0.000035226996,0.0001011659,0.000013168751,0.00042357482,0.000014422689,0.0005817521,0.0009597104,0.000021778234,0.0011258207],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003397145,0.0017206441,0.027884547,0.000011162388,0.00009480731,0.000031321677,0.012738353,0.0019481176,0.048181895,0.06599928,0.6754037,0.1659522],"study_design_scores_gemma":[0.00018807086,0.00007114159,0.0058673667,0.000004669004,0.0000053698996,0.000004249224,0.00015569407,0.81018454,0.003611923,0.00007273878,0.17956999,0.0002642603],"about_ca_topic_score_codex":0.00007080286,"about_ca_topic_score_gemma":0.000015823283,"teacher_disagreement_score":0.8826,"about_ca_system_score_codex":0.00003251683,"about_ca_system_score_gemma":0.000025490192,"threshold_uncertainty_score":0.9996519},"labels":[],"label_agreement":null},{"id":"W2140199509","doi":"","title":"Effects of Navigation Tool Information on Hypertext Navigation Behavior: A Configural Analysis of Page-Transition Data","year":2002,"lang":"en","type":"article","venue":"Journal of educational multimedia and hypermedia","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Hypertext; Transition (genetics); Computer science; Information retrieval; Recall; Multidimensional scaling; Task (project management); Hypermedia; World Wide Web; Psychology; Machine learning; Engineering","score_opus":0.022271881880696225,"score_gpt":0.2947755494152077,"score_spread":0.2725036675345115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140199509","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9829932,0.00028245422,0.014532201,0.0010837287,0.0006258206,0.00021401442,0.00018278086,0.000008018214,0.0000777825],"genre_scores_gemma":[0.9926178,0.00018343325,0.005955045,0.00017919055,0.00010953417,0.0000042118227,0.0009314757,0.000004149776,0.000015176065],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983847,0.000072849856,0.00074087735,0.0001369943,0.000561989,0.00010257571],"domain_scores_gemma":[0.99772394,0.0005970808,0.0007666934,0.0002889916,0.0005256931,0.00009759162],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030359052,0.0001143478,0.00030906228,0.0005641419,0.00005193839,0.000059201026,0.0004248809,0.000070658134,0.00006977607],"category_scores_gemma":[0.0003632961,0.00010069456,0.00009154122,0.00070628134,0.00008817927,0.0018768319,0.000039757677,0.00012347859,0.00000832091],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035026282,0.011940631,0.07263895,0.0024641047,0.0052032536,0.000049250422,0.07240187,0.004084674,0.109584734,0.059690688,0.025903964,0.63568765],"study_design_scores_gemma":[0.0017962711,0.00037563287,0.23246689,0.00036065682,0.0016150466,0.000057650217,0.00031632115,0.7575451,0.004111228,0.00030804102,0.0007602052,0.00028692008],"about_ca_topic_score_codex":0.000012320089,"about_ca_topic_score_gemma":0.0000011417497,"teacher_disagreement_score":0.75346047,"about_ca_system_score_codex":0.000029183619,"about_ca_system_score_gemma":0.00009346208,"threshold_uncertainty_score":0.4106205},"labels":[],"label_agreement":null},{"id":"W2140704526","doi":"10.1109/iv.2007.139","title":"Visualizing Web Navigation Data with Polygon Graphs","year":2007,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Visualization; Polygon (computer graphics); Data visualization; Information visualization; Web application; Tree (set theory); Data structure; Data mining; Theoretical computer science; World Wide Web; Programming language","score_opus":0.040171215753971236,"score_gpt":0.3430823389002629,"score_spread":0.30291112314629165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140704526","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0064558913,0.000020892003,0.98707736,0.000222752,0.00008026077,0.000047782345,0.0000068415666,0.00021896932,0.0058692778],"genre_scores_gemma":[0.9154681,0.000014796834,0.08194317,0.0013892358,0.000047581223,5.115148e-7,0.00038373287,0.00001053601,0.0007423401],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99908966,0.000015124835,0.00015543512,0.00029789584,0.00026616373,0.00017574172],"domain_scores_gemma":[0.9989342,0.000033290173,0.000057048772,0.0008382529,0.00005655765,0.000080634934],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004959496,0.00007548016,0.00006637587,0.00010460386,0.00008257483,0.00019225957,0.0009619093,0.000025004709,0.00001997799],"category_scores_gemma":[0.000014882234,0.00005785171,0.000010524954,0.0006978303,0.00002489382,0.0010773743,0.00030489438,0.000048039066,0.00004823738],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000056598005,0.0000899637,0.0044885054,0.000013841752,0.000020914606,0.000026681895,0.00018625574,0.000012558864,0.0014555465,0.96054083,0.006245136,0.026914088],"study_design_scores_gemma":[0.00080853194,0.00014586729,0.00320192,0.00008179814,0.000020272615,0.000059379356,0.00031659703,0.869384,0.007583616,0.0022716944,0.11559757,0.0005287845],"about_ca_topic_score_codex":0.000025623602,"about_ca_topic_score_gemma":0.00007450173,"teacher_disagreement_score":0.9582692,"about_ca_system_score_codex":0.000009881265,"about_ca_system_score_gemma":0.000042303884,"threshold_uncertainty_score":0.23591243},"labels":[],"label_agreement":null},{"id":"W2140950617","doi":"10.1002/jhbs.20078","title":"The early origins and development of the scatterplot","year":2005,"lang":"en","type":"article","venue":"Journal of the History of the Behavioral Sciences","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":188,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Graphics; Statistical graphics; Computer science; Galton's problem; Data science; History; Machine learning; Computer graphics (images)","score_opus":0.06953833514314313,"score_gpt":0.31656690263049825,"score_spread":0.24702856748735513,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140950617","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9879426,0.0006848455,0.0011338515,0.007077375,0.002856169,0.000095721036,0.000001822683,0.0000052233886,0.000202444],"genre_scores_gemma":[0.9944092,0.000015277816,0.003178378,0.00030089862,0.000041707845,4.6796305e-7,1.6380497e-8,0.0000026691107,0.0020513828],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99854493,0.00011715075,0.00039023708,0.000091494665,0.0007329211,0.00012328442],"domain_scores_gemma":[0.9987366,0.000037429716,0.0007358703,0.00034107274,0.00010875596,0.00004026725],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011536962,0.000071391965,0.0001110274,0.000042798743,0.00051635405,0.00006215605,0.003267826,0.00001886898,0.000006161842],"category_scores_gemma":[0.000033015418,0.000026386744,0.00010137381,0.00028597095,0.00095413753,0.00035985486,0.00045023442,0.00011965162,0.0000012343277],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006431384,0.0018990828,0.3258681,0.000066890985,0.00014335492,0.0000035874064,0.08124292,0.002070894,0.049708027,0.060928043,0.14655413,0.33145067],"study_design_scores_gemma":[0.0004828557,0.00021277883,0.26321295,0.00025687568,0.00009341818,0.00007592756,0.000556123,0.0022622587,0.01169817,0.0007528653,0.720137,0.00025877394],"about_ca_topic_score_codex":0.0000372212,"about_ca_topic_score_gemma":0.00010944857,"teacher_disagreement_score":0.5735829,"about_ca_system_score_codex":0.0002180566,"about_ca_system_score_gemma":0.00061283115,"threshold_uncertainty_score":0.60724884},"labels":[],"label_agreement":null},{"id":"W2141088087","doi":"10.1109/tvcg.2011.242","title":"The Effect of Colour and Transparency on the Perception of Overlaid Grids","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Athabasca University","keywords":"Computer science; Transparency (behavior); Grayscale; Artificial intelligence; Salient; Computer vision; Clutter; Image (mathematics)","score_opus":0.023008041218173212,"score_gpt":0.26755261566625405,"score_spread":0.24454457444808084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141088087","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05978761,0.000021948677,0.93956184,0.00006208522,0.00023196268,0.00019429672,0.000012849893,0.00004130056,0.00008607563],"genre_scores_gemma":[0.9988829,0.0006704829,0.00015498768,0.00023289004,0.000012413244,0.0000098417895,0.0000029424507,0.000008280376,0.000025276307],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99886054,0.0002406823,0.00030943204,0.00021909931,0.00025528288,0.00011495837],"domain_scores_gemma":[0.9991147,0.0002920091,0.00013404044,0.0003146064,0.000092852126,0.000051808496],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039353958,0.00014257265,0.00016207683,0.00015010043,0.00031120414,0.000064479704,0.00029496843,0.00006455175,0.000010580015],"category_scores_gemma":[0.0000047695517,0.00008658944,0.000073058654,0.000519655,0.00020839246,0.00016887016,0.0000047597905,0.00010558677,0.0000013128584],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007249896,0.00017549492,0.00069647585,0.00007803068,0.00007090166,5.6932316e-7,0.0024751518,0.00009572747,0.00007371729,0.9792725,0.00019780106,0.01679112],"study_design_scores_gemma":[0.00087273016,0.0027000133,0.0069497973,0.00011240626,0.00008176667,0.0000084718695,0.00012572392,0.97866523,0.008628373,0.0011424234,0.00048608467,0.00022699703],"about_ca_topic_score_codex":0.000017223056,"about_ca_topic_score_gemma":0.000012632452,"teacher_disagreement_score":0.9785695,"about_ca_system_score_codex":0.000006081078,"about_ca_system_score_gemma":0.000015663021,"threshold_uncertainty_score":0.3531015},"labels":[],"label_agreement":null},{"id":"W2141673665","doi":"10.1109/uidis.2001.929931","title":"On-line analytical processing while immersed in a CAVE","year":2002,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Visualization; Online analytical processing; Data visualization; Virtual machine; Human–computer interaction; Set (abstract data type); Virtual reality; Interactive visual analysis; Data warehouse; Data mining","score_opus":0.07964166395715515,"score_gpt":0.32835805128003914,"score_spread":0.24871638732288398,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141673665","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001882511,0.000021199327,0.93477285,0.0020847523,0.000050520066,0.000056808796,0.0000014741161,0.00010334786,0.06102654],"genre_scores_gemma":[0.9895562,0.0000062439585,0.0037860419,0.002560067,0.00001892272,0.0000013517646,0.0000038636467,0.0000040980094,0.0040632393],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927515,0.000017946484,0.00015887019,0.00021508896,0.0001737996,0.00015917003],"domain_scores_gemma":[0.99962837,0.000028418837,0.000025830102,0.00022031885,0.000031955675,0.00006508253],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009815707,0.00006754014,0.00009062939,0.00013332181,0.00003268763,0.00012836588,0.0003013831,0.000026671603,0.00037212527],"category_scores_gemma":[0.000044164593,0.00005568388,0.000021125396,0.0006711567,0.000017953946,0.0002519978,0.00006492975,0.00006561629,0.00024670095],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004222326,0.0008420734,0.001140857,0.00002583071,0.000011180396,0.00008386344,0.0011095207,0.0027285707,0.000039605602,0.86874324,0.038178124,0.08709292],"study_design_scores_gemma":[0.00023049022,0.00003379206,0.00009631782,0.000013517563,0.000001274916,0.0000019927306,0.00002680752,0.99714774,0.00006744481,0.0004344242,0.001865253,0.00008092801],"about_ca_topic_score_codex":0.00000768503,"about_ca_topic_score_gemma":0.000010192828,"teacher_disagreement_score":0.99441916,"about_ca_system_score_codex":0.000022150827,"about_ca_system_score_gemma":0.000012454947,"threshold_uncertainty_score":0.40745106},"labels":[],"label_agreement":null},{"id":"W2141716420","doi":"10.1145/1166253.1166279","title":"Mnemonic rendering","year":2006,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Mnemonic; Computer science; Rendering (computer graphics); Sight; Human–computer interaction; Visualization; Parallel rendering; Software; Multimedia; Artificial intelligence; Programming language; Cognitive psychology; Psychology","score_opus":0.01756363786153465,"score_gpt":0.268812268089317,"score_spread":0.2512486302277824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141716420","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00040649,0.000010750308,0.91452503,0.00032374077,0.00004713272,0.000008207528,1.9798601e-7,0.00014247227,0.08453599],"genre_scores_gemma":[0.9353148,0.000004039486,0.048548296,0.00063729595,0.000048919544,5.865794e-7,0.000006035651,0.0000028905415,0.015437162],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99971795,0.0000043312884,0.000058204463,0.000083839186,0.00006817909,0.00006749426],"domain_scores_gemma":[0.9997891,0.0000052981936,0.00001124327,0.00016856642,0.000011248358,0.000014537589],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000037941227,0.000025143914,0.000025191235,0.000025567058,0.000026860005,0.000087247965,0.00021909131,0.000008082403,0.000041872416],"category_scores_gemma":[0.0000029818655,0.000021587,0.0000113236065,0.00014966994,0.0000046223563,0.00017828184,0.00006875183,0.000013116926,0.00011811387],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.3315157e-8,0.0000096528165,0.00022697552,8.9319633e-7,6.4195444e-7,0.0000015035434,0.0000059113036,0.00007804276,0.00016793497,0.9809391,0.015756087,0.0028132524],"study_design_scores_gemma":[0.00013769613,0.00001274354,0.0026185992,0.0000043731843,0.0000016774685,0.0000074492286,0.00001107205,0.7564731,0.0064235902,0.020179577,0.21395946,0.00017063515],"about_ca_topic_score_codex":0.000025778145,"about_ca_topic_score_gemma":0.000012132898,"teacher_disagreement_score":0.9607595,"about_ca_system_score_codex":0.0000055554583,"about_ca_system_score_gemma":0.000008784389,"threshold_uncertainty_score":0.15181543},"labels":[],"label_agreement":null},{"id":"W2141752259","doi":"10.1145/2702123.2702476","title":"Trajectory Bundling for Animated Transitions","year":2015,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Defense Advanced Research Projects Agency","keywords":"Computer science; Tracking (education); Trajectory; Movement (music); Computer vision; Video tracking; Object (grammar); Visualization; Artificial intelligence; Animation; Computer graphics (images); Human–computer interaction","score_opus":0.08512820427975884,"score_gpt":0.3340681487253276,"score_spread":0.24893994444556874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141752259","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0003317603,0.000012972021,0.99450165,0.0006378392,0.00009017227,0.00005483206,0.000008209428,0.00019252444,0.004170068],"genre_scores_gemma":[0.72238743,0.0000052977152,0.27208897,0.0026014347,0.00009406975,0.0000149684965,0.00009627765,0.000011967874,0.0026996061],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99964565,0.000009112963,0.00008110849,0.00010362586,0.00007561997,0.000084906605],"domain_scores_gemma":[0.9996797,0.000015144377,0.000013219943,0.00013124906,0.00008674268,0.00007393548],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011988671,0.00003655466,0.000046085454,0.000041755007,0.00004107468,0.00008115265,0.00019328124,0.000015550517,0.000011757695],"category_scores_gemma":[0.00002185037,0.000032588716,0.0000231696,0.00017071182,0.00000822575,0.00025716968,0.000014066908,0.000014857748,0.000026901631],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000024998967,0.00012412904,0.000043718494,0.000015216368,0.000015173507,0.0000012438212,0.0014301804,0.0012388767,0.0007991344,0.9460723,0.04729354,0.0029640335],"study_design_scores_gemma":[0.00035905212,0.000051994983,0.000026458676,0.0000038202165,0.0000044085295,0.0000024990718,0.00013314359,0.9441167,0.0006730229,0.0025247617,0.05201747,0.000086675886],"about_ca_topic_score_codex":0.0000039091424,"about_ca_topic_score_gemma":0.000011260662,"teacher_disagreement_score":0.9435475,"about_ca_system_score_codex":0.000010273483,"about_ca_system_score_gemma":0.000047205165,"threshold_uncertainty_score":0.13289294},"labels":[],"label_agreement":null},{"id":"W2142225493","doi":"10.1109/tvcg.2005.2","title":"A Parallel Coordinates Style Interface for Exploratory Volume Visualization","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":75,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"","keywords":"Computer science; Visualization; Usability; Data visualization; Human–computer interaction; Volume rendering; User interface; Parallel coordinates; Rendering (computer graphics); Information visualization; Interface (matter); Computer graphics (images); Parallel rendering; Backtracking; Volume (thermodynamics); Data mining; Programming language","score_opus":0.024807271009512473,"score_gpt":0.2961167480024483,"score_spread":0.27130947699293584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142225493","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013237682,0.00005899966,0.99677217,0.00019029673,0.0006772782,0.00043294736,0.000037353864,0.00049049716,0.00001670516],"genre_scores_gemma":[0.98516446,0.0003985983,0.011099903,0.002740326,0.00009348085,0.00011095396,0.000082247774,0.000058856862,0.00025115916],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99819624,0.00009717555,0.00046401174,0.00061562954,0.00032182265,0.00030510788],"domain_scores_gemma":[0.99881727,0.00007390781,0.00016740926,0.00040864266,0.0003463067,0.00018646539],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002603604,0.00030097525,0.00026878348,0.00051340915,0.0004808335,0.00047751048,0.0004261516,0.0001491235,0.00001213006],"category_scores_gemma":[0.0000079182155,0.00031628687,0.00012488743,0.0010716673,0.000104089406,0.0009814227,0.000012347367,0.00012497138,0.000021495258],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026355774,0.00047863604,0.000024164518,0.00007083499,0.000064446765,0.0000017018501,0.001679947,0.011581998,0.000030202635,0.9820523,0.00093266706,0.0030567278],"study_design_scores_gemma":[0.0016987885,0.0004970644,0.000038213344,0.00008107798,0.000034062985,0.000009795419,0.000109232904,0.98426265,0.002368207,0.0035723378,0.0069165463,0.0004120269],"about_ca_topic_score_codex":0.0000099247245,"about_ca_topic_score_gemma":0.000022971743,"teacher_disagreement_score":0.98567224,"about_ca_system_score_codex":0.000054591423,"about_ca_system_score_gemma":0.00008752911,"threshold_uncertainty_score":0.9999289},"labels":[],"label_agreement":null},{"id":"W2142453530","doi":"10.1111/j.1467-8659.2011.02087.x","title":"TreeMatrix: A Hybrid Visualization of Compound Graphs","year":2012,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Visualization; Graph drawing; Adjacency matrix; Cluster analysis; Adjacency list; Theoretical computer science; Data visualization; Graph; Information visualization; Data mining; Algorithm; Artificial intelligence","score_opus":0.02188529305257428,"score_gpt":0.2883071846232263,"score_spread":0.266421891570652,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142453530","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007078501,0.00024830646,0.9909864,0.00018633784,0.0008252358,0.00012988843,0.000014479242,0.00018771717,0.00034311955],"genre_scores_gemma":[0.9842552,0.00007818519,0.014316668,0.0011010412,0.00009604926,0.000003928763,0.00009529658,0.000017991464,0.000035657526],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983496,0.00009048564,0.00044922458,0.00027117477,0.00040517972,0.00043433224],"domain_scores_gemma":[0.9986476,0.00007966308,0.00024219956,0.0006590005,0.00018721519,0.00018436057],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037778096,0.00018776336,0.00026536573,0.0004777633,0.00013421585,0.00012659859,0.00087392115,0.00005733232,0.000009819601],"category_scores_gemma":[0.0000150263695,0.00018174204,0.0001628471,0.0011898776,0.000098567056,0.0010057259,0.000416226,0.000086660235,0.000023113467],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000017997469,0.00020938084,0.016870627,0.000032076394,0.000033177777,0.000001850651,0.00017749185,0.000019502275,0.000029457306,0.9701835,0.010144224,0.002296927],"study_design_scores_gemma":[0.0010360861,0.00024968656,0.008011881,0.000094996874,0.000047045272,0.000088423745,0.000033783675,0.8880309,0.0026117673,0.04231231,0.05678663,0.000696495],"about_ca_topic_score_codex":0.000009546687,"about_ca_topic_score_gemma":0.0000033589813,"teacher_disagreement_score":0.97717667,"about_ca_system_score_codex":0.00001341182,"about_ca_system_score_gemma":0.000033400564,"threshold_uncertainty_score":0.74112254},"labels":[],"label_agreement":null},{"id":"W2142477824","doi":"10.1109/icsmc.1994.399920","title":"Evaluating the role of intelligent support in user interfaces to supervisory control systems","year":2002,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Supervisory control; Computer science; Human–computer interaction; Control (management); User interface; Systems engineering; Artificial intelligence; Engineering; Operating system","score_opus":0.10536327279354211,"score_gpt":0.3489928349533652,"score_spread":0.24362956215982307,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142477824","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.098605365,0.0004933002,0.88749963,0.001487536,0.00035452066,0.0005963729,0.00001037433,0.000091951806,0.0108609395],"genre_scores_gemma":[0.99675596,0.000011876163,0.0008556,0.00059845834,0.000013015889,0.000008940378,9.794717e-7,0.0000036694128,0.001751526],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99903166,0.00010441615,0.00031865592,0.00016320555,0.0002466212,0.00013544198],"domain_scores_gemma":[0.99937534,0.00009288502,0.000050963794,0.00035771602,0.000080426405,0.00004268779],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060452847,0.00006744295,0.00012460453,0.000089667155,0.000025686371,0.00010751249,0.0006923689,0.000019396552,0.00027348776],"category_scores_gemma":[0.00007988554,0.0000438056,0.0000232567,0.00031867067,0.00001588872,0.00018510521,0.00015148919,0.000045870427,0.00014889248],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023142582,0.00084918854,0.037902016,0.00011687926,0.00013262818,0.000008383279,0.028693622,0.11086965,0.014132057,0.5693724,0.017046962,0.22085305],"study_design_scores_gemma":[0.0001239305,0.000114392664,0.00013062918,0.000019808787,0.0000030962249,0.0000016656319,0.00089867524,0.98844266,0.002315858,0.00007340741,0.0078116865,0.000064168],"about_ca_topic_score_codex":0.00010197972,"about_ca_topic_score_gemma":0.000035953297,"teacher_disagreement_score":0.89815056,"about_ca_system_score_codex":0.000017031498,"about_ca_system_score_gemma":0.000013790561,"threshold_uncertainty_score":0.29944995},"labels":[],"label_agreement":null},{"id":"W2142493242","doi":"10.1109/tvcg.2009.111","title":"A Nested Model for Visualization Design and Validation","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":899,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Visualization; Data visualization; Domain (mathematical analysis); Focus (optics); Vocabulary; Visual analytics; Task (project management); Data mining; Data modeling; Upstream (networking); Information visualization; Creative visualization; Data science; Human–computer interaction; Machine learning; Software engineering; Systems engineering","score_opus":0.04481429713190511,"score_gpt":0.3127659514960759,"score_spread":0.2679516543641708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142493242","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007380386,0.000023572069,0.9980259,0.00014927782,0.00019004931,0.00051333406,0.00001270375,0.00033907598,0.00000802775],"genre_scores_gemma":[0.94872016,0.000543943,0.045430973,0.0049132006,0.000058705722,0.00004597572,0.00008662784,0.000033324315,0.000167092],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985013,0.00012206395,0.0003750822,0.00051582436,0.0002664405,0.00021926897],"domain_scores_gemma":[0.99905986,0.00011895376,0.00013313617,0.00028122318,0.00025688094,0.0001499732],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00032891816,0.00023745593,0.00020921031,0.00048222102,0.00042461074,0.00046592116,0.00021625351,0.00013298768,0.0000021531491],"category_scores_gemma":[0.000007134483,0.0002466437,0.00006339836,0.00081112736,0.00004904002,0.00080626266,0.0000040887744,0.00007919016,0.0000017278428],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024904277,0.00024188247,0.0000069163775,0.000028286633,0.000022636674,5.669662e-7,0.0008416979,0.031576093,0.00005563272,0.95153445,0.00041067653,0.0152562745],"study_design_scores_gemma":[0.00079146633,0.00038175102,0.000050252675,0.000035470064,0.000036164816,0.000009250825,0.000010282892,0.98938936,0.0016731337,0.007086163,0.0002552147,0.0002814922],"about_ca_topic_score_codex":0.0000016625113,"about_ca_topic_score_gemma":0.0000017250086,"teacher_disagreement_score":0.95781326,"about_ca_system_score_codex":0.000019394716,"about_ca_system_score_gemma":0.00005164849,"threshold_uncertainty_score":0.99999857},"labels":[],"label_agreement":null},{"id":"W2142714683","doi":"","title":"A model of navigation for very large data views","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Autodesk (Canada); University of Toronto","funders":"","keywords":"Computer science; Panning (audio); Task (project management); Zoom; Turn-by-turn navigation; Domain (mathematical analysis); Human–computer interaction; Process (computing); Data modeling; Parameterized complexity; Artificial intelligence; Database; Robot; Mobile robot","score_opus":0.16050520993348602,"score_gpt":0.3726680778733217,"score_spread":0.21216286793983566,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142714683","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00058410875,0.000008787819,0.99814266,0.00022762231,0.000032113487,0.00011068307,0.00006574043,0.00002834262,0.0007999585],"genre_scores_gemma":[0.38699502,0.000018395865,0.6057998,0.0019459471,0.000036238678,0.000019106397,0.0011447258,0.000008153188,0.0040325797],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99957865,0.000006811027,0.00012779086,0.00013367637,0.000081468694,0.00007157559],"domain_scores_gemma":[0.9992449,0.000017197417,0.000044899698,0.00059338735,0.000075175005,0.000024382623],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015473782,0.000032495005,0.000057893587,0.000021920843,0.000021834649,0.000053449072,0.00067717273,0.000014364991,0.000023946423],"category_scores_gemma":[0.000024070654,0.000026143525,0.000013923387,0.000097090226,0.000005894676,0.00090329506,0.00026646125,0.000011790081,0.000037056776],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.183598e-7,0.000116570205,0.00008263139,0.000050415027,0.0000094774605,5.0843422e-8,0.00018137837,0.0004113108,0.0016169234,0.7736048,0.210402,0.013523813],"study_design_scores_gemma":[0.00010882974,0.0000072398147,0.000012283259,0.000005237708,0.0000018685898,1.1643028e-7,0.000009063914,0.9868167,0.00041004294,0.004842603,0.007751267,0.00003474178],"about_ca_topic_score_codex":0.00000844911,"about_ca_topic_score_gemma":0.000004084452,"teacher_disagreement_score":0.9864054,"about_ca_system_score_codex":0.0000028352758,"about_ca_system_score_gemma":0.000024530931,"threshold_uncertainty_score":0.12583667},"labels":[],"label_agreement":null},{"id":"W2144024567","doi":"10.1145/1518701.1518897","title":"Sizing the horizon","year":2009,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":298,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Chart; Sizing; Computer science; Series (stratigraphy); Range (aeronautics); Visualization; Data mining; Statistics; Mathematics; Engineering","score_opus":0.0229192824832289,"score_gpt":0.2963769941804312,"score_spread":0.2734577116972023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144024567","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00020683647,0.000016442453,0.9464885,0.0067186356,0.000051896346,0.000015119465,1.1209894e-7,0.000090144684,0.04641231],"genre_scores_gemma":[0.9757817,0.0000147632945,0.012463424,0.008474456,0.000052373856,2.384485e-7,0.000001382958,0.0000011399031,0.0032105444],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99974626,0.000008886522,0.000044206183,0.00006684965,0.0000753308,0.000058470345],"domain_scores_gemma":[0.9997309,0.0000120075065,0.000010674817,0.0002159418,0.000013442862,0.00001704585],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007811073,0.000023009285,0.000020950698,0.000012356196,0.0000546873,0.0001296975,0.00038107263,0.0000065884924,0.00001752079],"category_scores_gemma":[0.000012341944,0.000012884754,0.000011600796,0.00016800457,0.000004860742,0.00016177288,0.000034274228,0.000019485768,0.000079766556],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.793277e-8,0.000006249164,0.000013107781,1.236026e-7,5.3862954e-7,4.8428296e-7,0.000037821643,0.000007016353,0.00006694125,0.9117753,0.008272537,0.079819836],"study_design_scores_gemma":[0.00015189192,0.00014588372,0.0024373564,0.0000054664183,0.0000031852796,0.000007057524,0.000071450915,0.520182,0.0025473004,0.031685933,0.4425975,0.00016495962],"about_ca_topic_score_codex":0.0000014471944,"about_ca_topic_score_gemma":8.715167e-7,"teacher_disagreement_score":0.97557485,"about_ca_system_score_codex":0.00000279571,"about_ca_system_score_gemma":0.0000074182167,"threshold_uncertainty_score":0.12506759},"labels":[],"label_agreement":null},{"id":"W2144690375","doi":"10.1109/iv.2008.64","title":"No Going Back: An Interactive Visualization Application for Trailblazing on the Web","year":2008,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; University of Saskatchewan; York University","funders":"","keywords":"Computer science; World Wide Web; Web page; Web design; Visualization; Web navigation; Human–computer interaction; USable; Client-side scripting; Construct (python library); Static web page; Programming language","score_opus":0.045273796496145026,"score_gpt":0.33293511521320335,"score_spread":0.2876613187170583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144690375","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001941753,0.0000011934387,0.9850299,0.00040756405,0.000084122345,0.0002532767,0.0000044103126,0.00011285195,0.012164927],"genre_scores_gemma":[0.97263044,0.00002566276,0.017732223,0.0051362035,0.00017161458,0.00005613802,0.00012619019,0.000018321307,0.004103212],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993078,0.000044952052,0.00015219992,0.00023999627,0.00014056638,0.000114468305],"domain_scores_gemma":[0.99926627,0.00014525639,0.000079974314,0.0003250605,0.00014247102,0.000040991887],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018292922,0.00007855955,0.00006689596,0.000060166425,0.00021888992,0.000109019726,0.00041419975,0.00002594291,0.000044572236],"category_scores_gemma":[0.000076550095,0.00005553872,0.000032318545,0.00026700657,0.000022022636,0.00066573365,0.00004558548,0.000038736114,0.00030307885],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009907981,0.0001396512,0.0001503753,0.0000075703338,0.0000107756905,3.0733224e-7,0.00081502803,0.00019312665,0.0038325095,0.9766877,0.012429519,0.005723507],"study_design_scores_gemma":[0.00015288507,0.000078784964,0.00009630801,0.000008239097,0.0000020230784,0.0000022444117,0.00004273102,0.94802916,0.0032162657,0.00044807387,0.047835577,0.000087691864],"about_ca_topic_score_codex":0.000005464669,"about_ca_topic_score_gemma":0.0000139684125,"teacher_disagreement_score":0.9762396,"about_ca_system_score_codex":0.000026306629,"about_ca_system_score_gemma":0.000042409345,"threshold_uncertainty_score":0.38955665},"labels":[],"label_agreement":null},{"id":"W2144821674","doi":"10.1145/606658.606659","title":"Diagramming information structures using 3D perceptual primitives","year":2003,"lang":"en","type":"article","venue":"ACM Transactions on Computer-Human Interaction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":71,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Story-driven modeling; Computer science; Class diagram; Artificial intelligence; Theoretical computer science; Unified Modeling Language; Software; Programming language","score_opus":0.040781001308072606,"score_gpt":0.324196312995483,"score_spread":0.2834153116874104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144821674","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014620749,0.0000036811387,0.9831442,0.000080288286,0.0013204868,0.00015005124,0.000008921534,0.00025275478,0.00041885287],"genre_scores_gemma":[0.84066767,0.000009615666,0.1585477,0.00056308875,0.000079991405,0.0000074740897,0.000040031075,0.0000132583355,0.00007117878],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985469,0.00015138852,0.00042517594,0.0003177137,0.00031006229,0.00024877774],"domain_scores_gemma":[0.9987981,0.00011762708,0.00018728548,0.00063984893,0.00015737499,0.00009980802],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014990119,0.00022324764,0.00017245449,0.0004698242,0.0005742897,0.00064068777,0.0005434441,0.000086537366,0.00018621473],"category_scores_gemma":[0.000034098477,0.000229495,0.00011133334,0.0004028732,0.000044712277,0.0034623018,0.000022964992,0.00028841317,0.00006475025],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003108198,0.00070794864,0.00014434432,0.000099936806,0.00025595445,0.000011421356,0.009492228,0.13205662,0.0020294632,0.10814273,0.0012849142,0.74574333],"study_design_scores_gemma":[0.0013665512,0.0005589292,0.0012054663,0.00016622433,0.000081035105,0.00023089461,0.0011072664,0.91987914,0.008998944,0.0048870915,0.060489375,0.0010290882],"about_ca_topic_score_codex":0.00004309541,"about_ca_topic_score_gemma":0.000016854676,"teacher_disagreement_score":0.82604694,"about_ca_system_score_codex":0.00016988919,"about_ca_system_score_gemma":0.000048441783,"threshold_uncertainty_score":0.9358534},"labels":[],"label_agreement":null},{"id":"W2145029924","doi":"10.1109/iv.2007.123","title":"Visual Data Mining of Web Navigational Data","year":2007,"lang":"en","type":"article","venue":"Proceedings","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Web mining; Web modeling; World Wide Web; Web mapping; Data Web; Web navigation; Context (archaeology); Visualization; Web intelligence; Web page; Information retrieval; Data visualization; Data science; Data mining","score_opus":0.08576136147741431,"score_gpt":0.3777078133742804,"score_spread":0.2919464518968661,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2145029924","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.063568845,0.00015454774,0.9212199,0.0011484588,0.00038719494,0.00016019194,0.00022536583,0.0002884618,0.012847068],"genre_scores_gemma":[0.89860356,0.000016832504,0.099854365,0.00039660017,0.00016625276,4.2012485e-7,0.0007472316,0.000009083255,0.00020564604],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99880534,0.0000022234944,0.00026379857,0.00039296228,0.000372038,0.00016365884],"domain_scores_gemma":[0.99906945,0.00004308054,0.00014328766,0.0005036357,0.00017085446,0.000069701404],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010264731,0.00007220727,0.00009591986,0.000091256574,0.00005488268,0.000120913086,0.0029261827,0.00003179917,0.000019552646],"category_scores_gemma":[0.00026180618,0.000070693735,0.000009487382,0.0005346504,0.000042472686,0.0018295415,0.0021235922,0.00005508573,0.00001633667],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027674287,0.00064225117,0.06960838,0.00035250557,0.00012977116,0.000014696712,0.0025419015,0.000004706132,0.01943035,0.42461857,0.29191685,0.19071233],"study_design_scores_gemma":[0.00025922095,0.000031703454,0.0017832455,0.000056392502,0.000012005066,0.000013304193,0.00022899485,0.9323709,0.0019815483,0.00028146492,0.06282016,0.00016104271],"about_ca_topic_score_codex":0.000003343528,"about_ca_topic_score_gemma":0.000002288965,"teacher_disagreement_score":0.9323662,"about_ca_system_score_codex":0.000008386392,"about_ca_system_score_gemma":0.00007460635,"threshold_uncertainty_score":0.54376245},"labels":[],"label_agreement":null},{"id":"W2145353669","doi":"10.1109/iv.2004.127","title":"The effect of shading in extracting structure from space-filling visualizations","year":2004,"lang":"en","type":"article","venue":"Proceedings. Eighth International Conference on Information Visualisation, 2004. IV 2004.","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Shading; Computer science; Visibility; Visualization; Computer vision; Object (grammar); Process (computing); Artificial intelligence; Space (punctuation); Computer graphics (images); Human–computer interaction; Geography","score_opus":0.02250723809808847,"score_gpt":0.30950310306650486,"score_spread":0.2869958649684164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2145353669","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21888545,0.00014512165,0.747697,0.0047356393,0.0023832612,0.0014076246,0.0003582815,0.0005131084,0.023874486],"genre_scores_gemma":[0.9961199,0.000083868814,0.002773275,0.00032894444,0.00014718735,0.00002490227,0.0004295573,0.000016599537,0.00007576554],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969613,0.00005221571,0.0011846534,0.00036463418,0.0010824836,0.00035471906],"domain_scores_gemma":[0.9973284,0.0002113418,0.0010073317,0.0002694101,0.001064305,0.00011918813],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00077841594,0.00033570736,0.0003019819,0.0006420128,0.00037188467,0.0011967135,0.0012464937,0.00016106624,0.00015148583],"category_scores_gemma":[0.0009660802,0.00026917816,0.00009093198,0.0010459364,0.00009779376,0.0051385043,0.00014077644,0.00032137745,0.00006389918],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052523807,0.00004791181,0.005775396,0.00004398582,0.00005607679,8.113253e-7,0.004121651,0.005268726,0.0009440749,0.98032755,0.00071075873,0.0026505417],"study_design_scores_gemma":[0.0047913524,0.00053024705,0.0061417003,0.0010879008,0.00004869164,0.000020057365,0.0026240842,0.880603,0.050373286,0.041863214,0.010835267,0.0010812094],"about_ca_topic_score_codex":0.00012736363,"about_ca_topic_score_gemma":0.00003227774,"teacher_disagreement_score":0.93846434,"about_ca_system_score_codex":0.00037934916,"about_ca_system_score_gemma":0.00021401096,"threshold_uncertainty_score":0.99997604},"labels":[],"label_agreement":null},{"id":"W2145992510","doi":"10.1109/mcg.2013.24","title":"Data Visualization on Interactive Surfaces: A Research Agenda","year":2013,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":66,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Visualization; Computer science; Variety (cybernetics); Human–computer interaction; Data visualization; Interactive visualization; Information visualization; Computer graphics; Data science; Multimedia; Computer graphics (images); Artificial intelligence","score_opus":0.1475498341706475,"score_gpt":0.4169134611412503,"score_spread":0.2693636269706028,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2145992510","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018787463,0.00003549327,0.9960185,0.00082718825,0.000107717715,0.00045810564,0.00006605354,0.00012276959,0.00048541313],"genre_scores_gemma":[0.9707123,0.00081141805,0.021534758,0.0048044655,0.000528718,0.00034398708,0.0008509182,0.00004150164,0.00037191107],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984866,0.000116222844,0.00023313054,0.0006150538,0.00032862995,0.00022036527],"domain_scores_gemma":[0.9979275,0.00025282538,0.000078756275,0.0012682509,0.00035381273,0.00011885152],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042869526,0.00012006522,0.00011516357,0.00029483938,0.00036417792,0.00069438986,0.0013533036,0.00005366671,0.00001351957],"category_scores_gemma":[0.000012298055,0.00011056165,0.000022397271,0.0010324563,0.00011242091,0.00078157114,0.0005764289,0.00018523056,0.00019724105],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.6637895e-7,0.00019667658,0.00011644401,0.000015060555,0.000022955692,6.977955e-7,0.0001902066,0.000074622556,0.000088394205,0.9271327,0.046836175,0.025325282],"study_design_scores_gemma":[0.0001254842,0.000054882945,0.0008537356,0.000019563502,0.0000035742644,0.0000028888114,0.000023275285,0.847212,0.000079793375,0.012958796,0.13852581,0.00014018796],"about_ca_topic_score_codex":0.00005510505,"about_ca_topic_score_gemma":0.00001490596,"teacher_disagreement_score":0.9744837,"about_ca_system_score_codex":0.000013599339,"about_ca_system_score_gemma":0.000040926607,"threshold_uncertainty_score":0.66960174},"labels":[],"label_agreement":null},{"id":"W2146006703","doi":"10.1145/989863.989885","title":"ValueCharts","year":2004,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":65,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science","score_opus":0.024491748494121855,"score_gpt":0.2942547383328805,"score_spread":0.2697629898387587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2146006703","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002106103,0.0000035584462,0.9751737,0.001292134,0.00006271219,0.000010888395,2.1097506e-7,0.00012768799,0.023118459],"genre_scores_gemma":[0.80586034,0.000009668124,0.18156789,0.007560204,0.000042414496,0.0000011082461,0.000004862702,0.0000038349885,0.0049496866],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99975747,0.0000027961726,0.000040981067,0.000074089774,0.00007086335,0.00005377806],"domain_scores_gemma":[0.9997802,0.0000025064044,0.0000076056895,0.00016579403,0.000014401192,0.000029535318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000038235317,0.000021613358,0.000021529693,0.000021819616,0.000022561502,0.00006227763,0.00022746927,0.0000073735814,0.000039991017],"category_scores_gemma":[0.0000068896916,0.000017580605,0.000010229326,0.00013217998,0.000004866914,0.00020159424,0.00005795533,0.000011425382,0.0004175587],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.277406e-8,0.000010203536,0.000012310328,3.61044e-7,6.4514853e-7,0.0000014182997,0.000032019303,0.00007400916,0.0000357234,0.99690014,0.0014152849,0.0015178461],"study_design_scores_gemma":[0.0013218544,0.00010874549,0.0011123023,0.00002030487,0.000005064625,0.000035257097,0.00005669289,0.1454025,0.033250086,0.44223136,0.37595144,0.0005043974],"about_ca_topic_score_codex":0.000004655802,"about_ca_topic_score_gemma":0.0000014385993,"teacher_disagreement_score":0.8056497,"about_ca_system_score_codex":0.0000062394533,"about_ca_system_score_gemma":0.000018537876,"threshold_uncertainty_score":0.53670114},"labels":[],"label_agreement":null},{"id":"W2147062644","doi":"10.1109/tvcg.2010.190","title":"Result-Driven Exploration of Simulation Parameter Spaces for Visual Effects Design","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":121,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Animation; Visualization; Rendering (computer graphics); Cluster analysis; Interactive visual analysis; Set (abstract data type); Computer graphics; Data visualization; Volume rendering; Graphics; Computer graphics (images); Human–computer interaction; Artificial intelligence","score_opus":0.04378189514371345,"score_gpt":0.32987153132174746,"score_spread":0.286089636178034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147062644","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004311855,0.00000529689,0.99413824,0.000045370038,0.0007795029,0.0005316515,0.000013839738,0.00016958147,0.000004650883],"genre_scores_gemma":[0.96669537,0.00005409418,0.03262302,0.00044011915,0.000062910774,0.000043629258,0.00003118569,0.000021875489,0.0000277883],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985903,0.0001392339,0.0003990282,0.0004038775,0.0002903661,0.00017722767],"domain_scores_gemma":[0.99831283,0.00074012787,0.00020529724,0.00030786791,0.000328692,0.000105167666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028856978,0.00020024835,0.00022477433,0.00045955993,0.00024232242,0.00024836216,0.000245704,0.00015045227,0.000003655321],"category_scores_gemma":[0.000029195842,0.00019759152,0.00009678481,0.00071769126,0.000085621614,0.0010409878,0.000005631113,0.00013483099,0.0000027007702],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000095859155,0.00060790684,0.000039561957,0.00018751454,0.00010350606,0.0000012887799,0.0018415387,0.17905782,0.0012092269,0.7888578,0.00024010702,0.027757877],"study_design_scores_gemma":[0.00074801105,0.0005316008,0.000057305395,0.00003678857,0.0000347459,0.0000015142938,0.000012928061,0.9803654,0.015271092,0.0021592213,0.0005709188,0.00021049257],"about_ca_topic_score_codex":0.0000040997893,"about_ca_topic_score_gemma":0.000010849892,"teacher_disagreement_score":0.9623835,"about_ca_system_score_codex":0.000010752145,"about_ca_system_score_gemma":0.000050875864,"threshold_uncertainty_score":0.80575484},"labels":[],"label_agreement":null},{"id":"W2147353820","doi":"10.1109/tvcg.2011.195","title":"Exploratory Analysis of Time-Series with ChronoLenses","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":90,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario College of Art and Design; University of Toronto","funders":"","keywords":"Computer science; Visualization; Visual analytics; Time series; Outlier; Data visualization; Exploratory data analysis; Focus (optics); Data mining; Scalability; Series (stratigraphy); Artificial intelligence; Data science; Human–computer interaction; Machine learning","score_opus":0.02674013143625667,"score_gpt":0.2543660216368068,"score_spread":0.22762589020055016,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147353820","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0061382987,0.000016804523,0.9933892,0.0000086079135,0.000093938695,0.00007834417,0.000020491581,0.0001545786,0.00009973],"genre_scores_gemma":[0.99192667,0.0003150711,0.0069062077,0.00066022377,0.000014998949,0.000011836825,0.000028628834,0.000020237656,0.00011614479],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989524,0.000080377555,0.0002785795,0.00031436334,0.00024267113,0.00013162613],"domain_scores_gemma":[0.99916947,0.000033497705,0.00013221566,0.0003762418,0.00019894454,0.00008964951],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011308491,0.00016086224,0.00025455377,0.0008603783,0.00014040702,0.000074165415,0.00025730493,0.00006045359,0.00005282973],"category_scores_gemma":[9.488023e-7,0.00014189938,0.000086211556,0.002384126,0.00013807995,0.0006028546,0.0000052417804,0.000064843196,0.000005803578],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006701681,0.0008413378,0.00092109764,0.000057874855,0.0014172712,0.000007521553,0.006153459,0.001843964,0.000044310436,0.9827518,0.00021565179,0.0056786803],"study_design_scores_gemma":[0.00036119204,0.0005464388,0.0012590799,0.000034996683,0.00036499134,0.000004868542,0.00007685381,0.9893175,0.0072170864,0.00020969711,0.0003365429,0.0002707668],"about_ca_topic_score_codex":0.000011255847,"about_ca_topic_score_gemma":0.000037638474,"teacher_disagreement_score":0.98747355,"about_ca_system_score_codex":0.000008206781,"about_ca_system_score_gemma":0.0000404578,"threshold_uncertainty_score":0.57864887},"labels":[],"label_agreement":null},{"id":"W2148893894","doi":"10.1111/cgf.12378","title":"ConVis: A Visual Text Analytic System for Exploring Blog Conversations","year":2014,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":79,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Automatic summarization; Metadata; Visualization; Set (abstract data type); Domain (mathematical analysis); Information retrieval; World Wide Web; Information visualization; Visual analytics; Human–computer interaction; Artificial intelligence","score_opus":0.03715807506847913,"score_gpt":0.27631692873404023,"score_spread":0.2391588536655611,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2148893894","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0021791102,0.000021897204,0.9949708,0.0007417046,0.0012016001,0.00024240265,0.000014232938,0.00044947487,0.00017876226],"genre_scores_gemma":[0.9797416,0.000013176706,0.01814466,0.0016349712,0.00025214246,0.000061148334,0.00007226119,0.000024781704,0.000055281063],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982637,0.000076180666,0.00041029995,0.0005214398,0.00028415522,0.0004442094],"domain_scores_gemma":[0.9985024,0.00025376774,0.00016835734,0.00064054277,0.00025036957,0.00018458693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045089153,0.00021370687,0.00029291,0.0004130456,0.00033727754,0.00042148252,0.0009067703,0.000073785064,0.0000027749581],"category_scores_gemma":[0.00003109808,0.00021312789,0.00019121109,0.00080319203,0.00007469667,0.0006451378,0.00033346002,0.0001077094,0.00004982696],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000022597662,0.00004925374,0.0007604933,0.00007510758,0.000053917025,0.0000015677567,0.00019985848,0.000147843,0.000010074489,0.99198335,0.0028403497,0.0038759375],"study_design_scores_gemma":[0.0006391321,0.00016724256,0.000206073,0.00006532147,0.00002981457,0.000009534083,0.00014052079,0.9729516,0.00017262402,0.0031853407,0.02216479,0.00026800745],"about_ca_topic_score_codex":0.000008262753,"about_ca_topic_score_gemma":0.000012649961,"teacher_disagreement_score":0.988798,"about_ca_system_score_codex":0.000040138526,"about_ca_system_score_gemma":0.00005171899,"threshold_uncertainty_score":0.8691103},"labels":[],"label_agreement":null},{"id":"W2149089202","doi":"10.1145/1017074.1017079","title":"Visualizing and discovering web navigational patterns","year":2004,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Web modeling; Web mapping; Web navigation; World Wide Web; Visualization; Data Web; Information retrieval; Web page; Web intelligence; Web mining; Human–computer interaction; Data mining","score_opus":0.01698991754727153,"score_gpt":0.2959849408491304,"score_spread":0.2789950233018589,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149089202","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08082404,0.000010165691,0.91738933,0.00060148456,0.000055635002,0.000020895335,0.0000044121466,0.00007962327,0.0010144274],"genre_scores_gemma":[0.9877312,0.00001761518,0.0113071995,0.00076506083,0.000025149975,8.8360554e-7,0.00001206668,0.0000029653042,0.0001378576],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995552,0.0000059088648,0.00008617272,0.0001435544,0.00012356431,0.00008561825],"domain_scores_gemma":[0.9997875,0.000010324004,0.00002044594,0.000117488926,0.000016390268,0.000047851267],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005808399,0.000048123333,0.000043674692,0.000033243057,0.00006066924,0.00021040121,0.00016121697,0.00001265633,0.000017475464],"category_scores_gemma":[0.000008495594,0.000042104104,0.000012061038,0.00011169912,0.0000121243465,0.000535545,0.00014877516,0.000026492671,0.00001830454],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.8911182e-7,0.000019355582,0.004294516,0.000007533685,0.000004217331,0.000003735503,0.00021952242,0.00020078587,0.00049537764,0.9926349,0.000061248924,0.0020586043],"study_design_scores_gemma":[0.0030887725,0.00015757598,0.043837186,0.00032609867,0.000017785023,0.00012649954,0.0007088767,0.8657339,0.015042597,0.046707336,0.023053784,0.0011995524],"about_ca_topic_score_codex":0.000024262057,"about_ca_topic_score_gemma":0.00001797156,"teacher_disagreement_score":0.94592756,"about_ca_system_score_codex":0.000013222221,"about_ca_system_score_gemma":0.000028990187,"threshold_uncertainty_score":0.20289038},"labels":[],"label_agreement":null},{"id":"W2149569288","doi":"10.1145/2559206.2574788","title":"Creating physical visualizations with makervis","year":2014,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Visualization; Workflow; Data visualization; Analytics; Variety (cybernetics); Human–computer interaction; Construct (python library); Visual analytics; Process (computing); Entertainment; Data science; Database; Artificial intelligence","score_opus":0.0263385900812774,"score_gpt":0.3293982502640645,"score_spread":0.30305966018278707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149569288","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007089213,0.000005434648,0.96852,0.00038557028,0.00009624718,0.00011541865,0.000010035915,0.00042512242,0.02973325],"genre_scores_gemma":[0.78703517,0.000023016426,0.20000449,0.0032703101,0.0006140001,0.0000489294,0.0006202518,0.00006339732,0.008320417],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99864537,0.00006698713,0.00020120858,0.00053716294,0.00035654067,0.00019273843],"domain_scores_gemma":[0.9985324,0.00006502971,0.0001609014,0.00095425313,0.0001806293,0.00010674222],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012311417,0.00021318595,0.00025919994,0.00011014832,0.00012173895,0.0006561904,0.0009937886,0.0000795176,0.00007537805],"category_scores_gemma":[0.000043421456,0.0001633973,0.00006803796,0.0003187281,0.000038789796,0.0001671796,0.001280806,0.00018969498,0.00013724394],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.856372e-7,0.00014953,0.000306383,0.00008889193,0.00005041904,0.0000041615895,0.00065457035,0.008127933,0.000009700793,0.98247087,0.005207005,0.0029296684],"study_design_scores_gemma":[0.00011851618,0.000034837994,0.00009351585,0.00008331928,0.000021729058,0.0000029256082,0.000020367044,0.9879852,0.00014390494,0.0043363567,0.0068866704,0.0002726925],"about_ca_topic_score_codex":0.00003270877,"about_ca_topic_score_gemma":0.000013515589,"teacher_disagreement_score":0.9798572,"about_ca_system_score_codex":0.000023609391,"about_ca_system_score_gemma":0.00012692499,"threshold_uncertainty_score":0.66631484},"labels":[],"label_agreement":null},{"id":"W2149576378","doi":"10.1007/11949619_31","title":"Clickstream Visualization Based on Usage Patterns","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Clickstream; Cluster analysis; Visualization; Data mining; Point cloud; Data visualization; Cloud computing; Set (abstract data type); Web server; Point (geometry); The Internet; Information retrieval; World Wide Web; Machine learning; Artificial intelligence; Web API","score_opus":0.01858013505904765,"score_gpt":0.283507413163195,"score_spread":0.26492727810414735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149576378","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000015668022,0.000023768052,0.99082357,0.00033637663,0.00090016983,0.00024172371,0.000033087712,0.00022729997,0.007398325],"genre_scores_gemma":[0.7005479,0.00008378527,0.26231048,0.028821407,0.0020947836,0.000025469373,0.0008633038,0.00023764872,0.005015239],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9961546,0.000048066977,0.00055191864,0.0014434165,0.0012746546,0.0005273296],"domain_scores_gemma":[0.99750495,0.00029484817,0.00032755348,0.00150423,0.00021256895,0.00015584785],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005960468,0.00051086466,0.00041201207,0.0011596181,0.00022363536,0.00086030056,0.002619914,0.0002758164,0.00005528181],"category_scores_gemma":[0.000071777,0.0004772232,0.00012555235,0.0007913817,0.0002728203,0.0005053054,0.00056875986,0.00040634614,0.000083362385],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000072659664,0.00025161362,0.0011547712,0.000107275584,0.000011894347,0.00016892758,0.00021768881,0.42173845,0.000037258935,0.11272573,0.00095032353,0.4626288],"study_design_scores_gemma":[0.00025786654,0.00016084759,0.00023708494,0.00035176863,0.0000065011773,0.0000062035856,3.892018e-8,0.982888,0.0005356947,0.010337212,0.004672432,0.0005463843],"about_ca_topic_score_codex":0.000029764858,"about_ca_topic_score_gemma":0.00006533443,"teacher_disagreement_score":0.7285131,"about_ca_system_score_codex":0.0002544579,"about_ca_system_score_gemma":0.00038455852,"threshold_uncertainty_score":0.99976796},"labels":[],"label_agreement":null},{"id":"W2149587266","doi":"10.1109/achi.2009.37","title":"Investigating the Comprehension Support for Effective Visualization Tools &amp;#150; A Case Study","year":2009,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Visualization; Program comprehension; Comprehension; GRASP; Set (abstract data type); Java; Software visualization; Human–computer interaction; Information visualization; Data visualization; Visual analytics; Data science; Software; Software engineering; Software development; Software system; Artificial intelligence; Programming language; Software construction","score_opus":0.07379102057723444,"score_gpt":0.38229152532921346,"score_spread":0.308500504751979,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149587266","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08539919,0.0000041221792,0.9124453,0.00037039944,0.00009470093,0.0010942535,0.0000042285583,0.00018809724,0.0003996828],"genre_scores_gemma":[0.9822141,9.665794e-7,0.013604915,0.0036736953,0.00005108371,0.000032849286,0.000047200658,0.0000069959333,0.0003682125],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998889,0.00014678748,0.00026056892,0.00030429772,0.00022471954,0.0001745848],"domain_scores_gemma":[0.99887025,0.00032285892,0.00010472422,0.00044092606,0.00018789883,0.000073322684],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005403358,0.00012273254,0.00013597566,0.00007035773,0.00036040653,0.00045266637,0.00036029145,0.000030183215,0.0000107228725],"category_scores_gemma":[0.0002653294,0.00008243901,0.00004618679,0.00051289506,0.000025283121,0.0005784734,0.00011042385,0.00005387942,0.000019336547],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014418604,0.0020721427,0.006169767,0.00006444862,0.0001271196,0.00018777812,0.027709138,0.0019554119,0.003191935,0.64680374,0.0398523,0.2718518],"study_design_scores_gemma":[0.0020132707,0.0017053201,0.0055392347,0.000034003286,0.000071108494,0.00054890796,0.0031204757,0.9592331,0.0011590079,0.00466498,0.021368802,0.00054178963],"about_ca_topic_score_codex":0.000033331897,"about_ca_topic_score_gemma":0.00006097119,"teacher_disagreement_score":0.9572777,"about_ca_system_score_codex":0.000022522672,"about_ca_system_score_gemma":0.000039781826,"threshold_uncertainty_score":0.43650723},"labels":[],"label_agreement":null},{"id":"W2149588749","doi":"10.1002/meet.14505001002","title":"The concept formerly known as information (the panel)","year":2013,"lang":"en","type":"article","venue":"Proceedings of the American Society for Information Science and Technology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Status quo; Typography; The arts; Identification (biology); Information science; Sociology; Computer science; Visual arts; Library science; Art; Political science; Law","score_opus":0.010373510234711678,"score_gpt":0.2615165043736869,"score_spread":0.25114299413897523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149588749","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.56994116,0.00013996319,0.13405044,0.2748983,0.000778353,0.004878156,0.000047756985,0.00091289775,0.014352962],"genre_scores_gemma":[0.9888531,0.00015322749,0.0050303666,0.0057396907,0.00001395307,0.00011811593,0.000002281538,0.0000026336606,0.00008661774],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988401,0.0000017002528,0.00033162738,0.000094411174,0.0004533242,0.00027886566],"domain_scores_gemma":[0.9972558,0.000067163084,0.00069273176,0.00021910173,0.0017253179,0.000039882798],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.000809218,0.00008636865,0.00010573271,0.000105431995,0.0011293107,0.00074847875,0.002010277,0.000034601988,0.000001020328],"category_scores_gemma":[0.00067424733,0.000043128257,0.00007169815,0.0030464397,0.0029130308,0.0075906613,0.00051868893,0.000105469655,0.00001793826],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000011404544,0.0000041695007,0.00017205412,0.000009437055,0.000010096361,6.183303e-10,0.0027091526,0.0000016043039,0.00042635362,0.7099761,0.016641399,0.27004853],"study_design_scores_gemma":[0.00043057752,0.00036515377,0.0016932505,0.000021428035,0.000020362908,0.000023953444,0.052273184,0.12031058,0.012411879,0.035631668,0.7765574,0.00026055495],"about_ca_topic_score_codex":0.000029412624,"about_ca_topic_score_gemma":3.553131e-7,"teacher_disagreement_score":0.759916,"about_ca_system_score_codex":0.000040860665,"about_ca_system_score_gemma":0.00015740072,"threshold_uncertainty_score":0.99980044},"labels":[],"label_agreement":null},{"id":"W2149931362","doi":"10.1109/mcg.2009.78","title":"CoCoNutTrix: Collaborative Retrofitting for Information Visualization","year":2009,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Petro-Canada","funders":"","keywords":"Computer science; Visualization; Retrofitting; Data visualization; Information visualization; Domain (mathematical analysis); Data science; Social network analysis; Human–computer interaction; World Wide Web; Data mining; Engineering; Social media","score_opus":0.013904848544250422,"score_gpt":0.2959758157368013,"score_spread":0.28207096719255087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149931362","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00026551622,0.000026098236,0.9979763,0.00068897166,0.00008814081,0.00054864376,0.000033607306,0.00015774147,0.00021500133],"genre_scores_gemma":[0.78073424,0.00046657573,0.19563061,0.020768326,0.0010125791,0.00042374435,0.0008887568,0.000021130914,0.000054014552],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99920344,0.000016511376,0.00028344072,0.00021556081,0.00013800383,0.00014304569],"domain_scores_gemma":[0.99902904,0.00006712121,0.00016876079,0.00027036067,0.00039787203,0.0000668685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001959799,0.00010972545,0.00011884639,0.00021572287,0.00031771063,0.00047649138,0.00030118448,0.000058065296,4.6371417e-7],"category_scores_gemma":[0.000009179849,0.00011157002,0.00003611601,0.0009058739,0.00003326132,0.00094061455,0.00003587694,0.000050809653,0.000005798022],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010333678,0.000027631891,0.000042968575,0.0000095660935,0.000005489684,4.7071037e-8,0.00012403201,0.00008169853,0.000027025404,0.9523309,0.002197449,0.045152187],"study_design_scores_gemma":[0.00037982574,0.00009106043,0.0006967097,0.000010297937,0.00000955927,0.0000023688665,0.000016581924,0.7905373,0.00021347911,0.032918938,0.17494756,0.00017634935],"about_ca_topic_score_codex":0.0000015027462,"about_ca_topic_score_gemma":9.46745e-7,"teacher_disagreement_score":0.91941196,"about_ca_system_score_codex":0.000010839006,"about_ca_system_score_gemma":0.00004035393,"threshold_uncertainty_score":0.45948175},"labels":[],"label_agreement":null},{"id":"W2151364652","doi":"10.1109/icsmc.1994.399869","title":"A continuously variable zoom for navigating large hierarchical networks","year":2002,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Zoom; Computer science; Variable (mathematics); Mathematics; Geology","score_opus":0.020673666407901317,"score_gpt":0.28270879710087377,"score_spread":0.26203513069297246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151364652","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00008831062,0.00003956827,0.9920462,0.000638171,0.00014273466,0.00010403224,0.000007379006,0.00018419813,0.0067494363],"genre_scores_gemma":[0.28940344,0.000031282107,0.6855486,0.011183697,0.00038839158,0.00003203014,0.00008037031,0.000025503328,0.013306686],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913806,0.00002576349,0.00018618091,0.00023363609,0.00012074705,0.000295616],"domain_scores_gemma":[0.99939555,0.00012453088,0.00004648013,0.00027945102,0.000064594075,0.00008942311],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026444858,0.00007789783,0.000111987356,0.000020123975,0.00014905017,0.00023633752,0.00044873072,0.000046424077,0.00022605722],"category_scores_gemma":[0.00008481969,0.00006825459,0.000041039504,0.000307265,0.000015982916,0.0002765865,0.00015130012,0.000101943544,0.000038970313],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.3655104e-7,0.00009054785,0.00020523377,0.000006825733,0.000010109858,0.0000020219438,0.00012962813,0.00033550835,0.000014084148,0.94171077,0.044468667,0.013025896],"study_design_scores_gemma":[0.00033140558,0.000030377643,0.000010862618,0.000013654639,0.0000029522412,0.0000031395903,0.000008928616,0.91322273,0.000019229023,0.0019473392,0.084315196,0.000094191404],"about_ca_topic_score_codex":0.0000048373627,"about_ca_topic_score_gemma":0.0000026545426,"teacher_disagreement_score":0.9397634,"about_ca_system_score_codex":0.000008652421,"about_ca_system_score_gemma":0.000008973047,"threshold_uncertainty_score":0.2783341},"labels":[],"label_agreement":null},{"id":"W2152621157","doi":"10.1109/tvcg.2009.122","title":"Bubble Sets: Revealing Set Relations with Isocontours over Existing Visualizations","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":311,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Canadian College of Osteopathy; University of Toronto","funders":"","keywords":"Computer science; Relation (database); Visualization; Set (abstract data type); Data visualization; Data mining; Data set; Variety (cybernetics); Cluster (spacecraft); Theoretical computer science; Artificial intelligence; Programming language","score_opus":0.030961614516373376,"score_gpt":0.3145584165828178,"score_spread":0.28359680206644444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152621157","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0024867742,0.00003449037,0.99568796,0.0003183896,0.00025930355,0.000284414,0.000033581,0.0005756349,0.00031946602],"genre_scores_gemma":[0.9826863,0.00019409558,0.010802463,0.005628024,0.000085813575,0.00002055155,0.00012038606,0.000042346324,0.00042005736],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99785554,0.00015970148,0.0005115971,0.0006379035,0.00048933725,0.00034594422],"domain_scores_gemma":[0.998615,0.00012747667,0.00021709575,0.0005146891,0.00029568732,0.00023001373],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00027661867,0.00032849135,0.00027943737,0.0006236508,0.00086513447,0.0005924395,0.00038023642,0.0001470941,0.000029676918],"category_scores_gemma":[0.000008080968,0.0003173662,0.00009166464,0.002021723,0.00008938037,0.0010716113,0.0000070607625,0.000235446,0.000013697702],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000128163665,0.00037648474,0.00015987357,0.000020490657,0.000058435646,0.000007170771,0.0014130156,0.00540439,0.000012083585,0.9854831,0.0014369766,0.005615133],"study_design_scores_gemma":[0.0009621906,0.0003874254,0.0005193428,0.00012387439,0.00005383301,0.000029660245,0.000073552066,0.9921466,0.00024108143,0.0019269,0.0030864123,0.00044913308],"about_ca_topic_score_codex":0.000019022591,"about_ca_topic_score_gemma":0.000040062427,"teacher_disagreement_score":0.9867422,"about_ca_system_score_codex":0.000047616017,"about_ca_system_score_gemma":0.000081642436,"threshold_uncertainty_score":0.9999278},"labels":[],"label_agreement":null},{"id":"W2153346883","doi":"10.1093/jof/104.6.316","title":"Challenges in Visualizing Forests and Landscapes","year":2006,"lang":"en","type":"article","venue":"Journal of Forestry","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"U.S. Forest Service; Clemson University; University of Alberta; Joint Fire Science Program; University of Toledo; U.S. Department of Agriculture","keywords":"Visualization; Computer science; Data science; Process (computing); Natural resource management; Resource (disambiguation); Quality (philosophy); Natural resource; Data mining; Ecology","score_opus":0.036459584273083386,"score_gpt":0.31084539647099996,"score_spread":0.2743858121979166,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2153346883","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9174014,0.0074774977,0.06627995,0.0032802632,0.00023755521,0.00005335251,0.0000020566522,0.000026797225,0.005241186],"genre_scores_gemma":[0.995993,0.00049871043,0.0033423763,0.000038550545,0.00010083588,1.7461943e-7,7.063067e-7,0.0000030458716,0.000022602864],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99941635,0.000020745227,0.00023895926,0.000074874915,0.00015225136,0.000096798576],"domain_scores_gemma":[0.99961495,0.00003774431,0.00014376067,0.00012280232,0.00004167498,0.000039062634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024437267,0.000051991756,0.00010920972,0.00015160664,0.000019487516,0.00007557315,0.00030322434,0.000031174506,0.0000015042771],"category_scores_gemma":[0.000041638068,0.000041663247,0.000025368325,0.00011590559,0.000010891248,0.000429654,0.000080713835,0.00007681822,0.0000011331101],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015297575,0.00026953654,0.38626853,0.000098949895,0.000024224802,0.00036516116,0.00050267595,0.0011429432,0.0001899897,0.5606142,0.004951499,0.045556955],"study_design_scores_gemma":[0.0015326249,0.00024051951,0.837423,0.0003036354,0.000012351693,0.0006349756,0.00029162504,0.077556066,0.0006390962,0.06837752,0.012727333,0.00026123598],"about_ca_topic_score_codex":0.0000050363574,"about_ca_topic_score_gemma":0.0001226854,"teacher_disagreement_score":0.4922367,"about_ca_system_score_codex":0.000009514262,"about_ca_system_score_gemma":0.000026723414,"threshold_uncertainty_score":0.16989778},"labels":[],"label_agreement":null},{"id":"W2153553545","doi":"10.3138/carto.46.4.239","title":"Visualizing the Dynamics of London's Bicycle-Hire Scheme","year":2011,"lang":"en","type":"article","venue":"Cartographica The International Journal for Geographic Information and Geovisualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":142,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Destinations; Flow map; Salience (neuroscience); Computer science; Representation (politics); Transport engineering; Operations research; Flow (mathematics); Geography; Tourism; Engineering; Mathematics; Artificial intelligence","score_opus":0.01890170425629471,"score_gpt":0.28172231511762463,"score_spread":0.2628206108613299,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2153553545","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022025319,0.00020492355,0.9722802,0.0029852658,0.0013362488,0.00036982854,0.000057614943,0.0000773666,0.00066324655],"genre_scores_gemma":[0.99133056,0.0014952994,0.0038593556,0.0027919407,0.00013903443,0.000031400174,0.0002733249,0.000014606249,0.000064469896],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981468,0.00008470484,0.00076054805,0.00014379759,0.0006482766,0.0002159168],"domain_scores_gemma":[0.9973146,0.00012945327,0.00074527436,0.000318476,0.0014041204,0.00008808274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012899794,0.00017055182,0.00015568039,0.00069373526,0.0005829882,0.0005837323,0.0013934615,0.00008507321,0.00002167265],"category_scores_gemma":[0.0002299596,0.00010828138,0.00021172925,0.00091055076,0.00023792336,0.0019910312,0.00022302117,0.00017852965,0.0000026584173],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037418133,0.000049134404,0.010877481,0.000021811762,0.00017317737,6.974418e-7,0.0021697227,0.000046208188,0.000021095764,0.9671543,0.0009036032,0.0185453],"study_design_scores_gemma":[0.0020041617,0.00031232412,0.019531222,0.000156907,0.000119700126,0.00031103092,0.0035204017,0.8358606,0.00051211996,0.053558286,0.08358389,0.00052935554],"about_ca_topic_score_codex":0.00004998928,"about_ca_topic_score_gemma":0.00003714596,"teacher_disagreement_score":0.9693053,"about_ca_system_score_codex":0.000021967187,"about_ca_system_score_gemma":0.00007426028,"threshold_uncertainty_score":0.5628944},"labels":[],"label_agreement":null},{"id":"W2153836330","doi":"10.1109/tvcg.2007.70436","title":"Visual Perception and Mixed-Initiative Interaction for Assisted Visualization Design","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Waterloo; National Science Foundation","keywords":"Computer science; Visualization; Human–computer interaction; Context (archaeology); Salient; Perception; Data visualization; Creative visualization; Domain (mathematical analysis); Data science; Artificial intelligence","score_opus":0.06620721598083383,"score_gpt":0.3252732925827256,"score_spread":0.25906607660189174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2153836330","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0067820386,0.000019712597,0.9915162,0.000070721944,0.0006964425,0.0005063807,0.000021824932,0.00036909114,0.00001762606],"genre_scores_gemma":[0.987418,0.0008745042,0.009455374,0.0018417877,0.000100217054,0.0000763939,0.00010883128,0.000041583186,0.000083326806],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979689,0.00029314394,0.0004846119,0.00064653903,0.0003466859,0.00026011985],"domain_scores_gemma":[0.99869436,0.00028627232,0.00021013651,0.00023907641,0.00039201442,0.00017812387],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003111216,0.00031083357,0.00028178535,0.00068058836,0.00085550983,0.0003066092,0.00019575744,0.00017537012,0.000011461841],"category_scores_gemma":[0.0000138899695,0.00032528094,0.00010003393,0.00092710636,0.00014403176,0.0011694825,0.000010034938,0.00014231948,0.000007240277],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003362212,0.002055473,0.00035042732,0.00029720773,0.0004099599,0.000017515616,0.010109501,0.005660021,0.0005855386,0.8565131,0.0054748273,0.11819021],"study_design_scores_gemma":[0.0010086797,0.0006869041,0.0015849455,0.000056885994,0.00004547956,0.00008325179,0.00011860041,0.99284965,0.0017083902,0.00042783556,0.0010571689,0.0003722205],"about_ca_topic_score_codex":0.000008397061,"about_ca_topic_score_gemma":0.000009747281,"teacher_disagreement_score":0.9871896,"about_ca_system_score_codex":0.00006507611,"about_ca_system_score_gemma":0.00008227527,"threshold_uncertainty_score":0.99991995},"labels":[],"label_agreement":null},{"id":"W2154768595","doi":"10.1002/meet.2011.14504801327","title":"Shaken and stirred: ASIS&amp;T 2011 attendee reactions to shaking it up: Embracing new methods for publishing, finding, discussing, and measuring our research output","year":2011,"lang":"en","type":"article","venue":"Proceedings of the American Society for Information Science and Technology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Timeline; Likert scale; Publishing; Computer science; Scale (ratio); Process (computing); Relevance (law); Data science; Exploratory research; Psychology; Sociology; Political science; Social science; Mathematics; Statistics","score_opus":0.20471762819332348,"score_gpt":0.42894187529671457,"score_spread":0.2242242471033911,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154768595","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.068831064,0.00006668742,0.87606496,0.05148903,0.00026078342,0.0012547978,0.00002505207,0.0002754548,0.0017321644],"genre_scores_gemma":[0.3843377,0.00007447811,0.6138536,0.0011009718,0.000030263522,0.0000641059,0.0000019225204,0.000009867604,0.00052712427],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99848115,0.0000063652446,0.000355692,0.00032712138,0.00041015362,0.00041950942],"domain_scores_gemma":[0.99775064,0.00007931607,0.0004866282,0.00020335612,0.0013349428,0.0001450872],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0045211264,0.000116591,0.0002012653,0.0006155875,0.0009895932,0.0010234165,0.00113635,0.00006670048,4.6257324e-7],"category_scores_gemma":[0.0030119997,0.000088313674,0.000055652952,0.0025480741,0.000722738,0.006596597,0.0011293114,0.00019498254,7.4837294e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016319254,0.000025072137,0.004190925,0.00020500041,0.000048849135,9.906243e-9,0.029797122,0.0000019011344,0.006586703,0.1950557,0.03700799,0.72706443],"study_design_scores_gemma":[0.0017945177,0.00094977336,0.011071554,0.0005393531,0.00012617343,0.00010114364,0.16898641,0.12333808,0.030947005,0.07776941,0.5831657,0.0012108564],"about_ca_topic_score_codex":0.000090681104,"about_ca_topic_score_gemma":0.0000059913204,"teacher_disagreement_score":0.72585356,"about_ca_system_score_codex":0.00006710244,"about_ca_system_score_gemma":0.00019329968,"threshold_uncertainty_score":0.9868829},"labels":[],"label_agreement":null},{"id":"W2155068847","doi":"10.1145/1054972.1055079","title":"Improving revisitation in fisheye views with visit wear","year":2005,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":54,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Distortion (music); Representation (politics); Usability; Computer science; Space (punctuation); Object (grammar); Artificial intelligence; Computer vision; Human–computer interaction","score_opus":0.020709045307082327,"score_gpt":0.2891603967303329,"score_spread":0.26845135142325055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2155068847","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0024637613,0.000029236226,0.98921263,0.0015867976,0.000018017028,0.000068470894,4.922155e-7,0.00007533299,0.0065452694],"genre_scores_gemma":[0.6104669,0.00004991375,0.37815958,0.0060173515,0.000111819914,0.0000062805116,0.000020599402,0.000012525233,0.005155026],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994188,0.000022974344,0.00014555317,0.00017547757,0.000130736,0.000106484644],"domain_scores_gemma":[0.9996415,0.000015852038,0.000044563294,0.00023155047,0.000030775795,0.00003579475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018487607,0.000058052872,0.000073928735,0.00008326698,0.000027008791,0.00015071996,0.00025579016,0.000016624355,0.000062453924],"category_scores_gemma":[0.000021157706,0.000042517662,0.000012560361,0.00037344306,0.000006905973,0.00081086514,0.0000590492,0.000040520208,0.00012754663],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000064528986,0.00017482416,0.0059636994,0.000057221256,0.000010379783,0.000012828245,0.001873536,0.0015389046,0.0011989309,0.2713371,0.011130122,0.70669603],"study_design_scores_gemma":[0.0003504254,0.00004802494,0.0017896619,0.000033955977,0.0000025862334,0.000002898426,0.00005776029,0.93595773,0.00075004844,0.000114311915,0.060737144,0.00015547156],"about_ca_topic_score_codex":0.000020043874,"about_ca_topic_score_gemma":0.00017457687,"teacher_disagreement_score":0.9344188,"about_ca_system_score_codex":0.000023693814,"about_ca_system_score_gemma":0.000024088182,"threshold_uncertainty_score":0.173382},"labels":[],"label_agreement":null},{"id":"W2155326742","doi":"","title":"XPlainer: Explaining XPath within Eclipse","year":2006,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"XPath; Computer science; Programming language; Debugging; Streaming XML; XSLT; XML; XML database; Information retrieval; Eclipse; XML Schema (W3C); Database; World Wide Web; XML Encryption","score_opus":0.018041850762399694,"score_gpt":0.26847898762012457,"score_spread":0.2504371368577249,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2155326742","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0028167963,0.000009818401,0.90814257,0.00038515145,0.00024514043,0.00003151219,0.0000019672227,0.00025742405,0.08810965],"genre_scores_gemma":[0.8274338,0.0000060127136,0.14466879,0.0029180676,0.0006642862,0.0000046811165,0.000061524974,0.000014479736,0.02422832],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992758,0.000021159847,0.00018136259,0.00020311866,0.00017451568,0.00014401083],"domain_scores_gemma":[0.9995177,0.000024739355,0.000051566054,0.00032250307,0.00003697789,0.00004654667],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018742903,0.000073988835,0.000075014155,0.00007114885,0.000082609804,0.00020163751,0.0004260389,0.00002408575,0.00009369464],"category_scores_gemma":[0.000020613963,0.00006172893,0.000025636653,0.00030874135,0.000015626803,0.00043687932,0.00012852966,0.000042450938,0.00021293724],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.3081315e-7,0.000026806227,0.00070486544,0.0000019131605,0.0000018707236,0.000008976721,0.000118826276,0.00040945123,0.00006396132,0.9602118,0.037440054,0.0010111275],"study_design_scores_gemma":[0.00037474264,0.00003590271,0.00044912324,0.000013221736,0.0000040495406,0.000017505521,0.00011964886,0.8948535,0.0020684896,0.01303182,0.088750444,0.00028157665],"about_ca_topic_score_codex":0.000039180388,"about_ca_topic_score_gemma":0.000034436463,"teacher_disagreement_score":0.94718,"about_ca_system_score_codex":0.000010724902,"about_ca_system_score_gemma":0.00002711717,"threshold_uncertainty_score":0.27369484},"labels":[],"label_agreement":null},{"id":"W2155467631","doi":"10.1080/00045608.2010.485449","title":"Illuminated Choropleth Maps","year":2010,"lang":"en","type":"article","venue":"Annals of the Association of American Geographers","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Cartography; Geography; Population; Contiguity; Enumeration; Statistics; Computer science; Artificial intelligence; Mathematics; Combinatorics","score_opus":0.013050351655089576,"score_gpt":0.28996119086708305,"score_spread":0.2769108392119935,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2155467631","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9453295,0.0000420008,0.0122983875,0.029660763,0.0012829482,0.00033793025,0.0001773283,0.00019272331,0.010678444],"genre_scores_gemma":[0.99625605,0.000053917138,0.0019183105,0.001304081,0.000016480617,0.0000014726046,0.000008183333,0.0000054007915,0.00043611776],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99893886,0.00009233891,0.00025513867,0.00013860108,0.00040957425,0.00016549596],"domain_scores_gemma":[0.998077,0.00008622716,0.0009073545,0.0004754667,0.00040605417,0.000047892863],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054188276,0.000075054646,0.00017345206,0.000108113156,0.00005852102,0.000029253259,0.00090069487,0.000036466034,0.00001751713],"category_scores_gemma":[0.00040609948,0.0000593923,0.0001711285,0.0014993076,0.00018593535,0.00017317697,0.00013466354,0.000114004586,0.0000048374427],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008001084,0.00034589926,0.7776989,0.000018680174,0.00043413497,3.5502367e-7,0.0012169118,0.00013140535,0.008477171,0.067747965,0.08887715,0.055043433],"study_design_scores_gemma":[0.00051360286,0.00021477307,0.84639376,0.000028172346,0.000052150834,9.900601e-7,0.000569432,0.005275513,0.03229305,0.0037972385,0.11046466,0.0003966476],"about_ca_topic_score_codex":0.00024916974,"about_ca_topic_score_gemma":0.00006374051,"teacher_disagreement_score":0.06869487,"about_ca_system_score_codex":0.00000556218,"about_ca_system_score_gemma":0.000042626194,"threshold_uncertainty_score":0.24219477},"labels":[],"label_agreement":null},{"id":"W2155565025","doi":"10.1111/j.1467-8659.2009.01444.x","title":"Collaborative Brushing and Linking for Co‐located Visual Analytics of Document Collections","year":2009,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":125,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Visual analytics; Computer science; Analytics; Visualization; World Wide Web; Cultural analytics; Human–computer interaction; Interactive visual analysis; Data science; Information retrieval; Semantic analytics; Data mining","score_opus":0.014168537897719711,"score_gpt":0.3101463555013526,"score_spread":0.2959778176036329,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2155565025","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020606234,0.00009026003,0.99616164,0.00095586176,0.00019670914,0.00027193167,0.000025144964,0.00009801147,0.0001398255],"genre_scores_gemma":[0.90234226,0.00021370412,0.09398538,0.0030272717,0.0001097376,0.000010087988,0.00013465254,0.000017271932,0.00015965005],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987576,0.000045283345,0.00037551878,0.00032999145,0.00022734473,0.00026425603],"domain_scores_gemma":[0.9988746,0.00014101273,0.00019854831,0.00026648212,0.0004164873,0.00010289161],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000283373,0.0001560588,0.00025285262,0.00043936737,0.00037243255,0.0003982146,0.000388143,0.00007673646,0.0000011450433],"category_scores_gemma":[0.000023902332,0.0001571273,0.000074934134,0.0019805739,0.00007498925,0.00042216256,0.00012574848,0.00009633124,6.3652084e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013062721,0.00017972318,0.0012692256,0.00003675262,0.000085129446,0.0000027873848,0.00070427125,0.00061875134,0.0001021939,0.9758371,0.011347874,0.009803143],"study_design_scores_gemma":[0.00070592127,0.0006005534,0.00073427876,0.000066008084,0.00002779844,0.0000057376037,0.000069648995,0.9596436,0.0011571071,0.026572295,0.010189141,0.00022793253],"about_ca_topic_score_codex":0.000004854634,"about_ca_topic_score_gemma":0.00001526204,"teacher_disagreement_score":0.95902485,"about_ca_system_score_codex":0.000023478453,"about_ca_system_score_gemma":0.000104960105,"threshold_uncertainty_score":0.6407466},"labels":[],"label_agreement":null},{"id":"W2155733062","doi":"10.1145/1168149.1168162","title":"Heuristics for information visualization evaluation","year":2006,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":136,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Heuristics; Computer science; Generalizability theory; Visualization; Heuristic; Categorization; Data visualization; Information visualization; Data science; Process (computing); Heuristic evaluation; Machine learning; Data mining; Artificial intelligence; Information retrieval; Human–computer interaction; Psychology","score_opus":0.024428909997915547,"score_gpt":0.3316553438817261,"score_spread":0.30722643388381055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2155733062","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00010172566,0.0000056133035,0.9890205,0.00017541448,0.00015605852,0.00022040248,0.000007786734,0.00013519864,0.010177303],"genre_scores_gemma":[0.8522017,0.000008323066,0.14117542,0.0021105926,0.0002127941,0.000071465656,0.002812053,0.000010262317,0.0013973748],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993214,0.000020449084,0.00021371337,0.00008728129,0.00026773408,0.00008942066],"domain_scores_gemma":[0.9992592,0.000030332907,0.00008285536,0.00016884423,0.00043898704,0.000019817544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003702425,0.00005192302,0.000047339887,0.00010405195,0.000077672776,0.00025650213,0.00018028436,0.000027615972,0.00002053633],"category_scores_gemma":[0.000118214986,0.000048780163,0.000021465865,0.00028754442,0.0000070105307,0.0012945926,0.000031249358,0.000011458078,0.000051803683],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.1648103e-7,0.00001761607,0.000083988205,0.00000708934,0.0000013525274,1.6097559e-8,0.000026295082,0.0012256413,0.00001686922,0.9621171,0.025809996,0.010693417],"study_design_scores_gemma":[0.0002680221,0.00001673816,0.00041961952,0.000002106613,0.0000061576434,4.807189e-7,0.000008350265,0.8970736,0.00049629656,0.014624566,0.08701734,0.00006672304],"about_ca_topic_score_codex":0.000012821787,"about_ca_topic_score_gemma":0.0000067375645,"teacher_disagreement_score":0.94749254,"about_ca_system_score_codex":0.000030355926,"about_ca_system_score_gemma":0.000049923394,"threshold_uncertainty_score":0.2473456},"labels":[],"label_agreement":null},{"id":"W2155901243","doi":"10.1109/tvcg.2010.60","title":"Tugging Graphs Faster: Efficiently Modifying Path-Preserving Hierarchies for Browsing Paths","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Institut national de recherche en informatique et en automatique (INRIA)","keywords":"Computer science; Theoretical computer science; Graph; Lattice graph; Line graph; Voltage graph","score_opus":0.022261438198900398,"score_gpt":0.2859705117104769,"score_spread":0.26370907351157646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2155901243","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021377949,0.000022120736,0.9763058,0.00009966105,0.0013678474,0.00032060212,0.00003555352,0.00042579466,0.00004468901],"genre_scores_gemma":[0.9822128,0.00012353741,0.015943931,0.0014505013,0.00009140231,0.0000371146,0.000031717384,0.000040823958,0.00006821239],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99808717,0.000093677605,0.00044504995,0.0006268218,0.00037371507,0.00037357173],"domain_scores_gemma":[0.99866563,0.00022634593,0.00014974787,0.00052978453,0.00023638621,0.00019208495],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00037607193,0.00028733723,0.0002490513,0.0007454279,0.0008751933,0.0008059418,0.0005659872,0.00013929112,0.00000922208],"category_scores_gemma":[0.000010355259,0.0002949942,0.0001569342,0.0010716758,0.000113964365,0.0007680392,0.000020742944,0.00029384953,0.0000034721793],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013145992,0.00027165536,0.000111732705,0.00011553265,0.000047965623,0.00000261316,0.0017602871,0.0018664916,0.00049251074,0.9705041,0.00025159164,0.024562377],"study_design_scores_gemma":[0.00065846206,0.00013455584,0.00010629945,0.00007698254,0.000025322308,0.000014448744,0.000052975625,0.9916951,0.0017428341,0.0026996306,0.0024460426,0.0003473434],"about_ca_topic_score_codex":0.000011052656,"about_ca_topic_score_gemma":0.000029365157,"teacher_disagreement_score":0.9898286,"about_ca_system_score_codex":0.000011923594,"about_ca_system_score_gemma":0.00004770818,"threshold_uncertainty_score":0.99995023},"labels":[],"label_agreement":null},{"id":"W2156295016","doi":"10.5753/jis.2013.627","title":"The BRAVA Initiative","year":2013,"lang":"en","type":"article","venue":"Journal on Interactive Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Exploratory research; Analytics; Field (mathematics); Computer science; Data science; Library science; Sociology; Social science","score_opus":0.031497508961625884,"score_gpt":0.3202313366264137,"score_spread":0.2887338276647878,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156295016","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0053070276,0.00022141711,0.90011436,0.009894818,0.010034542,0.00050156156,0.0000087557555,0.00012010456,0.07379744],"genre_scores_gemma":[0.99471426,0.000043737742,0.00014144799,0.0012254762,0.00035592835,0.000011898774,0.0000010496724,0.0000076220163,0.0034985682],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99883527,0.00025367542,0.00030234424,0.0001245092,0.00031364628,0.00017055716],"domain_scores_gemma":[0.9985438,0.0003599284,0.0003330414,0.0002503065,0.00040753421,0.00010541497],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00032842206,0.0000939644,0.000112139045,0.00008847946,0.00032916456,0.0017703058,0.00070020667,0.000024348925,0.000041483134],"category_scores_gemma":[0.00019949593,0.000052024225,0.0000621642,0.00018272131,0.0000210468,0.0012576426,0.00008377691,0.00028878156,0.0011178517],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019466795,0.00019729689,0.00040376929,0.000010757814,0.00030292207,0.00005477612,0.002898226,0.00040540696,0.00043783966,0.47919828,0.49253187,0.023539381],"study_design_scores_gemma":[0.0006657345,0.0006040133,0.00328061,0.00036081564,0.00001027421,0.0006154949,0.0052688536,0.29874197,0.0007266778,0.0056575444,0.68367827,0.00038972838],"about_ca_topic_score_codex":0.000015377134,"about_ca_topic_score_gemma":0.0000011173901,"teacher_disagreement_score":0.98940724,"about_ca_system_score_codex":0.000095154,"about_ca_system_score_gemma":0.000050125476,"threshold_uncertainty_score":0.9996599},"labels":[],"label_agreement":null},{"id":"W2156440763","doi":"10.1109/tvcg.2010.164","title":"How Information Visualization Novices Construct Visualizations","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":270,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Visualization; Computer science; Visual analytics; Data visualization; Information visualization; Construct (python library); Human–computer interaction; Process (computing); Interactive visual analysis; Heuristics; Software visualization; Bar chart; Data science; Data mining; Software; Software development; Programming language; Component-based software engineering","score_opus":0.012675590045371542,"score_gpt":0.2681414677359401,"score_spread":0.25546587769056855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156440763","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0029844425,0.00000995581,0.99372566,0.000262682,0.0017447843,0.00034712433,0.000053553867,0.0007133778,0.0001584138],"genre_scores_gemma":[0.9905159,0.00021706895,0.0048759677,0.0038313447,0.00013615823,0.00003894437,0.00021308674,0.000037527694,0.00013401786],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977759,0.00013984954,0.00057066657,0.00053668214,0.0006250213,0.0003518392],"domain_scores_gemma":[0.9980662,0.00012524317,0.0003154486,0.00063013175,0.0005839462,0.0002790206],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00030641147,0.0003828122,0.00029166392,0.0010761644,0.0007558108,0.002083575,0.00057973864,0.00026518275,0.000037665006],"category_scores_gemma":[0.000022744453,0.00039138182,0.00012076182,0.0020732563,0.00020932882,0.0039092405,0.000018099934,0.0003279582,0.000029619872],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000060217058,0.00016898029,0.00012254364,0.00004323874,0.00004030999,0.0000012029091,0.0006510151,0.00015031623,0.000076385804,0.9848283,0.00039999158,0.013511716],"study_design_scores_gemma":[0.0007758422,0.00016514822,0.00019978048,0.00002951863,0.000037273316,0.000042529744,0.00010309296,0.97066796,0.0027285314,0.0013442467,0.02341588,0.00049019814],"about_ca_topic_score_codex":0.000014725264,"about_ca_topic_score_gemma":0.00006139979,"teacher_disagreement_score":0.9888497,"about_ca_system_score_codex":0.000022177266,"about_ca_system_score_gemma":0.000098677614,"threshold_uncertainty_score":0.9998538},"labels":[],"label_agreement":null},{"id":"W2156744569","doi":"10.1190/1.3046456","title":"A visual data-mining methodology for seismic facies analysis: Part 2 — Application to 3D seismic data","year":2009,"lang":"en","type":"article","venue":"Geophysics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"ConocoPhillips (Canada); Université de Montréal; McGill University; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Facies; Geology; Cluster analysis; Seismic attribute; Visualization; Horizon; Siliciclastic; Data visualization; Data mining; Computer science; Seismology; Artificial intelligence; Paleontology","score_opus":0.1391564214387884,"score_gpt":0.40617404256359696,"score_spread":0.26701762112480854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156744569","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015567292,0.000024226161,0.99611866,0.001269243,0.00011881688,0.00023821686,0.0004633425,0.00015193522,0.00005883493],"genre_scores_gemma":[0.33198547,0.00003800552,0.6337197,0.015260948,0.0006148731,0.00004248471,0.017688295,0.000025122119,0.00062512944],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99806195,0.00010554247,0.00033832033,0.0009246427,0.00024267494,0.00032684684],"domain_scores_gemma":[0.9965969,0.00019819768,0.00017142459,0.0028035082,0.00011788952,0.00011210382],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007796385,0.00017087739,0.00033948952,0.00017823697,0.00016008224,0.00022347049,0.002987212,0.000056965913,0.000003106863],"category_scores_gemma":[0.00015460851,0.00017327949,0.000054892593,0.0015918296,0.00002555016,0.0009355322,0.0010586415,0.00006920693,0.00007712841],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001857395,0.00028995008,0.00012505834,0.000030778934,0.00045858024,0.0000026348484,0.0010362734,0.029275127,0.00072528137,0.027246322,0.03577849,0.9050129],"study_design_scores_gemma":[0.00012684695,0.00006675074,0.00026231934,0.0000040988707,0.00020203865,9.70167e-7,0.00006040893,0.89665437,0.000092549424,0.001953372,0.10038634,0.00018995268],"about_ca_topic_score_codex":0.000030309606,"about_ca_topic_score_gemma":0.00001561773,"teacher_disagreement_score":0.904823,"about_ca_system_score_codex":0.000018668119,"about_ca_system_score_gemma":0.00008413139,"threshold_uncertainty_score":0.7066133},"labels":[],"label_agreement":null},{"id":"W2157103903","doi":"10.1007/978-3-319-03841-4_6","title":"Graph Drawing through the Lens of a Framework for Analyzing Visualization Methods","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Visualization; sort; Graph drawing; Graph; Through-the-lens metering; Information visualization; Human–computer interaction; Lens (geology); Data science; Theoretical computer science; Information retrieval; Data mining","score_opus":0.0492574776147342,"score_gpt":0.3713611336227908,"score_spread":0.32210365600805657,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157103903","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000003147952,0.00038110424,0.99692684,0.0006578814,0.0009334324,0.000457062,0.000008111175,0.00008072675,0.0005517121],"genre_scores_gemma":[0.00555575,0.00010435822,0.9920919,0.0018619805,0.00023114822,0.000011475737,0.000013568981,0.000028703073,0.00010113638],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99728227,0.00008855583,0.0006570808,0.00093346706,0.0006095522,0.00042910615],"domain_scores_gemma":[0.9959893,0.0016200627,0.00057009584,0.0012823046,0.00047801677,0.00006017403],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0013369794,0.00035926202,0.0004942464,0.00050933886,0.00033966464,0.00059217296,0.0029442261,0.0002625312,0.000023217606],"category_scores_gemma":[0.00049878424,0.0002654011,0.00019976262,0.0012757324,0.0005842266,0.0009486592,0.00081907713,0.00037630295,0.0000054985417],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000011670184,0.000014622031,0.000010642266,0.000049523183,0.000019182628,7.5442676e-7,0.0013759485,0.012123586,0.000066911416,0.83681494,0.000037297497,0.14948542],"study_design_scores_gemma":[0.00007280976,0.000054855365,0.000008739747,0.00027983138,0.000015720962,0.0000030520916,5.9636244e-7,0.46949297,0.0009738381,0.5264266,0.002435195,0.00023579963],"about_ca_topic_score_codex":0.000018140725,"about_ca_topic_score_gemma":0.000009005927,"teacher_disagreement_score":0.4573694,"about_ca_system_score_codex":0.00007832119,"about_ca_system_score_gemma":0.00026038248,"threshold_uncertainty_score":0.9999798},"labels":[],"label_agreement":null},{"id":"W2157525828","doi":"10.1109/tvcg.2013.137","title":"Automatic Layout of Structured Hierarchical Reports","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Table (database); Tweaking; Readability; Column (typography); Information retrieval; Field (mathematics); Software; Data mining; Database; Computer graphics (images); Programming language","score_opus":0.013891120575177964,"score_gpt":0.26957118875603686,"score_spread":0.2556800681808589,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157525828","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02720481,0.000012485151,0.9717984,0.000071412425,0.00044023513,0.00020745613,0.000006465329,0.00021788734,0.000040826675],"genre_scores_gemma":[0.99358517,0.000048027425,0.005275195,0.0009727494,0.00002446602,0.000013397126,0.00001398728,0.000014281856,0.000052718256],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985094,0.00010512039,0.00050123903,0.00035760034,0.00035355292,0.00017306913],"domain_scores_gemma":[0.9989529,0.00007138825,0.00018000964,0.00045018393,0.0002013201,0.00014416785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013635862,0.0001739167,0.00022600066,0.000398682,0.00015955296,0.0002078913,0.00025039093,0.000099196324,0.0000848616],"category_scores_gemma":[0.000004767684,0.00016034774,0.000083781306,0.000827565,0.00010421683,0.0004891346,0.000008310532,0.00012694433,0.000007860665],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000029316209,0.0003760811,0.00028877487,0.0001104029,0.000091385235,0.000008339572,0.001189428,0.00079945946,0.000082092534,0.95142525,0.0011607788,0.04446508],"study_design_scores_gemma":[0.00023399216,0.0001282118,0.0011941225,0.000038354174,0.00001584943,0.000038021182,0.000014902784,0.99232054,0.0012371311,0.0042740894,0.0003288969,0.00017590013],"about_ca_topic_score_codex":0.000020888507,"about_ca_topic_score_gemma":0.00000625184,"teacher_disagreement_score":0.99152106,"about_ca_system_score_codex":0.000010246147,"about_ca_system_score_gemma":0.000044314816,"threshold_uncertainty_score":0.65387917},"labels":[],"label_agreement":null},{"id":"W2157689946","doi":"10.1109/tvcg.2010.149","title":"eSeeTrack—Visualizing Sequential Fixation Patterns","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":65,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Visualization; Eye tracking; Gaze; Timeline; Outlier; Data visualization; Artificial intelligence; Fixation (population genetics); Visual analytics; Computer vision; Data mining; Pattern recognition (psychology)","score_opus":0.023589402405802398,"score_gpt":0.3001605937277248,"score_spread":0.2765711913219224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157689946","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022717254,0.0000058387823,0.97473377,0.00009109676,0.0017568803,0.00016875776,0.000025420048,0.00043042202,0.000070538386],"genre_scores_gemma":[0.99532455,0.00014190585,0.0023348136,0.0018542756,0.00015071178,0.0000141486435,0.000049733622,0.000028066612,0.000101821664],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982136,0.000112465765,0.0004107878,0.00055000075,0.00043843055,0.00027471138],"domain_scores_gemma":[0.99887043,0.00008349081,0.0001497047,0.00048548676,0.00021031963,0.00020056743],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00028752006,0.00025587383,0.00019704449,0.0005454622,0.0004541887,0.00061780936,0.0004374673,0.00017830233,0.000062412764],"category_scores_gemma":[0.0000057828074,0.00026369683,0.00010526709,0.0008981448,0.00008108317,0.0008658834,0.00001158714,0.0003393115,0.000025517482],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000058441165,0.00027576083,0.00029951285,0.00003480203,0.000039545987,0.000005066894,0.00061788125,0.00020784566,0.0002813365,0.9838606,0.0002601957,0.014111578],"study_design_scores_gemma":[0.0005302542,0.00013500507,0.0006408311,0.00003238295,0.00002304033,0.000029249606,0.000022641841,0.98899734,0.005137082,0.00078867876,0.003317749,0.00034576145],"about_ca_topic_score_codex":0.000024602785,"about_ca_topic_score_gemma":0.00009307774,"teacher_disagreement_score":0.9887895,"about_ca_system_score_codex":0.000014748281,"about_ca_system_score_gemma":0.000052109954,"threshold_uncertainty_score":0.9999815},"labels":[],"label_agreement":null},{"id":"W2157821464","doi":"10.1145/2678025.2701370","title":"ConVisIT","year":2015,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":67,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Conversation; Asynchronous communication; Human–computer interaction; Visualization; User interface; Interface (matter); Social media; World Wide Web; Multimedia; Data science; Artificial intelligence","score_opus":0.0638934823926233,"score_gpt":0.32432783730641396,"score_spread":0.26043435491379063,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157821464","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00008444138,0.0000054749758,0.90741205,0.00072811387,0.00007338872,0.000007633656,2.0514791e-7,0.00008937151,0.09159931],"genre_scores_gemma":[0.8140619,0.000005156185,0.13027476,0.011587662,0.00008740906,0.000001153031,0.000011631021,0.000005214505,0.04396513],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997755,0.000006077647,0.00003699222,0.00005934887,0.000079021906,0.000043010128],"domain_scores_gemma":[0.9997364,0.0000041339727,0.0000075122816,0.00015326758,0.000035148216,0.00006348974],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000070385926,0.000017890163,0.00002205279,0.000016733304,0.000008523894,0.00006898821,0.00023469473,0.000006453798,0.00003125951],"category_scores_gemma":[0.00001812834,0.000014132967,0.0000059575186,0.00011075007,0.0000048734964,0.00019389331,0.00007569848,0.000009168885,0.0006145904],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.0054114e-8,0.0000065887116,0.00021192568,2.4392452e-7,8.417304e-7,0.0000012469526,0.000054541662,0.000006650456,0.0000041396675,0.9048121,0.09207013,0.0028315026],"study_design_scores_gemma":[0.00019685639,0.000020659141,0.00012888008,0.0000010064118,7.437708e-7,0.0000039937113,0.000038780658,0.37452716,0.0005304524,0.008636782,0.6158419,0.00007275147],"about_ca_topic_score_codex":0.0000035496844,"about_ca_topic_score_gemma":8.31602e-7,"teacher_disagreement_score":0.8961753,"about_ca_system_score_codex":0.000004018478,"about_ca_system_score_gemma":0.000021510969,"threshold_uncertainty_score":0.78995216},"labels":[],"label_agreement":null},{"id":"W2158927222","doi":"10.1186/1471-2288-11-11","title":"A multidisciplinary systematic review of the use of diagrams as a means of collecting data from research subjects: application, benefits and recommendations","year":2011,"lang":"en","type":"review","venue":"BMC Medical Research Methodology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":81,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Cancer Care Ontario","funders":"Canadian Institutes of Health Research","keywords":"Multidisciplinary approach; Data science; MEDLINE; Computer science; Medicine; Management science; Psychology; Engineering; Sociology","score_opus":0.8778009256423671,"score_gpt":0.6352939642163241,"score_spread":0.242506961426043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158927222","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[4.2050254e-7,0.7499209,0.24736191,0.00026556596,0.000056357832,0.0020463162,0.00023187866,0.000011785335,0.000104864244],"genre_scores_gemma":[9.2715754e-7,0.89207363,0.10718274,0.000034217872,0.000027174376,0.0002216424,0.00021094728,0.000026958987,0.00022174325],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.9441481,0.05035777,0.0021467626,0.0008785882,0.0020363706,0.0004323668],"domain_scores_gemma":[0.83884907,0.15204906,0.0016086211,0.0053369915,0.0017642006,0.00039206148],"candidate_categories":["metaresearch","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.062946066,0.00021088606,0.0024596632,0.00063513935,0.00018728108,0.00003427524,0.0058016377,0.00034540668,0.00017525838],"category_scores_gemma":[0.30409372,0.00013080485,0.00018244512,0.0038335146,0.0010545829,0.00017082145,0.0075042266,0.0009312625,0.000017664406],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000048673137,0.0002001343,0.000020532383,0.7350497,0.00018536739,0.0000014278943,0.00030098163,1.6945013e-7,6.5025046e-7,0.04443931,0.0037306293,0.21606624],"study_design_scores_gemma":[0.000212699,0.00013845915,0.000007155001,0.82451093,0.00042534946,0.000033140623,0.00016864778,0.008428734,0.000007189541,0.0015082686,0.16436984,0.00018956595],"about_ca_topic_score_codex":0.0011811752,"about_ca_topic_score_gemma":0.001106841,"teacher_disagreement_score":0.24114765,"about_ca_system_score_codex":0.000041887088,"about_ca_system_score_gemma":0.0030247737,"threshold_uncertainty_score":0.99957746},"labels":[{"model":"gemma","categories":["metaresearch"],"domain":"methods","study_design":"systematic_review","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"low"},{"model":"gpt","categories":["metaresearch"],"domain":"methods","study_design":"systematic_review","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"high"}],"label_agreement":"agree"},{"id":"W2159996805","doi":"10.1109/tvcg.2004.1260759","title":"Human factors in visualization research","year":2004,"lang":"en","type":"review","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":411,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Visualization; Data visualization; Data science; Human–computer interaction; Data mining","score_opus":0.13042994444724287,"score_gpt":0.43072250845631893,"score_spread":0.30029256400907606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2159996805","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00000825892,0.11496932,0.8834398,0.0000063299753,0.00055034325,0.0006589395,0.000036107434,0.00028961455,0.000041277304],"genre_scores_gemma":[0.0017416759,0.9972024,0.0002333084,0.00014748625,0.00007921191,0.00007222114,0.0002554495,0.00009694245,0.00017131868],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99530643,0.0008979316,0.0011408059,0.0011653763,0.0009295896,0.0005598858],"domain_scores_gemma":[0.99805504,0.00023939117,0.00031387515,0.00083205436,0.00030635713,0.000253261],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008772931,0.0006353078,0.0010892334,0.00371966,0.0006744633,0.00081130554,0.0010246561,0.0005888409,0.00002267719],"category_scores_gemma":[0.000010060491,0.000601919,0.000308334,0.005612562,0.00020014888,0.0006863149,0.000031064377,0.0008247856,0.000030909276],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010227857,0.00052293186,0.0000033658919,0.002784243,0.00006448561,0.000011319285,0.0006048907,0.00013058734,1.0206192e-7,0.9326023,0.00014936329,0.06312541],"study_design_scores_gemma":[0.001723342,0.0009429154,0.00002778738,0.02164925,0.000298075,0.000055352033,0.000102483646,0.3821353,0.000051281782,0.0047175246,0.58574885,0.0025478296],"about_ca_topic_score_codex":0.00006515008,"about_ca_topic_score_gemma":0.00008060316,"teacher_disagreement_score":0.92788476,"about_ca_system_score_codex":0.0002450748,"about_ca_system_score_gemma":0.00035842165,"threshold_uncertainty_score":0.9996432},"labels":[],"label_agreement":null},{"id":"W2160165932","doi":"10.1145/2344416.2344420","title":"Navigating tomorrow's web","year":2012,"lang":"en","type":"article","venue":"ACM Transactions on the Web","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; World Wide Web; Visualization; Web modeling; Information retrieval; Web navigation; Information space; Information visualization; Web application; Human–computer interaction; Web page; Data mining","score_opus":0.037061562157655104,"score_gpt":0.3128583078292578,"score_spread":0.27579674567160267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160165932","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012745025,0.000038582213,0.974881,0.009847355,0.00057768275,0.00009074725,0.000019273324,0.0002438815,0.0015564432],"genre_scores_gemma":[0.9894927,0.00003586178,0.007911839,0.0019890387,0.000061698345,0.000009759124,0.000003019357,0.000008350144,0.0004876937],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992454,0.000066122,0.00013343281,0.00013197245,0.00019856932,0.00022449344],"domain_scores_gemma":[0.99883497,0.00017260839,0.00004143744,0.00083660433,0.00003078472,0.000083618244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003033856,0.00008818488,0.000068869565,0.000026167836,0.00028667744,0.00011161598,0.00093978987,0.00003235974,0.00023201172],"category_scores_gemma":[0.00004400443,0.00006248924,0.000060498478,0.0004364706,0.000032332962,0.00048202832,0.000019268628,0.00021396778,0.0005285686],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014096363,0.0015495528,0.0015592885,0.000048084727,0.0002351636,0.000008265899,0.008021186,0.001817641,0.011469879,0.31756783,0.021206483,0.63650256],"study_design_scores_gemma":[0.0013131811,0.00021035125,0.00094586407,0.000251845,0.00012878676,0.00011579501,0.001309327,0.6276736,0.05047103,0.008042788,0.30824903,0.0012883778],"about_ca_topic_score_codex":0.000007678858,"about_ca_topic_score_gemma":0.000008631451,"teacher_disagreement_score":0.9767477,"about_ca_system_score_codex":0.000020121726,"about_ca_system_score_gemma":0.000031705677,"threshold_uncertainty_score":0.6793856},"labels":[],"label_agreement":null},{"id":"W2160559232","doi":"10.1080/01449290110049790","title":"The role of visual search in the design of effective soft keyboards","year":2001,"lang":"en","type":"article","venue":"Behaviour and Information Technology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Saint John Regional Hospital; University of New Brunswick","funders":"","keywords":"Text entry; Key (lock); Human–computer interaction; Computer science; Matching (statistics); Component (thermodynamics); Mobile device; Visual search; Engineering drawing; Artificial intelligence; World Wide Web; Engineering","score_opus":0.009240934277195034,"score_gpt":0.2850228449133381,"score_spread":0.2757819106361431,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160559232","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15007223,0.00010603371,0.8481192,0.0006976688,0.000030305597,0.00036166442,0.000004260339,0.00004908868,0.0005595659],"genre_scores_gemma":[0.9991073,0.00011938936,0.0006915481,0.000056077348,0.0000018910666,0.000013197144,0.0000035959056,0.0000010130443,0.0000059738586],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994435,0.000053019852,0.00021898345,0.000047064863,0.0001427149,0.00009475817],"domain_scores_gemma":[0.99953425,0.00008828044,0.000088148394,0.00018142334,0.00009850035,0.000009390556],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053160597,0.000044546465,0.00007360059,0.00022070252,0.000066270244,0.000037836006,0.0004239142,0.00005977263,0.0000015166962],"category_scores_gemma":[0.000067080255,0.000026868762,0.000012841155,0.00063972676,0.00011826415,0.00056815,0.000108432934,0.000084447885,0.000003452266],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012579152,0.000078741665,0.04394571,0.000007689053,0.000006276116,6.2669386e-7,0.0020340953,0.00012228834,0.00021199229,0.40064496,0.00009419231,0.5528408],"study_design_scores_gemma":[0.0018516516,0.001696984,0.15728045,0.00006163748,0.000030020588,0.00011984064,0.016207917,0.73318255,0.051081993,0.02076044,0.01737015,0.0003563522],"about_ca_topic_score_codex":0.000019836796,"about_ca_topic_score_gemma":0.0000029698263,"teacher_disagreement_score":0.8490351,"about_ca_system_score_codex":0.000007427303,"about_ca_system_score_gemma":0.000027233682,"threshold_uncertainty_score":0.109567635},"labels":[],"label_agreement":null},{"id":"W2161218269","doi":"10.1109/iv.2007.68","title":"Imago: An integrated prototyping, evaluation and transitioning environment for information visualisation","year":2007,"lang":"en","type":"article","venue":"Proceedings","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"Defence Science and Technology Group","keywords":"Imago; Visualization; Computer science; Relation (database); Process (computing); Human–computer interaction; Rapid prototyping; Software engineering; Engineering; Programming language; Artificial intelligence; Data mining","score_opus":0.026510258973697565,"score_gpt":0.3186589070975228,"score_spread":0.29214864812382524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161218269","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01649372,0.000009821756,0.9820442,0.00017283898,0.000034072746,0.0007774152,0.0000038442736,0.000093334056,0.0003707638],"genre_scores_gemma":[0.90142053,0.000016495203,0.09748574,0.00053641776,0.00005840797,0.00013961553,0.0003150675,0.000008522385,0.000019193545],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992319,0.0000059855247,0.00022538417,0.00015758416,0.00024948257,0.00012969921],"domain_scores_gemma":[0.99949,0.00001158395,0.00011088131,0.000057118454,0.0002679589,0.00006245713],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013928515,0.00007734331,0.00006124343,0.00014485377,0.0001378424,0.0003363873,0.00011952693,0.000040054023,0.0000075505563],"category_scores_gemma":[0.000077943005,0.00007593288,0.000014170214,0.00017440472,0.000020441348,0.0035541125,0.000019731626,0.000039163297,0.000004979545],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042726166,0.000091139555,0.0008626154,0.00011918509,0.000016634056,8.756406e-8,0.012804873,0.000080393256,0.0029976058,0.17345735,0.0003435999,0.8091838],"study_design_scores_gemma":[0.00066321576,0.00017562055,0.0023455466,0.000028643082,0.000022142201,0.0000045336815,0.00078363455,0.94997233,0.005129394,0.0020671622,0.038644828,0.00016295286],"about_ca_topic_score_codex":0.000005128484,"about_ca_topic_score_gemma":0.0000012980388,"teacher_disagreement_score":0.9498919,"about_ca_system_score_codex":0.000060746766,"about_ca_system_score_gemma":0.000024724248,"threshold_uncertainty_score":0.32437906},"labels":[],"label_agreement":null},{"id":"W2161243549","doi":"10.1057/ivs.2009.28","title":"Science of Analytical Reasoning","year":2009,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"U.S. Department of Homeland Security","keywords":"Visual analytics; Cultural analytics; Computer science; Analytics; Data science; Visual reasoning; Field (mathematics); Analytic reasoning; Visualization; Work (physics); Software analytics; Management science; Artificial intelligence; Semantic analytics; World Wide Web; Reasoning system; Software; The Internet","score_opus":0.016295437988318257,"score_gpt":0.32918149585067413,"score_spread":0.3128860578623559,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161243549","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0035173,0.0000040616655,0.9790822,0.00016617554,0.00008138429,0.000066346285,0.0000021959381,0.0001224046,0.016957927],"genre_scores_gemma":[0.9911094,0.000009583031,0.007938713,0.000817946,0.000014801856,5.746852e-7,0.000050207876,0.0000015942377,0.000057231708],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987883,0.000018020182,0.0004086915,0.0001057212,0.0005330034,0.0001462422],"domain_scores_gemma":[0.9988954,0.000013639051,0.00022347749,0.00029172597,0.00050182414,0.000073921554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000508094,0.00007010726,0.00009577009,0.00066665397,0.000118314,0.00026061828,0.00051935937,0.000031761643,0.000016018816],"category_scores_gemma":[0.00036905782,0.00006771761,0.000026494235,0.0027819169,0.000069201626,0.005952098,0.000063235515,0.00003260243,0.00004410024],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012002297,0.000023091397,0.00009573467,0.0000051638413,0.0000013036197,8.9854e-8,0.0004646845,0.0005290031,0.0001410677,0.98812586,0.00053601986,0.010076777],"study_design_scores_gemma":[0.00017152577,0.00008604386,0.0028192904,0.000020771546,0.0000035037624,0.0000030657684,0.000052467323,0.98637724,0.0033900521,0.0016978207,0.0052836817,0.000094536714],"about_ca_topic_score_codex":0.0000019337544,"about_ca_topic_score_gemma":9.478392e-8,"teacher_disagreement_score":0.98759204,"about_ca_system_score_codex":0.000039106602,"about_ca_system_score_gemma":0.00019169041,"threshold_uncertainty_score":0.43151274},"labels":[],"label_agreement":null},{"id":"W2161323095","doi":"10.1109/ccece.2001.933658","title":"A Classification Canvas for the analysis of biomedical data","year":2002,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Institute for Biodiagnostics","funders":"","keywords":"Computer science; Suite; Modularity (biology); Java; Domain (mathematical analysis); Graphical user interface; Software; Human–computer interaction; Software engineering; Data science; Data mining; Programming language","score_opus":0.20473588566838963,"score_gpt":0.3765605026838714,"score_spread":0.1718246170154818,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161323095","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00003662802,0.000027957813,0.9950809,0.0041999323,0.00003754625,0.000044160206,0.00006914473,0.000020189342,0.00048352816],"genre_scores_gemma":[0.95014656,0.00014423729,0.044702288,0.0014381941,0.000052639614,0.0000082067545,0.0006804306,0.0000043483474,0.0028230716],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994935,0.000012437372,0.00013727581,0.00014888599,0.00014935774,0.000058592945],"domain_scores_gemma":[0.9987758,0.00014700329,0.00005244223,0.0009491033,0.00004901262,0.00002663903],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022375032,0.00002827957,0.000068365116,0.00010687938,0.0000413681,0.00004531398,0.0011967269,0.000014840898,0.00014739965],"category_scores_gemma":[0.00010199896,0.000016742862,0.000031484207,0.0012099618,0.0000373285,0.00015459914,0.0001554493,0.000013879196,0.000007779007],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.817896e-7,0.000195047,0.00064857816,0.000008790229,0.0006034039,2.340767e-7,0.00026614906,0.00007415269,0.00017852338,0.6346729,0.24127725,0.12207425],"study_design_scores_gemma":[0.000047403795,0.000005460971,0.0014280337,5.72565e-7,0.00011604231,1.1468526e-7,0.000024357381,0.9081634,0.000012942053,0.00004568424,0.09013402,0.000021917756],"about_ca_topic_score_codex":0.00002847196,"about_ca_topic_score_gemma":0.000047143352,"teacher_disagreement_score":0.9503786,"about_ca_system_score_codex":0.0000042044708,"about_ca_system_score_gemma":0.000011106734,"threshold_uncertainty_score":0.22238363},"labels":[],"label_agreement":null},{"id":"W2161555761","doi":"10.1109/tvcg.2009.151","title":"Interaction Techniques for Selecting and Manipulating Subgraphs in Network Visualizations","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Institute for Cancer Research; École de Technologie Supérieure","funders":"Ontario Genomics Institute; Genome Canada","keywords":"Computer science; Visualization; Graph drawing; Usability; Extensibility; Human–computer interaction; Set (abstract data type); Graphical user interface; Graph Layout; Software; Theoretical computer science; Data mining; Programming language","score_opus":0.027777396432850366,"score_gpt":0.3211007481828402,"score_spread":0.2933233517499898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161555761","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0034100094,0.000030827137,0.995474,0.00010377671,0.00024384551,0.00036175534,0.000004518285,0.00033117898,0.00004009391],"genre_scores_gemma":[0.9799253,0.00037369374,0.017170284,0.0023383,0.00008986471,0.00003113375,0.000029094175,0.000020395224,0.000021930198],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985446,0.000103681494,0.00044180237,0.00046959848,0.00017503872,0.00026532792],"domain_scores_gemma":[0.9992567,0.00015472225,0.00014158474,0.00020399802,0.00014761629,0.0000954015],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033859926,0.00021223549,0.00021461818,0.00061041565,0.00042817285,0.00038113672,0.00017133052,0.0001170251,0.0000022868276],"category_scores_gemma":[0.000006543364,0.00023211523,0.000060433937,0.0014332728,0.000035171215,0.0007068968,0.000004223759,0.00015163394,5.195911e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016827793,0.00023251973,0.0005229229,0.000039265225,0.000022081997,0.000001247738,0.0008259971,0.0026723864,0.00003906035,0.94977736,0.00016620275,0.045684133],"study_design_scores_gemma":[0.00038751555,0.00031208305,0.00076034316,0.00010518831,0.000015825808,0.0000156957,0.000035605437,0.9924941,0.0006512899,0.0040357844,0.0009279069,0.00025864333],"about_ca_topic_score_codex":0.000009838325,"about_ca_topic_score_gemma":0.00005598748,"teacher_disagreement_score":0.98982173,"about_ca_system_score_codex":0.00002634321,"about_ca_system_score_gemma":0.00001965351,"threshold_uncertainty_score":0.94653845},"labels":[],"label_agreement":null},{"id":"W2162091140","doi":"10.1109/iv.2002.1028791","title":"Towards a visual interface for information visualization","year":2003,"lang":"en","type":"article","venue":"Proceedings Sixth International Conference on Information Visualisation","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Visualization; Human–computer interaction; Focus (optics); Context (archaeology); Information visualization; Interface (matter); Representation (politics); Vocabulary; User interface; Data visualization; Process (computing); Popularity; Artificial intelligence; Programming language; Linguistics","score_opus":0.042096324842409154,"score_gpt":0.3460419637798579,"score_spread":0.30394563893744875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162091140","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0019170588,0.0000025391803,0.9339582,0.0011933494,0.0013174879,0.00070785417,0.000065250955,0.0004181494,0.060420133],"genre_scores_gemma":[0.98432684,0.000044165023,0.0112293335,0.002817382,0.00011098414,0.00024158442,0.0010119284,0.000017110762,0.00020068068],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972419,0.00003886267,0.0010503313,0.0003116273,0.0010034667,0.0003537948],"domain_scores_gemma":[0.99589914,0.000055452125,0.0008041998,0.00019143522,0.00288839,0.00016139196],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0009535385,0.00033323767,0.00023905627,0.0009371336,0.000287142,0.0023007349,0.0008311673,0.0001745163,0.00018174715],"category_scores_gemma":[0.0014378565,0.0003395908,0.00011497639,0.00073492306,0.00004149219,0.016127817,0.00011014934,0.00015580488,0.00035603187],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045098714,0.000076660705,0.00010475046,0.000059142723,0.00003205447,4.9065513e-8,0.002162688,0.000112658476,0.00017961938,0.9844965,0.0033863415,0.009344466],"study_design_scores_gemma":[0.0017825007,0.00044565683,0.00027166322,0.00010760536,0.00001878883,0.0000096420035,0.001806311,0.75528675,0.013538245,0.019989759,0.20612825,0.00061483955],"about_ca_topic_score_codex":0.000007906287,"about_ca_topic_score_gemma":9.4114137e-7,"teacher_disagreement_score":0.9824098,"about_ca_system_score_codex":0.00029455556,"about_ca_system_score_gemma":0.00025027772,"threshold_uncertainty_score":0.9999056},"labels":[],"label_agreement":null},{"id":"W2162103458","doi":"10.1145/1923947.1923961","title":"Visual guidance in the exploration of large databases","year":2010,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Thumbnail; Slicing; Notice; Selection (genetic algorithm); Data mining; Information retrieval; Data science; Database; Human–computer interaction; World Wide Web; Artificial intelligence","score_opus":0.056121865775221595,"score_gpt":0.3740614256411419,"score_spread":0.3179395598659203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162103458","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008680858,0.0000055228843,0.98828244,0.0007493982,0.00008919943,0.000039715007,0.0000062481263,0.0000204987,0.0021261207],"genre_scores_gemma":[0.9868696,0.000004945193,0.011982195,0.0009427427,0.00002225789,0.000002383366,0.000025927837,0.0000013904058,0.00014858907],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995612,0.00002927037,0.000119302065,0.00008939639,0.00013481466,0.000066010405],"domain_scores_gemma":[0.99958587,0.000040322226,0.000035995934,0.00029350698,0.00003309406,0.000011216395],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037933717,0.00003110163,0.00003969195,0.0000408232,0.000022656268,0.000039082006,0.0004179685,0.0000091690445,0.00003671644],"category_scores_gemma":[0.00008200926,0.000019982974,0.00000990561,0.00025665673,0.00001350416,0.0008851231,0.00008485519,0.000044666263,0.000018682378],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.2457555e-7,0.00008723286,0.0011530925,0.0000026982968,5.893051e-7,7.178102e-7,0.00031233433,0.0000042039146,0.001203386,0.9933275,0.0027515744,0.0011563186],"study_design_scores_gemma":[0.00058967475,0.00006320663,0.0109442845,0.000019636176,0.0000037231475,0.0000038933645,0.0006988557,0.7858444,0.023955507,0.0049464223,0.17271371,0.0002166982],"about_ca_topic_score_codex":0.000018188943,"about_ca_topic_score_gemma":0.00030914994,"teacher_disagreement_score":0.9883811,"about_ca_system_score_codex":0.00000115836,"about_ca_system_score_gemma":0.000018366214,"threshold_uncertainty_score":0.0814882},"labels":[],"label_agreement":null},{"id":"W2162285260","doi":"10.1109/acsac.2008.16","title":"Improving Security Visualization with Exposure Map Filtering","year":2008,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Visualization; Focus (optics); Network security; Data mining; Volume (thermodynamics); Process (computing); Data visualization; Filter (signal processing); Traffic analysis; Flow network; Computer security; Computer network; Computer vision","score_opus":0.016951190076520708,"score_gpt":0.25587634661064146,"score_spread":0.23892515653412075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162285260","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008274539,0.00001348486,0.98964244,0.00009650769,0.00007277108,0.000050575192,0.0000014653681,0.00025852167,0.0015897135],"genre_scores_gemma":[0.9702263,0.0000107748265,0.02789722,0.0005848027,0.000045867306,0.0000028155202,0.000022340759,0.000008658735,0.0012012392],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99929357,0.000020781546,0.00012657813,0.00021844957,0.000201186,0.00013943452],"domain_scores_gemma":[0.9995026,0.000011663246,0.000054144508,0.00029434662,0.000075401054,0.00006185539],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000075663265,0.00008168673,0.00007628742,0.00006289094,0.00013799596,0.000107188214,0.00030831838,0.000025709327,0.000051631956],"category_scores_gemma":[0.000013100424,0.00006500238,0.000016946618,0.0002912001,0.000023460254,0.00069380883,0.00012975832,0.000037985144,0.000039396997],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017750457,0.0004329152,0.028722243,0.00020938212,0.000062476305,0.00021558533,0.0074605,0.0008578242,0.0041388143,0.92532796,0.020370847,0.012183736],"study_design_scores_gemma":[0.00054909557,0.00017774837,0.0011398754,0.000024983936,0.000005472936,0.00008211573,0.00009638495,0.9756955,0.009018659,0.00036442603,0.012488163,0.0003575778],"about_ca_topic_score_codex":0.000024109915,"about_ca_topic_score_gemma":0.000013472566,"teacher_disagreement_score":0.97483766,"about_ca_system_score_codex":0.000013957427,"about_ca_system_score_gemma":0.00004139061,"threshold_uncertainty_score":0.26507202},"labels":[],"label_agreement":null},{"id":"W2162456078","doi":"10.1145/1124772.1124965","title":"Keepin' it real","year":2006,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":292,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Variety (cybernetics); Computer science; Visualization; Human–computer interaction; Virtual world; Data visualization; Virtual desktop; Virtual reality; Computer graphics (images); Virtual machine; Artificial intelligence; Operating system","score_opus":0.019542589962104825,"score_gpt":0.2928941373454395,"score_spread":0.27335154738333467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162456078","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00018380664,0.0000019144159,0.69063956,0.001073848,0.000047283018,0.000010012526,6.2329644e-7,0.00010257764,0.30794036],"genre_scores_gemma":[0.73001367,0.000053071042,0.111291476,0.008821767,0.00030184473,0.0000018942216,0.00006679776,0.0000108419645,0.14943863],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99964917,0.000006924744,0.00007580053,0.00009946627,0.00009334267,0.00007527538],"domain_scores_gemma":[0.9997344,0.000008587886,0.000014643833,0.00019864138,0.000022360311,0.000021350406],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000052565003,0.00002940416,0.00003248716,0.000030497096,0.000028155497,0.00009326183,0.00027410986,0.000011796714,0.00008944486],"category_scores_gemma":[0.0000039121533,0.000025046023,0.00001390857,0.00018511116,0.000007745491,0.00018656824,0.0000696191,0.000013849154,0.00030278406],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.036523e-8,0.000014363503,0.00024659786,6.278315e-7,6.1096046e-7,0.0000016030225,0.000010435646,0.000018053368,0.000034523728,0.87030405,0.12794556,0.001423486],"study_design_scores_gemma":[0.0002446658,0.000025104568,0.005718567,0.000004334798,0.0000025093702,0.000005602617,0.000021628399,0.43974993,0.0015148144,0.016767617,0.5357423,0.00020292767],"about_ca_topic_score_codex":0.00013315762,"about_ca_topic_score_gemma":0.00004657427,"teacher_disagreement_score":0.8535365,"about_ca_system_score_codex":0.000005387837,"about_ca_system_score_gemma":0.00001311708,"threshold_uncertainty_score":0.38917774},"labels":[],"label_agreement":null},{"id":"W2162857327","doi":"10.1109/iv.2007.138","title":"Visualizing the Decision-Making Process in a Face-to-Face Meeting","year":2007,"lang":"en","type":"article","venue":"Proceedings","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Process (computing); Face-to-face; Face (sociological concept); Strengths and weaknesses; Visualization; Quality (philosophy); Decision-making; Human–computer interaction; Outcome (game theory); Data science; Process management; Psychology; Artificial intelligence; Engineering; Social psychology; Operations management","score_opus":0.021677470159121304,"score_gpt":0.3560972294727978,"score_spread":0.3344197593136765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162857327","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23371942,0.00005982499,0.757871,0.00083811797,0.00013228247,0.00025841774,7.2261423e-7,0.00019564202,0.006924625],"genre_scores_gemma":[0.98446923,0.0000053854387,0.013817448,0.0015787493,0.000062182895,0.0000075315975,4.406048e-7,0.000013220808,0.000045818055],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983473,0.0000059510094,0.00036099652,0.00039670686,0.00047210828,0.00041697017],"domain_scores_gemma":[0.9992651,0.00018064644,0.00012774309,0.00015513528,0.00017815873,0.000093246075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017208748,0.00013860677,0.00013775987,0.00026282232,0.00019688293,0.0004938885,0.0012302705,0.000047605325,0.000004745305],"category_scores_gemma":[0.00095828844,0.0001058713,0.000031867112,0.00201844,0.000023552491,0.00070218486,0.00040358675,0.00015320034,0.00004826346],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009213979,0.0003960884,0.067271635,0.00034071473,0.000044958397,0.000053927262,0.15623097,0.0027637298,0.0041161296,0.32493967,0.006333913,0.43741614],"study_design_scores_gemma":[0.00088407984,0.00015069895,0.011156,0.002286673,0.000019141127,0.00006714593,0.022607144,0.8984718,0.010573529,0.02100683,0.03156481,0.0012121502],"about_ca_topic_score_codex":0.0000048407833,"about_ca_topic_score_gemma":0.000011487645,"teacher_disagreement_score":0.8957081,"about_ca_system_score_codex":0.000057041438,"about_ca_system_score_gemma":0.000035707893,"threshold_uncertainty_score":0.47625786},"labels":[],"label_agreement":null},{"id":"W2163988312","doi":"10.1002/asi.22915","title":"Reducing subject tree browsing complexity","year":2013,"lang":"en","type":"article","venue":"Journal of the American Society for Information Science and Technology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Interdisciplinary Research in Music Media and Technology; McGill University","funders":"","keywords":"Subject (documents); Computer science; Tree (set theory); Subject access; Simple (philosophy); Tree structure; Visualization; Information retrieval; World Wide Web; Data science; Data structure; Artificial intelligence; Mathematics","score_opus":0.02708280647840516,"score_gpt":0.3032392824662218,"score_spread":0.2761564759878166,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163988312","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3636512,0.000027343565,0.60358614,0.031604007,0.0002898298,0.00023303893,0.0000037663801,0.000071448914,0.00053323264],"genre_scores_gemma":[0.9162093,0.000045547087,0.08085772,0.0028435928,0.000021680431,0.0000025219383,3.6410634e-7,0.0000017703213,0.000017516599],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991014,0.000007665031,0.0003094946,0.000068364156,0.0003475041,0.00016555816],"domain_scores_gemma":[0.9979936,0.0000385118,0.00074793724,0.00022675555,0.000946479,0.00004672756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00084740436,0.000055429726,0.00012954239,0.00022340332,0.00039222944,0.0003246406,0.0010989191,0.000020797635,0.0000010934772],"category_scores_gemma":[0.00037551147,0.000035754187,0.0000884925,0.0025815093,0.0013444221,0.0037695586,0.0002592336,0.0001092144,0.0000028144473],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000035622616,0.00003537165,0.0018591499,0.000024399105,0.00004279149,1.09270665e-7,0.0026513275,0.000065108616,0.010059704,0.19162542,0.03136322,0.76226985],"study_design_scores_gemma":[0.0014170452,0.0008405618,0.020843035,0.000110563014,0.00004995623,0.00052452093,0.018197527,0.7640456,0.02050895,0.052537866,0.12038524,0.00053914264],"about_ca_topic_score_codex":0.0000138294345,"about_ca_topic_score_gemma":5.7808126e-7,"teacher_disagreement_score":0.7639805,"about_ca_system_score_codex":0.00006166849,"about_ca_system_score_gemma":0.00022345666,"threshold_uncertainty_score":0.49535793},"labels":[],"label_agreement":null},{"id":"W2164160556","doi":"10.1145/1936652.1936692","title":"OA-graphs","year":2010,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Legibility; Computer science; Visualization; Graph drawing; Chart; Orientation (vector space); Human–computer interaction; Graph; Data visualization; Table (database); Information visualization; Computer graphics (images); Artificial intelligence; Theoretical computer science; Data mining; Mathematics; Geometry","score_opus":0.016183881706910538,"score_gpt":0.2919025078937949,"score_spread":0.27571862618688436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2164160556","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017104441,0.0000012809779,0.92333245,0.00086553633,0.0002996978,0.000014123091,5.3246265e-7,0.0001618525,0.073614106],"genre_scores_gemma":[0.8890487,0.00000315629,0.101205304,0.003398406,0.00003646083,9.1591704e-7,0.000005030214,0.0000031782527,0.006298868],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997323,0.0000033880974,0.00004650946,0.00008657587,0.00007062305,0.000060615897],"domain_scores_gemma":[0.9996566,0.000008240198,0.00001009091,0.00026250293,0.000022294287,0.000040274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000059573118,0.000025360689,0.000024667828,0.00003434959,0.000027497366,0.00009836589,0.00037664684,0.00001413529,0.00024577937],"category_scores_gemma":[0.000014702661,0.000019898303,0.000014104908,0.00018083192,0.000011081914,0.00019517778,0.00007593397,0.00003884784,0.000294383],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.6881679e-8,0.00000860945,0.0002854857,3.3723856e-7,7.582543e-7,5.459268e-7,0.000013486434,2.8415715e-7,0.0006941454,0.9829122,0.008916846,0.007167274],"study_design_scores_gemma":[0.00018052505,0.000018846533,0.00239147,0.0000012103988,0.0000019074662,0.000009361547,0.000011824256,0.27381295,0.006566021,0.04237377,0.67444795,0.0001841411],"about_ca_topic_score_codex":0.0000051342026,"about_ca_topic_score_gemma":0.000020421798,"teacher_disagreement_score":0.9405384,"about_ca_system_score_codex":6.3915843e-7,"about_ca_system_score_gemma":0.0000091674765,"threshold_uncertainty_score":0.3783796},"labels":[],"label_agreement":null},{"id":"W2164660100","doi":"10.1109/vl.1994.363618","title":"Representing nodes and arcs in 3D networks","year":2002,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Visualization; Computer science; Object (grammar); Arc (geometry); Surface (topology); Texture (cosmology); Computer graphics (images); Artificial intelligence; Information retrieval; Computer vision; Theoretical computer science; Image (mathematics); Mathematics; Geometry","score_opus":0.03367245486821109,"score_gpt":0.2753362201864684,"score_spread":0.24166376531825734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2164660100","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0026836388,0.00010000248,0.9770701,0.00041865336,0.00003768377,0.000019675535,1.224018e-7,0.000054519987,0.019615637],"genre_scores_gemma":[0.97167027,0.0001524433,0.023896761,0.0009075009,0.000029086254,7.016082e-7,0.000001300791,0.000002701344,0.0033392245],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996234,0.000014362669,0.00008429851,0.0001308846,0.00005647349,0.00009054825],"domain_scores_gemma":[0.99975914,0.000026392321,0.000015590558,0.00016288787,0.000009623754,0.000026393423],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009265305,0.000031167787,0.000042218344,0.000040926632,0.00002529623,0.00012280229,0.00015250493,0.000014392427,0.000054843775],"category_scores_gemma":[0.000025780591,0.000027375865,0.0000060789794,0.0002197179,0.000011434367,0.00022618475,0.00014507903,0.00003205971,0.000012172948],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.296376e-7,0.00016641124,0.21660526,0.000019002679,0.00001144613,0.000050833387,0.0010958986,0.006867991,0.00004963389,0.45960087,0.027675787,0.28785616],"study_design_scores_gemma":[0.00006671651,0.0000022077156,0.0021834648,0.000004822594,3.6913693e-7,0.0000020948826,0.000009276344,0.995005,0.000010919629,0.00017351158,0.0025029194,0.00003870859],"about_ca_topic_score_codex":0.000014679906,"about_ca_topic_score_gemma":0.000012041226,"teacher_disagreement_score":0.988137,"about_ca_system_score_codex":0.0000026650803,"about_ca_system_score_gemma":0.0000011923769,"threshold_uncertainty_score":0.11841852},"labels":[],"label_agreement":null},{"id":"W2165002216","doi":"10.1145/2207676.2208607","title":"The bohemian bookshelf","year":2012,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":189,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures; University of Calgary","keywords":"Serendipity; Curiosity; Visualization; World Wide Web; Context (archaeology); Computer science; Software deployment; Information visualization; Data science; Psychology; History; Artificial intelligence; Archaeology; Epistemology","score_opus":0.02241552267235638,"score_gpt":0.2925935648064387,"score_spread":0.27017804213408236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2165002216","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00011100926,0.00009900665,0.86310124,0.0019812135,0.00026732867,0.000021930648,3.2604277e-7,0.000111889785,0.13430603],"genre_scores_gemma":[0.90569305,0.00006579075,0.018445635,0.0066619385,0.00025280702,0.0000039056636,0.0000039174724,0.0000065999034,0.06886636],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99968034,0.000010409293,0.000052744377,0.00004495735,0.00008183834,0.0001296889],"domain_scores_gemma":[0.9996249,0.000028700946,0.000012568809,0.00026426077,0.000013850059,0.00005570438],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015448025,0.000026066104,0.000019762527,0.000009003059,0.000117644835,0.00012864609,0.00039251056,0.000008555159,0.000027490101],"category_scores_gemma":[0.00001909445,0.000014539489,0.000013059834,0.00009059128,0.00001369792,0.000292122,0.00010932872,0.000020390813,0.00033089955],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.4960977e-8,0.000006617365,0.00042261375,2.7585264e-7,0.0000013919577,6.054477e-8,0.00006002134,2.053922e-7,0.000015104744,0.9411059,0.049060706,0.0093270615],"study_design_scores_gemma":[0.000028581397,0.0000028022873,0.0004816189,6.18447e-7,7.510775e-7,0.0000017716092,0.000025585938,0.012428156,0.0008084678,0.0008952593,0.98528713,0.000039284558],"about_ca_topic_score_codex":0.0000022201903,"about_ca_topic_score_gemma":0.000001969436,"teacher_disagreement_score":0.94021064,"about_ca_system_score_codex":0.0000046586943,"about_ca_system_score_gemma":0.000008561855,"threshold_uncertainty_score":0.42531547},"labels":[],"label_agreement":null},{"id":"W2165706283","doi":"10.5555/602099.602136","title":"GeneVis: visualization tools for genetic regulatory network dynamics","year":2002,"lang":"en","type":"article","venue":"IEEE Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Visualization; Computer science; Focus (optics); Process (computing); Information visualization; Data visualization; Human–computer interaction; Artificial intelligence","score_opus":0.03905607807491299,"score_gpt":0.3019224198744776,"score_spread":0.2628663417995646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2165706283","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0024797139,0.0002516404,0.9940877,0.00012952727,0.0015564549,0.0005085175,0.000026777268,0.00050229067,0.00045739193],"genre_scores_gemma":[0.8587672,0.0016558954,0.12268837,0.005101184,0.0035296613,0.00035155585,0.0024410214,0.00032973333,0.0051353895],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99769884,0.00013688869,0.0006241024,0.0006089362,0.0004678579,0.000463395],"domain_scores_gemma":[0.9982458,0.00017935407,0.00032318017,0.0007278001,0.0003741368,0.00014976467],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00033508093,0.00026784732,0.00025895901,0.00021162916,0.00034097958,0.0007394743,0.0007032331,0.00016920961,0.00007004966],"category_scores_gemma":[0.00021756555,0.00029354918,0.000113978705,0.0013371805,0.000048137947,0.0014017584,0.000087158776,0.000054947428,0.000096472715],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014729399,0.00022723089,0.0006865686,0.00009696436,0.00006511943,0.0000029261973,0.00036455115,0.028513541,0.00019496799,0.8624535,0.054786425,0.05259344],"study_design_scores_gemma":[0.0007344694,0.00014193219,0.0005370388,0.000036735833,0.000034056586,0.0000040010236,0.000018196639,0.97472644,0.00037172443,0.0014929187,0.021530984,0.00037152713],"about_ca_topic_score_codex":0.000003042363,"about_ca_topic_score_gemma":0.000021193175,"teacher_disagreement_score":0.9462129,"about_ca_system_score_codex":0.00015267012,"about_ca_system_score_gemma":0.00004329881,"threshold_uncertainty_score":0.99995166},"labels":[],"label_agreement":null},{"id":"W2165820996","doi":"10.1057/palgrave.ivs.9500051","title":"Visualization of High-Dimensional Data with Relational Perspective Map","year":2004,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Shell Canada","keywords":"Multidimensional scaling; Computer science; Curvilinear coordinates; Scaling; Visualization; Perspective (graphical); Partition (number theory); Surface (topology); Degeneracy (biology); Multidimensional data; Data mining; Algorithm; Theoretical computer science; Artificial intelligence; Mathematics; Machine learning; Geometry","score_opus":0.02428067067097816,"score_gpt":0.3074571855781747,"score_spread":0.28317651490719653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2165820996","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015113115,0.000019039568,0.9962893,0.0006477598,0.00019157905,0.0002482253,0.00010092688,0.00020127789,0.000790557],"genre_scores_gemma":[0.9438585,0.000017469676,0.04656331,0.0010737572,0.00007115796,0.000010309018,0.008316796,0.00001893679,0.000069736365],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99793303,0.000059167312,0.000643721,0.0002926587,0.0008933992,0.0001780316],"domain_scores_gemma":[0.997333,0.000043556807,0.0005696789,0.00075765117,0.0012120439,0.00008407874],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038184065,0.00017732287,0.000188591,0.00044967319,0.00017138451,0.00017586266,0.00068990653,0.00009245694,0.000055319266],"category_scores_gemma":[0.00019870803,0.0001619285,0.00002738683,0.0012299776,0.00007921757,0.008651821,0.00028539586,0.000067355766,0.00012229344],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017137982,0.00009387629,0.00023071004,0.000029787721,0.00002846217,5.7477547e-7,0.0010485926,0.03598242,0.00002311714,0.96120775,0.0008746672,0.0004629272],"study_design_scores_gemma":[0.0038902478,0.00038467167,0.0052906047,0.00023029906,0.00006250738,0.00003568997,0.0006034138,0.9468269,0.002898372,0.028585592,0.010509885,0.00068181875],"about_ca_topic_score_codex":0.00013733967,"about_ca_topic_score_gemma":0.00002095605,"teacher_disagreement_score":0.949726,"about_ca_system_score_codex":0.00015664949,"about_ca_system_score_gemma":0.0003884339,"threshold_uncertainty_score":0.6603252},"labels":[],"label_agreement":null},{"id":"W216667309","doi":"10.1007/978-90-481-8816-1_8","title":"Research and Guidelines on Computer-Generated Visualizations","year":2010,"lang":"en","type":"book-chapter","venue":"Models and modeling in science education","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Visualization; Computer science; Information visualization; Computer graphics; Scientific visualization; Context (archaeology); Software; Computer graphics (images); Graphics; Human–computer interaction; Software visualization; Multimedia; Software development; Artificial intelligence; Component-based software engineering; Programming language","score_opus":0.30666681265881657,"score_gpt":0.4601528827718991,"score_spread":0.15348607011308252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W216667309","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023483774,0.00034810038,0.9754798,0.0012026245,0.0007275945,0.00026391976,0.000008187541,0.00006215217,0.019559266],"genre_scores_gemma":[0.38308483,0.011427425,0.44313163,0.0056862957,0.0019935195,0.00008975424,0.00045082666,0.00017687607,0.15395883],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976361,0.000021689037,0.0004435851,0.0008952347,0.0007114452,0.00029198042],"domain_scores_gemma":[0.9975855,0.00004288626,0.00009955402,0.0005750145,0.0015079643,0.00018910143],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016429191,0.00020573701,0.00019855135,0.0011957526,0.00053990807,0.0008366219,0.000699293,0.00018296961,0.0000049773244],"category_scores_gemma":[0.000066787674,0.00019663136,0.00001786104,0.00047205822,0.00035491126,0.00085108593,0.0004011905,0.00040809912,0.0000068437785],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.831773e-7,0.00004749952,0.0000017804372,0.000011471049,0.0000014620915,4.008906e-7,0.00037669524,0.03644698,0.00009341687,0.94024986,0.00030146755,0.022467982],"study_design_scores_gemma":[0.00006291723,0.000044997978,0.0000013257475,0.00020582204,0.0000022637068,0.0000038732637,0.000022864124,0.8455179,0.00002405126,0.15167835,0.0022579904,0.00017765726],"about_ca_topic_score_codex":0.000077861594,"about_ca_topic_score_gemma":0.00006616272,"teacher_disagreement_score":0.8090709,"about_ca_system_score_codex":0.00007494487,"about_ca_system_score_gemma":0.0014592955,"threshold_uncertainty_score":0.80675644},"labels":[],"label_agreement":null},{"id":"W2166763164","doi":"10.3138/carto.42.2.117","title":"Designing Visual Analytics Methods for Massive Collections of Movement Data","year":2007,"lang":"en","type":"article","venue":"Cartographica The International Journal for Geographic Information and Geovisualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":105,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Visual analytics; Visualization; Data type; Data visualization; Data mining; Interactive visual analysis; Software; Function (biology); Data analysis; Analytics; Data science; Programming language","score_opus":0.03708831899106356,"score_gpt":0.3916481710865717,"score_spread":0.3545598520955081,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2166763164","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0003843727,0.00011317072,0.99653673,0.0010749183,0.001121938,0.0004903634,0.000109932975,0.00004243244,0.00012615063],"genre_scores_gemma":[0.2528695,0.0033537543,0.7280492,0.009870728,0.0009183397,0.00012848018,0.0043765083,0.00005971738,0.00037374697],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979994,0.000078311365,0.0009816844,0.00019599179,0.00049437035,0.00025018328],"domain_scores_gemma":[0.9958948,0.00061168446,0.0008474226,0.00034134285,0.0021886665,0.00011611586],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043233195,0.00016150282,0.00018912577,0.001351705,0.00071778457,0.0007943131,0.0012681423,0.0000900368,0.0000067196843],"category_scores_gemma":[0.0007672263,0.00012908498,0.00016395097,0.0013636226,0.00012201403,0.0019533585,0.00027680173,0.00012254708,3.723056e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027970524,0.00026357002,0.0031246096,0.00012690571,0.0012462732,0.000001178431,0.0026165529,0.0028210601,0.0013413994,0.78226423,0.013510602,0.19240394],"study_design_scores_gemma":[0.001564099,0.00027094065,0.0006030288,0.000058027876,0.00013504316,0.000034896355,0.0016258451,0.8246669,0.0023532647,0.021807754,0.14661875,0.00026143686],"about_ca_topic_score_codex":0.000014478557,"about_ca_topic_score_gemma":0.000026392794,"teacher_disagreement_score":0.8218458,"about_ca_system_score_codex":0.00003064862,"about_ca_system_score_gemma":0.00012365043,"threshold_uncertainty_score":0.76595795},"labels":[],"label_agreement":null},{"id":"W2167252678","doi":"10.1109/tvcg.2008.34","title":"GrouseFlocks: Steerable Exploration of Graph Hierarchy Space","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":154,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"University of British Columbia; Institut national de recherche en informatique et en automatique (INRIA)","keywords":"Computer science; Theoretical computer science; Hierarchy; Graph; Lattice graph; Cluster analysis; Voltage graph; Line graph; Artificial intelligence","score_opus":0.040993972136533566,"score_gpt":0.2795971650931736,"score_spread":0.23860319295664006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167252678","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004000515,0.00005134968,0.9949523,0.00009339097,0.00040517777,0.00016915632,0.000013871043,0.00023609734,0.00007813225],"genre_scores_gemma":[0.9905585,0.0023953188,0.0056652566,0.0009928017,0.0000468063,0.000016397475,0.000026770991,0.000025900506,0.00027222728],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984394,0.0001341028,0.00041109434,0.00039876736,0.00041972447,0.00019696282],"domain_scores_gemma":[0.99895877,0.00007680962,0.00015558337,0.00042530082,0.0002522309,0.00013130979],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016729944,0.00020280461,0.00023715351,0.0006481399,0.0003838291,0.00010082195,0.00032424674,0.00009979487,0.000012008131],"category_scores_gemma":[0.0000032287458,0.00020690473,0.000099761,0.0015413145,0.00014563875,0.0012521354,0.000007535915,0.00013341446,0.000007249978],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011930143,0.00038243525,0.000098369645,0.000040846207,0.00004712658,0.0000050213644,0.0019276091,0.0027097217,0.000038386293,0.992284,0.0007257887,0.0017287397],"study_design_scores_gemma":[0.00072203024,0.0003580784,0.0001729358,0.000050057,0.000020528289,0.000029857747,0.000049050064,0.98749715,0.005576662,0.003182909,0.0020397634,0.00030094804],"about_ca_topic_score_codex":0.000019620857,"about_ca_topic_score_gemma":0.00001119366,"teacher_disagreement_score":0.9892871,"about_ca_system_score_codex":0.000013951189,"about_ca_system_score_gemma":0.00005794364,"threshold_uncertainty_score":0.843733},"labels":[],"label_agreement":null},{"id":"W2167335266","doi":"10.1109/waina.2010.187","title":"User Interface Development for a Computer-Based User Study: The Universal Model Approach","year":2010,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Swansea University; Royal Society; Natural Sciences and Engineering Research Council of Canada; Universiti Tun Hussein Onn Malaysia","keywords":"Computer science; Human–computer interaction; User interface; Interface (matter); Representation (politics); Software; Test (biology); Programming language","score_opus":0.04683861323668711,"score_gpt":0.3057497860014852,"score_spread":0.25891117276479814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167335266","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0089759575,5.783144e-7,0.9895848,0.0003561821,0.00014556246,0.00036099672,0.0000026802616,0.000121083016,0.00045217437],"genre_scores_gemma":[0.3893888,9.1737704e-8,0.6076517,0.0007680911,0.000022112816,0.000014295785,0.00000918805,0.0000073955302,0.0021383127],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99918044,0.000024717403,0.00015619218,0.0002856583,0.000188644,0.00016432929],"domain_scores_gemma":[0.99924636,0.000052640702,0.000046291287,0.00048924313,0.000105365616,0.000060098093],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030129732,0.00010839517,0.00009357432,0.000056764155,0.00016495372,0.0002585745,0.0011150024,0.00003106041,0.000009572391],"category_scores_gemma":[0.0000088075185,0.000070466056,0.000032646945,0.0001959069,0.000029368066,0.00023939915,0.00030321194,0.00009540265,0.000014700983],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031927408,0.0030989356,0.0017820074,0.000038654798,0.00019985053,0.0000025902393,0.008523417,0.2501834,0.0003437316,0.65499073,0.061851334,0.018953407],"study_design_scores_gemma":[0.0004928353,0.000037537357,0.00011316415,0.0000014762257,0.000005651712,5.028365e-7,0.00013873428,0.9708312,0.00040928627,0.000043395594,0.027811911,0.00011429554],"about_ca_topic_score_codex":0.0000066042203,"about_ca_topic_score_gemma":0.000053442567,"teacher_disagreement_score":0.7206478,"about_ca_system_score_codex":0.000016598984,"about_ca_system_score_gemma":0.00016676214,"threshold_uncertainty_score":0.28735226},"labels":[],"label_agreement":null},{"id":"W2167338201","doi":"10.1109/pst.2008.17","title":"LogView: Visualizing Event Log Clusters","year":2008,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"National Institute for Materials Science; Natural Sciences and Engineering Research Council of Canada; Mitacs; Dalhousie University","keywords":"Computer science; Automatic summarization; Cluster analysis; Event (particle physics); Visualization; Web log analysis software; Data mining; Hierarchical clustering; Data visualization; Information retrieval; Artificial intelligence; The Internet; World Wide Web","score_opus":0.04209104348254463,"score_gpt":0.3234309417369488,"score_spread":0.2813398982544042,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167338201","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006998105,0.000056333778,0.98912627,0.00075992197,0.00017306245,0.00004125769,7.4307616e-7,0.00018196633,0.008960641],"genre_scores_gemma":[0.92064804,0.00040320618,0.050701816,0.013729303,0.000106371735,0.00000461518,0.000023585702,0.000015206072,0.014367833],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992281,0.000036330228,0.00016996916,0.00020494337,0.00019800343,0.0001626618],"domain_scores_gemma":[0.999476,0.000025875283,0.000042060725,0.00033200515,0.000041831678,0.0000822174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013664355,0.000074439224,0.00008969622,0.00007025211,0.00011409919,0.000055361907,0.0004925146,0.000024410514,0.00008505596],"category_scores_gemma":[0.000027778202,0.000062933024,0.00004409627,0.0003033082,0.000030029354,0.00035616683,0.00021540147,0.000039671864,0.00037596474],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000020678724,0.00023901452,0.0025074764,0.000024482715,0.00003296432,0.000099482575,0.001324996,0.0005871818,0.00019435416,0.7280058,0.2491672,0.01781498],"study_design_scores_gemma":[0.00039174178,0.0000631133,0.0010491856,0.000017903454,0.000004857433,0.000095799376,0.000058154248,0.6929787,0.0011681593,0.0009696214,0.30288035,0.00032245394],"about_ca_topic_score_codex":0.000012588869,"about_ca_topic_score_gemma":0.00000428179,"teacher_disagreement_score":0.93842447,"about_ca_system_score_codex":0.000020989553,"about_ca_system_score_gemma":0.000039094357,"threshold_uncertainty_score":0.48323914},"labels":[],"label_agreement":null},{"id":"W2167736126","doi":"10.1109/mcg.2015.40","title":"Preparing Undergraduates for Visual Analytics","year":2015,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visual analytics; Computer science; Analytics; Data science; Visualization; Component (thermodynamics); Computer graphics; Cognition; Human–computer interaction; Artificial intelligence; Psychology","score_opus":0.04897367556961103,"score_gpt":0.3289652691882265,"score_spread":0.2799915936186155,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167736126","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00047117923,0.00006187464,0.99827915,0.00047236256,0.00011560228,0.00025349678,0.000011572897,0.00014057317,0.00019415635],"genre_scores_gemma":[0.82682514,0.00021085977,0.16931646,0.0023338627,0.0006852582,0.00024811184,0.00012765577,0.000031389387,0.00022128456],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99914455,0.000015246719,0.00020074105,0.00033050054,0.00014437777,0.00016455904],"domain_scores_gemma":[0.9991213,0.00008440657,0.00007825395,0.0003336302,0.00020054984,0.0001818508],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019996271,0.000109835695,0.00012303144,0.00013460212,0.0001666054,0.0003202357,0.0003947378,0.000042845513,1.9991948e-7],"category_scores_gemma":[0.000006095512,0.00010762562,0.000048337664,0.00044181832,0.000055748085,0.00022291597,0.00012904817,0.000054243163,0.000006602295],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.788799e-7,0.00007556913,0.00028054888,0.000014262045,0.0000226211,1.8134219e-7,0.00006790042,0.00041478113,0.000010476613,0.977165,0.008754438,0.013193357],"study_design_scores_gemma":[0.00024179227,0.00005169945,0.000083422325,0.000005226474,0.000013472537,0.000004345424,0.0000084213325,0.84198666,0.00007834704,0.058386937,0.09900366,0.00013602019],"about_ca_topic_score_codex":0.0000055917003,"about_ca_topic_score_gemma":0.0000097164775,"teacher_disagreement_score":0.91877806,"about_ca_system_score_codex":0.000011106015,"about_ca_system_score_gemma":0.0000536669,"threshold_uncertainty_score":0.43888456},"labels":[],"label_agreement":null},{"id":"W2167822596","doi":"10.1007/978-3-642-32232-7_6","title":"A Functional Framework for Evaluating Financial Visualization Products","year":2012,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Scope (computer science); Visualization; Portfolio; Process (computing); Table (database); Order (exchange); Bridge (graph theory); Analytics; Imperfect; Application portfolio management; Software deployment; Operations research; Management science; Risk analysis (engineering); Process management; Data science; Project portfolio management; Finance; Systems engineering; Engineering; Data mining; Business; Project management; Software engineering","score_opus":0.10664337188574546,"score_gpt":0.3601493736347961,"score_spread":0.25350600174905064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167822596","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[3.2927343e-7,0.00018820049,0.96255136,0.00034397165,0.0009651684,0.0003869013,0.000031091156,0.00019370393,0.035339262],"genre_scores_gemma":[0.00020985636,0.00006964385,0.38122168,0.0025001476,0.002526906,0.000045271296,0.0011249763,0.00007144006,0.61223006],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99836946,0.00001562419,0.00036511623,0.00050363253,0.00050735957,0.00023882915],"domain_scores_gemma":[0.9984159,0.0001325667,0.00028474376,0.0005064183,0.00057650096,0.000083898594],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048665347,0.0002431492,0.00022870251,0.00016224274,0.00017346529,0.00018362777,0.00040395214,0.00028430944,0.0005263995],"category_scores_gemma":[0.0006785089,0.00023297657,0.00009750226,0.00010956075,0.000028806298,0.00042441915,0.00019098974,0.00014430204,0.00026642173],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003524568,0.000019336803,0.0000020529214,0.000051664843,0.00001442248,2.0056801e-7,0.00004488827,0.000014141353,0.0000068570685,0.9540394,0.027882593,0.017920926],"study_design_scores_gemma":[0.00020930082,0.000103827784,0.000023490145,0.00013535481,0.000058411926,0.0000043126834,0.0000017105363,0.046931796,0.00011187094,0.42147747,0.5304777,0.00046476425],"about_ca_topic_score_codex":9.689103e-7,"about_ca_topic_score_gemma":0.0000017093804,"teacher_disagreement_score":0.5813297,"about_ca_system_score_codex":0.000056769666,"about_ca_system_score_gemma":0.00033430025,"threshold_uncertainty_score":0.9500509},"labels":[],"label_agreement":null},{"id":"W2167915891","doi":"10.1109/infovis.2005.5","title":"An Interactive 3D Integration of Parallel Coordinates and Star Glyphs","year":2006,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":60,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Offset (computer science); Focus (optics); Set (abstract data type); Computer graphics (images); Star (game theory); Impression; Context (archaeology); Artificial intelligence; Mathematics","score_opus":0.013008340508290119,"score_gpt":0.2941019813236538,"score_spread":0.28109364081536364,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167915891","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.031959847,0.000011562293,0.96533084,0.00013275756,0.000028908298,0.00003431039,0.0000038963044,0.000043481887,0.0024543991],"genre_scores_gemma":[0.93182373,0.00000542294,0.067629516,0.00011325508,0.000009817796,7.743287e-7,0.000029496377,0.0000019210825,0.0003860674],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996099,0.000023028531,0.00011757993,0.00012204871,0.00007284412,0.00005463461],"domain_scores_gemma":[0.9996835,0.000019407893,0.000050481103,0.0001456427,0.000078309975,0.000022665095],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006694721,0.000046940626,0.00006523603,0.000055613258,0.000022946291,0.00008339116,0.00015798141,0.000015756097,0.000022311975],"category_scores_gemma":[0.000010981741,0.000037077192,0.000009504196,0.00012699088,0.00002471834,0.0006801483,0.000043375072,0.000024077432,0.000003802857],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008559232,0.0002172887,0.0016821054,0.000009376731,0.000010175063,0.000001848784,0.0005694648,0.00018671341,0.0065617533,0.9606581,0.002695829,0.027398802],"study_design_scores_gemma":[0.00020358337,0.00010847673,0.007222812,0.000010232846,0.0000035342027,0.0000018298384,0.00019656772,0.9782432,0.0065374356,0.006260961,0.0011251679,0.0000862098],"about_ca_topic_score_codex":0.00033535963,"about_ca_topic_score_gemma":0.00010310104,"teacher_disagreement_score":0.9780565,"about_ca_system_score_codex":0.000006330805,"about_ca_system_score_gemma":0.000010606186,"threshold_uncertainty_score":0.1511964},"labels":[],"label_agreement":null},{"id":"W2168705291","doi":"10.1109/tvcg.2010.137","title":"MulteeSum: A Tool for Comparative Spatial and Temporal Gene Expression Data","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Computing Research Association; Helen Hay Whitney Foundation; National Science Foundation","keywords":"Expression (computer science); DNA microarray; Spatial analysis; Computer science; Computational biology; Gene; Gene expression; Visualization; Biology; Data mining; Genetics; Geography","score_opus":0.055261641292226625,"score_gpt":0.3408637091949665,"score_spread":0.2856020679027399,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168705291","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0106832655,0.000012001629,0.98786265,0.000064185595,0.00069594843,0.00033493212,0.00017509446,0.00016445649,0.000007458877],"genre_scores_gemma":[0.9611428,0.0000923091,0.037465442,0.0008475251,0.00011267745,0.000024110428,0.00024993243,0.000017097565,0.000048117505],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99858326,0.000071969545,0.00031525522,0.00061344716,0.00023374872,0.00018234014],"domain_scores_gemma":[0.99881566,0.000133432,0.000115267205,0.0006407013,0.0001633322,0.00013158978],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025794498,0.00020585081,0.0002146138,0.00024931098,0.00041851058,0.00039083435,0.000484018,0.00011652087,0.000007934355],"category_scores_gemma":[0.000005501101,0.00019447086,0.000041952524,0.00035914197,0.00011083241,0.00074686273,0.00002803323,0.00017069747,0.0000024899011],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014244627,0.0015309503,0.0012284814,0.00018911091,0.00018475576,0.0000067210376,0.004266549,0.00036128677,0.003975626,0.93612736,0.0054698233,0.0465169],"study_design_scores_gemma":[0.0008684772,0.00015193256,0.00022794536,0.000021908982,0.00002153949,0.000012103961,0.000016621703,0.9860924,0.00656884,0.0004394954,0.005325945,0.00025281205],"about_ca_topic_score_codex":0.000018829744,"about_ca_topic_score_gemma":0.00009762708,"teacher_disagreement_score":0.98573107,"about_ca_system_score_codex":0.000004937876,"about_ca_system_score_gemma":0.000044329012,"threshold_uncertainty_score":0.7930292},"labels":[],"label_agreement":null},{"id":"W2168899303","doi":"10.1109/hicss.2006.107","title":"CrystalChat: Visualizing Personal Chat History","year":2006,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"University of Calgary","keywords":"Conversation; Instant messaging; Computer science; Social media; World Wide Web; Mores; Tone (literature); Visualization; Multimedia; Human–computer interaction; Psychology; Communication; Artificial intelligence; Linguistics","score_opus":0.02384777817345053,"score_gpt":0.2624374877862888,"score_spread":0.23858970961283826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168899303","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008432401,0.00023192755,0.9366394,0.00045921808,0.00027399426,0.00003235607,0.0000014697306,0.00027964124,0.06123873],"genre_scores_gemma":[0.87249404,0.000023005035,0.026309723,0.005674391,0.00038866868,0.0000052316527,0.00006280653,0.00002203977,0.0950201],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99924684,0.00001969109,0.00013256537,0.00021465919,0.00022280317,0.0001634524],"domain_scores_gemma":[0.99965173,0.000016202172,0.00004186214,0.00019770951,0.000043144668,0.0000493655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001136567,0.00007821231,0.00007574315,0.000089117435,0.00005499711,0.00007833694,0.00033806104,0.000027052196,0.00038908547],"category_scores_gemma":[0.00000775014,0.00007225587,0.000043546544,0.00014578241,0.000038120706,0.00045315005,0.00011403511,0.00003723031,0.0001555108],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.1303153e-7,0.000055091878,0.00019095141,0.000006254041,0.0000034032864,0.000007770638,0.00027740607,0.000008910637,0.0007770685,0.8358946,0.16138239,0.0013957625],"study_design_scores_gemma":[0.0001534652,0.000015754411,0.00030621345,0.000006117707,0.0000024919773,0.000007862609,0.00005691799,0.28530815,0.0003585674,0.0008584698,0.7127634,0.00016256425],"about_ca_topic_score_codex":0.000086993634,"about_ca_topic_score_gemma":0.000017995262,"teacher_disagreement_score":0.9103297,"about_ca_system_score_codex":0.000097034565,"about_ca_system_score_gemma":0.000054336815,"threshold_uncertainty_score":0.4260213},"labels":[],"label_agreement":null},{"id":"W2170305770","doi":"10.1007/978-1-4020-6528-6_30","title":"Local Navigation Can Reveal Implicit Relations","year":2007,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Meaning (existential); Graph; Human–computer interaction; Visualization; Information retrieval; Data science; World Wide Web; Order (exchange); Theoretical computer science; Data mining; Epistemology","score_opus":0.03558852272309984,"score_gpt":0.30748095489366345,"score_spread":0.2718924321705636,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170305770","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[3.8078895e-7,0.00001534656,0.55143297,0.00027203775,0.00009592443,0.000055432334,0.000020232392,0.00011703134,0.4479907],"genre_scores_gemma":[0.0017564669,0.000018077555,0.012442631,0.0014963284,0.00011037944,0.000001198974,0.0006816861,0.000024765252,0.9834685],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99875647,0.000007292769,0.00036750524,0.00035774335,0.00034423874,0.00016674954],"domain_scores_gemma":[0.9989493,0.000043142656,0.00015352665,0.0005749777,0.0001556931,0.00012337907],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018521395,0.00018109148,0.0001667962,0.0001866491,0.000107052525,0.00012734067,0.0005059539,0.00022837991,0.00033667084],"category_scores_gemma":[0.0000068448358,0.000176407,0.000080528094,0.00009979657,0.000054327986,0.00019752815,0.00017645485,0.00022331433,0.00067878194],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.8334154e-7,0.0000045167003,0.000005051864,0.0000053638646,0.000011375134,0.000008404398,0.000031082,0.000027524315,0.0000016350214,0.96236104,0.02336366,0.014180087],"study_design_scores_gemma":[0.0001791686,0.000045269844,0.00007710371,0.00013905187,0.000035189583,0.000036673435,0.000009715892,0.04499679,0.000046395096,0.122311614,0.83155364,0.0005694021],"about_ca_topic_score_codex":0.000036227906,"about_ca_topic_score_gemma":0.00007184926,"teacher_disagreement_score":0.8400494,"about_ca_system_score_codex":0.00011138395,"about_ca_system_score_gemma":0.000119691606,"threshold_uncertainty_score":0.8724595},"labels":[],"label_agreement":null},{"id":"W2170326681","doi":"10.1007/978-1-4615-0111-4_17","title":"The Complexity of Visual Search Tasks","year":2002,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Function (biology); Resource (disambiguation); Cognitive psychology; Cognitive science; Data science; Psychology","score_opus":0.128329510755485,"score_gpt":0.34498230447776723,"score_spread":0.21665279372228224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170326681","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[3.953868e-7,0.00007205349,0.21444191,0.0006038197,0.00010594808,0.00007491388,0.000020680889,0.000056172863,0.7846241],"genre_scores_gemma":[0.0014670878,0.0003286866,0.0024377874,0.00033872703,0.00006277828,5.425168e-7,0.00003488557,0.000013901315,0.9953156],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988334,0.000019885543,0.00027887305,0.00023423253,0.0004835076,0.00015008975],"domain_scores_gemma":[0.998961,0.000078238714,0.000111035486,0.00061685004,0.00016887866,0.00006402327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022259116,0.00013593449,0.00018205191,0.00007473075,0.00012720673,0.00014918929,0.0011476439,0.000086391345,0.0007138012],"category_scores_gemma":[0.000011592763,0.00009000305,0.00009087339,0.000058390473,0.0003947339,0.00009340072,0.00050995906,0.00016026032,0.00034298294],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.4224817e-7,0.000012210682,0.0000013385092,0.0000081040125,0.000019257135,0.0000017098491,0.000024923707,0.0000017605572,0.0000012259,0.9754829,0.016660724,0.007785399],"study_design_scores_gemma":[0.00011789972,0.0000800774,0.000016888733,0.00003525005,0.000010471621,0.000004658509,0.0000067754104,0.16826443,0.00009469144,0.05714249,0.77400064,0.00022570259],"about_ca_topic_score_codex":0.000012473798,"about_ca_topic_score_gemma":0.0000137880925,"teacher_disagreement_score":0.91834044,"about_ca_system_score_codex":0.000017260674,"about_ca_system_score_gemma":0.00004822568,"threshold_uncertainty_score":0.7815622},"labels":[],"label_agreement":null},{"id":"W2170406185","doi":"10.1109/tvcg.2010.237","title":"Whisper, Don't Scream: Grids and Transparency","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; USable; Transparency (behavior); Grid; Presentation (obstetrics); Visualization; Artificial intelligence; Computer vision; Human–computer interaction; Multimedia","score_opus":0.01598287099181107,"score_gpt":0.27466134873515813,"score_spread":0.25867847774334707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170406185","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009914319,0.000029937113,0.9884096,0.00017853458,0.0008914813,0.00014174936,0.000022913662,0.00029312013,0.000118349744],"genre_scores_gemma":[0.9923869,0.0008033908,0.0042865947,0.0022321213,0.00009655318,0.0000121623425,0.000021844562,0.000024251765,0.00013619025],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985625,0.00006912774,0.00033103497,0.0005153654,0.0002961302,0.0002258391],"domain_scores_gemma":[0.99906164,0.00006669658,0.000077288554,0.00042863574,0.00013710833,0.00022863364],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020082683,0.00023376601,0.00020975854,0.0004066644,0.00039710393,0.00043273217,0.00034585324,0.00014704143,0.000039373197],"category_scores_gemma":[0.0000029771634,0.00022872072,0.000065413755,0.00081383996,0.00015008905,0.00063246855,0.000006928291,0.00027608438,0.0000075969624],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006653081,0.0002394328,0.00024531985,0.000034232176,0.000031781816,0.0000033215995,0.0007125005,0.000054607586,0.00010724379,0.9810957,0.0004603316,0.017008882],"study_design_scores_gemma":[0.0007437792,0.00019381632,0.0007823572,0.00003121216,0.00003093763,0.00004233048,0.00002550508,0.98580694,0.0012292153,0.001332995,0.009419931,0.00036097734],"about_ca_topic_score_codex":0.000021048016,"about_ca_topic_score_gemma":0.00010357061,"teacher_disagreement_score":0.98575234,"about_ca_system_score_codex":0.0000060215007,"about_ca_system_score_gemma":0.000039740207,"threshold_uncertainty_score":0.93269604},"labels":[],"label_agreement":null},{"id":"W2171088036","doi":"10.1177/0165551507087711","title":"Metadata-enhanced visual interfaces to digital libraries","year":2008,"lang":"en","type":"article","venue":"Journal of Information Science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Metadata; Computer science; Digital library; Visualization; World Wide Web; Interface (matter); Information retrieval; Metadata repository; User interface; Meta Data Services; Representation (politics); Human–computer interaction; Data mining","score_opus":0.023816579478941953,"score_gpt":0.3003478346537549,"score_spread":0.276531255174813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171088036","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.060564958,0.000007142558,0.9361123,0.000509654,0.0003137957,0.000033864362,0.0000040922996,0.000024166131,0.0024300436],"genre_scores_gemma":[0.9694985,0.000017340562,0.029143369,0.0011571139,0.00002951318,3.4807638e-7,0.0000018488347,0.0000013169945,0.0001506481],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9983576,0.000009203238,0.00054119417,0.00007399886,0.0008631245,0.0001548775],"domain_scores_gemma":[0.99855554,0.000037120823,0.0003940019,0.00018000432,0.0006474537,0.00018588857],"candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.00051679095,0.0000705783,0.00012385377,0.00061089353,0.00020644451,0.0020686274,0.0014596673,0.000014859386,0.000011288273],"category_scores_gemma":[0.0007039202,0.000052737054,0.000035170648,0.0017062166,0.00016485837,0.07222645,0.00032453958,0.00007503684,0.00012324899],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013086616,0.00045587905,0.0022184744,0.00006848063,0.00010096207,0.00004539825,0.06865045,0.01179775,0.014485626,0.46766138,0.07340198,0.36098275],"study_design_scores_gemma":[0.0018615562,0.0018833578,0.011898804,0.00022130493,0.000018817032,0.001448381,0.0042717317,0.17848885,0.417803,0.0026331504,0.37830538,0.0011656748],"about_ca_topic_score_codex":5.7493475e-7,"about_ca_topic_score_gemma":1.0906426e-7,"teacher_disagreement_score":0.9089335,"about_ca_system_score_codex":0.0000332484,"about_ca_system_score_gemma":0.00045219218,"threshold_uncertainty_score":0.99896735},"labels":[],"label_agreement":null},{"id":"W2171240564","doi":"10.1111/j.1467-8659.2009.01439.x","title":"DocuBurst: Visualizing Document Content using Language Structure","year":2009,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":147,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; University of Toronto","funders":"","keywords":"Computer science; Zoom; Visualization; Focus (optics); Information retrieval; Granularity; Natural language processing; Space (punctuation); Word (group theory); Information visualization; Artificial intelligence; Programming language; Linguistics","score_opus":0.030859509247845578,"score_gpt":0.31202998401733023,"score_spread":0.28117047476948465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171240564","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02269915,0.00027741014,0.9749322,0.0010378326,0.00059972523,0.00013750562,0.000010568508,0.0002500217,0.000055588112],"genre_scores_gemma":[0.93896186,0.000028551984,0.05240019,0.00835126,0.00017199572,7.313437e-7,0.000045844357,0.000013227383,0.000026340746],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99830174,0.000061226376,0.00033893553,0.00045362895,0.00039338224,0.0004510666],"domain_scores_gemma":[0.99890786,0.00002709087,0.00014698383,0.00063995743,0.00011287894,0.00016523247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015943307,0.00023002557,0.00023278681,0.00028236932,0.00020309466,0.0005643686,0.00097286224,0.000085005784,0.000012087528],"category_scores_gemma":[0.00000897233,0.00020974218,0.00012739438,0.000715036,0.000042160842,0.0007018519,0.00031707287,0.00017019997,0.000008118408],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002649534,0.00006129029,0.0005798537,0.0000136224135,0.000034426066,0.00004402236,0.0008009692,0.00033116722,0.0010355904,0.97078705,0.0013341684,0.024975168],"study_design_scores_gemma":[0.00069555483,0.00021270679,0.0010966744,0.000084848056,0.000021803222,0.00006796539,0.00014017108,0.9611434,0.0022933509,0.028023789,0.0056872093,0.0005325315],"about_ca_topic_score_codex":0.000021840016,"about_ca_topic_score_gemma":0.000009551092,"teacher_disagreement_score":0.9608122,"about_ca_system_score_codex":0.00004182333,"about_ca_system_score_gemma":0.000040583855,"threshold_uncertainty_score":0.85530376},"labels":[],"label_agreement":null},{"id":"W2171558823","doi":"10.1109/wi-iat.2009.242","title":"CubanSea: Cluster-Based Visualization of Search Results","year":2009,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Visualization; Information retrieval; Cluster analysis; Set (abstract data type); Data mining; Search engine; Web search query; Data visualization; Information visualization; Machine learning","score_opus":0.03569790378896716,"score_gpt":0.3459254595206958,"score_spread":0.31022755573172867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171558823","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00095445995,0.0000054957413,0.9870995,0.001496893,0.000040299437,0.00006309798,0.0000059059025,0.000108159715,0.010226178],"genre_scores_gemma":[0.9784675,0.000005885528,0.018447733,0.0020434607,0.000018647324,3.7716183e-7,0.0000630076,0.0000031135403,0.0009502292],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990728,0.00005954791,0.00025373622,0.0001915739,0.0002981682,0.00012421238],"domain_scores_gemma":[0.99929494,0.000044892124,0.000058706566,0.00038196213,0.00016272976,0.00005678403],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032617224,0.00006195646,0.0000892487,0.00014081901,0.000038439463,0.00007131142,0.0004288653,0.000031628508,0.000016869859],"category_scores_gemma":[0.00006526719,0.000053872453,0.000031141146,0.00065982126,0.000018804856,0.00026679144,0.0000429394,0.000028095827,0.000026155594],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003282607,0.00041487286,0.00035156944,0.00002363104,0.000007252174,0.0000031780933,0.00042578214,0.0053268005,0.0011876437,0.950378,0.019173868,0.022674577],"study_design_scores_gemma":[0.00065538014,0.00016581146,0.0011064549,0.000015253554,0.0000022742756,6.410476e-7,0.00001195621,0.9811034,0.013397579,0.00051519094,0.002938477,0.0000875519],"about_ca_topic_score_codex":0.000009351501,"about_ca_topic_score_gemma":0.0000029547614,"teacher_disagreement_score":0.9775131,"about_ca_system_score_codex":0.00001188574,"about_ca_system_score_gemma":0.00007004694,"threshold_uncertainty_score":0.21968548},"labels":[],"label_agreement":null},{"id":"W2171689778","doi":"10.1145/1133265.1133308","title":"An integrated task-based framework for the design and evaluation of visualizations to support preferential choice","year":2006,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Task (project management); Human–computer interaction; Visualization; Task analysis; Software engineering; Systems engineering; Data mining; Engineering","score_opus":0.08588271643349943,"score_gpt":0.4013876672372688,"score_spread":0.3155049508037694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171689778","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013357943,0.000006024357,0.9976438,0.0002842256,0.00007070872,0.00053444784,0.000019238174,0.000054974815,0.00005076596],"genre_scores_gemma":[0.73405135,8.7855466e-7,0.2651483,0.0004890776,0.000033780205,0.000046071782,0.00015874545,0.0000062752847,0.00006554165],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99908,0.00013257797,0.00019991222,0.00019375613,0.0002939715,0.000099767094],"domain_scores_gemma":[0.99880797,0.0002618629,0.00007118532,0.000321046,0.00049385533,0.00004408644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007807282,0.00007289119,0.000077863035,0.00008625972,0.00010421419,0.0001706398,0.0003425721,0.000039414295,0.00006950596],"category_scores_gemma":[0.00022473696,0.00005023468,0.000019749808,0.00046619654,0.000023977716,0.00022235804,0.000029595993,0.000027225295,0.0000025813042],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017046614,0.00040001085,0.00070729083,0.000019003479,0.000027393458,6.549013e-8,0.00026553165,0.18782972,0.001270974,0.7618786,0.012005591,0.035578765],"study_design_scores_gemma":[0.00026866404,0.0001539053,0.0013980417,0.000008379385,0.000042107862,1.4725387e-7,0.000020277916,0.9874276,0.0038179164,0.0041332957,0.002658334,0.00007136081],"about_ca_topic_score_codex":0.00008335356,"about_ca_topic_score_gemma":0.00007604394,"teacher_disagreement_score":0.79959786,"about_ca_system_score_codex":0.000014975704,"about_ca_system_score_gemma":0.00016604358,"threshold_uncertainty_score":0.20485109},"labels":[],"label_agreement":null},{"id":"W2172437073","doi":"10.1007/978-94-007-2105-0_7","title":"Applying Data Visualization to Improve the e-Health Decision Making","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in electrical engineering","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Visualization; Snapshot (computer storage); Zoom; Computer science; Information visualization; Data science; Field (mathematics); Data mining; Database; Engineering","score_opus":0.028733897189365594,"score_gpt":0.30590132447441726,"score_spread":0.27716742728505167,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2172437073","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[5.3871884e-7,0.0008173907,0.9967132,0.000183963,0.0003512067,0.0005607903,0.000015704372,0.00018676404,0.0011703967],"genre_scores_gemma":[0.22927612,0.0027857304,0.7222333,0.0342277,0.0037913849,0.00038915747,0.0014438195,0.0011011822,0.0047515896],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99778163,0.000020665595,0.0005206534,0.0007736567,0.00045280813,0.00045056664],"domain_scores_gemma":[0.99773717,0.0005014126,0.00016931666,0.0014180664,0.000060390495,0.00011361892],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005155562,0.00034552568,0.0003702573,0.00048143908,0.0000995737,0.00020837455,0.0021839265,0.00023745766,0.000019223675],"category_scores_gemma":[0.00083218614,0.00027729434,0.000055860786,0.00061997265,0.00001064016,0.00022662243,0.00087265606,0.00062381726,0.00003305349],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000590229,0.0000138574715,0.0000031554644,0.000039178714,0.000020579588,0.00000822402,0.0001499775,0.016723068,0.00003215145,0.22304137,0.00039122213,0.7595713],"study_design_scores_gemma":[0.00009419761,0.00008024088,0.000008325342,0.0003085641,0.0000102790555,0.000008637499,1.5257443e-7,0.9089948,0.000049318918,0.012165672,0.07792248,0.0003573166],"about_ca_topic_score_codex":0.000012500237,"about_ca_topic_score_gemma":0.000026648087,"teacher_disagreement_score":0.89227176,"about_ca_system_score_codex":0.00021402664,"about_ca_system_score_gemma":0.0001341633,"threshold_uncertainty_score":0.99996793},"labels":[],"label_agreement":null},{"id":"W2179780355","doi":"10.1145/2817721.2817735","title":"Understanding Researchers' Use of a Large, High-Resolution Display Across Disciplines","year":2015,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Zoom; Multitude; Context (archaeology); Data science; Variety (cybernetics); Computer science; Resolution (logic); Human–computer interaction; Engineering; Artificial intelligence; Epistemology; Geography","score_opus":0.4117889416396599,"score_gpt":0.43941079540111655,"score_spread":0.02762185376145665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2179780355","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007915345,0.000008391235,0.99071443,0.0007585144,0.000108034255,0.00004964683,0.000032713528,0.00006261183,0.00035032758],"genre_scores_gemma":[0.98223406,0.000008949265,0.015490321,0.00011638395,0.000026001204,0.0000012076913,0.000032376403,0.000005080205,0.0020856292],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99898803,0.000059660455,0.0001675789,0.00018007096,0.00036988538,0.0002347801],"domain_scores_gemma":[0.99925715,0.00007495911,0.00005517898,0.00034684705,0.0001322691,0.00013359144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005928033,0.0000624827,0.000094399664,0.00006434441,0.00008845768,0.00023282718,0.00038026844,0.000033789875,0.000009227626],"category_scores_gemma":[0.00025434245,0.000048198035,0.000025912414,0.0005322395,0.000057919784,0.0009927544,0.00051552575,0.000050352566,0.000019353212],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006624711,0.00007797642,0.0021984202,0.000008750355,0.000009511147,0.0000024478672,0.0009368239,0.0005654697,0.00008849543,0.9804668,0.015548259,0.00009041973],"study_design_scores_gemma":[0.0006654365,0.000068276284,0.001862004,0.000026252597,0.0000036805427,0.0000016626226,0.0012373194,0.97820693,0.00045131074,0.009425643,0.007909212,0.00014225561],"about_ca_topic_score_codex":0.00008797495,"about_ca_topic_score_gemma":0.00018976092,"teacher_disagreement_score":0.97764146,"about_ca_system_score_codex":0.00007375509,"about_ca_system_score_gemma":0.00006296575,"threshold_uncertainty_score":0.22451578},"labels":[],"label_agreement":null},{"id":"W2180305847","doi":"10.1260/1478-0771.13.2.217","title":"Harnessing Design Space: A Similarity-Based Exploration Method for Generative Design","year":2015,"lang":"en","type":"article","venue":"International Journal of Architectural Computing","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Networks of Centres of Excellence of Canada; Mitacs","keywords":"Cluster analysis; Computer science; Generative Design; Similarity (geometry); Data mining; Visualization; Parametric statistics; Parametric design; Space (punctuation); Machine learning; Artificial intelligence; Engineering; Image (mathematics)","score_opus":0.1626037918793429,"score_gpt":0.4022945369658353,"score_spread":0.23969074508649238,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2180305847","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004279296,0.000039388884,0.99262494,0.005755774,0.0009396054,0.00014589459,0.0000034589534,0.000041677693,0.000021323043],"genre_scores_gemma":[0.16534388,8.625357e-7,0.83327305,0.00090506446,0.00044431098,0.0000013510614,0.000008402689,0.000009643757,0.000013411301],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997993,0.00047146154,0.0005174143,0.00019819144,0.00064157165,0.000178377],"domain_scores_gemma":[0.996859,0.00079306186,0.0006140784,0.00012747376,0.0014651676,0.00014121537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021885305,0.00014555815,0.00020809211,0.00036143308,0.00011555235,0.0005494031,0.0009694424,0.000038046157,0.0000018278165],"category_scores_gemma":[0.0008567878,0.00012224079,0.00011948143,0.00023416954,0.000027333974,0.00072164024,0.00012989478,0.0001740746,0.000002028092],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000105387444,0.000043946617,0.000024386976,0.0000046262626,0.00007074951,0.000024124009,0.001730502,0.92718625,0.001341668,0.00547426,0.0011097318,0.06288438],"study_design_scores_gemma":[0.0010605592,0.0002384297,0.00001610934,0.00007626055,0.000013364121,0.000118840464,0.000076366065,0.96855235,0.014382267,0.014523965,0.0008037715,0.00013771442],"about_ca_topic_score_codex":0.000003924943,"about_ca_topic_score_gemma":9.318505e-7,"teacher_disagreement_score":0.16491595,"about_ca_system_score_codex":0.00012864047,"about_ca_system_score_gemma":0.00042029095,"threshold_uncertainty_score":0.52979064},"labels":[],"label_agreement":null},{"id":"W2180906","doi":"10.1007/978-3-642-29752-6_25","title":"Using Social Network Analysis to Study the Knowledge Sharing Patterns of Health Professionals Using Web 2.0 Tools","year":2013,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Social network analysis; World Wide Web; Process (computing); Knowledge management; Social network (sociolinguistics); Knowledge sharing; Health professionals; Network analysis; Health care; Data science; Social media; Engineering","score_opus":0.2314457414666685,"score_gpt":0.4444271780363277,"score_spread":0.2129814365696592,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2180906","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018575437,0.00014686146,0.9920171,0.0006272466,0.00017953698,0.0008157492,0.000028541213,0.000035010788,0.004292431],"genre_scores_gemma":[0.8049026,0.00040638246,0.18984513,0.0038343668,0.00013724552,0.00004077835,0.00014090168,0.000021633674,0.0006709672],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99782467,0.00012728572,0.0010769648,0.0002667751,0.00046612942,0.00023815829],"domain_scores_gemma":[0.9968232,0.00015935686,0.0007325204,0.0016650677,0.0005410817,0.00007878276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027436519,0.00017778092,0.00039539105,0.0009964844,0.0011469413,0.000784211,0.0037970708,0.000057831032,0.000012796593],"category_scores_gemma":[0.000029490891,0.00014518734,0.00006688393,0.0017883183,0.00019114699,0.0035278187,0.0049739988,0.00023990509,0.000009914395],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000015358397,0.00018619906,0.003153267,0.000058658097,0.00019445122,1.3726326e-7,0.029104479,0.01709923,0.0000019192316,0.76040727,0.00033628824,0.18945657],"study_design_scores_gemma":[0.00011795687,0.00002560206,0.0055232695,0.0001290673,0.000034020923,0.0000013074404,0.00021552251,0.988707,4.3925306e-7,0.00065206503,0.004424631,0.00016909679],"about_ca_topic_score_codex":0.000047781978,"about_ca_topic_score_gemma":0.000035628967,"teacher_disagreement_score":0.9716078,"about_ca_system_score_codex":0.00013969357,"about_ca_system_score_gemma":0.00045401359,"threshold_uncertainty_score":0.8821461},"labels":[],"label_agreement":null},{"id":"W2182090185","doi":"10.5555/2873021.2873030","title":"Exploratory sequential data analysis for multi-agent occupancy simulation results","year":2015,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Autodesk (Canada)","funders":"","keywords":"Computer science; Replicate; Debugging; Energy consumption; Occupancy; Domain (mathematical analysis); Exploratory analysis; Exploratory data analysis; Resource (disambiguation); Code (set theory); Data mining; Machine learning; Operating system; Data science; Programming language; Engineering","score_opus":0.44774847199633844,"score_gpt":0.4501440166168782,"score_spread":0.002395544620539758,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2182090185","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001767846,0.000017065631,0.9987404,0.00014980604,0.00021028394,0.000118650256,0.00026433682,0.00014172109,0.00018099321],"genre_scores_gemma":[0.6594773,0.0000062768318,0.33454224,0.000692093,0.000121675774,0.000006754923,0.003578638,0.000009267714,0.0015657875],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99878114,0.00005604791,0.00029826013,0.0004609913,0.0002573172,0.00014623239],"domain_scores_gemma":[0.99811924,0.00005243918,0.00010685774,0.0013347379,0.0002448921,0.00014184335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007240357,0.00008721959,0.00013216406,0.00018021207,0.000061703344,0.00021339655,0.0010261153,0.000034889785,0.0000072370244],"category_scores_gemma":[0.00035660452,0.00007698942,0.000051259973,0.00081463216,0.000014325821,0.0011697498,0.00050924515,0.000027104867,0.00005546218],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015612681,0.0010866706,0.0077269785,0.00004701622,0.0014295488,0.000018740893,0.0045881174,0.6971647,0.00009587769,0.07916188,0.18210056,0.02642379],"study_design_scores_gemma":[0.00075135054,0.000020132262,0.00015575893,0.0000016091961,0.00007351417,1.0006044e-7,0.00007080706,0.96160126,0.00006140801,0.000088102504,0.03706849,0.00010744884],"about_ca_topic_score_codex":0.000019029896,"about_ca_topic_score_gemma":0.000085470754,"teacher_disagreement_score":0.6641981,"about_ca_system_score_codex":0.000030006328,"about_ca_system_score_gemma":0.000105014245,"threshold_uncertainty_score":0.31395376},"labels":[],"label_agreement":null},{"id":"W2182924104","doi":"10.1109/ldav.2015.7348082","title":"Skydive: An interactive data visualization engine","year":2015,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Visualization; Interactivity; Visual analytics; Data visualization; Interactive visual analysis; Information visualization; Analytics; Clutter; Data science; Information retrieval; Data mining; World Wide Web","score_opus":0.1204784396990315,"score_gpt":0.4082524507496901,"score_spread":0.2877740110506586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2182924104","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00029284402,0.0000078461735,0.9937559,0.00024011363,0.00021877655,0.000041442374,0.00001488085,0.00022707623,0.005201122],"genre_scores_gemma":[0.84770477,0.00001797257,0.13969153,0.0044947257,0.00030732818,0.0000035719024,0.0032483444,0.000025502288,0.004506277],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99922335,0.000051955743,0.00012634438,0.00028970576,0.00020826265,0.000100388825],"domain_scores_gemma":[0.99869305,0.000017999555,0.000044561053,0.000938175,0.00015863085,0.00014760086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027953915,0.000067015244,0.00006823947,0.000078027035,0.000030039102,0.00024844697,0.0012712232,0.000021769456,0.00004844007],"category_scores_gemma":[0.00014712328,0.000057653266,0.000007340703,0.00035008695,0.000012282243,0.0031222184,0.00065911224,0.000033467193,0.00016190487],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000066179073,0.00037207676,0.0007762445,0.000006135547,0.000027968146,0.000010604991,0.0019323253,0.00038181353,0.00007724877,0.83919454,0.119027264,0.038187135],"study_design_scores_gemma":[0.00018385075,0.000047027017,0.00007715659,0.0000031047518,0.0000030813856,0.0000035893263,0.00015071829,0.94369423,0.00033819635,0.00092460815,0.054481935,0.000092487295],"about_ca_topic_score_codex":0.000027827191,"about_ca_topic_score_gemma":0.000018210272,"teacher_disagreement_score":0.9433124,"about_ca_system_score_codex":0.000019082043,"about_ca_system_score_gemma":0.00006512238,"threshold_uncertainty_score":0.239578},"labels":[],"label_agreement":null},{"id":"W2184384562","doi":"10.14236/ewic/eva2008.30","title":"VISUALIZATION TECHNIQUES IN VIDEO GAMES","year":2008,"lang":"en","type":"article","venue":"Electronic workshops in computing","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Visualization; Computer science; Human–computer interaction; Data visualization; Multimedia; Information visualization; Visual analytics; Cursor (databases); Video game; Artificial intelligence","score_opus":0.01668151168592911,"score_gpt":0.3025449956075264,"score_spread":0.2858634839215973,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2184384562","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029150745,0.00034868417,0.9684907,0.00027095806,0.000087533495,0.00014302856,1.9415387e-7,0.00031961605,0.0011885451],"genre_scores_gemma":[0.9879711,0.00021488508,0.011080561,0.0005091599,0.00007007947,0.0000048076895,0.000011849304,0.000013982052,0.0001235306],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99825525,0.00012543272,0.00042273724,0.00040920675,0.00023638592,0.0005509719],"domain_scores_gemma":[0.99932474,0.00013537605,0.00011076504,0.00034377715,0.000044887227,0.000040446746],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006219916,0.00014674135,0.00019992575,0.0004077064,0.000102306876,0.000085278974,0.0006626002,0.00008299592,0.000008856448],"category_scores_gemma":[0.0001229642,0.00016055918,0.000036358964,0.0019831215,0.00003756345,0.00040398768,0.00024214012,0.0002949894,0.000011302435],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012589321,0.00053928373,0.063457415,0.000042766336,0.00002117696,0.00014292952,0.0045950236,0.011536456,0.00035692207,0.63982135,0.0043359306,0.27513817],"study_design_scores_gemma":[0.00039013987,0.00005604902,0.0046338686,0.00017707898,0.0000015725168,0.000049256527,0.000046787656,0.9806852,0.0020377657,0.003738521,0.00784105,0.00034274787],"about_ca_topic_score_codex":0.000023190754,"about_ca_topic_score_gemma":0.00008233507,"teacher_disagreement_score":0.9691487,"about_ca_system_score_codex":0.00023755382,"about_ca_system_score_gemma":0.00018265315,"threshold_uncertainty_score":0.65474135},"labels":[],"label_agreement":null},{"id":"W2184914077","doi":"10.1109/vast.2015.7347681","title":"Topicks: Visualizing complex topic models for user comprehension","year":2015,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario College of Art and Design","funders":"","keywords":"Computer science; Comprehension; Human–computer interaction; Visualization; Data science; World Wide Web; Artificial intelligence; Programming language","score_opus":0.21544756117193747,"score_gpt":0.3768201970036711,"score_spread":0.1613726358317336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2184914077","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00056689815,0.000021328047,0.9923247,0.0011581281,0.0002018843,0.0001213286,0.0000021943947,0.00017152309,0.0054320344],"genre_scores_gemma":[0.44230393,0.000020192718,0.53450495,0.0099955965,0.00023070457,0.000018249451,0.00012189572,0.000020801821,0.012783676],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99925035,0.000024242978,0.00017139188,0.00021534557,0.00017826752,0.00016039186],"domain_scores_gemma":[0.9993131,0.000037910024,0.000038725364,0.00032735025,0.00016572478,0.0001172017],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001375259,0.00008101764,0.000117277785,0.000053811968,0.00006314918,0.00015950172,0.00042591142,0.000031547406,0.000014990413],"category_scores_gemma":[0.000018991197,0.000069151916,0.00003951,0.0001484184,0.0000140299735,0.0005429208,0.00019652113,0.000026487916,0.000025087778],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000014781692,0.00003518264,0.00008844773,0.000008669085,0.000005426419,7.313334e-7,0.00021900021,0.0013333713,0.00007713219,0.9443092,0.05124346,0.00267791],"study_design_scores_gemma":[0.00034020108,0.00003468327,0.000037356494,0.0000046844193,0.0000024004123,0.0000015718604,0.000049956296,0.7627231,0.00015590795,0.014201947,0.22236009,0.0000881321],"about_ca_topic_score_codex":0.00002901596,"about_ca_topic_score_gemma":0.000017241151,"teacher_disagreement_score":0.93010724,"about_ca_system_score_codex":0.000020676081,"about_ca_system_score_gemma":0.00003673442,"threshold_uncertainty_score":0.28199333},"labels":[],"label_agreement":null},{"id":"W2192089045","doi":"10.1016/j.jcss.2015.10.004","title":"Self-regularized causal structure discovery for trajectory-based networks","year":2015,"lang":"en","type":"article","venue":"Journal of Computer and System Sciences","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Regularization (linguistics); Computer science; Causal structure; Trajectory; Bayesian network; Bayesian probability; Causal model; Artificial intelligence; Mathematical optimization; Mathematics","score_opus":0.026347632885163855,"score_gpt":0.2808468392128732,"score_spread":0.25449920632770934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2192089045","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009122763,0.00020887703,0.98892325,0.00020243308,0.0013738167,0.000087148466,0.0000047142544,0.00002994027,0.000047041034],"genre_scores_gemma":[0.7860212,0.0000029026269,0.21331804,0.00020808376,0.00043076026,5.121139e-7,0.0000012728415,0.0000033582812,0.000013883577],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99869835,0.00010827894,0.00039046674,0.00018347532,0.0004437544,0.0001756939],"domain_scores_gemma":[0.99898165,0.00011636981,0.00033813543,0.0001375585,0.00025325944,0.00017304101],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011647022,0.00010872659,0.00026650156,0.00016341095,0.00014913404,0.0009228908,0.00070683786,0.000043912132,3.3141868e-7],"category_scores_gemma":[0.000013474455,0.000071355076,0.000075768345,0.00033982072,0.00006945391,0.0010148896,0.00006833996,0.00006622829,2.2370021e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017302291,0.00042561832,0.010187874,0.0008502166,0.0004048537,0.00014591122,0.0043304493,0.32755452,0.0002815343,0.5968661,0.03713707,0.021642864],"study_design_scores_gemma":[0.00082177256,0.00039279982,0.00019117001,0.00006977275,0.000017040433,0.00012713914,0.00010763101,0.9964255,0.000046311266,0.00031531122,0.0013816812,0.00010389063],"about_ca_topic_score_codex":0.000001624181,"about_ca_topic_score_gemma":0.0000018175,"teacher_disagreement_score":0.77689844,"about_ca_system_score_codex":0.000033475622,"about_ca_system_score_gemma":0.00032833745,"threshold_uncertainty_score":0.8899457},"labels":[],"label_agreement":null},{"id":"W2194371155","doi":"10.1145/2836034.2836036","title":"Visual analytics for supporting evidence-based interpretation of molecular cytogenomic findings","year":2015,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Workflow; Visual analytics; Data science; Usability; Analytics; Process (computing); World Wide Web; Interpretation (philosophy); Visualization; Human–computer interaction; Data mining","score_opus":0.07517049689439914,"score_gpt":0.3721119032248745,"score_spread":0.29694140633047533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2194371155","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.035659783,0.000020988899,0.96355975,0.00033978466,0.00007313028,0.000119824486,0.000003989039,0.000050019138,0.00017270376],"genre_scores_gemma":[0.9390589,0.0000014440043,0.060150765,0.00064961344,0.000010761878,0.0000036654883,0.0000227775,0.0000063895286,0.000095703814],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990431,0.00003089876,0.00034835827,0.00020464207,0.0002240495,0.00014897353],"domain_scores_gemma":[0.9990974,0.000119335884,0.0001568648,0.00022434993,0.00030799565,0.00009406228],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063613715,0.00008102591,0.00013969802,0.00015510779,0.000023953951,0.00009840039,0.00041697166,0.000032703912,0.000009187383],"category_scores_gemma":[0.000647151,0.00007612926,0.0000728629,0.00033225268,0.000024701609,0.00046739198,0.00008755444,0.000027569304,0.000010082119],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025685888,0.00075634784,0.017492654,0.0006430014,0.00027680228,0.0000293888,0.0045741294,0.10556938,0.119653985,0.6482078,0.016808541,0.08573111],"study_design_scores_gemma":[0.00025390377,0.00015499671,0.00003308116,0.00004076079,0.000015499902,6.9994576e-7,0.000069187445,0.9282432,0.07009926,0.0008292464,0.00017132952,0.000088793546],"about_ca_topic_score_codex":0.000008861571,"about_ca_topic_score_gemma":0.0000021455596,"teacher_disagreement_score":0.903409,"about_ca_system_score_codex":0.00004410092,"about_ca_system_score_gemma":0.00022870116,"threshold_uncertainty_score":0.3104461},"labels":[],"label_agreement":null},{"id":"W2196021064","doi":"10.25035/pad.2015.002","title":"Cloud-based Meta-analysis to Bridge Science and Practice: Welcome to metaBUS","year":2015,"lang":"en","type":"article","venue":"Personnel Assessment and Decisions","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Northern Alberta Institute of Technology; University of Calgary","funders":"SHRM Foundation; Virginia Commonwealth University; National Science Foundation","keywords":"Bridge (graph theory); Computer science; Cloud computing; Data science; Interface (matter); The Internet; Interpretation (philosophy); World Wide Web; Information overload","score_opus":0.27955150299751713,"score_gpt":0.4648037222280033,"score_spread":0.18525221923048618,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2196021064","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0054700756,0.0001743767,0.9771884,0.015413225,0.00019223442,0.00020809648,0.000035726327,0.00006263313,0.0012552096],"genre_scores_gemma":[0.70704556,0.000014200964,0.2853226,0.007326801,0.000041900617,0.000023594419,0.0000061531805,0.0000070119404,0.00021220327],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99721754,0.0001347128,0.00028899498,0.00073367165,0.0013210516,0.0003040317],"domain_scores_gemma":[0.99659705,0.0007425984,0.00009474406,0.00075749477,0.0008457835,0.00096231356],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.003505737,0.00017767408,0.00047547402,0.0008816209,0.00041520532,0.0013124357,0.0007897988,0.000029551506,0.000030272371],"category_scores_gemma":[0.0022860218,0.00013502825,0.00014346611,0.004446231,0.00008930416,0.0010159827,0.0006672163,0.00008214221,0.000044269542],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023447984,0.0027418344,0.0058047855,0.000025849935,0.040842235,0.00026101235,0.029525777,0.022166058,0.0011804601,0.6940308,0.16016404,0.04302266],"study_design_scores_gemma":[0.0012772882,0.0007324682,0.013874996,0.000008726093,0.035687167,0.00003967944,0.0044120275,0.8078032,0.00011557691,0.0016304009,0.13330649,0.0011119895],"about_ca_topic_score_codex":0.00007257383,"about_ca_topic_score_gemma":0.000046400804,"teacher_disagreement_score":0.78563714,"about_ca_system_score_codex":0.00007763637,"about_ca_system_score_gemma":0.00042120338,"threshold_uncertainty_score":0.99972427},"labels":[],"label_agreement":null},{"id":"W2200301959","doi":"","title":"The effect of animation, dual view, difference layers, and relative re-layout in hierarchical diagram differencing","year":2011,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Storyboard; Animation; Visualization; Information visualization; Node (physics); Diagram; Dual (grammatical number); Computer graphics (images); Human–computer interaction; Information retrieval; Theoretical computer science; Data mining; Multimedia; Database","score_opus":0.02520441950114451,"score_gpt":0.27646637576149846,"score_spread":0.25126195626035397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2200301959","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3787324,0.000095062445,0.61594915,0.00028336968,0.00008081539,0.00022535994,0.0000037783193,0.000061866034,0.004568194],"genre_scores_gemma":[0.9969422,0.000043755776,0.0027195667,0.00005355222,0.000006600209,0.0000055914334,0.000002902184,0.000003402739,0.00022242714],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9989926,0.00023186997,0.00025425066,0.00020191907,0.0001723114,0.00014700391],"domain_scores_gemma":[0.9990756,0.0004808693,0.00008209407,0.00027268878,0.000033336422,0.00005539046],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043553323,0.00009854885,0.00016058302,0.000066635446,0.000087253364,0.00006430304,0.00031239627,0.000038897088,0.000010579081],"category_scores_gemma":[0.0002622971,0.00005616987,0.000023764072,0.00028581577,0.000103214195,0.0002461922,0.00022673544,0.00011424354,0.0000043518467],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019543917,0.00004904039,0.10327129,0.000032092637,0.000019953675,0.000004648709,0.005147574,0.000002262705,0.00018782132,0.85428584,0.00014284397,0.036837086],"study_design_scores_gemma":[0.0010985057,0.0008727533,0.5604178,0.00012053477,0.000020195097,0.000006628667,0.00018410609,0.4058726,0.004664979,0.026241671,0.00018466929,0.00031557126],"about_ca_topic_score_codex":0.000056437504,"about_ca_topic_score_gemma":0.00011337302,"teacher_disagreement_score":0.8280442,"about_ca_system_score_codex":0.000011776243,"about_ca_system_score_gemma":0.000017100323,"threshold_uncertainty_score":0.22905408},"labels":[],"label_agreement":null},{"id":"W2202808018","doi":"","title":"Filtering and Integrating Visual Information with Motion","year":2001,"lang":"en","type":"article","venue":"University of New Hampshire Scholars Repository (University of New Hampshire at Manchester)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Computer vision; Pairwise comparison; Visualization; Motion (physics); Filter (signal processing); Structure from motion; Artificial intelligence; Perception; Dimension (graph theory); Mathematics","score_opus":0.013306971313137114,"score_gpt":0.20668355585277987,"score_spread":0.19337658453964274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2202808018","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.58445185,0.000039589744,0.4125636,0.0004071509,0.00007727546,0.00014828007,0.0000059153112,0.00011962882,0.0021867056],"genre_scores_gemma":[0.9471701,0.00015262108,0.04475649,0.00011001245,0.000040756695,2.4851545e-8,0.00007005278,0.000013565812,0.0076863696],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99859864,0.000082561426,0.00022848646,0.00039447687,0.00044657502,0.00024928476],"domain_scores_gemma":[0.9984257,0.00005352594,0.00051106466,0.0004753624,0.00021933932,0.0003150117],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00017511463,0.00022510464,0.00032824147,0.00029832328,0.000551252,0.00014394202,0.00077880814,0.00014973796,0.000044630546],"category_scores_gemma":[0.000027896476,0.00028043555,0.00010409852,0.00059470435,0.00017796505,0.0055460357,0.00065257464,0.00021723368,0.000020168574],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029083076,0.0009801578,0.3365496,0.00128104,0.0013033113,0.0016192491,0.18480627,0.0025390952,0.04844112,0.017104976,0.029038565,0.3734283],"study_design_scores_gemma":[0.016570332,0.002429294,0.3511252,0.0024381476,0.00060638104,0.0016088067,0.07886568,0.1544994,0.005364943,0.0005220636,0.382688,0.0032817717],"about_ca_topic_score_codex":0.00064742204,"about_ca_topic_score_gemma":0.00030169694,"teacher_disagreement_score":0.3701465,"about_ca_system_score_codex":0.00016953009,"about_ca_system_score_gemma":0.00020017143,"threshold_uncertainty_score":0.9999648},"labels":[],"label_agreement":null},{"id":"W2207077672","doi":"10.1609/aaai.v29i1.9775","title":"Towards User-Adaptive Information Visualization","year":2015,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Human–computer interaction; Visualization; Eye tracking; Adaptation (eye); Information visualization; Task (project management); User modeling; Gaze; User satisfaction; User interface; User interface design; Data visualization; User experience design; Artificial intelligence; Engineering","score_opus":0.12215215806384717,"score_gpt":0.33792099899056927,"score_spread":0.2157688409267221,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2207077672","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006709067,0.0000063940206,0.9566517,0.0023153492,0.0005545551,0.00033413456,0.00001144903,0.00016335299,0.033253994],"genre_scores_gemma":[0.99513227,0.000014564376,0.004042749,0.0005718076,0.00004042374,0.000009022696,0.000003999144,0.0000059340164,0.00017923847],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984539,0.000017031909,0.00048249288,0.00021644954,0.00063313433,0.00019700137],"domain_scores_gemma":[0.99775755,0.000020095275,0.00039081826,0.00022500042,0.0014922123,0.000114296374],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005054731,0.00014981124,0.00015980627,0.00016077675,0.00010433514,0.0004155361,0.00143889,0.000067435205,0.000023218267],"category_scores_gemma":[0.00062594627,0.000113493144,0.00005794935,0.0009507262,0.000120525365,0.0019109725,0.00035339012,0.00011751416,0.00019228598],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001816932,0.000054160584,0.000054905515,0.000009757671,0.0000058199566,6.0033564e-8,0.0015298951,0.000089502544,0.00032818603,0.9706032,0.001079093,0.026227253],"study_design_scores_gemma":[0.00005563045,0.00028522944,0.00009777178,0.00011827523,0.00001208181,0.0000028777908,0.0017645351,0.5950058,0.1973451,0.20188926,0.0031637882,0.000259645],"about_ca_topic_score_codex":0.000035431673,"about_ca_topic_score_gemma":0.000003918887,"teacher_disagreement_score":0.98842317,"about_ca_system_score_codex":0.00005797482,"about_ca_system_score_gemma":0.00019573492,"threshold_uncertainty_score":0.46281162},"labels":[],"label_agreement":null},{"id":"W2216277247","doi":"10.1016/j.plrev.2015.10.005","title":"The importance of accurately modelling human interactions","year":2015,"lang":"en","type":"review","venue":"Physics of Life Reviews","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science","score_opus":0.4648620256987295,"score_gpt":0.4905606230033225,"score_spread":0.025698597304593007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2216277247","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[4.3445155e-8,0.78787583,0.21099961,0.000015556154,0.00013306378,0.00030870034,0.000021984131,0.000013587703,0.0006316225],"genre_scores_gemma":[0.000001751999,0.99681956,0.0027268324,0.0000363724,0.00015357762,0.000027530226,0.000068937276,0.000016559485,0.00014887047],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99752176,0.00024591017,0.001526028,0.00027341902,0.00028319645,0.00014970342],"domain_scores_gemma":[0.9957526,0.00017482576,0.0024502291,0.0012676101,0.00026499026,0.00008980006],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00094605546,0.00024916278,0.0016540394,0.000047723024,0.00009218953,0.00008425539,0.0017373248,0.000044239143,0.0000029955434],"category_scores_gemma":[0.0001250368,0.0001532147,0.00054264895,0.0006980437,0.00006342248,0.0003887024,0.00032453536,0.00020478328,0.000042831354],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.5747763e-7,0.000055495344,0.0000011988587,0.0063480735,0.00006336762,1.7452075e-7,0.0000443248,0.00005886725,8.978301e-8,0.12572196,0.007067094,0.8606392],"study_design_scores_gemma":[0.00002634531,0.000009937323,1.6910993e-8,0.0044210954,0.00013087573,7.461215e-7,0.00000265983,0.007625024,4.4695932e-7,0.0026148383,0.9850315,0.00013654953],"about_ca_topic_score_codex":0.0000041850785,"about_ca_topic_score_gemma":0.0000026301964,"teacher_disagreement_score":0.97796434,"about_ca_system_score_codex":0.000030505575,"about_ca_system_score_gemma":0.00031945755,"threshold_uncertainty_score":0.62479144},"labels":[],"label_agreement":null},{"id":"W2220644283","doi":"10.1299/jsmecmd.2012.25._f-4_","title":"F102 Implementation of Large Scale Visualization in AVS/Express","year":2012,"lang":"en","type":"article","venue":"Keisan Rikigaku Koenkai koen ronbunshu/Keisan Rikigaku Kouenkai kouen rombunshuu","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Cybernet Systems Corporation (Canada)","funders":"","keywords":"Visualization; Computer science; Scale (ratio); Computer graphics (images); Human–computer interaction; Data mining; Cartography; Geography","score_opus":0.017217373284240722,"score_gpt":0.3307440633212132,"score_spread":0.3135266900369725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2220644283","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8260091,0.001619238,0.15382491,0.0013138383,0.0030327754,0.0031315763,0.00075808226,0.0014308792,0.0088795815],"genre_scores_gemma":[0.9859192,0.0002909288,0.0086946245,0.0018764953,0.00059883745,0.00017678567,0.0011296283,0.00021865997,0.0010948548],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.98864794,0.0010434564,0.0031145292,0.0019170902,0.002281431,0.0029955641],"domain_scores_gemma":[0.9933727,0.0003345559,0.0015658087,0.0029637853,0.0006290776,0.0011340926],"candidate_categories":["metaepi_narrow"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.0030891323,0.0013581989,0.0017481991,0.0016818667,0.0005746221,0.00054924877,0.003473765,0.0006461487,0.0008265611],"category_scores_gemma":[0.0002104099,0.0014205405,0.00057874876,0.0037566258,0.0003567437,0.005609186,0.0014881982,0.0008056893,0.0004348181],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013233499,0.004844828,0.61612624,0.00078863587,0.00045001242,0.000064504675,0.03372444,0.0005451193,0.008890118,0.29509437,0.02998541,0.009353953],"study_design_scores_gemma":[0.019932117,0.001495268,0.5839323,0.0015042467,0.00075881986,0.00023291608,0.022014996,0.070973255,0.06590719,0.0059456965,0.21862073,0.008682482],"about_ca_topic_score_codex":0.0007170119,"about_ca_topic_score_gemma":0.0010625528,"teacher_disagreement_score":0.2891487,"about_ca_system_score_codex":0.0005487467,"about_ca_system_score_gemma":0.0004617353,"threshold_uncertainty_score":0.9999169},"labels":[],"label_agreement":null},{"id":"W2223264347","doi":"10.1162/leon_a_01229","title":"Beyond Data: Abstract Motionscapes as Affective Visualization","year":2016,"lang":"en","type":"article","venue":"Leonardo","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Affordance; Evocation; Computer science; Human–computer interaction; Set (abstract data type); Affect (linguistics); Visualization; Motion (physics); Modality (human–computer interaction); Space (punctuation); Cognitive science; Psychology; Artificial intelligence; Art; Communication","score_opus":0.027746597367698675,"score_gpt":0.3249954986971215,"score_spread":0.29724890132942283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2223264347","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014267555,0.000050702325,0.98635334,0.00436945,0.00031200497,0.000095436604,0.000069797024,0.00023663518,0.0070859],"genre_scores_gemma":[0.98886406,0.00016570884,0.0065452,0.0013527245,0.0002173765,0.0000071343734,0.0002196626,0.00001949652,0.0026086436],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989343,0.000043250675,0.00016667553,0.0004124009,0.00027245175,0.00017090412],"domain_scores_gemma":[0.99875176,0.00011042228,0.00008580775,0.0008780618,0.00009305983,0.000080867525],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00022964647,0.000104826075,0.00010024741,0.00009948831,0.00010705711,0.0001588419,0.0009804505,0.000047500354,0.00017756232],"category_scores_gemma":[0.0001908984,0.00007488857,0.000029190094,0.0003294234,0.000041596977,0.0016018405,0.0003573319,0.000034687626,0.00089872885],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001922267,0.00009040033,0.0007365206,0.0000070898545,0.000022376333,0.000008615942,0.00012038981,0.000011091754,0.0008904976,0.9005754,0.011718646,0.08581706],"study_design_scores_gemma":[0.0035227234,0.00050457567,0.0654056,0.00037782307,0.000105961946,0.00013130481,0.0006600978,0.1250856,0.017952986,0.15429248,0.62979114,0.0021697069],"about_ca_topic_score_codex":0.000011465947,"about_ca_topic_score_gemma":0.000013779016,"teacher_disagreement_score":0.9874373,"about_ca_system_score_codex":0.000028609053,"about_ca_system_score_gemma":0.00005956942,"threshold_uncertainty_score":0.9998792},"labels":[],"label_agreement":null},{"id":"W2223846508","doi":"10.5281/zenodo.44215","title":"gapminder: v0.2.0","year":2015,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science","score_opus":0.0848012090833918,"score_gpt":0.2922256862018373,"score_spread":0.20742447711844553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2223846508","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007543741,0.00004999068,0.73138463,0.002418772,0.0002089924,0.00018360368,0.000055955836,0.0016218671,0.26332185],"genre_scores_gemma":[0.9671099,0.00008961393,0.0133389635,0.0026983584,0.00047621713,3.922565e-8,0.002859182,0.0019454795,0.01148224],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99862367,0.00018540998,0.00017642412,0.00032966147,0.00042553068,0.00025932142],"domain_scores_gemma":[0.9984409,0.000010232375,0.00006741282,0.0005894354,0.00061046483,0.00028151076],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00066443416,0.00009372762,0.000091423004,0.00017807928,0.00080078497,0.0013789656,0.0018377288,0.000038239632,0.0015519463],"category_scores_gemma":[0.00054550637,0.00009638956,0.000029859488,0.0007309896,0.0000700328,0.0005928404,0.0015894837,0.00012402303,0.013354038],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006357282,0.00010572378,0.0000035855926,0.000010969609,0.000015387575,0.000014199904,0.0011393984,0.000073513314,0.0002150737,0.15380053,0.75715077,0.08746449],"study_design_scores_gemma":[0.00031942307,0.0000983401,0.000051248873,0.000006447865,0.0000031430518,0.00006305173,0.00013350935,0.01455819,0.00020142045,0.0010124625,0.98343015,0.00012263119],"about_ca_topic_score_codex":0.0000048141196,"about_ca_topic_score_gemma":9.589797e-8,"teacher_disagreement_score":0.96635556,"about_ca_system_score_codex":0.00007764434,"about_ca_system_score_gemma":0.000007050591,"threshold_uncertainty_score":0.9996577},"labels":[],"label_agreement":null},{"id":"W2225624130","doi":"","title":"Selecting Media for Explaining Algorithms","year":2004,"lang":"en","type":"article","venue":"EdMedia: World Conference on Educational Media and Technology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Acadia University","funders":"","keywords":"Algorithm; Computer science; Artificial intelligence","score_opus":0.049025296812979284,"score_gpt":0.31729133875621496,"score_spread":0.26826604194323567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2225624130","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020498368,0.00025162805,0.2747054,0.7173935,0.003353378,0.00037457724,0.000038902035,0.00049163034,0.0013411095],"genre_scores_gemma":[0.93021977,0.0001050187,0.06766864,0.000865566,0.00055270665,0.00016986715,0.00013764598,0.0000154627,0.00026532274],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986346,0.000016953452,0.00026958456,0.00048433372,0.00024771932,0.00034682098],"domain_scores_gemma":[0.9984826,0.000637811,0.00012587766,0.00031240302,0.0002885357,0.00015277804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020721156,0.00017713332,0.00021112354,0.0007349642,0.00020985186,0.000115637595,0.00062144536,0.000115548355,0.000052010368],"category_scores_gemma":[0.001050076,0.00017267383,0.000027866794,0.0011221851,0.00017784922,0.00025545512,0.000121416546,0.00023981417,0.000034605004],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000017335229,0.00007796512,0.00046311875,0.000007961874,0.0000106274365,0.0000016183326,0.00077060604,0.000003350427,0.00011204544,0.9884753,0.0007053336,0.009370298],"study_design_scores_gemma":[0.00057513674,0.00006754568,0.00049272855,0.0000749513,0.000008724787,0.000017115435,0.00011427224,0.0038446204,0.002209687,0.99131554,0.0010516682,0.00022798545],"about_ca_topic_score_codex":0.000005072372,"about_ca_topic_score_gemma":0.00012890888,"teacher_disagreement_score":0.9281699,"about_ca_system_score_codex":0.000046079673,"about_ca_system_score_gemma":0.00058928883,"threshold_uncertainty_score":0.70414346},"labels":[],"label_agreement":null},{"id":"W2229031938","doi":"10.14288/1.0076352","title":"Applying the chronographical approach for modelling to different types of projects","year":2015,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Schedule; Computer science; Planner; Graphical user interface; Representation (politics); Dimension (graph theory); Graphical model; Human–computer interaction; Data mining; Artificial intelligence; Programming language; Mathematics","score_opus":0.0453707630644506,"score_gpt":0.22484094929935863,"score_spread":0.17947018623490804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2229031938","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09910619,0.000028708391,0.90002346,0.000059151054,0.00003562804,0.0004372172,0.000028676928,0.00002732713,0.00025364794],"genre_scores_gemma":[0.97107136,0.000010729996,0.028720425,0.000046947145,0.000012895945,0.000003886692,0.000013366475,0.0000039315755,0.00011645434],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993782,0.000025971223,0.00007989658,0.00020418363,0.00019339203,0.00011836439],"domain_scores_gemma":[0.9994005,0.00002498573,0.00006585944,0.0002437485,0.00018087866,0.000084059175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018141528,0.000025196425,0.00013573829,0.000039658808,0.00009843384,0.00008490985,0.00060544454,0.000033300785,0.0000011396503],"category_scores_gemma":[0.000016381111,0.000058619848,0.000061266444,0.00034781013,0.00007220711,0.00017606831,0.00020211271,0.00003994941,8.791481e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003408067,0.0010260162,0.006825651,0.00049889466,0.00019399935,0.000011518476,0.0039110044,0.055497307,0.00017544413,0.003368621,0.022066247,0.9063912],"study_design_scores_gemma":[0.00045518103,0.00007761485,0.014541704,0.000039266008,0.000018758245,0.0000040571267,0.0010466421,0.9822925,0.0000025715965,0.00051165523,0.00090722746,0.000102843864],"about_ca_topic_score_codex":0.0029242611,"about_ca_topic_score_gemma":0.0033648328,"teacher_disagreement_score":0.9267952,"about_ca_system_score_codex":0.000017146323,"about_ca_system_score_gemma":0.000052570867,"threshold_uncertainty_score":0.44206277},"labels":[],"label_agreement":null},{"id":"W2232530087","doi":"10.1038/nmeth.3699","title":"Pathways","year":2015,"lang":"en","type":"article","venue":"Nature Methods","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"","keywords":"Computational biology; Chemistry; Biology; Cell biology","score_opus":0.09044882062203148,"score_gpt":0.4474333865705118,"score_spread":0.3569845659484803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2232530087","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000036380396,0.00038517022,0.97873294,0.00054041867,0.00074907887,0.000024707158,0.0000017390796,0.00014733509,0.019382214],"genre_scores_gemma":[0.0068285875,0.0000052745013,0.98974544,0.0025957702,0.00008843658,0.0000010898857,0.000006083828,0.0000042941783,0.0007250127],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99924636,0.00020059002,0.0000884913,0.00017194073,0.00018344268,0.0001091907],"domain_scores_gemma":[0.9992652,0.00006639843,0.000033968245,0.00040353872,0.00011228973,0.000118622505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011307553,0.00005953219,0.000081060214,0.000060352417,0.000026738979,0.000096142096,0.0005828155,0.0001145404,0.000008257893],"category_scores_gemma":[0.00056951394,0.000047938738,0.000027408973,0.000437277,0.000012089121,0.00022989487,0.00016805441,0.00020487557,0.000049300248],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.228202e-7,0.00002337434,0.0000589988,0.0000028644702,0.000005661155,0.000006594209,0.00035899068,0.000012944323,0.00046740207,0.8163789,0.035616618,0.14706683],"study_design_scores_gemma":[0.00017978989,0.000024726978,0.00010445938,0.0000036891236,0.0000032568187,0.000008803349,0.000024148865,0.08155369,0.00656081,0.04221455,0.8692056,0.00011645283],"about_ca_topic_score_codex":0.0000011140373,"about_ca_topic_score_gemma":4.1709765e-7,"teacher_disagreement_score":0.833589,"about_ca_system_score_codex":0.000016536223,"about_ca_system_score_gemma":0.00005731707,"threshold_uncertainty_score":0.19548851},"labels":[],"label_agreement":null},{"id":"W2234779292","doi":"10.1145/2847557.2847560","title":"Machine learning meets visualization for extracting insights from text data","year":2016,"lang":"en","type":"article","venue":"AI Matters","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; National Aeronautics and Space Administration; Boeing","keywords":"Computer science; Visual analytics; Visualization; Process (computing); Data science; Analytics; Text mining; Data visualization; Biomedical text mining; Path (computing); Natural language processing; Information retrieval; Artificial intelligence","score_opus":0.04219726391390411,"score_gpt":0.32903505059119653,"score_spread":0.28683778667729243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2234779292","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00025401957,0.000047353984,0.9776817,0.02145883,0.0002171261,0.00007953647,0.000058912166,0.00014753467,0.000054995897],"genre_scores_gemma":[0.89353657,0.00012204976,0.03716633,0.064921066,0.00032837124,0.0000142731515,0.0019597833,0.000064049826,0.0018875336],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99903756,0.00005570637,0.00019958355,0.00039125892,0.00016763616,0.0001482252],"domain_scores_gemma":[0.9989316,0.0002409081,0.00012824348,0.0005892454,0.000051334402,0.000058656427],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001391638,0.000098182114,0.00010306173,0.00007948055,0.00013317865,0.00020790832,0.0008563414,0.0000324362,0.000052782983],"category_scores_gemma":[0.00012578456,0.00007186699,0.000022113658,0.00015958423,0.000017971432,0.001463246,0.00035257553,0.00003999878,0.000110582136],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032478223,0.00026895254,0.0039845756,0.00008571968,0.00020842467,0.000021276759,0.0022508746,0.00025617666,0.05644667,0.28673357,0.3898373,0.259874],"study_design_scores_gemma":[0.00039201925,0.000018842942,0.00015942748,0.00005401799,0.000010824559,0.0000012574046,0.000020965466,0.46020317,0.0012067031,0.001264957,0.53651285,0.00015498791],"about_ca_topic_score_codex":0.00003923555,"about_ca_topic_score_gemma":0.000019776458,"teacher_disagreement_score":0.94051534,"about_ca_system_score_codex":0.000019497658,"about_ca_system_score_gemma":0.00002123401,"threshold_uncertainty_score":0.29306507},"labels":[],"label_agreement":null},{"id":"W2237259080","doi":"","title":"User-adaptive visualizations: can gaze data tell us when a user needs them?","year":2011,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Human–computer interaction; Visualization; Gaze; Eye tracking; Focus (optics); Task (project management); Perception; Data visualization; Information visualization; User interface; Cognition; Interface (matter); Multimedia; Artificial intelligence; Psychology","score_opus":0.1376752557995135,"score_gpt":0.31330304428053335,"score_spread":0.17562778848101984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2237259080","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00044377067,0.00002597183,0.97092366,0.00021445495,0.00017482565,0.00014454928,0.00008423822,0.00030779553,0.027680723],"genre_scores_gemma":[0.4699982,0.00021711053,0.4316138,0.012734233,0.00028147394,0.000026797898,0.0010468955,0.00010283449,0.08397862],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998567,0.00007971111,0.00029842823,0.00045480925,0.00031435624,0.0002856871],"domain_scores_gemma":[0.9976767,0.00004638897,0.00010659169,0.0018440288,0.00016444949,0.00016186989],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002582823,0.00017713409,0.00016481504,0.00017063884,0.0001303164,0.0002710192,0.0027061799,0.0000627463,0.0010348472],"category_scores_gemma":[0.000075251,0.00014904514,0.000034401608,0.00080244645,0.000063278385,0.0013837883,0.0013179297,0.00008013785,0.0004293979],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000030187102,0.00018842705,0.006693849,0.000006735499,0.000038645067,0.0000072635053,0.002304597,0.0000070226056,0.000015760741,0.9364011,0.053162813,0.0011707462],"study_design_scores_gemma":[0.0008607135,0.00016472019,0.0034103368,0.00005331211,0.00007889525,0.000029889467,0.0012643514,0.52523327,0.0016654013,0.009478255,0.45678326,0.0009776065],"about_ca_topic_score_codex":0.00056652026,"about_ca_topic_score_gemma":0.00028117423,"teacher_disagreement_score":0.92692286,"about_ca_system_score_codex":0.000025073823,"about_ca_system_score_gemma":0.00013978824,"threshold_uncertainty_score":0.99987835},"labels":[],"label_agreement":null},{"id":"W2241722660","doi":"10.2139/ssrn.2200126","title":"Business Models and Audit Risk Assessment: An Investigation of Alternative Information Presentation Techniques","year":2013,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; University of Waterloo","funders":"","keywords":"Audit; Presentation (obstetrics); Risk assessment; Business; Actuarial science; Business risks; Risk analysis (engineering); Accounting; Computer science; Medicine; Computer security","score_opus":0.014181859854312525,"score_gpt":0.2959013280441125,"score_spread":0.2817194681898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2241722660","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08259098,0.000026834241,0.91661125,0.0004286554,0.000035234443,0.00012050049,0.0000034778366,0.000034844386,0.00014823306],"genre_scores_gemma":[0.98331416,0.0014278907,0.015031053,0.000093414645,0.000044213877,0.0000070870133,0.000042166073,0.000004387604,0.000035652283],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99893486,0.00010707014,0.0002768124,0.000094319475,0.0002518926,0.00033501792],"domain_scores_gemma":[0.9988502,0.000019500969,0.00042141104,0.00013605038,0.0005174008,0.00005541885],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007136572,0.000076350996,0.000087057844,0.00019062907,0.00010925387,0.00029039368,0.00028547778,0.000033697343,0.0000032117132],"category_scores_gemma":[0.000030602092,0.00006707221,0.000015570038,0.00030012638,0.00003593344,0.009194627,0.00005752871,0.0002978648,0.0000029617945],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000028503646,0.000034603236,0.003754673,0.00001567624,0.000051246163,1.24581e-7,0.001271764,0.0016780199,0.0006123836,0.86071485,0.0001435269,0.13172029],"study_design_scores_gemma":[0.0001659199,0.00009334748,0.004931524,0.0000120828445,0.000008074228,0.000016314754,0.00029628375,0.45452988,0.00046600966,0.5393828,0.000032021006,0.000065758635],"about_ca_topic_score_codex":0.00028524752,"about_ca_topic_score_gemma":0.000043614687,"teacher_disagreement_score":0.9015802,"about_ca_system_score_codex":0.00013002563,"about_ca_system_score_gemma":0.0005492552,"threshold_uncertainty_score":0.6665883},"labels":[],"label_agreement":null},{"id":"W2242704387","doi":"10.1007/978-3-642-36981-0_53","title":"Building Accountability for Decision-Making into Cognitive Systems","year":2013,"lang":"en","type":"book-chapter","venue":"Advances in intelligent systems and computing","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Accountability; Dashboard; Visual analytics; Cognition; Computer science; Analytics; Knowledge management; Management science; Human–computer interaction; Cognitive science; Data science; Process management; Artificial intelligence; Psychology; Visualization; Engineering; Political science","score_opus":0.02783588941760643,"score_gpt":0.35395951594719266,"score_spread":0.3261236265295862,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2242704387","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009124263,0.020178964,0.9668879,0.000008411059,0.0023797546,0.0010827526,0.000023773522,0.00010260113,0.0092446245],"genre_scores_gemma":[0.93008643,0.003161714,0.059671953,0.00020458428,0.0010147931,0.000109314315,0.000047130998,0.00012574668,0.0055783275],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970312,0.00004828015,0.0011776875,0.0009612869,0.00041022536,0.00037131622],"domain_scores_gemma":[0.99595207,0.002341783,0.00071739854,0.00045732022,0.00043123116,0.000100222016],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008875728,0.00043381122,0.00073573465,0.00031665587,0.0002512941,0.00081220095,0.00073549175,0.00022309249,0.000008029576],"category_scores_gemma":[0.0002860239,0.00040635906,0.00011319167,0.00012774197,0.00008840529,0.00077674753,0.00055338634,0.00026743294,0.000026076927],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000057222223,0.00001481912,0.000075629694,0.00065124815,0.000031747077,0.0000042623915,0.00033258784,0.00481939,7.0234603e-7,0.7598224,0.00008411683,0.23415734],"study_design_scores_gemma":[0.00015964429,0.00007690716,0.000006434935,0.012828356,0.000024637262,0.000027164942,0.00047449494,0.8370866,0.0000041601525,0.039059334,0.10962619,0.0006260576],"about_ca_topic_score_codex":0.000069193215,"about_ca_topic_score_gemma":0.000021555681,"teacher_disagreement_score":0.9299952,"about_ca_system_score_codex":0.00018488492,"about_ca_system_score_gemma":0.000060155493,"threshold_uncertainty_score":0.9998388},"labels":[],"label_agreement":null},{"id":"W2249976896","doi":"10.20380/gi2015.16","title":"Exploiting analysis history to support collaborative data analysis","year":2015,"lang":"en","type":"article","venue":"Canada Human-Computer Communications Society","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Dimension (graph theory); Computer science; Representation (politics); Perspective (graphical); Space (punctuation); Data science; Plan (archaeology); Data visualization; Visualization; Data mining; Theoretical computer science; Artificial intelligence; Mathematics; Geography","score_opus":0.18235724756287972,"score_gpt":0.36008103584912204,"score_spread":0.17772378828624233,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2249976896","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00028811028,0.00027572934,0.9934156,0.0032029494,0.0001847521,0.00016432047,0.00021751712,0.00016989585,0.0020811546],"genre_scores_gemma":[0.24293712,0.00007324743,0.7331674,0.01370441,0.0001481448,0.000042238178,0.0076694875,0.000031287258,0.0022266877],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974256,0.00026356525,0.00059396727,0.0007194597,0.0006580602,0.0003393452],"domain_scores_gemma":[0.99006355,0.00015001591,0.00028725734,0.008219759,0.0008000071,0.00047939707],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0009137458,0.00022481162,0.00047489762,0.0003263099,0.0004694488,0.00029235432,0.008496451,0.0000612555,0.000050855142],"category_scores_gemma":[0.000054939374,0.00025270876,0.00020510907,0.0059603564,0.00011741946,0.00079774956,0.0046056476,0.00020857713,0.000014962176],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.292825e-7,0.00010079729,0.0018310297,0.000005565166,0.002970883,0.000003909098,0.0061433986,0.0054429965,0.0000058707956,0.025724364,0.956562,0.0012086709],"study_design_scores_gemma":[0.00014762455,0.000018612358,0.0005926811,0.0000031389723,0.0006937241,6.178839e-7,0.0006297231,0.57837594,0.0000036789188,0.00005677148,0.41920844,0.0002690592],"about_ca_topic_score_codex":0.05735018,"about_ca_topic_score_gemma":0.39038023,"teacher_disagreement_score":0.57293296,"about_ca_system_score_codex":0.001353549,"about_ca_system_score_gemma":0.0026259725,"threshold_uncertainty_score":0.9999925},"labels":[],"label_agreement":null},{"id":"W2250190567","doi":"","title":"An investigation of issues and techniques in highly interactive computational visualization","year":2007,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Visualization; Computer science; Interactive visualization; Rendering (computer graphics); Information visualization; Set (abstract data type); Human–computer interaction; Creative visualization; Data visualization; Data science; Data mining; Computer graphics (images); Programming language","score_opus":0.019316600411755223,"score_gpt":0.3598329299493882,"score_spread":0.340516329537633,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2250190567","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08331401,0.0000079864185,0.91616505,0.00013249638,0.000018054994,0.00006070871,0.0000012464234,0.00007163025,0.00022880842],"genre_scores_gemma":[0.90753466,0.000008692462,0.092071235,0.00029984294,0.000010412879,7.8623003e-7,0.000045454777,0.000002729062,0.000026163889],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99940866,0.00003816633,0.00021763291,0.0001407118,0.00013251047,0.000062326195],"domain_scores_gemma":[0.9996168,0.000051969128,0.00007841244,0.00009719346,0.00011837969,0.000037271457],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035438823,0.000050110248,0.00007167829,0.00024706373,0.000018413704,0.00005213348,0.00013390761,0.000028174063,0.0000048432335],"category_scores_gemma":[0.00002096857,0.000048156897,0.000006012496,0.00038343968,0.00003868405,0.0008969408,0.00004251659,0.000026337746,0.000001031104],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000059087506,0.000080444115,0.045413274,0.000016684477,0.000004618243,0.0000017617508,0.0025161982,0.00034148348,0.0057626273,0.93500197,0.00019319766,0.010661841],"study_design_scores_gemma":[0.00020360982,0.00015011108,0.06688623,0.000045490753,0.0000022372096,0.0000032401347,0.00027761183,0.83098507,0.07351424,0.02758494,0.00020376546,0.0001434773],"about_ca_topic_score_codex":0.00007654652,"about_ca_topic_score_gemma":0.000040208386,"teacher_disagreement_score":0.907417,"about_ca_system_score_codex":0.000015249474,"about_ca_system_score_gemma":0.000019096859,"threshold_uncertainty_score":0.19637813},"labels":[],"label_agreement":null},{"id":"W2252678786","doi":"","title":"Supporting Research Literacy Using Topic Maps: Building a Mathematics Education Research Ontology","year":2013,"lang":"en","type":"article","venue":"E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Ontology; Computer science; Literacy; Mathematics education; Sociology; Data science; Pedagogy; Mathematics; Epistemology","score_opus":0.20685259206100154,"score_gpt":0.45905687208237805,"score_spread":0.2522042800213765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2252678786","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7995991,0.001836701,0.016315188,0.09036259,0.004951212,0.0044938666,0.000020416448,0.00057247706,0.08184843],"genre_scores_gemma":[0.93374646,0.00025996956,0.02066398,0.0011211421,0.000299414,0.00017338379,0.00004815811,0.000038029142,0.043649442],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9945773,0.0012757027,0.0008558063,0.0009509427,0.0013469863,0.0009932789],"domain_scores_gemma":[0.9964831,0.0004996298,0.0007374302,0.0007253595,0.0011854069,0.00036911306],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0030637132,0.0002882711,0.0003710599,0.00084994646,0.00081132853,0.0013501948,0.00078532984,0.00017455262,0.0003412515],"category_scores_gemma":[0.00042521604,0.00030123844,0.000041285406,0.0021078112,0.00017810617,0.0011881716,0.00037469878,0.0014821794,0.00014659678],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010213788,0.0006140865,0.047109317,0.00033526885,0.000011392158,0.0000036696931,0.002583823,0.000022415405,0.00049281796,0.8520593,0.0035615962,0.09319612],"study_design_scores_gemma":[0.0014817453,0.0012230037,0.20423837,0.004921299,0.000029519211,0.00006404764,0.01836721,0.11859947,0.00061031216,0.4604477,0.1880394,0.0019779275],"about_ca_topic_score_codex":0.0021789537,"about_ca_topic_score_gemma":0.00019518881,"teacher_disagreement_score":0.3916116,"about_ca_system_score_codex":0.00092847267,"about_ca_system_score_gemma":0.00219257,"threshold_uncertainty_score":0.999944},"labels":[],"label_agreement":null},{"id":"W2257719909","doi":"10.1260/1478-0771.8.4.461","title":"ViSA: A Parametric Design Modeling Method to Enhance Visual Sensitivity Control and Analysis","year":2010,"lang":"en","type":"article","venue":"International Journal of Architectural Computing","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Simon Fraser University","keywords":"Parametric statistics; Parametric design; Parametric model; Computer science; Sensitivity (control systems); Visualization; Key (lock); Control (management); Human–computer interaction; Control engineering; Simulation; Engineering; Artificial intelligence","score_opus":0.017657440599199846,"score_gpt":0.37092389563328787,"score_spread":0.35326645503408804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2257719909","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29309678,0.00000826643,0.70570433,0.00084184983,0.00027471242,0.000042945812,0.0000024676533,0.000019578369,0.000009075824],"genre_scores_gemma":[0.6131122,9.1794595e-7,0.3862673,0.00046403465,0.00014786763,1.4737618e-7,9.800259e-7,0.000003709721,0.0000028307786],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981768,0.00028932426,0.0005086188,0.0002507484,0.00058682554,0.00018765609],"domain_scores_gemma":[0.9977686,0.0009246779,0.00033847787,0.00013235185,0.0006570445,0.00017884154],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020460943,0.000135799,0.00029975557,0.0010593319,0.00009117687,0.0004005279,0.0006100031,0.00003603075,0.0000033262857],"category_scores_gemma":[0.00068645034,0.00011477298,0.00015081945,0.00091235695,0.000022228793,0.00028986513,0.00026452876,0.00036160962,0.0000025971847],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000427834,0.0000437201,0.0011291943,0.000002470434,0.0005208776,0.00006560171,0.00050365034,0.7895578,0.013531321,0.0012538085,0.000011068348,0.19333766],"study_design_scores_gemma":[0.00023286596,0.000074509655,0.0017578109,0.00001795535,0.00006437376,0.00036166172,0.000011913627,0.9952574,0.0015767596,0.00048730627,0.00003000483,0.000127452],"about_ca_topic_score_codex":0.000026831443,"about_ca_topic_score_gemma":0.000010922803,"teacher_disagreement_score":0.32001543,"about_ca_system_score_codex":0.00002899213,"about_ca_system_score_gemma":0.000060609887,"threshold_uncertainty_score":0.46803063},"labels":[],"label_agreement":null},{"id":"W2261029459","doi":"10.1108/oir-02-2015-0067","title":"Visual Twitter Analytics (Vista)","year":2016,"lang":"en","type":"article","venue":"Online Information Review","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Social media; Visual analytics; Analytics; Originality; Software; Event (particle physics); Visualization; Data science; Sentiment analysis; Focus (optics); World Wide Web; Social media analytics; Interactive visualization; Matching (statistics); Data visualization; Information retrieval; Data mining; Artificial intelligence; Qualitative research","score_opus":0.029739960048944337,"score_gpt":0.3414256730954154,"score_spread":0.311685713046471,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2261029459","genre_codex":"methods","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006133119,0.0007928387,0.98388386,0.012559187,0.00012196531,0.00013974124,0.00003614545,0.00014016632,0.0022647597],"genre_scores_gemma":[0.049117435,0.29783994,0.13029125,0.50327283,0.000903313,0.0000748999,0.0030996203,0.000068055175,0.015332696],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989236,0.00003485542,0.0005154282,0.00009838223,0.00028495103,0.00014275743],"domain_scores_gemma":[0.9990633,0.000036081092,0.00021988433,0.0003856283,0.00021134807,0.00008375469],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00028624362,0.0001026397,0.00017026564,0.00010022916,0.000042286625,0.00011308152,0.00046556824,0.000030703966,0.0002177063],"category_scores_gemma":[0.00020384723,0.00006287296,0.000068426365,0.00048298706,0.000020187872,0.0022745014,0.0001380825,0.000045857476,0.0013175117],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.247858e-7,0.000077027566,0.00022352989,0.0007617544,0.000021231284,0.0000016514225,0.00005931925,0.000004933821,0.000015162929,0.055744447,0.22049582,0.7225942],"study_design_scores_gemma":[0.00016996585,0.000021035055,0.00028002064,0.0008273764,0.000010265601,0.0000066708444,0.0000046739206,0.016538192,0.00002346594,0.00013132583,0.9818578,0.00012923357],"about_ca_topic_score_codex":8.006655e-7,"about_ca_topic_score_gemma":6.8496524e-7,"teacher_disagreement_score":0.85359263,"about_ca_system_score_codex":0.00002803495,"about_ca_system_score_gemma":0.00006422795,"threshold_uncertainty_score":0.9994601},"labels":[],"label_agreement":null},{"id":"W2274780007","doi":"10.1007/s00371-015-1186-8","title":"EnergyViz: an interactive system for visualization of energy systems","year":2015,"lang":"en","type":"article","venue":"The Visual Computer","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Energy Research Institute; University of Calgary","funders":"Canada School of Energy and Environment","keywords":"Computer science; Visualization; Energy flow; Animation; Human–computer interaction; Interactive visualization; Data flow diagram; Energy (signal processing); Information visualization; Data visualization; Diagram; Representation (politics); Data mining; Computer graphics (images); Database","score_opus":0.042098739760155046,"score_gpt":0.3324936358029506,"score_spread":0.29039489604279556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2274780007","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0021179758,0.000045180626,0.9959688,0.000044730175,0.0012138194,0.0001424432,0.000010535354,0.00018013055,0.0002763745],"genre_scores_gemma":[0.9953538,0.000002585747,0.0036956088,0.0002445713,0.0004116258,0.000021288537,0.000088702276,0.000018464612,0.00016333653],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99853086,0.00027392534,0.00038393095,0.0002910706,0.00032988473,0.0001903097],"domain_scores_gemma":[0.99845725,0.00013300862,0.00026715614,0.00047876977,0.00053638127,0.0001274294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005558526,0.00014954871,0.00023797915,0.00016255012,0.00008824384,0.0002518861,0.0008852713,0.00005399261,8.550217e-7],"category_scores_gemma":[0.000020987756,0.000106067164,0.00006201536,0.0004763565,0.00004142302,0.0006269739,0.00025944432,0.000035275614,0.0000069431976],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000332485,0.00017931132,0.00004658278,0.00006351132,0.00005976025,0.0000016962418,0.0011606291,0.01084591,0.0001214937,0.97807807,0.0041834386,0.00522637],"study_design_scores_gemma":[0.00042386347,0.00044335413,0.000019897136,0.000054031483,0.000014296779,0.000012556761,0.00023138005,0.987783,0.0014477341,0.00028700643,0.009144058,0.00013879701],"about_ca_topic_score_codex":0.000094965726,"about_ca_topic_score_gemma":0.000005758121,"teacher_disagreement_score":0.9932358,"about_ca_system_score_codex":0.000065923734,"about_ca_system_score_gemma":0.00008687009,"threshold_uncertainty_score":0.43252936},"labels":[],"label_agreement":null},{"id":"W2275137739","doi":"","title":"Summative overview of the ATUAV project: Advanced Tools for User-Adaptive Information Visualization","year":2014,"lang":"en","type":"article","venue":"International Conference on Human-Computer Interaction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Summative assessment; Computer science; Visualization; Information visualization; Human–computer interaction; Software engineering; Multimedia; Formative assessment; Data mining; Mathematics education","score_opus":0.18181612365739622,"score_gpt":0.4268710507768834,"score_spread":0.2450549271194872,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2275137739","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002818176,0.0000020290374,0.9888562,0.0006454711,0.0017200025,0.000531167,0.00005014728,0.0000856408,0.005291158],"genre_scores_gemma":[0.98827165,0.00001800143,0.009350847,0.0014361822,0.00019952154,0.000079141966,0.00033040004,0.0000120336845,0.0003022061],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983826,0.00013365579,0.00056682155,0.00028401,0.00048422784,0.00014864706],"domain_scores_gemma":[0.9976524,0.00018591086,0.000686763,0.00038189546,0.0010648419,0.00002817678],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028465624,0.00018518498,0.00019503308,0.00026664685,0.0001523962,0.000551925,0.0010153276,0.000065959495,0.000039146566],"category_scores_gemma":[0.00018211265,0.00014951781,0.00013268828,0.00027090058,0.000043949825,0.0038819828,0.00021660677,0.00012764777,0.000027802223],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032830005,0.00008974496,0.000025631005,0.000028035882,0.00003883361,6.450954e-8,0.00077300845,0.0009132263,0.00033934385,0.94940406,0.0019501493,0.046405066],"study_design_scores_gemma":[0.0007789346,0.00039519183,0.00099295,0.0003977595,0.000012568895,0.000003360807,0.00018931588,0.9293876,0.004616552,0.0063850433,0.056610618,0.00023005909],"about_ca_topic_score_codex":0.000020628388,"about_ca_topic_score_gemma":0.000020064943,"teacher_disagreement_score":0.9854535,"about_ca_system_score_codex":0.00012557651,"about_ca_system_score_gemma":0.000071725684,"threshold_uncertainty_score":0.60971594},"labels":[],"label_agreement":null},{"id":"W2279979045","doi":"","title":"A geovisual analytics approach to spatial and visual feature organization and exploration","year":2013,"lang":"en","type":"dissertation","venue":"Memorial University Research Repository (Memorial University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Memorial University of Newfoundland; Strong","keywords":"Scrolling; Sonar; Computer science; Zoom; Cluster analysis; Field (mathematics); Feature (linguistics); Geovisualization; Spatial analysis; Geography; Cartography; Artificial intelligence; Computer vision; Visualization; Data mining; Information visualization; Remote sensing; Engineering","score_opus":0.028307746542493933,"score_gpt":0.2793699306010849,"score_spread":0.25106218405859093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2279979045","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.37442508,0.00013430245,0.52083856,0.0008570101,0.018079903,0.005485261,0.00017855846,0.0012329338,0.07876839],"genre_scores_gemma":[0.57863885,0.0013008685,0.00984688,0.00010209449,0.011233384,0.000003379398,0.005438557,0.00023714539,0.39319882],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99584943,0.0007597895,0.0002630583,0.001318188,0.0012347578,0.00057476864],"domain_scores_gemma":[0.99659544,0.00017296008,0.0002500542,0.00053122453,0.0017879107,0.0006624212],"candidate_categories":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00051435136,0.00043184374,0.0005286009,0.0020696968,0.0015115995,0.0011414614,0.0012637337,0.0006692569,0.000012698743],"category_scores_gemma":[0.0003218578,0.0005260459,0.00008650026,0.0034410018,0.00018920696,0.0023042727,0.0010189086,0.0008022996,0.00003464151],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008895342,0.004362531,0.002489545,0.0031415306,0.0026146623,0.004028472,0.040557034,0.0010033277,0.04450682,0.6430624,0.20291917,0.042419184],"study_design_scores_gemma":[0.019017575,0.0060286005,0.005705284,0.0009455107,0.0018467329,0.00023470109,0.07034809,0.26995406,0.024080819,0.0010621557,0.5926439,0.00813256],"about_ca_topic_score_codex":0.0009180425,"about_ca_topic_score_gemma":0.00018848179,"teacher_disagreement_score":0.64200026,"about_ca_system_score_codex":0.00053766347,"about_ca_system_score_gemma":0.0009139973,"threshold_uncertainty_score":0.99989545},"labels":[],"label_agreement":null},{"id":"W2284526201","doi":"10.1680/jmapl.15.00039","title":"A chronographic protocol for modelling construction projects","year":2016,"lang":"en","type":"article","venue":"Proceedings of the Institution of Civil Engineers - Management Procurement and Law","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Computer science; Protocol (science); Graphics; Visualization; Process (computing); Schedule; Planner; Set (abstract data type); Scheduling (production processes); Table (database); Statistical graphics; Computer graphics; Human–computer interaction; Data mining; Software engineering; Information retrieval; Artificial intelligence; Programming language; Computer graphics (images); Engineering","score_opus":0.027383433100267446,"score_gpt":0.25586008109972197,"score_spread":0.22847664799945452,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2284526201","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00032539203,0.000007425806,0.9647833,0.00047949373,0.00008789964,0.02588576,0.000003771314,0.00007222606,0.008354705],"genre_scores_gemma":[0.9225708,0.000040814863,0.05426256,0.000108109765,0.000049517515,0.022674654,0.0000014906909,0.00001356546,0.0002784536],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991063,0.0000024930941,0.00028147397,0.0002073047,0.00026703055,0.00013539396],"domain_scores_gemma":[0.99942344,0.0000073200495,0.00023097108,0.00010807134,0.0002007177,0.000029463718],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002782394,0.00011241446,0.00012012463,0.00014035094,0.00010144076,0.00005089283,0.0003547956,0.000030809657,0.0000021240683],"category_scores_gemma":[0.0000121564335,0.00006948492,0.00005806845,0.0003173426,0.00016132009,0.00072757236,0.00014066792,0.000026966754,1.9994866e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015139153,0.00004802082,0.00011991512,0.00091542414,0.000041641353,2.4306425e-8,0.000073136376,0.0003657933,0.0005422335,0.9960485,0.0003353963,0.0014947864],"study_design_scores_gemma":[0.011821104,0.00081634574,0.00018516886,0.0052475296,0.00029426216,0.0000106493735,0.00044529614,0.43040872,0.11757864,0.07723019,0.35484922,0.0011128932],"about_ca_topic_score_codex":0.0000022417566,"about_ca_topic_score_gemma":0.0000021479204,"teacher_disagreement_score":0.92224544,"about_ca_system_score_codex":0.000025403247,"about_ca_system_score_gemma":0.000017353032,"threshold_uncertainty_score":0.28335127},"labels":[],"label_agreement":null},{"id":"W2285348533","doi":"10.16995/dm.52","title":"Reading: Exploration of a Large Database of French Notarial Acts with Social Network Methods","year":2013,"lang":"en","type":"article","venue":"Digital Medievalist","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Relational database; Consistency (knowledge bases); Set (abstract data type); Information retrieval; DECIPHER; Relational model; Relation (database); Variety (cybernetics); Data mining; Visualization; Data science; Artificial intelligence; Programming language","score_opus":0.04974956432205806,"score_gpt":0.3537140026639678,"score_spread":0.3039644383419097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2285348533","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015013845,0.00001113761,0.992558,0.00028844323,0.00022295894,0.0001427186,0.00012074671,0.0000422695,0.00511234],"genre_scores_gemma":[0.8935086,0.000008214884,0.10471935,0.00023379052,0.00037184617,0.000011990609,0.000807637,0.000017001654,0.00032154674],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99888176,0.00006484095,0.0003084747,0.00020518254,0.0003462385,0.00019352284],"domain_scores_gemma":[0.9990082,0.000109893976,0.00023957914,0.00031500426,0.00025086277,0.00007650758],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003375097,0.00010389522,0.0002140001,0.000060529335,0.000052495023,0.00017443145,0.00040985248,0.000039122384,0.000025858271],"category_scores_gemma":[0.0002483509,0.00008416967,0.000039427978,0.00049762335,0.00007948788,0.0026589863,0.00020194765,0.000056228564,0.000013540585],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005061126,0.000854213,0.0022525245,0.0002783733,0.00019607614,0.0000107905125,0.0067384527,0.00016283423,0.002304194,0.88908064,0.05844068,0.03963058],"study_design_scores_gemma":[0.010124069,0.0022897616,0.0076283403,0.0012379622,0.0003196781,0.000027936541,0.0025395805,0.629505,0.03723509,0.07615966,0.23002802,0.0029048955],"about_ca_topic_score_codex":0.00003672004,"about_ca_topic_score_gemma":0.000010953761,"teacher_disagreement_score":0.89200723,"about_ca_system_score_codex":0.00001234052,"about_ca_system_score_gemma":0.000072189185,"threshold_uncertainty_score":0.34323394},"labels":[],"label_agreement":null},{"id":"W2286218711","doi":"10.11575/prism/31050","title":"Visualizing highly multidimensional time varying Microseismic Events","year":2012,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; Alberta Innovates - Technology Futures; ConocoPhillips","keywords":"Microseism; Computer science; Visualization; Interactive visual analysis; Rendering (computer graphics); Visual analytics; Data visualization; Data mining; Set (abstract data type); Domain (mathematical analysis); Data science; Filter (signal processing); Outlier; Process (computing); Interactive visualization; Anomaly detection; Data set; Curse of dimensionality; Machine learning; Artificial intelligence; Computer vision; Engineering","score_opus":0.023307040798653134,"score_gpt":0.3019470958313597,"score_spread":0.27864005503270656,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2286218711","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02707909,0.000096729294,0.96761024,0.0004433973,0.000481503,0.00008501786,0.000005732079,0.0003466357,0.003851671],"genre_scores_gemma":[0.86505246,0.0000106794305,0.12257979,0.0043518567,0.00015633459,0.000002688576,0.00005711976,0.000017305276,0.0077717532],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990188,0.000045166686,0.00018788918,0.00019320607,0.00023855755,0.00031639673],"domain_scores_gemma":[0.99940807,0.000050238654,0.000057003064,0.0002860412,0.000046258807,0.00015240052],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00026640855,0.000105668594,0.000102800244,0.00009129611,0.00012416199,0.000056014782,0.0003568374,0.00003655341,0.00015747003],"category_scores_gemma":[0.000025191357,0.000092867995,0.000045227953,0.00026439285,0.0000129429,0.0009642003,0.00031923468,0.000052374893,0.002174521],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008894773,0.0012369686,0.013369587,0.000043643286,0.00012467874,0.000011249171,0.0019742472,0.00027430608,0.18114458,0.707662,0.077956125,0.016193708],"study_design_scores_gemma":[0.0008082908,0.000034682573,0.0029464173,0.00004641646,0.000016154381,0.000040860927,0.0000194104,0.80876905,0.03588366,0.0005414787,0.15028828,0.0006053027],"about_ca_topic_score_codex":0.00001220949,"about_ca_topic_score_gemma":1.4323814e-7,"teacher_disagreement_score":0.8450304,"about_ca_system_score_codex":0.000026979975,"about_ca_system_score_gemma":0.00002605977,"threshold_uncertainty_score":0.9986024},"labels":[],"label_agreement":null},{"id":"W229098299","doi":"","title":"Visual Analytics in Public Safety: Example Capabilities for Example Government Agencies","year":2011,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Visual analytics; Analytics; Government (linguistics); Agency (philosophy); Intelligence analysis; Adaptation (eye); Business; Data science; Computer science; Public relations; Visualization; Computer security; Political science; Psychology; Sociology; Artificial intelligence","score_opus":0.12268898738577111,"score_gpt":0.2936081732553018,"score_spread":0.1709191858695307,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W229098299","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0058694044,0.000016200362,0.9784361,0.00020144536,0.00014440152,0.0002167847,0.000028977704,0.00012056426,0.014966114],"genre_scores_gemma":[0.93935615,0.000035737794,0.05479758,0.0009734599,0.00004265604,0.00003249226,0.0000397069,0.000015984697,0.0047062584],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984602,0.000045868946,0.0003840171,0.0003793572,0.00037162722,0.00035893495],"domain_scores_gemma":[0.99907225,0.00015606011,0.000081300466,0.00048720813,0.00008973909,0.0001134579],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005703991,0.00014102522,0.00018956015,0.00010204863,0.00010213813,0.00017951957,0.0006858324,0.000047687845,0.0003069876],"category_scores_gemma":[0.0001468981,0.0001261488,0.000065089494,0.0004568124,0.00006224684,0.0007173754,0.00028591952,0.000050477727,0.000024427869],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000056585245,0.00018102006,0.004095598,0.00002469881,0.000018965728,0.0000020012944,0.0027113701,0.000014096667,0.00003644077,0.9860012,0.0025346456,0.004374323],"study_design_scores_gemma":[0.0013406717,0.00046342198,0.010798349,0.000022714683,0.000022296806,0.000005567943,0.007496365,0.6829448,0.0035997971,0.025148066,0.26731756,0.00084042107],"about_ca_topic_score_codex":0.0008117024,"about_ca_topic_score_gemma":0.0011398139,"teacher_disagreement_score":0.9608531,"about_ca_system_score_codex":0.00017756724,"about_ca_system_score_gemma":0.00011597956,"threshold_uncertainty_score":0.5144199},"labels":[],"label_agreement":null},{"id":"W2291242049","doi":"10.1145/2856767.2856782","title":"MultiConVis","year":2016,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Set (abstract data type); World Wide Web; Conversation; Thread (computing); Information retrieval; Visual analytics; Interface (matter); User interface; Data science; Visualization; Human–computer interaction; Artificial intelligence","score_opus":0.023553548544749375,"score_gpt":0.292693289499394,"score_spread":0.2691397409546446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2291242049","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00017963791,0.0000017011192,0.98608375,0.002234326,0.00005019656,0.000008664053,5.568832e-7,0.000098060635,0.011343119],"genre_scores_gemma":[0.9122808,0.000015758269,0.054899447,0.0027221055,0.000028710372,9.967721e-7,6.5837634e-7,0.000002873522,0.030048674],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.999773,0.000005743497,0.00004174104,0.00007347703,0.000052596275,0.00005341069],"domain_scores_gemma":[0.9997357,0.000020101386,0.000008272445,0.00019031441,0.000016291417,0.000029322491],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003587819,0.000020217643,0.000021109507,0.00001875621,0.000013750974,0.00003205944,0.00024539093,0.0000067656297,0.00018420705],"category_scores_gemma":[0.000022325996,0.000010344106,0.000009385382,0.00006632595,0.000008097659,0.00022694588,0.000070660695,0.0000044555986,0.0007764018],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.108193e-8,0.000009353719,0.00039788723,3.6841226e-7,0.0000013927327,7.98273e-7,0.000015580645,1.3579061e-7,0.00091685925,0.8996176,0.010899299,0.08814064],"study_design_scores_gemma":[0.0007855046,0.00003665167,0.0027968371,0.000016489987,0.0000022178876,0.0000057881803,0.000012058667,0.12403978,0.027159588,0.010852375,0.83402497,0.00026777165],"about_ca_topic_score_codex":0.0000015102524,"about_ca_topic_score_gemma":9.472018e-7,"teacher_disagreement_score":0.9311843,"about_ca_system_score_codex":0.000003546572,"about_ca_system_score_gemma":0.0000065000672,"threshold_uncertainty_score":0.9979333},"labels":[],"label_agreement":null},{"id":"W2292406619","doi":"10.11575/prism/31497","title":"Towards Supporting Interactive Sketch-Based Visualizations","year":2013,"lang":"en","type":"article","venue":"PRISM (University of Calgary)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Sketch; Computer science; Computer graphics (images); Human–computer interaction","score_opus":0.014311673152114176,"score_gpt":0.2601628132738898,"score_spread":0.2458511401217756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2292406619","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0065315077,0.000005559058,0.9844149,0.00109307,0.00006507057,0.00010726218,5.170811e-7,0.00010079956,0.007681336],"genre_scores_gemma":[0.65137833,0.000015738535,0.34452817,0.00084591046,0.000011984521,7.2146605e-7,0.00008478958,0.000013152908,0.0031211753],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992625,0.000051190586,0.00012548422,0.00020366283,0.0002032039,0.00015393636],"domain_scores_gemma":[0.99922925,0.000040542393,0.00016560311,0.0002823775,0.00017998637,0.00010222183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010169409,0.00007960547,0.00012928623,0.00016970014,0.00012749314,0.000059375066,0.0006194564,0.00004391698,0.0005183476],"category_scores_gemma":[0.000053947577,0.00009459101,0.00006958305,0.0003445003,0.00006801837,0.0009070357,0.00023705306,0.00007114353,0.00013212832],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014307764,0.0006969793,0.004402172,0.000109671935,0.0001444732,0.000052835396,0.011385478,0.000040586412,0.0012444012,0.22493415,0.03962477,0.7173502],"study_design_scores_gemma":[0.00028834603,0.000036062138,0.004851255,0.000017881152,0.000011682486,8.6094565e-7,0.00011348056,0.9844034,0.00050554174,0.0013746839,0.008275519,0.00012128728],"about_ca_topic_score_codex":0.0005092308,"about_ca_topic_score_gemma":0.0000051883553,"teacher_disagreement_score":0.98436284,"about_ca_system_score_codex":0.00003308419,"about_ca_system_score_gemma":0.00011938501,"threshold_uncertainty_score":0.5675543},"labels":[],"label_agreement":null},{"id":"W2292818183","doi":"10.1145/2854158","title":"Interactive Topic Modeling for Exploring Asynchronous Online Conversations","year":2016,"lang":"en","type":"article","venue":"ACM Transactions on Interactive Intelligent Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia","keywords":"Computer science; Asynchronous communication; Human–computer interaction; Conversation; Interface (matter); User interface; Visualization; Interactive visualization; User modeling; Data science; Multimedia; Artificial intelligence","score_opus":0.11520375059996209,"score_gpt":0.3402242574535698,"score_spread":0.22502050685360775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2292818183","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0035802263,0.000030704217,0.9910313,0.0012354585,0.0029672943,0.0005590368,0.00021463708,0.00023334526,0.0001480348],"genre_scores_gemma":[0.9911915,0.00017759271,0.0068293936,0.0001964169,0.00015869018,0.00035917075,0.000027987675,0.000030377,0.001028888],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980954,0.00010973804,0.0005965888,0.0005941763,0.000275095,0.00032901842],"domain_scores_gemma":[0.997304,0.000993878,0.00019152933,0.00089729286,0.00047281195,0.00014045498],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018135991,0.00026682805,0.00029363864,0.00041288402,0.00023683644,0.00021038947,0.00096302555,0.00007225589,0.00010296482],"category_scores_gemma":[0.00022375534,0.00020730271,0.0002110039,0.0002896156,0.000037337813,0.0018138826,0.000034740904,0.00017971147,0.00018402532],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00061582855,0.004250443,0.00021761878,0.0004186089,0.002434227,0.000031564494,0.017988762,0.18502314,0.006944,0.089742996,0.0011163853,0.6912164],"study_design_scores_gemma":[0.0008267697,0.000471387,0.0000131244515,0.0007699007,0.00006170185,0.000027614105,0.004109391,0.9550095,0.019412735,0.0017925951,0.016956115,0.0005491612],"about_ca_topic_score_codex":0.00010603833,"about_ca_topic_score_gemma":0.00004017813,"teacher_disagreement_score":0.98761123,"about_ca_system_score_codex":0.00047692136,"about_ca_system_score_gemma":0.00008194724,"threshold_uncertainty_score":0.8453559},"labels":[],"label_agreement":null},{"id":"W2293244354","doi":"10.1007/978-3-319-27863-6_42","title":"JackVR: A Virtual Reality Training System for Landing Oil Rigs","year":2015,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Training (meteorology); Marine engineering; Process (computing); Virtual reality; Task (project management); Simulation; Oil spill; Domain (mathematical analysis); Aeronautics; Human–computer interaction; Petroleum engineering; Systems engineering; Geology; Engineering; Meteorology","score_opus":0.08681396153898545,"score_gpt":0.3229985181598097,"score_spread":0.23618455662082422,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2293244354","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000056723425,0.000110062145,0.99149984,0.0003780575,0.0018758293,0.00017133067,0.0000630181,0.00027318904,0.0056230207],"genre_scores_gemma":[0.2873579,0.000061396444,0.6976957,0.0033315774,0.003769359,0.00005580968,0.0003166331,0.00018456901,0.007227084],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99644756,0.00004185334,0.0005904252,0.0013082627,0.000994118,0.00061779586],"domain_scores_gemma":[0.99741477,0.00041801442,0.00035499118,0.0011267045,0.00041638425,0.0002691572],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0021194264,0.00043109912,0.00059386564,0.00061200204,0.00028985008,0.0008107697,0.002866036,0.00026914716,0.000006623827],"category_scores_gemma":[0.000220588,0.00039003853,0.00013500686,0.00055605173,0.0003225765,0.0006301093,0.0008832023,0.0003838175,0.000028999775],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000778873,0.000019697574,0.000008094112,0.00015112926,0.000019380905,0.00004125171,0.0021286295,0.018168122,0.0000288074,0.35233423,0.00045567047,0.6266372],"study_design_scores_gemma":[0.00042380719,0.0001420634,0.0000023420214,0.000628563,0.00001297715,0.000055879693,0.0000028792267,0.95623255,0.00008808848,0.023838552,0.01802287,0.000549448],"about_ca_topic_score_codex":0.000015409205,"about_ca_topic_score_gemma":0.00005206702,"teacher_disagreement_score":0.9380644,"about_ca_system_score_codex":0.00047228846,"about_ca_system_score_gemma":0.00084466644,"threshold_uncertainty_score":0.99985516},"labels":[],"label_agreement":null},{"id":"W2293495121","doi":"10.1109/hicss.2016.180","title":"Introduction to the Minitrack on Interactive Visual Decision Analytics","year":2016,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Visual analytics; Computer science; Data science; Big data; Analytics; Visualization; Interactive visual analysis; Context (archaeology); Data visualization; Information visualization; Cultural analytics; Business analytics; Semantic analytics; World Wide Web; Artificial intelligence; Data mining","score_opus":0.019648181242597,"score_gpt":0.33186643013506756,"score_spread":0.3122182488924706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2293495121","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0032906272,0.0000011389317,0.9626015,0.031780787,0.0005577182,0.00007163885,0.000002785061,0.000067898975,0.0016259259],"genre_scores_gemma":[0.95872504,0.000023529054,0.016783921,0.009131972,0.0013727496,0.000006469106,0.0000062822714,0.000013256947,0.013936772],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991,0.00004112366,0.00016240387,0.00029822154,0.0002661142,0.00013211118],"domain_scores_gemma":[0.9990334,0.00023665074,0.000045674882,0.00048722263,0.00012266835,0.00007441385],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00023908929,0.000082427934,0.000072788636,0.0001242621,0.000078493285,0.00014654791,0.000542596,0.000022308575,0.00021549051],"category_scores_gemma":[0.00039017643,0.00003795558,0.000035464305,0.00048091006,0.000017515573,0.0003997037,0.00018525183,0.000044354932,0.0020820922],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029875126,0.00013895305,0.00007303723,8.615241e-7,0.000018966335,0.0000021421213,0.00021969425,0.00018458805,0.00076951424,0.13844435,0.45141587,0.40870214],"study_design_scores_gemma":[0.00037383256,0.00045705764,0.0014223187,0.000041078176,0.000010022382,0.000008679172,0.0001343118,0.08637495,0.014375342,0.002316176,0.8942339,0.0002523322],"about_ca_topic_score_codex":0.000002863319,"about_ca_topic_score_gemma":0.000016622582,"teacher_disagreement_score":0.95543444,"about_ca_system_score_codex":0.00004651915,"about_ca_system_score_gemma":0.000021384263,"threshold_uncertainty_score":0.9986949},"labels":[],"label_agreement":null},{"id":"W2293541784","doi":"10.1109/biovis.2011.6094039","title":"Challenges session","year":2011,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Cancer Agency","funders":"","keywords":"Visualization; Session (web analytics); Computer science; Presentation (obstetrics); Data visualization; Cover (algebra); Information visualization; Data science; World Wide Web; Multimedia; Artificial intelligence; Engineering","score_opus":0.14931870773254977,"score_gpt":0.3284194477397812,"score_spread":0.17910074000723145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2293541784","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00004948165,0.00003865142,0.66514343,0.00023969237,0.00006261197,0.000008658306,8.637399e-8,0.0001064427,0.33435094],"genre_scores_gemma":[0.8822735,0.0004173919,0.110705316,0.0013561731,0.00003138797,0.0000013909122,0.000001946026,0.000004349119,0.0052085617],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99975187,0.000008837967,0.000042020558,0.00008954769,0.00005657692,0.000051143707],"domain_scores_gemma":[0.9997395,0.0000040009936,0.000011088913,0.00019976796,0.000016281643,0.000029342606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005496609,0.00002433316,0.000025086403,0.000023663817,0.000017962391,0.000016655425,0.00026682098,0.00001091217,0.00013225095],"category_scores_gemma":[0.0000057632055,0.0000177488,0.0000089324385,0.00006266782,0.000004986727,0.00022679611,0.00009208968,0.000012298998,0.00021796994],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.8506916e-8,0.000019801648,0.000048562855,0.0000012874619,9.421703e-7,0.0000011793672,0.0003328861,6.816619e-8,0.000011897884,0.9457319,0.0015722214,0.052279156],"study_design_scores_gemma":[0.0008420215,0.0002801371,0.03904119,0.000061522645,0.0000103676075,0.00003344689,0.00093185663,0.3243023,0.03042025,0.120577864,0.48259673,0.0009023243],"about_ca_topic_score_codex":0.0000028843176,"about_ca_topic_score_gemma":0.0000031994484,"teacher_disagreement_score":0.882224,"about_ca_system_score_codex":0.0000017118725,"about_ca_system_score_gemma":0.000006096396,"threshold_uncertainty_score":0.28016353},"labels":[],"label_agreement":null},{"id":"W2293580069","doi":"","title":"Towards a Characterization of Interactivity in Visual Analytics","year":2012,"lang":"en","type":"article","venue":"J. Multim. Process. Technol.","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Interactivity; Visual analytics; Human–computer interaction; Computer science; Analytics; Cultural analytics; Data science; Perception; Visualization; Interactive visual analysis; Component (thermodynamics); Multimedia; Psychology; World Wide Web; Artificial intelligence; Semantic analytics; The Internet","score_opus":0.021829224285279284,"score_gpt":0.3317405587100771,"score_spread":0.30991133442479785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2293580069","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39870816,0.00001901524,0.5998948,0.0002535681,0.00015120578,0.00019435726,0.00001753028,0.00026054052,0.0005007822],"genre_scores_gemma":[0.995174,0.000021950294,0.004518168,0.00011195783,0.000035374105,0.000015146175,0.000040905106,0.0000112256985,0.00007126876],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998721,0.00002491355,0.0003847921,0.00025519013,0.0003284132,0.00028566882],"domain_scores_gemma":[0.9991087,0.000021362135,0.0002613174,0.00035626852,0.00017741352,0.000074946554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034551346,0.00015042533,0.0002370481,0.0004179469,0.000036170957,0.00006325701,0.0006154447,0.00012000282,0.000021577316],"category_scores_gemma":[0.0002479868,0.00014326752,0.00004398271,0.0015524478,0.00004867346,0.0016051766,0.00024258094,0.00017138201,0.000016528878],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005885674,0.0068243425,0.2629646,0.0009228765,0.00011607953,0.00001558284,0.0085947765,0.00020304936,0.12011026,0.038805567,0.0003294104,0.5610546],"study_design_scores_gemma":[0.0005871248,0.00007648952,0.033225954,0.00013580608,0.000015418962,0.000006371835,0.00016219632,0.7627782,0.199906,0.00043980268,0.0022853327,0.00038125785],"about_ca_topic_score_codex":0.000017954331,"about_ca_topic_score_gemma":0.0000069477564,"teacher_disagreement_score":0.7625752,"about_ca_system_score_codex":0.00005980385,"about_ca_system_score_gemma":0.00007795429,"threshold_uncertainty_score":0.584228},"labels":[],"label_agreement":null},{"id":"W2293620324","doi":"10.1145/2598510.2598566","title":"Constructive visualization","year":2014,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":178,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Networks of Centres of Excellence of Canada; Natural Sciences and Engineering Research Council of Canada; Singapore-MIT Alliance for Research and Technology Centre; Association Nationale de la Recherche et de la Technologie; Alberta Innovates - Technology Futures","keywords":"Visualization; Constructive; Computer science; Human–computer interaction; Simple (philosophy); Data visualization; Process (computing); Data science; Artificial intelligence; Programming language; Epistemology","score_opus":0.0233952798134759,"score_gpt":0.32284521055227505,"score_spread":0.29944993073879916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2293620324","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00008536332,0.000011767155,0.9732184,0.00020667474,0.0009962182,0.00009324331,0.000008041845,0.00035048916,0.025029825],"genre_scores_gemma":[0.71180815,0.00014987141,0.27042878,0.008048811,0.0008805074,0.000034757544,0.0010384681,0.000058806923,0.0075518545],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989247,0.00007195764,0.00022300509,0.00042308567,0.00023337756,0.00012387724],"domain_scores_gemma":[0.9988759,0.00003072544,0.00015710066,0.00069217087,0.00017548526,0.000068630325],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016555694,0.00014457792,0.00017784744,0.00013186267,0.000047766793,0.00039813956,0.00090167,0.00013382777,0.00008457964],"category_scores_gemma":[0.000061549654,0.00013403656,0.00005717659,0.00017022391,0.000039007035,0.00016584477,0.0013986904,0.0001242576,0.00015487516],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.0898052e-7,0.000013745684,0.0000963754,0.000023380599,0.000013391924,7.2155234e-7,0.000072445764,0.00035092878,0.0000032520077,0.98675066,0.009776249,0.0028986128],"study_design_scores_gemma":[0.00009752466,0.0000107854285,0.0000857293,0.00003243787,0.000008264566,0.0000029084256,0.00001053815,0.93067765,0.00027580056,0.043903727,0.024661928,0.00023272059],"about_ca_topic_score_codex":0.00001148379,"about_ca_topic_score_gemma":0.0000026807224,"teacher_disagreement_score":0.94284695,"about_ca_system_score_codex":0.000027067026,"about_ca_system_score_gemma":0.00010944359,"threshold_uncertainty_score":0.5465852},"labels":[],"label_agreement":null},{"id":"W2293683087","doi":"10.1201/9781003059325-21","title":"Geo-Topo Maps: Hybrid Visualization of Movement Data over Building Floor Plans and Maps","year":2020,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Visualization; Movement (music); Cartography; Computer science; Geography; Data mining; Art","score_opus":0.04377196011768018,"score_gpt":0.2999623425003111,"score_spread":0.2561903823826309,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2293683087","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000006385392,0.00015116796,0.92826957,0.00034345652,0.00024109439,0.00022698379,0.0023087293,0.00014359262,0.068309024],"genre_scores_gemma":[0.011204968,0.0075211236,0.15784629,0.038566727,0.0019414881,0.00001828032,0.065122336,0.0005438879,0.7172349],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980093,0.00001769541,0.0005234968,0.00076398416,0.0005231887,0.00016232103],"domain_scores_gemma":[0.9983008,0.000033907083,0.00031134073,0.0011321206,0.00008865231,0.00013317811],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00020872113,0.0002790237,0.0003638528,0.00018497824,0.00006133848,0.00021756535,0.0013277396,0.00009577967,0.00025334145],"category_scores_gemma":[0.00003554848,0.00026713527,0.000046253164,0.00008076125,0.00005462712,0.0005560752,0.001974154,0.000112583504,0.00003896233],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003276232,0.000017746861,0.000025311474,0.000120169716,0.0000654228,0.000013155615,0.000038494873,0.00001060017,0.000052760424,0.9578596,0.039181527,0.0026119412],"study_design_scores_gemma":[0.0005810841,0.00013272332,0.0000332831,0.00030294148,0.000101796635,0.000008254531,0.000013398151,0.2839039,0.00066546194,0.044079088,0.6695056,0.0006724621],"about_ca_topic_score_codex":0.000030321848,"about_ca_topic_score_gemma":0.000015314994,"teacher_disagreement_score":0.9137805,"about_ca_system_score_codex":0.000025802257,"about_ca_system_score_gemma":0.000082750186,"threshold_uncertainty_score":0.99997807},"labels":[],"label_agreement":null},{"id":"W2293979936","doi":"10.1007/978-3-319-24282-8_7","title":"Geo-Coordinated Parallel Coordinates (GCPC): A Case Study of Environmental Data Analysis","year":2015,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Geospatial analysis; Computer science; Parallel coordinates; Geovisualization; Curse of dimensionality; Visualization; Data science; Data mining; Data visualization; Knowledge extraction; Information retrieval; Machine learning; Cartography; Information visualization; Geography","score_opus":0.05141459868308177,"score_gpt":0.3120588057251402,"score_spread":0.26064420704205843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2293979936","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011348969,0.0003316525,0.99713194,0.00008448632,0.00031922932,0.00040710185,0.0001809818,0.00008202191,0.00032768206],"genre_scores_gemma":[0.9351026,0.000020066776,0.063930936,0.00020046122,0.000084925065,0.0000035242006,0.00020050275,0.000026585722,0.0004304351],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9954934,0.000086760185,0.000803624,0.0019381631,0.0012145013,0.0004635436],"domain_scores_gemma":[0.99499404,0.00024303215,0.0005384987,0.003807878,0.00017825636,0.00023829125],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0013691466,0.00050722435,0.0008624325,0.0014381189,0.00019127176,0.00039698603,0.0059311916,0.00019950193,0.00006095701],"category_scores_gemma":[0.00008942142,0.00045774164,0.00010980942,0.0016590918,0.0005353679,0.000770475,0.005263968,0.0004374476,0.000019076415],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000317491,0.0024278397,0.0058800913,0.0000998704,0.001758714,0.010416288,0.008212293,0.42832243,0.00004689288,0.007950821,0.00086042035,0.5339926],"study_design_scores_gemma":[0.0005836191,0.0003245742,0.00012075768,0.000040161398,0.00026994228,0.00022176954,0.000010962001,0.99350893,0.00001371836,0.003808716,0.0005531552,0.0005437161],"about_ca_topic_score_codex":0.0003940688,"about_ca_topic_score_gemma":0.00078399864,"teacher_disagreement_score":0.93396765,"about_ca_system_score_codex":0.00018710304,"about_ca_system_score_gemma":0.00029714007,"threshold_uncertainty_score":0.99978745},"labels":[],"label_agreement":null},{"id":"W2294575332","doi":"10.1109/hicss.2016.183","title":"The Human-Computer System: Towards an Operational Model for Problem Solving","year":2016,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Visual analytics; Computer science; Analytics; Visualization; Human–computer interaction; Data science; Cultural analytics; Data visualization; Human-in-the-loop; Interactive visual analysis; Cognition; Artificial intelligence; Semantic analytics","score_opus":0.049081275961382106,"score_gpt":0.3204828716736957,"score_spread":0.2714015957123136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2294575332","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009819344,0.000003708732,0.9965717,0.0014745247,0.00009627733,0.00014664789,0.000008282181,0.00015029324,0.0014503784],"genre_scores_gemma":[0.39200953,0.0000045128786,0.5926946,0.0011675982,0.00029464698,0.000044610282,0.000021214519,0.000014494185,0.013748842],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923563,0.000023732231,0.00018502731,0.00022199971,0.00017388172,0.00015973616],"domain_scores_gemma":[0.9993593,0.00004048019,0.000040152365,0.00033741005,0.00016590819,0.00005675399],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003610806,0.00007143914,0.00006519725,0.00002699092,0.00040205836,0.0004907244,0.00069942116,0.000023446943,0.0000054561297],"category_scores_gemma":[0.000007484983,0.000034112283,0.000033173284,0.000064477776,0.000021841623,0.00073768216,0.00014586432,0.000016464288,0.000016039829],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.8884545e-7,0.0000132589685,0.000008682768,0.0000069149914,0.0000051242973,1.2528716e-7,0.000098269295,0.0008479584,0.00020852155,0.9811547,0.0068299295,0.0108261565],"study_design_scores_gemma":[0.00018350786,0.000027744318,0.000016650141,0.000015821623,0.0000019915558,0.000001861222,0.000011601679,0.99236697,0.00019162656,0.004557238,0.002546173,0.00007883659],"about_ca_topic_score_codex":0.0000047279414,"about_ca_topic_score_gemma":0.000017411825,"teacher_disagreement_score":0.991519,"about_ca_system_score_codex":0.000031140848,"about_ca_system_score_gemma":0.000082792416,"threshold_uncertainty_score":0.47320667},"labels":[],"label_agreement":null},{"id":"W2295883547","doi":"10.1007/978-3-319-27857-5_77","title":"An Interactive Node-Link Visualization of Convolutional Neural Networks","year":2015,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":112,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Convolutional neural network; Visualization; Link (geometry); Node (physics); Artificial neural network; Artificial intelligence; Computer graphics (images); Computer network","score_opus":0.030750413901685848,"score_gpt":0.31889527773733545,"score_spread":0.2881448638356496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2295883547","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000014685729,0.00017940928,0.99724233,0.00019995647,0.0013530813,0.00017754435,0.000015866863,0.00010390544,0.0007132257],"genre_scores_gemma":[0.8605616,0.000049048904,0.13520363,0.002453191,0.0011419121,0.000005216631,0.0003062232,0.000060447943,0.00021869889],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99702764,0.00006652464,0.0005857588,0.00097549515,0.0009790857,0.00036549405],"domain_scores_gemma":[0.99723804,0.0002056844,0.00047753495,0.0009748717,0.00090141455,0.00020242944],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007526006,0.00035583173,0.0004352428,0.0006799005,0.00011733792,0.00034365,0.002451097,0.00024104168,0.0000306613],"category_scores_gemma":[0.000106123465,0.00033930072,0.0000830184,0.0007146246,0.00056367886,0.0012863441,0.000750433,0.00039557752,0.000009580296],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010730801,0.00006269456,0.00013508167,0.000020153733,0.000014387589,0.000016681286,0.0005173503,0.6789532,0.00003487518,0.15421839,0.00009814278,0.16591834],"study_design_scores_gemma":[0.00022075888,0.00016782247,0.000069325986,0.00012341408,0.000007790577,0.000019132805,2.5471908e-7,0.96598125,0.00009088288,0.032368243,0.00061124103,0.00033986435],"about_ca_topic_score_codex":0.000015358255,"about_ca_topic_score_gemma":0.000026318077,"teacher_disagreement_score":0.8620387,"about_ca_system_score_codex":0.00021516366,"about_ca_system_score_gemma":0.00047786016,"threshold_uncertainty_score":0.9999059},"labels":[],"label_agreement":null},{"id":"W2302306061","doi":"10.1007/s00371-016-1217-0","title":"Illustrative multilevel focus+context visualization along snaking paths","year":2016,"lang":"en","type":"article","venue":"The Visual Computer","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures","keywords":"Focus (optics); Visualization; Computer science; Context (archaeology); Computer graphics (images); Computer graphics; Process (computing); Flexibility (engineering); Path (computing); Geometry; Artificial intelligence; Algorithm; Mathematics; Physics; Geology; Optics","score_opus":0.03449269902264162,"score_gpt":0.3148964529472386,"score_spread":0.280403753924597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2302306061","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008777801,0.000028639779,0.98881924,0.0011172738,0.00048807918,0.00019326621,0.0000085012425,0.00027090148,0.00029629626],"genre_scores_gemma":[0.9930632,0.000014740754,0.0044435277,0.0016646009,0.00033769282,0.000008943808,0.000009182897,0.000021140228,0.00043698752],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99813247,0.00024152594,0.00039404916,0.00046539927,0.00040731035,0.0003592578],"domain_scores_gemma":[0.9986208,0.00031828685,0.0001990263,0.00054442487,0.00021001576,0.00010745231],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044540092,0.00023180219,0.00020395726,0.00012689678,0.00028166987,0.00033883564,0.0010616835,0.00007180738,0.000055224973],"category_scores_gemma":[0.000055595166,0.00012765483,0.000092817216,0.0004215132,0.00011789023,0.00087304367,0.00056693744,0.00008884366,0.00031922292],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007238838,0.00011722442,0.00043277707,0.000007284225,0.000045537017,0.000010696731,0.0014877765,0.000043737073,0.0007555921,0.46101877,0.0033026813,0.5327707],"study_design_scores_gemma":[0.0011851153,0.0002895516,0.0038162882,0.00017838657,0.000020219237,0.000026451808,0.00009487577,0.9650261,0.006656476,0.006956513,0.015171438,0.0005785893],"about_ca_topic_score_codex":0.000030280271,"about_ca_topic_score_gemma":0.000024297999,"teacher_disagreement_score":0.9843757,"about_ca_system_score_codex":0.000055552835,"about_ca_system_score_gemma":0.00006820284,"threshold_uncertainty_score":0.5205613},"labels":[],"label_agreement":null},{"id":"W2306434602","doi":"10.1186/s40327-016-0036-8","title":"VisArchive: a time and relevance based visual interface for searching, browsing, and exploring project archives","year":2016,"lang":"en","type":"article","venue":"Visualization in Engineering","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Timeline; Computer science; Relevance (law); Context (archaeology); Interface (matter); Information retrieval; World Wide Web; Set (abstract data type); User interface; Human–computer interaction; Data science; Programming language","score_opus":0.027401701419935226,"score_gpt":0.3113593204105141,"score_spread":0.2839576189905789,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2306434602","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026715621,0.00007572325,0.9725944,0.00010539787,0.000076342425,0.00022633182,0.00000976636,0.00017344115,0.000022981423],"genre_scores_gemma":[0.90743065,0.00045635554,0.091117114,0.0001412327,0.00011129348,0.00014672942,0.000030857515,0.00008234166,0.00048342822],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989703,0.000046004698,0.00023896477,0.00036596795,0.00013105795,0.00024767232],"domain_scores_gemma":[0.99913853,0.00055679015,0.000055501783,0.0001545573,0.000024866462,0.00006975372],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022080606,0.00014732406,0.00014949552,0.00042131843,0.000062314284,0.00015735484,0.00018686046,0.000026734815,0.0000022126221],"category_scores_gemma":[0.00046323333,0.00012701003,0.000021311436,0.00032211686,0.000033200537,0.0006879588,0.00015033635,0.00004888917,0.0000018506842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017097412,0.00048713342,0.009789012,0.0024870667,0.0001171952,0.000019893581,0.012900241,0.041237082,0.39013693,0.2573031,0.0006151912,0.28473622],"study_design_scores_gemma":[0.0006136641,0.00008202222,0.00044658472,0.00038115197,0.0000028111194,0.0000024539086,0.000014975119,0.9873922,0.0065290285,0.00013052323,0.0042128847,0.00019173199],"about_ca_topic_score_codex":0.0000036983536,"about_ca_topic_score_gemma":0.0000015746169,"teacher_disagreement_score":0.9461551,"about_ca_system_score_codex":0.00002179723,"about_ca_system_score_gemma":0.000036567595,"threshold_uncertainty_score":0.5179319},"labels":[],"label_agreement":null},{"id":"W2311061725","doi":"","title":"Visualizing Streamlines using Depth-Dependent Halos","year":2011,"lang":"fr","type":"preprint","venue":"University of Groningen research database (University of Groningen / Centre for Information Technology)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek; National Science Foundation","keywords":"Streamlines, streaklines, and pathlines; Halo; Computer science; Artificial intelligence; Geology; Computer graphics (images); Physics; Astronomy","score_opus":0.11695052472731897,"score_gpt":0.3229132712586329,"score_spread":0.2059627465313139,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2311061725","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04467361,0.0006110896,0.942573,0.0017727287,0.00047595205,0.0018738934,0.0048986464,0.00034069025,0.0027803902],"genre_scores_gemma":[0.34559318,0.0068282504,0.62550664,0.000070816335,0.00016798213,0.0000012302329,0.012015683,0.00012025438,0.009695929],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99544424,0.0003453159,0.00072975614,0.0009436918,0.0013225114,0.001214457],"domain_scores_gemma":[0.9922134,0.00024247302,0.0016794592,0.0018077827,0.0036644551,0.0003923839],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0021198224,0.0005370833,0.0009274355,0.00362378,0.0015922596,0.00014636175,0.004869258,0.00094044564,0.00040509857],"category_scores_gemma":[0.0005123437,0.0007935529,0.00040328814,0.0021710128,0.0020466754,0.005391857,0.0077892044,0.0011956617,0.00013626307],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00064592314,0.000990268,0.0032512234,0.0035602371,0.0014919691,0.00013152868,0.022862036,0.0034414337,0.0010273252,0.91327226,0.009041857,0.04028394],"study_design_scores_gemma":[0.0057489886,0.000786994,0.0006649592,0.0035863228,0.00096604176,0.000040685405,0.10848579,0.6011889,0.0047817854,0.004287185,0.26762378,0.0018385412],"about_ca_topic_score_codex":0.007260065,"about_ca_topic_score_gemma":0.002736739,"teacher_disagreement_score":0.9089851,"about_ca_system_score_codex":0.00082050584,"about_ca_system_score_gemma":0.0014877268,"threshold_uncertainty_score":0.9997075},"labels":[],"label_agreement":null},{"id":"W2312702360","doi":"10.1068/b37148","title":"More Art Than Science: The Sources and Effects of Stylistic Variation in Visualization for Planning and Design","year":2012,"lang":"en","type":"article","venue":"Environment and Planning B Planning and Design","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"University of Pittsburgh","keywords":"Visualization; Interactivity; Credibility; Presentation (obstetrics); Computer science; Context (archaeology); Urban planning; Plan (archaeology); Data science; Information visualization; Field (mathematics); Human–computer interaction; Multimedia; Engineering; Geography; Artificial intelligence; Civil engineering; Political science","score_opus":0.0361598530740666,"score_gpt":0.29271979606060655,"score_spread":0.25655994298653995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2312702360","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11085159,0.002432115,0.88630855,0.0000367671,0.00004859358,0.00027819368,0.000002448298,0.000019699639,0.00002200964],"genre_scores_gemma":[0.98261166,0.000073121206,0.017092543,0.000108512904,0.000036390902,0.000015993006,0.000011719628,0.000008255257,0.000041817195],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989658,0.000117259566,0.00019142916,0.00027424438,0.00020443503,0.0002468382],"domain_scores_gemma":[0.9987598,0.0008816584,0.00013209769,0.0001209124,0.000009497733,0.00009602914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013912033,0.00014227585,0.00016329653,0.0001751513,0.0003368431,0.00020129385,0.00012482742,0.00005546187,6.445284e-7],"category_scores_gemma":[0.0001535007,0.00011090884,0.000009083387,0.00015561425,0.00018892116,0.0004944227,0.00009692327,0.00006775726,3.5276264e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018767393,0.00019021974,0.7937388,0.00049931026,0.00008231341,0.000016266404,0.10492162,0.06378096,0.010132604,0.020245949,0.0012109899,0.004993322],"study_design_scores_gemma":[0.000724618,0.00024849118,0.30327767,0.00029933656,0.00004738029,0.00001632933,0.000798409,0.69192815,0.0013316621,0.000521523,0.0005514253,0.00025503236],"about_ca_topic_score_codex":0.00000424256,"about_ca_topic_score_gemma":2.9598397e-8,"teacher_disagreement_score":0.8717601,"about_ca_system_score_codex":0.000012168111,"about_ca_system_score_gemma":0.000019462363,"threshold_uncertainty_score":0.45227313},"labels":[],"label_agreement":null},{"id":"W2313426939","doi":"10.1177/154193120504900342","title":"Visual Sensitivity of Dynamic Graphical Objects","year":2005,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Graphical user interface; Computer science; Graphical display; Feature (linguistics); Human–computer interaction; Graphical model; Visualization; Sensitivity (control systems); Computer graphics (images); Computer vision; Artificial intelligence; Engineering; Programming language","score_opus":0.010804919261750172,"score_gpt":0.25725541727012874,"score_spread":0.24645049800837857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2313426939","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99877244,0.000026597603,0.00069892756,0.00012844864,0.00004965057,0.000065695465,0.000017169454,0.000035460187,0.0002055816],"genre_scores_gemma":[0.9968215,0.000040574578,0.0029545766,0.00010038552,0.000035718058,5.675536e-7,0.0000022798845,0.000007403093,0.000036948444],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907917,0.000011875798,0.0003096562,0.00024470815,0.00016642017,0.00018815527],"domain_scores_gemma":[0.9992668,0.000071975126,0.0003302506,0.000092239796,0.00017717188,0.0000615502],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058421236,0.00013837387,0.0002250373,0.000037134843,0.00025339157,0.00007723522,0.0003466723,0.00007915278,9.57703e-7],"category_scores_gemma":[0.00008244386,0.00010631454,0.00018108629,0.00022119019,0.00018403614,0.0005085993,0.00049316965,0.00014141604,2.8010078e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043995107,0.0010307899,0.2993198,0.0010452506,0.00052324,3.632772e-7,0.09232218,0.0004288863,0.29028815,0.30213422,0.0038910916,0.008972006],"study_design_scores_gemma":[0.0012661422,0.00028669415,0.22407427,0.00048916566,0.0001397331,0.000013738616,0.018435616,0.6454018,0.104172446,0.0033754406,0.0012098089,0.0011351659],"about_ca_topic_score_codex":0.000028968525,"about_ca_topic_score_gemma":0.000013753365,"teacher_disagreement_score":0.64497286,"about_ca_system_score_codex":0.000031892385,"about_ca_system_score_gemma":0.000021118056,"threshold_uncertainty_score":0.4335381},"labels":[],"label_agreement":null},{"id":"W2320793254","doi":"","title":"The role of emotion in visualization","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Visualization; Cognition; Perception; Cognitive psychology; Cognitive science; Psychology; Creativity; Creative visualization; Computer science; Artificial intelligence; Social psychology","score_opus":0.009823097994241628,"score_gpt":0.2730671949763129,"score_spread":0.26324409698207124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2320793254","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01037881,0.00003188593,0.9769733,0.0003947946,0.00005302264,0.00008647695,2.280721e-7,0.000038265964,0.012043216],"genre_scores_gemma":[0.9982203,0.000022986214,0.0011522457,0.00010692897,0.0000054316915,0.000002130921,0.0000029653647,0.0000013758589,0.00048560588],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99965984,0.000024228968,0.00011510712,0.000058953374,0.0000870541,0.00005479381],"domain_scores_gemma":[0.9997273,0.000023094532,0.000033927885,0.00014927863,0.00005364107,0.000012725932],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000104601764,0.000023128312,0.000029346702,0.000036839545,0.000025035348,0.00007237142,0.00022579792,0.000011470342,0.00003198128],"category_scores_gemma":[0.000027863562,0.00001488228,0.0000086902,0.00028206882,0.000011085246,0.0003140539,0.00005186048,0.000012084835,0.000051564144],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.380154e-8,0.000017521736,0.0027995966,9.646691e-7,7.9925036e-7,2.1639623e-8,0.00011939063,0.000032320237,0.0004380304,0.9623365,0.00052931235,0.033725444],"study_design_scores_gemma":[0.000057831934,0.000010178967,0.008442776,0.00000360729,3.3867775e-7,2.1706447e-7,0.00015491142,0.9614702,0.0035868124,0.020852366,0.0053906664,0.000030122852],"about_ca_topic_score_codex":0.00007257472,"about_ca_topic_score_gemma":0.000019205985,"teacher_disagreement_score":0.98784155,"about_ca_system_score_codex":0.000005373601,"about_ca_system_score_gemma":0.000009737671,"threshold_uncertainty_score":0.06978793},"labels":[],"label_agreement":null},{"id":"W2321485485","doi":"10.1386/vi.4.2.123_1","title":"From numbers to discourse and action: Visualizing meaning through data as it happens","year":2015,"lang":"en","type":"article","venue":"Visual Inquiry","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Meaning (existential); Narrative; Action (physics); Visualization; Data science; Data visualization; Computer science; Macro; Meaning-making; Power (physics); Epistemology; Sociology; Psychology; Artificial intelligence; Linguistics","score_opus":0.3394831082283758,"score_gpt":0.4986565274434143,"score_spread":0.15917341921503853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2321485485","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.062368948,0.0000894545,0.927085,0.0039149164,0.0017323691,0.00016552517,0.000044220596,0.00029317904,0.004306374],"genre_scores_gemma":[0.9479164,0.000070561735,0.03872735,0.010295444,0.0016524197,0.0000073313463,0.0004992306,0.000047632817,0.00078363705],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9981114,0.00009449785,0.00029010218,0.0007253751,0.00048421166,0.00029439718],"domain_scores_gemma":[0.99843436,0.000080539576,0.00010261256,0.0009471903,0.000092569084,0.0003427419],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040551712,0.00018909152,0.00021256457,0.00008644055,0.00015462124,0.00064191676,0.0011290618,0.000070461545,0.000044374043],"category_scores_gemma":[0.00025314165,0.0001837481,0.000023667031,0.00052346446,0.00008874555,0.0025596207,0.0018703922,0.00011922225,0.00047895612],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007823284,0.0004982811,0.0018021767,0.00004086007,0.0002183785,0.00014593342,0.10849906,0.0002133771,0.0017033629,0.25827184,0.59720546,0.031323053],"study_design_scores_gemma":[0.0014356656,0.0005526757,0.00019716815,0.0002451688,0.0000902377,0.000058882717,0.053571437,0.27595782,0.002545944,0.008467773,0.6556655,0.0012117224],"about_ca_topic_score_codex":0.00059662183,"about_ca_topic_score_gemma":0.000099525845,"teacher_disagreement_score":0.88835764,"about_ca_system_score_codex":0.000045173027,"about_ca_system_score_gemma":0.00012923361,"threshold_uncertainty_score":0.749303},"labels":[],"label_agreement":null},{"id":"W2326743463","doi":"10.1061/41020(339)99","title":"Visualization Configuration Model for Integrating Presentation of Construction Project Management Data","year":2009,"lang":"en","type":"article","venue":"Construction Research Congress 2009","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visualization; Computer science; Flexibility (engineering); Information visualization; Domain (mathematical analysis); Data visualization; Focus (optics); Software visualization; Software; Human–computer interaction; Software engineering; Data science; Data mining; Software development; Component-based software engineering","score_opus":0.14853998039603197,"score_gpt":0.455847474439159,"score_spread":0.30730749404312707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2326743463","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00051949354,0.00004575,0.99478716,0.00036595415,0.00034665063,0.0011252615,0.00012571295,0.00012845267,0.0025555927],"genre_scores_gemma":[0.34401283,0.0005792857,0.64956695,0.00020275431,0.000229982,0.00012224377,0.0027456502,0.000032615477,0.0025077106],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99734825,0.00024503452,0.0006192764,0.0006346709,0.00082364504,0.00032911205],"domain_scores_gemma":[0.9970324,0.00013488054,0.00033125814,0.0009499657,0.0014740563,0.00007742251],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013446248,0.0001567515,0.00021362893,0.0007839406,0.00032244052,0.00039108447,0.0010049545,0.000098472934,0.000013518412],"category_scores_gemma":[0.0004639643,0.00015814882,0.00004676079,0.0012930435,0.0002545697,0.001923679,0.000200122,0.00014943097,0.000004794757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038543243,0.00008149952,0.00012720209,0.0000859331,0.000031691732,0.0000011095315,0.0002013817,0.0005560582,0.001219282,0.7666642,0.008209221,0.2227839],"study_design_scores_gemma":[0.000737659,0.00011833807,0.00010647708,0.00009447729,0.000018351528,0.00001261106,0.0006301263,0.97310865,0.005512507,0.017319433,0.0021855978,0.00015578732],"about_ca_topic_score_codex":0.000015693302,"about_ca_topic_score_gemma":0.0000116392,"teacher_disagreement_score":0.9725526,"about_ca_system_score_codex":0.00007141535,"about_ca_system_score_gemma":0.00026258812,"threshold_uncertainty_score":0.6449122},"labels":[],"label_agreement":null},{"id":"W2330383126","doi":"10.1109/mcg.2016.38","title":"Spatial Analytic Interfaces: Spatial User Interfaces for In Situ Visual Analytics","year":2016,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":65,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Human–computer interaction; Computer science; Leverage (statistics); Analytics; Visual analytics; Wearable computer; User interface; Mobile device; Spatial contextual awareness; Context (archaeology); Wearable technology; Data science; Visualization; Multimedia; World Wide Web; Artificial intelligence","score_opus":0.023904535606675863,"score_gpt":0.30351686188614424,"score_spread":0.27961232627946836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2330383126","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015312212,0.00003552015,0.9829841,0.00087877194,0.00019108903,0.0004150988,0.000044737197,0.00009365661,0.000044805965],"genre_scores_gemma":[0.99188805,0.00014688628,0.007009772,0.00049070606,0.00023405012,0.00009316352,0.00002248044,0.000016513859,0.000098379984],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983933,0.000041236868,0.00046216155,0.0006087498,0.00019440612,0.00030012024],"domain_scores_gemma":[0.99880826,0.0002377932,0.00015859494,0.00048759312,0.00016892042,0.0001388587],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002509182,0.00021601135,0.00026757637,0.00039039817,0.00013903916,0.00029331716,0.0007096719,0.00009263494,0.0000054152347],"category_scores_gemma":[0.0000114925915,0.00016905638,0.00007695996,0.0005662135,0.00013718812,0.00035572218,0.00022926516,0.00009568466,0.000017437367],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029501123,0.00077538565,0.008718994,0.00012482308,0.00018258809,0.0000049730293,0.00046473937,0.00025402167,0.0045147236,0.595711,0.0040918915,0.38512737],"study_design_scores_gemma":[0.0017329961,0.00030940532,0.005017852,0.00013545532,0.000054367512,0.0000090592475,0.000023425475,0.9259223,0.006787555,0.014838328,0.044482596,0.0006866553],"about_ca_topic_score_codex":0.00006168436,"about_ca_topic_score_gemma":0.0006566628,"teacher_disagreement_score":0.97657585,"about_ca_system_score_codex":0.000030186375,"about_ca_system_score_gemma":0.000053090007,"threshold_uncertainty_score":0.6893919},"labels":[],"label_agreement":null},{"id":"W2335570229","doi":"10.1177/154193120204601708","title":"Judgments of 3D Bars in Depth","year":2002,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Scaling; Bar (unit); Statistics; Mathematics; Approximation error; Geometry; Apparent Size; Physics; Psychology; Cognitive psychology","score_opus":0.02820221458998811,"score_gpt":0.2512582793017291,"score_spread":0.223056064711741,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2335570229","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99819005,0.000052705676,0.00010692391,0.00005395203,0.000051067676,0.00006319894,0.000009420745,0.000015586384,0.0014571158],"genre_scores_gemma":[0.9970316,0.00008772552,0.002682559,0.000078753095,0.00001481716,8.763656e-7,8.698582e-7,0.000005604684,0.00009718277],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99921423,0.000004544787,0.00030867482,0.00018809477,0.00012629353,0.00015818187],"domain_scores_gemma":[0.9994975,0.000026219142,0.00027000843,0.000085628955,0.00008256915,0.000038097165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002509683,0.00010355378,0.00017515046,0.000035826924,0.00012699008,0.000059520225,0.000527705,0.00005203166,0.0000034966813],"category_scores_gemma":[0.000045561177,0.000080867634,0.00008324777,0.00021001068,0.00008671587,0.00042194859,0.0003867172,0.00009676985,3.707221e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000057450743,0.0003321371,0.85609823,0.00040410922,0.000101846126,1.071515e-7,0.062889636,0.0002256902,0.008285736,0.06294104,0.0064567924,0.002258916],"study_design_scores_gemma":[0.0037064601,0.00044199245,0.49986747,0.0015253933,0.00013040475,0.0000062937097,0.039180707,0.36934495,0.07237083,0.005785388,0.005778641,0.0018614859],"about_ca_topic_score_codex":0.00003759504,"about_ca_topic_score_gemma":0.0000040371774,"teacher_disagreement_score":0.36911926,"about_ca_system_score_codex":0.00002767298,"about_ca_system_score_gemma":0.0000059147933,"threshold_uncertainty_score":0.32976863},"labels":[],"label_agreement":null},{"id":"W2337383841","doi":"10.2200/s00685ed1v01y201512vis005","title":"Design of Visualizations for Human-Information Interaction: A Pattern-Based Framework","year":2016,"lang":"en","type":"article","venue":"Synthesis lectures on visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Visualization; Information visualization; Human–computer interaction; Computer science; Data science; Data visualization; Artificial intelligence","score_opus":0.03961794713901291,"score_gpt":0.3472980871411811,"score_spread":0.3076801400021682,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2337383841","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00015763719,0.000007100561,0.99831533,0.00044675005,0.0002321588,0.00046575765,0.0000473557,0.0002182092,0.000109692875],"genre_scores_gemma":[0.98557335,0.000012371656,0.0126829995,0.0013533464,0.00007519993,0.00015462552,0.00008946179,0.000026059033,0.000032609823],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99825424,0.00022653936,0.0005824529,0.00030540224,0.000405484,0.00022591029],"domain_scores_gemma":[0.99704295,0.0014633414,0.00047164925,0.0005322857,0.00041803176,0.00007172094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003980287,0.00021269049,0.00024173065,0.0005216843,0.00022399912,0.00018203934,0.0005247383,0.00014378854,0.00015975146],"category_scores_gemma":[0.0015482915,0.00015988007,0.00010361327,0.00062651274,0.00004819767,0.00093469955,0.000040790652,0.000044826942,0.00003481051],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008533833,0.00043630364,0.0003292096,0.00019043505,0.00009415311,5.416006e-7,0.0007246447,0.014886984,0.005696722,0.89366084,0.0055156928,0.07837911],"study_design_scores_gemma":[0.0008910245,0.00056010275,0.00029700098,0.00085070153,0.000068351495,0.0000018035095,0.000044334745,0.67887485,0.29477745,0.014747079,0.008308101,0.00057920156],"about_ca_topic_score_codex":0.000005106294,"about_ca_topic_score_gemma":0.0000026521461,"teacher_disagreement_score":0.98563236,"about_ca_system_score_codex":0.00008880198,"about_ca_system_score_gemma":0.00009409713,"threshold_uncertainty_score":0.651972},"labels":[],"label_agreement":null},{"id":"W2339610053","doi":"10.1145/2818373","title":"Area-Preserving Simplification and Schematization of Polygonal Subdivisions","year":2016,"lang":"en","type":"article","venue":"ACM Transactions on Spatial Algorithms and Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Exploratory Research for Advanced Technology; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Subdivision; Computer science; Polygon (computer graphics); Quadratic equation; Enhanced Data Rates for GSM Evolution; Simple (philosophy); Set (abstract data type); Algorithm; Topology (electrical circuits); Property (philosophy); Mathematics; Mathematical optimization; Geometry; Combinatorics; Artificial intelligence","score_opus":0.03803996597717287,"score_gpt":0.28357849866395446,"score_spread":0.24553853268678158,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2339610053","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004390972,0.00006545622,0.99444395,0.00064465904,0.00016307001,0.0001277204,0.00006763417,0.000048240632,0.00004829602],"genre_scores_gemma":[0.9928876,0.00018416569,0.0066311425,0.000026412818,0.000026575723,0.000011645535,0.000007836036,0.0000067229917,0.00021785675],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99906087,0.000051094685,0.00029506907,0.00025135046,0.00023051117,0.00011108454],"domain_scores_gemma":[0.9990268,0.00022079673,0.000118232485,0.0004236403,0.00012450964,0.00008602764],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020032276,0.000099000375,0.00015411542,0.00014484885,0.00015166712,0.00010325614,0.0002651625,0.000055540826,0.00001851931],"category_scores_gemma":[0.00007257572,0.00006984609,0.000026671425,0.00021737698,0.00004611126,0.00042146567,0.000023650671,0.000039967854,0.0000037534921],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021810722,0.00036819157,0.0020729154,0.00023340578,0.00013343149,0.0000028173943,0.0011336395,0.00091829454,0.018135479,0.06169691,0.0002488863,0.91503423],"study_design_scores_gemma":[0.0007893439,0.00017580253,0.0039199586,0.00031286475,0.000028497849,0.000017485483,0.00017234226,0.9872122,0.004111694,0.0016850805,0.0013110199,0.00026375128],"about_ca_topic_score_codex":0.00018550282,"about_ca_topic_score_gemma":0.0000198365,"teacher_disagreement_score":0.98849666,"about_ca_system_score_codex":0.000013473818,"about_ca_system_score_gemma":0.000023088527,"threshold_uncertainty_score":0.2848241},"labels":[],"label_agreement":null},{"id":"W2340581292","doi":"10.1093/llc/fqv046","title":"Trading Consequences: A Case Study of Combining Text Mining and Visualization to Facilitate Document Exploration","year":2015,"lang":"en","type":"article","venue":"Digital Scholarship in the Humanities","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; University of Saskatchewan","funders":"Nipissing University","keywords":"Visualization; Digitization; Data science; Context (archaeology); Computer science; Information visualization; Visual analytics; Scale (ratio); Creative visualization; Commodity; Point (geometry); Perspective (graphical); Comparative historical research; Data visualization; World Wide Web; Data mining; Archaeology; Artificial intelligence; Geography; Cartography; Sociology; Social science","score_opus":0.29586004946215166,"score_gpt":0.35680738888335545,"score_spread":0.06094733942120378,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2340581292","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97983426,0.00003084509,0.018699292,0.00006228783,0.00005217241,0.0002522669,0.0000058661735,0.00003717971,0.0010258444],"genre_scores_gemma":[0.9994571,0.0000013028288,0.00022913454,0.0002031363,0.0000078610165,0.000018177205,0.000009593889,0.0000046670752,0.00006903583],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9988845,0.00018183391,0.00029908767,0.00018543261,0.00032758512,0.000121585224],"domain_scores_gemma":[0.99942553,0.00014026539,0.00008872149,0.0001983214,0.00010395011,0.000043216194],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0008906766,0.00009703478,0.00012216186,0.0001895853,0.00014450599,0.0018392849,0.00031954874,0.00001779485,0.0000012526148],"category_scores_gemma":[0.00026285977,0.00007932017,0.000012234128,0.0003596468,0.000075755306,0.0035191125,0.00012478513,0.00005396459,0.0000025670445],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012423068,0.00030192343,0.012465175,0.000033934648,0.000019977912,0.00029840553,0.84394485,0.00033274436,0.000023129136,0.13705947,0.000106253596,0.0054017305],"study_design_scores_gemma":[0.0014390866,0.0015405655,0.0005815478,0.0001841236,0.000017193193,0.00034096578,0.9604577,0.011993131,0.00014257852,0.021924779,0.0009812431,0.00039708294],"about_ca_topic_score_codex":0.00008879247,"about_ca_topic_score_gemma":0.00023673529,"teacher_disagreement_score":0.11651287,"about_ca_system_score_codex":0.00003335644,"about_ca_system_score_gemma":0.000036662685,"threshold_uncertainty_score":0.9991969},"labels":[],"label_agreement":null},{"id":"W2344318755","doi":"10.1007/s10707-019-00350-5","title":"A dynamic approach for presenting local and global information in geospatial network visualizations","year":2019,"lang":"en","type":"article","venue":"GeoInformatica","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Geospatial analysis; Computer science; Scalability; Visualization; Data mining; Graph; Theoretical computer science; Geography; Cartography; Database","score_opus":0.007273992546117808,"score_gpt":0.2653024820631423,"score_spread":0.25802848951702445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2344318755","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002328242,0.000009515135,0.99261624,0.000074507494,0.000092708375,0.00046299005,0.000027779759,0.00007366738,0.004314329],"genre_scores_gemma":[0.75378126,0.000016311651,0.24417776,0.0010504712,0.00002114658,0.0000522808,0.0007756518,0.0000067678507,0.00011832844],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99897164,0.000018026145,0.00042601535,0.00011084564,0.00018855094,0.0002849299],"domain_scores_gemma":[0.9994468,0.000040478633,0.00013492985,0.00024353949,0.00007094407,0.00006331809],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029074604,0.00010261121,0.00014346583,0.00008108356,0.00008728102,0.00031951212,0.00030446358,0.00005665906,0.0000074803283],"category_scores_gemma":[0.00004221159,0.00009872058,0.000029715029,0.00049186114,0.000025524265,0.0024900918,0.00023792776,0.000050509436,0.000043910277],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016847556,0.0000897194,0.00841051,0.00067880366,0.00003420693,3.1823052e-7,0.0041870815,0.24846143,6.463461e-7,0.69572324,0.0026824437,0.039714787],"study_design_scores_gemma":[0.00051759667,0.000026632719,0.0018775599,0.000017735889,0.000004182976,0.000005566729,0.00030706104,0.9909512,5.798012e-7,0.0016452809,0.004525161,0.00012144996],"about_ca_topic_score_codex":0.000016663573,"about_ca_topic_score_gemma":0.0000158081,"teacher_disagreement_score":0.75145304,"about_ca_system_score_codex":0.000041944608,"about_ca_system_score_gemma":0.000060605635,"threshold_uncertainty_score":0.40257084},"labels":[],"label_agreement":null},{"id":"W2345320856","doi":"10.1145/2851581.2890257","title":"GaussBox","year":2016,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"European Research Council; Social Sciences and Humanities Research Council of Canada","keywords":"Computer science; Human–computer interaction; Craft; Visualization; Interaction design; Artificial intelligence","score_opus":0.02281916782210229,"score_gpt":0.2894154769053476,"score_spread":0.2665963090832453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2345320856","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00007564678,0.0000019626455,0.96288145,0.002729106,0.000052609645,0.0000067993315,4.5803117e-7,0.00009650166,0.034155454],"genre_scores_gemma":[0.852451,0.000030079465,0.0523829,0.0051286058,0.00006114544,0.0000013100753,0.000001119861,0.0000043065384,0.08993948],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99977374,0.000005059199,0.000038886315,0.00007203242,0.000057318837,0.000052934127],"domain_scores_gemma":[0.9997518,0.000013129659,0.000007849749,0.00018422451,0.000015122591,0.00002784807],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000038451435,0.000019067842,0.000019566074,0.000018440529,0.000013191187,0.000031913718,0.00024792991,0.0000064164956,0.00022353223],"category_scores_gemma":[0.000014570018,0.000009573493,0.000008621613,0.00008202068,0.000006762857,0.00022607627,0.00006772316,0.0000042684933,0.0008401155],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.355483e-8,0.0000047153762,0.00019050627,2.1941555e-7,7.404716e-7,5.7149333e-7,0.000005898899,6.13117e-8,0.0003942556,0.93975365,0.024986472,0.034662876],"study_design_scores_gemma":[0.00031062472,0.00002541806,0.0013098812,0.000009835949,0.0000011071816,0.0000047880553,0.0000048655056,0.014590978,0.011854846,0.020009592,0.95172775,0.00015029614],"about_ca_topic_score_codex":8.7710185e-7,"about_ca_topic_score_gemma":8.733967e-7,"teacher_disagreement_score":0.9267413,"about_ca_system_score_codex":0.0000033491199,"about_ca_system_score_gemma":0.000007997995,"threshold_uncertainty_score":0.99993783},"labels":[],"label_agreement":null},{"id":"W2345880672","doi":"10.1145/2909437.2909459","title":"Towards Interactive Visual Exploration of Parallel Programs using a Domain-Specific Language","year":2016,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Computer science; Visualization; Correctness; Massively parallel; Compiler; Source code; Kernel (algebra); Interactive visualization; Code (set theory); Domain (mathematical analysis); Programming language; Data visualization; Program optimization; Parallel computing; Artificial intelligence","score_opus":0.0627637678072851,"score_gpt":0.35179831271067424,"score_spread":0.28903454490338915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2345880672","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023699583,0.000013547545,0.97465265,0.00026124358,0.00008595502,0.00008862372,0.0000021159146,0.000076465614,0.0011198131],"genre_scores_gemma":[0.8450056,0.000022960037,0.15445668,0.00010252043,0.00004918152,0.00000514432,0.000011323363,0.0000074804893,0.00033915823],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926704,0.000043337044,0.00019062852,0.00018717475,0.00019329049,0.00011849838],"domain_scores_gemma":[0.9995148,0.000020894462,0.0000992387,0.00022327478,0.00009659479,0.00004519767],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001216633,0.00007476767,0.00010112623,0.00008256284,0.000028143888,0.000082470564,0.00027381172,0.000024758856,0.000053075993],"category_scores_gemma":[0.000009349629,0.00004728687,0.000038655424,0.00026426185,0.000036446316,0.0013756385,0.00013460824,0.000022496286,0.000031033345],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021145093,0.00032370436,0.00020027255,0.0000121996945,0.000031536507,0.000010310474,0.005829441,0.000014042025,0.021053838,0.5581513,0.00046474344,0.41388747],"study_design_scores_gemma":[0.012344321,0.002335777,0.001792571,0.0012506075,0.000058707494,0.000078507466,0.025571719,0.5093498,0.2251617,0.052866682,0.16626681,0.0029227447],"about_ca_topic_score_codex":0.00001608914,"about_ca_topic_score_gemma":0.000007352076,"teacher_disagreement_score":0.821306,"about_ca_system_score_codex":0.000032145363,"about_ca_system_score_gemma":0.00003496177,"threshold_uncertainty_score":0.19283026},"labels":[],"label_agreement":null},{"id":"W2345881254","doi":"10.1145/2851581.2892334","title":"PaperQuest","year":2016,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Focus (optics); sort; Citation; Information retrieval; Visualization; Component (thermodynamics); Key (lock); Reading (process); Data science; World Wide Web; Data mining","score_opus":0.01875055119751902,"score_gpt":0.2830697176278619,"score_spread":0.2643191664303429,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2345881254","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000074119765,0.0000022970676,0.95380336,0.0027526428,0.000051076524,0.000006754565,4.602688e-7,0.00010981737,0.04319945],"genre_scores_gemma":[0.88522565,0.000045591063,0.044806585,0.0059898403,0.00006490885,0.0000014416759,0.0000013059908,0.000004250783,0.06386044],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99978304,0.000005520565,0.000038142825,0.00007082146,0.000052547264,0.000049939194],"domain_scores_gemma":[0.99975955,0.000013658888,0.0000072067573,0.0001771948,0.000015131047,0.000027255273],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003689161,0.00001911821,0.000019094492,0.00001414944,0.000013460702,0.000033874276,0.00023597405,0.0000065454783,0.00019745882],"category_scores_gemma":[0.000015305564,0.00000959099,0.000007828411,0.000068829984,0.000007016895,0.00024093685,0.000062472885,0.0000042679385,0.00070464617],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.6323996e-8,0.000004781516,0.0002672232,2.13925e-7,6.5225845e-7,6.382345e-7,0.00000542211,4.0377635e-8,0.00056900823,0.94560003,0.01301118,0.040540766],"study_design_scores_gemma":[0.00021052304,0.000020688032,0.001483269,0.000008641673,7.989693e-7,0.000003796975,0.0000033276192,0.0069614206,0.0066480893,0.010420586,0.9741204,0.000118463635],"about_ca_topic_score_codex":0.000001126483,"about_ca_topic_score_gemma":0.0000014992698,"teacher_disagreement_score":0.9611092,"about_ca_system_score_codex":0.0000033826382,"about_ca_system_score_gemma":0.000007999437,"threshold_uncertainty_score":0.9057036},"labels":[],"label_agreement":null},{"id":"W2346033130","doi":"10.1007/978-1-4020-8658-8","title":"Medial Representations","year":2008,"lang":"en","type":"book","venue":"Computational imaging and vision","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":194,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Cognitive science; Computer science; Psychology","score_opus":0.02193884423960733,"score_gpt":0.3533278790274547,"score_spread":0.33138903478784737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2346033130","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000008592993,0.00070058275,0.89868903,0.0015045292,0.0006025037,0.000101430705,0.000036230584,0.00021267327,0.09814443],"genre_scores_gemma":[0.0046091555,0.0017449625,0.13939862,0.005645767,0.0020865216,0.000015009434,0.006395165,0.00011352947,0.8399913],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986958,0.000036117995,0.0002688049,0.00044678675,0.0004239518,0.00012857311],"domain_scores_gemma":[0.99909014,0.00019857805,0.00014439832,0.00026275805,0.00019575038,0.000108396525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010259814,0.00016772284,0.00017364889,0.00023842487,0.00024882832,0.00027487706,0.00034758705,0.000056882986,0.000012028721],"category_scores_gemma":[0.000044132285,0.00016958824,0.00005847078,0.00012664187,0.00011519145,0.00044577592,0.00030217745,0.00015647695,0.000093180744],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000015856594,0.000034970464,0.000083519335,0.000026786895,0.000017515167,0.000045892903,0.00030259008,0.0013793762,0.000002286393,0.21988903,0.75498533,0.023231104],"study_design_scores_gemma":[0.00030400275,0.00001797739,0.00063799415,0.00010752031,0.000012509085,0.00010264741,0.000004659837,0.6409055,0.0000015852128,0.06796941,0.28967467,0.00026151678],"about_ca_topic_score_codex":0.0000024996107,"about_ca_topic_score_gemma":4.1225024e-7,"teacher_disagreement_score":0.7592904,"about_ca_system_score_codex":0.000040394643,"about_ca_system_score_gemma":0.00027955166,"threshold_uncertainty_score":0.69156075},"labels":[],"label_agreement":null},{"id":"W2346931493","doi":"10.5555/2981324.2981340","title":"Daisy visualization for graphs","year":2016,"lang":"en","type":"article","venue":"Non-Photorealistic Animation and Rendering","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Visualization; Graph drawing; Computer science; Information visualization; Graph; Data visualization; Human–computer interaction; Theoretical computer science; Data science; Information retrieval; Artificial intelligence","score_opus":0.027975039560057275,"score_gpt":0.304007348158856,"score_spread":0.27603230859879874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2346931493","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008140899,0.000012213349,0.99721944,0.00024219288,0.00014282347,0.00015096614,0.00003313356,0.00012352261,0.001261612],"genre_scores_gemma":[0.98097366,0.00010887908,0.017841129,0.00042321076,0.000057692076,0.000030986754,0.00008011694,0.000015654654,0.00046867094],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991933,0.000018921235,0.00021705695,0.00026115196,0.00015437663,0.00015516694],"domain_scores_gemma":[0.9994219,0.000098519595,0.00010059807,0.00019717174,0.00009706606,0.0000847513],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020798501,0.00010320977,0.0001115256,0.00012174587,0.00015064124,0.00014347195,0.00018018771,0.000047147576,0.00001797978],"category_scores_gemma":[0.00009684571,0.00007403916,0.000032631542,0.00019306446,0.000032220774,0.00042088146,0.00006465943,0.000017791768,0.0000052321616],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000061856194,0.00002063639,0.0001939811,0.00006585484,0.000017290298,9.79555e-7,0.00037072596,0.0000051325515,0.0076321512,0.9705501,0.0021921932,0.018944731],"study_design_scores_gemma":[0.0023830011,0.00024356147,0.0057311314,0.0002692012,0.000055622822,0.000028487759,0.00019858153,0.8859246,0.010046297,0.059070885,0.03532965,0.0007190074],"about_ca_topic_score_codex":0.000012885321,"about_ca_topic_score_gemma":0.000007183347,"teacher_disagreement_score":0.9801596,"about_ca_system_score_codex":0.00002417083,"about_ca_system_score_gemma":0.000025929774,"threshold_uncertainty_score":0.30192295},"labels":[],"label_agreement":null},{"id":"W23598379","doi":"10.1007/978-3-7908-2127-7_7","title":"Visual Computing an der FH Bonn-Rhein-Sieg","year":2008,"lang":"de","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Chemistry; Humanities; Art","score_opus":0.04759769678627447,"score_gpt":0.31707458698410995,"score_spread":0.2694768901978355,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W23598379","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00013506367,0.000641122,0.80650085,0.00037157087,0.0017584757,0.00032384356,0.0000484181,0.0006066256,0.18961404],"genre_scores_gemma":[0.11216313,0.005208638,0.092268646,0.027767017,0.0070819505,0.000005057146,0.0035953035,0.00061948906,0.7512908],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9951098,0.00010650844,0.0011887779,0.0016087492,0.0011663593,0.00081981515],"domain_scores_gemma":[0.99668294,0.00014626226,0.0005890503,0.0014291512,0.0004883042,0.00066426303],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00044415842,0.0008913498,0.0008655658,0.00048853,0.00069901533,0.0009563698,0.0020041142,0.0005516383,0.002107026],"category_scores_gemma":[0.000046885045,0.00088559976,0.0003354441,0.00027833652,0.00034155505,0.0008765404,0.0012926236,0.0006336212,0.005794128],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010576734,0.00037439718,0.00016698621,0.000085617554,0.00034032747,0.00045244495,0.0012588621,0.00034382765,0.00003071162,0.8975693,0.032784026,0.06658294],"study_design_scores_gemma":[0.0004229698,0.0002470157,0.00008645431,0.00017333259,0.00008647638,0.00010343335,0.000032625918,0.53513867,0.00006970972,0.0004967441,0.4620514,0.0010911894],"about_ca_topic_score_codex":0.000065927736,"about_ca_topic_score_gemma":0.000033363238,"teacher_disagreement_score":0.89707255,"about_ca_system_score_codex":0.000098192264,"about_ca_system_score_gemma":0.00034799814,"threshold_uncertainty_score":0.9993595},"labels":[],"label_agreement":null},{"id":"W2389212687","doi":"","title":"Modeling the Joint Distribution of Scene Events at an Edge","year":2016,"lang":"en","type":"article","venue":"Purdue e-Pubs (Purdue University System)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Joint (building); Computer science; Computer vision; Enhanced Data Rates for GSM Evolution; Artificial intelligence; Engineering","score_opus":0.027625536167346105,"score_gpt":0.22692502961188507,"score_spread":0.19929949344453896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2389212687","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09994551,0.000029261464,0.8978376,0.000688402,0.00032231343,0.0002223768,0.00019808162,0.00014657885,0.0006099098],"genre_scores_gemma":[0.9978521,0.000025467793,0.00053510687,0.000028152992,0.000053692205,5.8890583e-7,0.0000863778,0.000007981459,0.0014105408],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99841446,0.00024955827,0.00027188417,0.00038370962,0.00040080733,0.00027960257],"domain_scores_gemma":[0.9984592,0.000048316415,0.00018237958,0.00085926056,0.00028425513,0.00016658744],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064739154,0.00015077603,0.00022956995,0.00010983172,0.0003302786,0.00004906415,0.0011221969,0.00007725815,0.000013144811],"category_scores_gemma":[0.000060829792,0.00010449063,0.000111006426,0.00044103697,0.00006713587,0.00096246816,0.00057342515,0.000062967396,0.0000923233],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014554357,0.0005736155,0.006038522,0.0006184562,0.00027041885,0.000095771924,0.0026197543,0.0053333174,0.00670537,0.9597071,0.0066528446,0.011239311],"study_design_scores_gemma":[0.0014960065,0.00011527566,0.0021903305,0.00057762803,0.0000716705,0.00004347723,0.0010529957,0.97556716,0.0023648357,0.00024622792,0.015845086,0.00042927454],"about_ca_topic_score_codex":0.000117852804,"about_ca_topic_score_gemma":0.000040637195,"teacher_disagreement_score":0.97023386,"about_ca_system_score_codex":0.0004527227,"about_ca_system_score_gemma":0.00009610333,"threshold_uncertainty_score":0.42610043},"labels":[],"label_agreement":null},{"id":"W2393302563","doi":"10.1111/cgf.12804","title":"A Descriptive Framework for Temporal Data Visualizations Based on Generalized Space‐Time Cubes","year":2016,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":171,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Agence Nationale de la Recherche; Science Foundation Ireland","keywords":"Data cube; Cube (algebra); Computer science; Parameterized complexity; Visualization; Online analytical processing; Theoretical computer science; Space (punctuation); Data mining; Algorithm; Mathematics; Geometry","score_opus":0.05749521673658341,"score_gpt":0.3254449557592869,"score_spread":0.26794973902270347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2393302563","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00013069599,0.000023309225,0.9907055,0.0072476133,0.00065253675,0.00037129948,0.00046483,0.00036157755,0.000042620664],"genre_scores_gemma":[0.085111864,0.0000506589,0.89994854,0.012618202,0.00045775858,0.00005929326,0.0012259209,0.00008218092,0.00044558637],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977592,0.00012406072,0.00037613252,0.0008553369,0.00039364985,0.0004915973],"domain_scores_gemma":[0.99682176,0.0004759716,0.00018580575,0.0020625119,0.00025618818,0.00019775386],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004020795,0.00028169854,0.0002943511,0.00040849205,0.00032546022,0.0003995348,0.0023527802,0.00014461769,0.000025425363],"category_scores_gemma":[0.00017683259,0.00021044926,0.00014147538,0.0009204228,0.00012260051,0.00082361506,0.0007621731,0.00009898705,0.00006299993],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013155355,0.00015656567,0.0013376042,0.00001050227,0.000037227448,0.000002894162,0.00005027211,0.00010020574,0.0000180861,0.9329494,0.06203891,0.0032851507],"study_design_scores_gemma":[0.0008171258,0.00021419318,0.00012336425,0.00013913804,0.000016997928,0.0000016624239,0.0000043634577,0.8770877,0.00015383022,0.056504272,0.06461872,0.000318642],"about_ca_topic_score_codex":0.000007042384,"about_ca_topic_score_gemma":0.000009976262,"teacher_disagreement_score":0.87698746,"about_ca_system_score_codex":0.000035620786,"about_ca_system_score_gemma":0.00014751329,"threshold_uncertainty_score":0.85818714},"labels":[],"label_agreement":null},{"id":"W2394943030","doi":"","title":"Usefulness Evaluation on Visualization of Researcher Networks.","year":2011,"lang":"fr","type":"article","venue":"Ingénierie des systèmes d information","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Visualization; Computer science; Data science; Artificial intelligence","score_opus":0.1271827700784808,"score_gpt":0.33780143904747706,"score_spread":0.21061866896899625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2394943030","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007512673,0.0003543837,0.95341945,0.00006722452,0.0015009198,0.0005937237,0.000044808352,0.00010263321,0.036404204],"genre_scores_gemma":[0.9961342,0.0002160559,0.0019784386,0.00034449197,0.00012394803,0.00004258986,0.00050300517,0.000019895124,0.00063737977],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99665314,0.0005717143,0.0010662063,0.00022940178,0.0010628998,0.00041664674],"domain_scores_gemma":[0.9962877,0.00010009528,0.0007574625,0.00060805265,0.0020996723,0.00014703796],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0028634116,0.00023985335,0.00027475427,0.00053733634,0.00024066921,0.0003835305,0.0005984018,0.0002417794,0.0006462203],"category_scores_gemma":[0.0010085152,0.00025437583,0.000094685456,0.0017098555,0.00032135387,0.007415219,0.00018970922,0.00016266786,0.00024744147],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005446616,0.00021778735,0.0009997374,0.0004944506,0.00006536643,0.0000015871111,0.020761963,0.0067906417,0.0000058196174,0.7294538,0.0040213144,0.23713309],"study_design_scores_gemma":[0.0005888383,0.0003277841,0.012774815,0.0006755275,0.000056318982,0.000009337911,0.00063192984,0.9693991,0.0011647318,0.008155386,0.00593044,0.0002857747],"about_ca_topic_score_codex":0.00032017744,"about_ca_topic_score_gemma":0.000024127163,"teacher_disagreement_score":0.98862153,"about_ca_system_score_codex":0.0003590982,"about_ca_system_score_gemma":0.0003548337,"threshold_uncertainty_score":0.9999908},"labels":[],"label_agreement":null},{"id":"W2396435331","doi":"","title":"Visual motion in a railed shooter game: A designer study.","year":2013,"lang":"en","type":"article","venue":"Foundations of Digital Games","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Perception; Computer science; Motion (physics); Game design; Human–computer interaction; Visual perception; Focus (optics); Feeling; Communication design; Visualization; Sensory cue; Multimedia; Artificial intelligence; Psychology","score_opus":0.023857658885414763,"score_gpt":0.30403355255962905,"score_spread":0.2801758936742143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2396435331","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34757695,0.000008389846,0.6498241,0.00037282356,0.00008745317,0.0004210543,0.00000696625,0.00019085269,0.0015114252],"genre_scores_gemma":[0.9977488,0.0000014538493,0.0015204625,0.000057229016,0.0000144255,0.000029151104,0.000030921885,0.000010873161,0.0005866952],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990712,0.000034217243,0.00031657377,0.0002186569,0.00022191703,0.00013742704],"domain_scores_gemma":[0.99936664,0.00005660081,0.000089062196,0.0002929171,0.00014571956,0.000049059978],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009514437,0.00009355858,0.0001335781,0.00025565055,0.00002633507,0.00063202385,0.00036934577,0.000025707503,0.000056169163],"category_scores_gemma":[0.00014877485,0.000085263215,0.000040242227,0.00060815574,0.000043878343,0.002490279,0.00014694185,0.000044790966,0.00029202673],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017734938,0.010159105,0.3076937,0.00007640736,0.00019418671,0.000015132159,0.00956021,0.0014721956,0.0007264317,0.084349155,0.007588494,0.57814723],"study_design_scores_gemma":[0.0036769076,0.0010863042,0.44155407,0.00011530107,0.000034990997,0.000010620019,0.0027460482,0.5147663,0.00069670856,0.028248336,0.0060628797,0.0010015601],"about_ca_topic_score_codex":0.000024357327,"about_ca_topic_score_gemma":0.000015478476,"teacher_disagreement_score":0.6501718,"about_ca_system_score_codex":0.00002493156,"about_ca_system_score_gemma":0.00004467564,"threshold_uncertainty_score":0.6094621},"labels":[],"label_agreement":null},{"id":"W2399796084","doi":"","title":"Visualizing Stock Market Data with Self-Organizing Map.","year":2013,"lang":"en","type":"article","venue":"The Florida AI Research Society","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MacEwan University","funders":"","keywords":"Cluster analysis; Self-organizing map; Computer science; Visualization; Stock market; Data visualization; Stock (firearms); Unsupervised learning; Data mining; Data science; Artificial intelligence; Engineering; Geography","score_opus":0.09079074700080957,"score_gpt":0.38880200293762973,"score_spread":0.29801125593682015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2399796084","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0108408285,0.0005362559,0.9239428,0.053171683,0.0007301018,0.0021149672,0.00009424503,0.0014600927,0.0071090376],"genre_scores_gemma":[0.6502941,0.0022125354,0.2740502,0.024402857,0.0047524245,0.00036908564,0.0007498848,0.00040114793,0.042767737],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9966648,0.00039130248,0.00022465561,0.0006073634,0.0013798286,0.0007320158],"domain_scores_gemma":[0.9961552,0.00043034382,0.000063343214,0.0025724012,0.0005773219,0.00020140788],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0035077436,0.00016728314,0.00016177814,0.00005836381,0.0009231394,0.0015086813,0.0048468825,0.00006567715,0.00031602473],"category_scores_gemma":[0.00014541617,0.000105229774,0.000052872434,0.0015394862,0.00020716903,0.0019109913,0.0035862704,0.0006196867,0.00051382615],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000024684502,0.000059003214,0.0005240743,0.000053846612,0.000096961194,0.0000037603425,0.0022926063,0.000007615385,0.00021510193,0.009427371,0.9856362,0.001681041],"study_design_scores_gemma":[0.00039221055,0.0000878471,0.00092416344,0.000047975736,0.000013153542,0.000011999338,0.001438654,0.8165781,0.00029886223,0.0011837995,0.17875135,0.00027187032],"about_ca_topic_score_codex":0.00016948977,"about_ca_topic_score_gemma":0.000010616423,"teacher_disagreement_score":0.8165705,"about_ca_system_score_codex":0.00010168,"about_ca_system_score_gemma":0.0003187625,"threshold_uncertainty_score":0.9995279},"labels":[],"label_agreement":null},{"id":"W2400082606","doi":"","title":"User Task Adaptation in Multimedia Presentations.","year":2013,"lang":"en","type":"article","venue":"International Conference on User Modeling, Adaptation, and Personalization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland; University of British Columbia","funders":"","keywords":"Computer science; Presentation (obstetrics); Graphics; Multimedia; Adaptation (eye); Visualization; Reading (process); Scrolling; Set (abstract data type); Artificial intelligence; Linguistics; Computer graphics (images)","score_opus":0.09195351315500712,"score_gpt":0.3219189628515722,"score_spread":0.22996544969656507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2400082606","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011822702,0.00003749264,0.9833367,0.0019312424,0.00033445956,0.00033617928,0.000021019887,0.00010452213,0.0020756947],"genre_scores_gemma":[0.9767387,0.00037453763,0.019338416,0.0009768504,0.00009301798,0.00009015997,0.0006167292,0.000018701416,0.0017529234],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980473,0.00010909717,0.0004929311,0.0005229885,0.0006144274,0.00021326811],"domain_scores_gemma":[0.99849325,0.00007179978,0.00017910408,0.00023393378,0.00090247404,0.00011945741],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020928639,0.0002141934,0.00015992034,0.00045110547,0.00013374884,0.00062831724,0.00046906984,0.00009949595,0.0003695241],"category_scores_gemma":[0.00014986163,0.00022000195,0.000042106083,0.0003744679,0.00003732288,0.0022026324,0.00006970485,0.00013057726,0.000117661504],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002327894,0.00023650445,0.0051024184,0.000027074422,0.000047992802,0.0000032905418,0.016563779,0.13231276,0.00027541214,0.82938606,0.001935299,0.014086144],"study_design_scores_gemma":[0.0006835471,0.000035205838,0.0025346756,0.00005477695,0.000006532519,0.0000029046569,0.0017054686,0.98664075,0.000017869128,0.0068581332,0.0012191726,0.00024093753],"about_ca_topic_score_codex":0.00096268184,"about_ca_topic_score_gemma":0.00047956646,"teacher_disagreement_score":0.964916,"about_ca_system_score_codex":0.000063198124,"about_ca_system_score_gemma":0.00014961677,"threshold_uncertainty_score":0.89714193},"labels":[],"label_agreement":null},{"id":"W2401880028","doi":"","title":"A Framework for Capturing Distinguishing User Interaction Behaviors in Novel Interfaces.","year":2011,"lang":"en","type":"article","venue":"Educational Data Mining","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Human–computer interaction; User interface; Operating system","score_opus":0.23172724384943497,"score_gpt":0.41645990057115273,"score_spread":0.18473265672171776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2401880028","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034929283,0.000020000809,0.9626509,0.000485343,0.0012482072,0.00010361611,0.0001096985,0.00003858402,0.000414382],"genre_scores_gemma":[0.5060645,0.0000012588719,0.49292922,0.0001771363,0.00014089585,0.000016370797,0.0005208127,0.000008423875,0.0001413884],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99902654,0.000015500593,0.00026759048,0.00039358408,0.00013020655,0.00016658813],"domain_scores_gemma":[0.998895,0.0002624191,0.00013307652,0.0005880961,0.00006818442,0.000053259188],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003358545,0.000092214315,0.00009025406,0.00014523395,0.00008146568,0.00020640763,0.0011911502,0.00003989918,0.00006289037],"category_scores_gemma":[0.0011259861,0.00009977529,0.00001610183,0.00025384268,0.000018120352,0.0015658617,0.00046637552,0.00011386227,0.000012000084],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025903231,0.0014804258,0.095753044,0.000102989296,0.000057909077,0.0000039622983,0.06001732,0.00012360321,0.00044593873,0.79609084,0.011210622,0.03468744],"study_design_scores_gemma":[0.0019227952,0.00017776716,0.23632088,0.0028168173,0.0001175773,0.00008674599,0.01752225,0.6422043,0.0028746861,0.024138277,0.069490105,0.0023278184],"about_ca_topic_score_codex":0.00013632946,"about_ca_topic_score_gemma":0.000084205094,"teacher_disagreement_score":0.77195257,"about_ca_system_score_codex":0.000070051676,"about_ca_system_score_gemma":0.00016769054,"threshold_uncertainty_score":0.4068718},"labels":[],"label_agreement":null},{"id":"W2402245555","doi":"10.1145/2858036.2858488","title":"Egocentric Analysis of Dynamic Networks with EgoLines","year":2016,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":53,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Autodesk (Canada); University of Toronto","funders":"","keywords":"Subnetwork; Computer science; Social network analysis; Metaphor; Intelligence analysis; Human–computer interaction; TRACE (psycholinguistics); Visualization; Set (abstract data type); Domain (mathematical analysis); Visual analytics; Network analysis; Data science; Dynamic network analysis; Data visualization; Artificial intelligence; World Wide Web","score_opus":0.01212505991232214,"score_gpt":0.2873682652388568,"score_spread":0.2752432053265346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2402245555","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00041849483,0.00010439375,0.99721235,0.00027217297,0.00013287542,0.0000700444,0.00003048317,0.000103143284,0.0016560577],"genre_scores_gemma":[0.9670232,0.00047155438,0.0287702,0.0003016597,0.00004306067,0.0000050550475,0.00028028403,0.000014100161,0.0030908994],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99874365,0.000040803287,0.0003237682,0.00044228506,0.00027866053,0.00017080552],"domain_scores_gemma":[0.99827105,0.00005338861,0.00030641354,0.0010666747,0.00023076158,0.00007173338],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014227409,0.00016944243,0.00042078417,0.0006342752,0.000024993753,0.00010972534,0.0011686775,0.00010615674,0.00008424225],"category_scores_gemma":[0.000015329855,0.00010283475,0.00015328407,0.001743867,0.00004161285,0.00011058819,0.0009612403,0.00009858452,0.000006065844],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024125991,0.00050951634,0.03678924,0.0002503981,0.010009177,0.00004132379,0.0002993383,0.46827656,0.000012513148,0.40433684,0.0070245387,0.07242643],"study_design_scores_gemma":[0.000094258525,0.000011954229,0.0029568821,0.000040309184,0.0004196066,5.7965525e-7,0.0000035852145,0.9955029,0.000007138711,0.00052323216,0.0002758043,0.00016374447],"about_ca_topic_score_codex":0.000023542065,"about_ca_topic_score_gemma":0.000093712086,"teacher_disagreement_score":0.96844214,"about_ca_system_score_codex":0.000032353386,"about_ca_system_score_gemma":0.00008998056,"threshold_uncertainty_score":0.4193479},"labels":[],"label_agreement":null},{"id":"W2403157585","doi":"","title":"TweetViz: Following Twitter Hashtags to Support Storytelling.","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Visualization; Computer science; Zoom; Storytelling; Data science; World Wide Web; Social network analysis; Data visualization; Information visualization; Information retrieval; Social media; Data mining; Narrative","score_opus":0.03290436842139519,"score_gpt":0.3076754668991064,"score_spread":0.2747710984777112,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2403157585","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0030716774,0.0000018587355,0.97326887,0.0011631193,0.00039887262,0.000048246882,5.0111026e-7,0.00019591744,0.021850962],"genre_scores_gemma":[0.86220914,0.0000013333522,0.086389415,0.029149704,0.00015243482,0.000004033368,0.0000139143185,0.000014911719,0.022065097],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99907774,0.00002838916,0.00016328187,0.00027965492,0.00024389559,0.000207018],"domain_scores_gemma":[0.9992496,0.00003380571,0.00002691765,0.0004918803,0.00003623416,0.00016158045],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00033002143,0.00008939837,0.000110935456,0.00010336453,0.00006967284,0.00021349132,0.0006659318,0.000027668464,0.0001614755],"category_scores_gemma":[0.000048177757,0.000078291974,0.000063169995,0.00029136892,0.0000074586687,0.00031167717,0.00019357026,0.000043816606,0.0015138279],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000027298393,0.00015050644,0.0068537397,0.000018936858,0.00005074293,0.000023188766,0.0024106924,0.0004679677,0.0009791362,0.3120297,0.5918926,0.08512008],"study_design_scores_gemma":[0.00019378247,0.00010283578,0.00029902149,0.000008171611,0.000005879857,0.0000018833356,0.000025607624,0.103432305,0.0012837943,0.0005836988,0.8938394,0.00022361636],"about_ca_topic_score_codex":0.000008950503,"about_ca_topic_score_gemma":0.0000064948254,"teacher_disagreement_score":0.88687944,"about_ca_system_score_codex":0.000014284407,"about_ca_system_score_gemma":0.000026158252,"threshold_uncertainty_score":0.9992636},"labels":[],"label_agreement":null},{"id":"W2403466964","doi":"","title":"A software behaviour analysis framework based on the human perception systems.","year":2011,"lang":"en","type":"article","venue":"International Conference on Software Engineering","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Perception; Software; Software system; Software engineering; Human–computer interaction; Programming language; Psychology","score_opus":0.061963916777489775,"score_gpt":0.2996796333380656,"score_spread":0.2377157165605758,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2403466964","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008276887,0.0000028295635,0.9901204,0.00014231277,0.00046869545,0.00009285535,0.000038648457,0.00038371465,0.00047363545],"genre_scores_gemma":[0.9644044,0.0000029082569,0.03484565,0.00039496267,0.000066771434,0.0000321186,0.00007446228,0.000014370592,0.00016434414],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986125,0.000041909745,0.0002593405,0.0003552464,0.00054873904,0.0001822376],"domain_scores_gemma":[0.99886346,0.00014259822,0.000105809035,0.0005671999,0.00024108335,0.00007985518],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023587747,0.00018556682,0.00016044613,0.00041292937,0.00011518806,0.00034249417,0.0011853129,0.000082556544,0.0005516538],"category_scores_gemma":[0.00036161122,0.0001500252,0.00012746105,0.00051807164,0.000021572208,0.00023085711,0.00009964929,0.0002505172,0.00009463872],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000054597053,0.00016657273,0.028952932,0.000013510971,0.00021794302,0.000019838388,0.00076741725,0.034154654,0.000037206904,0.93448687,0.00036316575,0.00081445306],"study_design_scores_gemma":[0.00010647101,0.00006353406,0.038194023,0.00015873913,0.000050314404,0.0000016244071,0.00007847392,0.96035707,0.000054443502,0.00041650858,0.000260424,0.00025834792],"about_ca_topic_score_codex":0.000046012403,"about_ca_topic_score_gemma":0.0000030462065,"teacher_disagreement_score":0.9561275,"about_ca_system_score_codex":0.000092920236,"about_ca_system_score_gemma":0.000034987603,"threshold_uncertainty_score":0.611785},"labels":[],"label_agreement":null},{"id":"W2403494083","doi":"","title":"Interactive Dimensionality Reduction for Visual Analytics","year":2014,"lang":"en","type":"article","venue":"Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B))","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Dimensionality reduction; Visualization; Visual analytics; Data visualization; Focus (optics); Reduction (mathematics); Metric (unit); Interactive visual analysis; Curse of dimensionality; Analytics; Variable (mathematics); Data mining; Human–computer interaction; Machine learning; Mathematics","score_opus":0.01352812769843497,"score_gpt":0.24043666886151271,"score_spread":0.22690854116307774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2403494083","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16532494,0.00015801378,0.76602113,0.014449601,0.00047968913,0.0013541594,0.00042358573,0.00071814604,0.051070742],"genre_scores_gemma":[0.9751955,0.00017800872,0.004460384,0.0022698345,0.00019091462,0.000006911085,0.00044589143,0.000076744924,0.017175777],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9965723,0.0003731349,0.0004039545,0.0011508657,0.0005624003,0.00093731884],"domain_scores_gemma":[0.99654496,0.00079037214,0.00047823007,0.0009120788,0.0005243629,0.0007500139],"candidate_categories":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00069241814,0.0006244928,0.0007155082,0.0009384403,0.0018186411,0.0018440402,0.0027456733,0.00032133207,0.00007950574],"category_scores_gemma":[0.00030435697,0.00062891754,0.00041838727,0.0018823612,0.0006444741,0.0027029077,0.003574875,0.0004377115,0.00004002435],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018456896,0.0002635945,0.001229282,0.00009859858,0.00041133497,0.00013402778,0.028034735,0.001243142,0.00019290099,0.94657016,0.0068893465,0.013087215],"study_design_scores_gemma":[0.0067801024,0.0006444181,0.0043257778,0.00018878814,0.0004775178,0.00032726108,0.0044646924,0.19000988,0.001393175,0.02295128,0.76671696,0.0017201815],"about_ca_topic_score_codex":0.00027743325,"about_ca_topic_score_gemma":0.000036350855,"teacher_disagreement_score":0.92361885,"about_ca_system_score_codex":0.0012315755,"about_ca_system_score_gemma":0.0003450222,"threshold_uncertainty_score":0.9996162},"labels":[],"label_agreement":null},{"id":"W2404542298","doi":"10.5220/0005268000170028","title":"Supporting Event-based Geospatial Anomaly Detection with Geovisual Analytics","year":2015,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland; University of Regina","funders":"","keywords":"Geospatial analysis; Analytics; Anomaly detection; Computer science; Event (particle physics); Data science; Anomaly (physics); Data mining; Remote sensing; Geography; Physics","score_opus":0.02873025003845955,"score_gpt":0.3190142085016863,"score_spread":0.2902839584632268,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2404542298","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021724852,0.0000033503304,0.97678304,0.0001671383,0.00011091119,0.000067717694,0.000002913786,0.00021608979,0.0009239822],"genre_scores_gemma":[0.982545,2.9151184e-7,0.015941605,0.00068491534,0.000058059628,0.0000023872667,0.000025160713,0.000008668365,0.0007338749],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99878657,0.00004273238,0.00024537565,0.00027733122,0.0003954607,0.00025256118],"domain_scores_gemma":[0.9990612,0.00002327903,0.00013967052,0.00035047068,0.00022847348,0.00019685281],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003702508,0.000116373514,0.00012005541,0.00012918074,0.000077142366,0.00023548742,0.00035861693,0.0000401285,0.000030548523],"category_scores_gemma":[0.000076285396,0.00009251779,0.000034382585,0.00058692804,0.00002645037,0.0004826982,0.000085965345,0.00006650462,0.00006524042],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039388583,0.0030135459,0.27326405,0.00022031476,0.0005169394,0.00061756355,0.0034080923,0.2716961,0.004529307,0.1475424,0.034327846,0.26046997],"study_design_scores_gemma":[0.0005615848,0.00027551188,0.00066252885,0.000005476007,0.00001265848,0.000008161881,0.00008908399,0.98908484,0.005971853,0.000100205376,0.0030635823,0.00016448824],"about_ca_topic_score_codex":0.00011754556,"about_ca_topic_score_gemma":0.0004156239,"teacher_disagreement_score":0.9608414,"about_ca_system_score_codex":0.000046794616,"about_ca_system_score_gemma":0.00025215987,"threshold_uncertainty_score":0.3772766},"labels":[],"label_agreement":null},{"id":"W2406427913","doi":"10.1201/9781003059325-19","title":"Information Visualization Techniques for Exploring Oil Well Trajectories in Reservoir Models","year":2020,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Petroleum engineering; Visualization; Geology; Data science; Data mining","score_opus":0.09224389927520679,"score_gpt":0.30283166892655555,"score_spread":0.21058776965134876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2406427913","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[5.523639e-7,0.000018654953,0.74464476,0.00028351686,0.000114798204,0.00015514059,0.00002773458,0.00037062235,0.2543842],"genre_scores_gemma":[0.0050652814,0.0074482076,0.31072518,0.009180116,0.001166985,0.0008609594,0.007886305,0.00031662625,0.65735036],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986798,0.00001179801,0.0005698291,0.00025245512,0.0003272315,0.00015885234],"domain_scores_gemma":[0.9990846,0.000049088445,0.00021504151,0.0003602786,0.0002214699,0.00006951362],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020612129,0.0002357804,0.00027175143,0.0004104975,0.000063479354,0.00032118897,0.0006254124,0.00017170236,0.000024762187],"category_scores_gemma":[0.000044566616,0.00023779173,0.000080177386,0.000169682,0.000020436357,0.0040887245,0.0002228729,0.00012141654,0.00003817986],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000472571,0.0000057534207,8.925767e-7,0.00013719758,0.000007145681,6.16597e-7,0.00045119377,0.00025220576,0.0000019630515,0.985313,0.0037103025,0.010114996],"study_design_scores_gemma":[0.00016273189,0.000061285406,2.8693657e-7,0.00016931858,0.000008013071,7.755888e-7,0.000045670953,0.37803414,0.0005490127,0.072436966,0.5481996,0.0003322071],"about_ca_topic_score_codex":0.000015036469,"about_ca_topic_score_gemma":0.000032946067,"teacher_disagreement_score":0.91287607,"about_ca_system_score_codex":0.00009882144,"about_ca_system_score_gemma":0.00010080818,"threshold_uncertainty_score":0.9696865},"labels":[],"label_agreement":null},{"id":"W2410483946","doi":"10.1017/cbo9780511550881.011","title":"DISTRIBUTED OBSERVER CHAINS","year":2000,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Observer (physics); Computer science; Physics","score_opus":0.03254500024012271,"score_gpt":0.22006835640732791,"score_spread":0.1875233561672052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2410483946","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000004026063,0.000037065063,0.107667804,0.000032257838,0.0001479368,0.00014558532,0.00094723055,0.00029297004,0.89072514],"genre_scores_gemma":[0.00019402777,0.00015825119,0.00031506273,0.00023716196,0.000069265196,1.7186896e-7,0.0005564321,0.000023397975,0.9984462],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986447,0.000029629511,0.00018313661,0.00056800456,0.00030963332,0.0002648935],"domain_scores_gemma":[0.9984912,0.000029879444,0.00016357897,0.0009823323,0.0001237571,0.00020924261],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000062067265,0.00031335276,0.0003089164,0.0001509422,0.00017634941,0.00015594544,0.0015684685,0.0002572237,0.000016162665],"category_scores_gemma":[0.000005100061,0.00037288282,0.00018750608,0.000021769589,0.00012058125,0.00023226293,0.00063906383,0.0002761009,0.0000788971],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000060340435,0.000008889436,6.0128883e-7,0.000016917522,0.000054948912,0.00019575776,0.000014216808,0.000008053185,0.000001661367,0.92728406,0.07086977,0.0015391005],"study_design_scores_gemma":[0.00031570022,0.000022511744,0.00001169057,0.0000704763,0.000059895017,0.0000081989765,0.0000029646906,0.0058228443,0.00003877546,0.00003757864,0.9931975,0.00041186393],"about_ca_topic_score_codex":0.000036391968,"about_ca_topic_score_gemma":0.0000015252859,"teacher_disagreement_score":0.92724645,"about_ca_system_score_codex":0.00012979007,"about_ca_system_score_gemma":0.000118696946,"threshold_uncertainty_score":0.9998723},"labels":[],"label_agreement":null},{"id":"W2414646049","doi":"10.1111/cgf.12936","title":"Formalizing Emphasis in Information Visualization","year":2016,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; University of Calgary","funders":"","keywords":"Emphasis (telecommunications); Computer science; Visualization; Set (abstract data type); Information visualization; Point (geometry); Data science; Human–computer interaction; Artificial intelligence; Programming language; Mathematics","score_opus":0.014101237655204853,"score_gpt":0.268268665144024,"score_spread":0.2541674274888191,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2414646049","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0019152294,0.000015981335,0.99593604,0.0011580295,0.00038244348,0.000104291605,0.0000063884304,0.00019267587,0.000288929],"genre_scores_gemma":[0.97963613,0.00018229078,0.014547975,0.0054228343,0.00007180049,0.000013542136,0.00006732065,0.000013748033,0.000044330383],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99877995,0.000045899174,0.00039824366,0.00019820647,0.00026987802,0.00030783121],"domain_scores_gemma":[0.9992192,0.000053077783,0.0001314481,0.00039355175,0.00012483462,0.00007788584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028663245,0.00012914908,0.0001288455,0.00061245565,0.00009493381,0.0002509851,0.0006272205,0.0000709672,0.000007299682],"category_scores_gemma":[0.000028659882,0.000099106954,0.000058985028,0.0010762085,0.000033185042,0.0039829044,0.00031765376,0.00004869811,0.000068476904],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016280263,0.000027868358,0.0092948405,0.000009687793,0.0000057134266,0.0000016135169,0.00021628245,0.000020605296,0.0000111510835,0.90912557,0.0032334267,0.078051634],"study_design_scores_gemma":[0.0012329554,0.00010350337,0.0073823296,0.00013970141,0.000004059431,0.000013147222,0.000027610886,0.83590335,0.0004871339,0.01849438,0.13582174,0.0003900771],"about_ca_topic_score_codex":0.000009031487,"about_ca_topic_score_gemma":0.000021777645,"teacher_disagreement_score":0.98138803,"about_ca_system_score_codex":0.00003807763,"about_ca_system_score_gemma":0.000038601334,"threshold_uncertainty_score":0.40414643},"labels":[],"label_agreement":null},{"id":"W2460509427","doi":"10.29173/cais220","title":"Information Visualization User Testing guided by BASSTEP Approach to Design: Preliminary Results","year":2013,"lang":"fr","type":"article","venue":"Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Novelty; Visualization; Computer science; Psychology; Artificial intelligence","score_opus":0.060588860927256905,"score_gpt":0.28081456009188355,"score_spread":0.22022569916462664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2460509427","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14054357,0.00048254852,0.78981763,0.020857936,0.0011399831,0.0042943573,0.0013769714,0.0003529138,0.041134074],"genre_scores_gemma":[0.95939726,0.00009241788,0.03512501,0.0017674791,0.000112070826,0.00007610632,0.000091772796,0.000034709818,0.00330317],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99662405,0.00009756366,0.0013632756,0.0004330597,0.0008793453,0.0006027002],"domain_scores_gemma":[0.9202102,0.00028021052,0.0016910158,0.0004121858,0.077095784,0.0003106065],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0013899116,0.0004141941,0.0005176184,0.0003053571,0.00023168564,0.008547649,0.0028989092,0.00027072322,0.000019378664],"category_scores_gemma":[0.0429756,0.00036501078,0.00012187248,0.0018675721,0.00030509837,0.04020827,0.0013543998,0.00024616567,0.00004704234],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026045894,0.00095086056,0.009745758,0.0018695872,0.00018463285,5.100785e-7,0.09747657,0.0014467834,0.006642307,0.13612331,0.6999259,0.04537333],"study_design_scores_gemma":[0.0015522689,0.0014605336,0.013580622,0.0015488777,0.00018387943,0.000065218584,0.0040485165,0.7144832,0.027057098,0.0034660755,0.23152813,0.0010255498],"about_ca_topic_score_codex":0.00067750795,"about_ca_topic_score_gemma":0.0000013656805,"teacher_disagreement_score":0.8188537,"about_ca_system_score_codex":0.00010649,"about_ca_system_score_gemma":0.0004392882,"threshold_uncertainty_score":0.9998802},"labels":[],"label_agreement":null},{"id":"W2464003720","doi":"10.1111/cgf.12887","title":"Comparing Bar Chart Authoring with Microsoft Excel and Tangible Tiles","year":2016,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures","keywords":"Visualization; Computer science; Bar chart; Pipeline (software); Pie chart; Software; Human–computer interaction; Chart; Software visualization; Information visualization; Task (project management); Data science; Computer graphics (images); Software development; Data mining; Programming language; Component-based software engineering","score_opus":0.023054215843797,"score_gpt":0.25007970041044075,"score_spread":0.22702548456664376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2464003720","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018848922,0.00009528748,0.9787353,0.0015816605,0.00023128968,0.00008187319,0.000005770614,0.00022443093,0.00019542914],"genre_scores_gemma":[0.9697294,0.00010067905,0.028762033,0.0010601513,0.00009568559,0.0000048504025,0.000007715629,0.000020537242,0.00021890408],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99876755,0.000027551188,0.00019741307,0.0004322414,0.00020993003,0.00036531835],"domain_scores_gemma":[0.99914145,0.000063176216,0.000081451064,0.00047421642,0.000084991145,0.00015471129],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017098177,0.00017497246,0.0001962991,0.00019760942,0.00021262275,0.00031959784,0.0005970446,0.000049498623,0.0000047354147],"category_scores_gemma":[0.0000053861254,0.00011837303,0.00004289905,0.0003616362,0.0001153791,0.00063279073,0.0005530424,0.000077945435,0.000024247074],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005523186,0.000059377006,0.08796993,0.000034792465,0.000051382372,0.000018583834,0.00024509712,0.000013824721,0.0005152241,0.88908094,0.008080215,0.0139251],"study_design_scores_gemma":[0.002991642,0.00049960555,0.04038618,0.0008086363,0.000042170577,0.0001950883,0.000061806975,0.78065777,0.0040508034,0.015235371,0.15360685,0.001464092],"about_ca_topic_score_codex":0.000004997081,"about_ca_topic_score_gemma":0.000013604863,"teacher_disagreement_score":0.9508805,"about_ca_system_score_codex":0.00001269782,"about_ca_system_score_gemma":0.000027685839,"threshold_uncertainty_score":0.4827112},"labels":[],"label_agreement":null},{"id":"W2465065115","doi":"10.14236/ewic/ndm2009.28","title":"IMAGE: A Computer-Aided Cognition Capability for Understanding Complex Systems","year":2009,"lang":"en","type":"article","venue":"Electronic workshops in computing","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Defence Research and Development Canada","funders":"","keywords":"Computer science; Cognition; Set (abstract data type); Originality; Representation (politics); Comprehension; Human–computer interaction; Data science; Visualization; Cognitive computing; Empirical research; Image (mathematics); Artificial intelligence; Knowledge management","score_opus":0.05218811282895547,"score_gpt":0.3246837335014053,"score_spread":0.2724956206724498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2465065115","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0025698496,0.000119732984,0.9948855,0.0008509609,0.00028980072,0.000523506,0.000003958862,0.00030749562,0.00044919815],"genre_scores_gemma":[0.9407736,0.000008604989,0.05835772,0.00054105395,0.0002108721,0.0000053860585,0.00007568337,0.0000126950445,0.000014374532],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99751854,0.00016647905,0.00059210794,0.00061902584,0.00027529348,0.000828558],"domain_scores_gemma":[0.9986579,0.00046693487,0.0002161264,0.0004444431,0.00012565787,0.000088926085],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0012471639,0.00022749328,0.00034924503,0.00022261441,0.00029285398,0.0005650041,0.0007173903,0.00009111278,0.0000040897103],"category_scores_gemma":[0.000103316685,0.00024895623,0.00009487064,0.0009771897,0.000047342975,0.00043999456,0.00012668184,0.00030203298,0.000006493178],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025393847,0.00032922474,0.00020715833,0.00010313067,0.00004066359,0.000009956604,0.000698783,0.017230576,0.00053146516,0.94415647,0.0034828694,0.033184323],"study_design_scores_gemma":[0.00086255925,0.00015494545,0.0006073002,0.00013372708,0.000009288273,0.000018029676,0.000118496726,0.9652326,0.000024326571,0.032110196,0.0004540561,0.00027444202],"about_ca_topic_score_codex":0.000008168623,"about_ca_topic_score_gemma":0.00001642252,"teacher_disagreement_score":0.94800204,"about_ca_system_score_codex":0.0006661099,"about_ca_system_score_gemma":0.00015905374,"threshold_uncertainty_score":0.99999624},"labels":[],"label_agreement":null},{"id":"W2468977341","doi":"10.1111/cgf.12909","title":"PhysioEx: Visual Analysis of Physiological Event Streams","year":2016,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Ontario Tech University; Hospital for Sick Children","funders":"","keywords":"Computer science; Workflow; Data stream mining; Visualization; STREAMS; Dashboard; Event (particle physics); Data mining; Data visualization; Field (mathematics); Domain (mathematical analysis); Real-time computing; Artificial intelligence; Data science; Database","score_opus":0.01999936097246021,"score_gpt":0.30075985366494323,"score_spread":0.28076049269248304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2468977341","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037240263,0.000021093334,0.9617674,0.00054106617,0.00019709636,0.00005909416,0.00002800097,0.00011003346,0.000035997084],"genre_scores_gemma":[0.9950868,0.00006140463,0.003840321,0.0008653528,0.000050470313,0.0000029498613,0.000037553655,0.0000067396118,0.0000483983],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99846935,0.00007649577,0.0003689717,0.0004392361,0.00034333626,0.00030262803],"domain_scores_gemma":[0.99879706,0.00010029482,0.00019206165,0.00063811627,0.00015753484,0.0001149302],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015829859,0.00016623782,0.00036333533,0.0004873915,0.00007540448,0.000056950943,0.00094911386,0.000070114795,0.000026143614],"category_scores_gemma":[0.000014482947,0.00010577855,0.00036294106,0.002134526,0.00012002073,0.00032263546,0.0005872986,0.000058532634,0.000018981087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000059445942,0.00052488205,0.008829121,0.0000132255245,0.000868401,0.0000059156573,0.00008199349,0.00034877154,0.001800447,0.9144181,0.0071246596,0.065978505],"study_design_scores_gemma":[0.0003954043,0.000291239,0.030304106,0.00003488584,0.00013420152,0.0000010304932,0.000007820368,0.95670766,0.0011980992,0.007577136,0.0030729629,0.0002754801],"about_ca_topic_score_codex":0.000008179456,"about_ca_topic_score_gemma":0.0000068607746,"teacher_disagreement_score":0.95792705,"about_ca_system_score_codex":0.000014415437,"about_ca_system_score_gemma":0.000028745528,"threshold_uncertainty_score":0.4313524},"labels":[],"label_agreement":null},{"id":"W2470422954","doi":"10.1111/cgf.12919","title":"ConToVi: Multi‐Party Conversation Exploration using Topic‐Space Views","year":2016,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":75,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Conversation; Computer science; Glyph (data visualization); Metaphor; Visual analytics; Space (punctuation); Human–computer interaction; Visualization; Artificial intelligence; Natural language processing; Linguistics","score_opus":0.09749530294172569,"score_gpt":0.3216399128599146,"score_spread":0.2241446099181889,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2470422954","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015024681,0.00004756808,0.9934637,0.0037133994,0.0008729204,0.00016454268,0.000007778922,0.00018779322,0.00003985185],"genre_scores_gemma":[0.7861793,0.00029804878,0.20602225,0.006412329,0.0003946424,0.000017692544,0.000068007546,0.00003930802,0.00056843454],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986884,0.00009402298,0.00030287151,0.0003885509,0.0002455902,0.00028053552],"domain_scores_gemma":[0.998899,0.00006405499,0.0001714523,0.0005647652,0.00018923363,0.0001115149],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023616098,0.00016111707,0.00017305161,0.00019193973,0.00015677299,0.00021845281,0.00053666584,0.00007920546,0.000010551665],"category_scores_gemma":[0.000023645624,0.00012149657,0.000090730144,0.00043285606,0.00006584902,0.0016791361,0.00026603614,0.00006270051,0.00005248598],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000040032965,0.00010381625,0.005770903,0.000019139467,0.000035302164,0.000006467653,0.00091516605,0.00008972147,0.0010830426,0.9546092,0.007958841,0.029404365],"study_design_scores_gemma":[0.0008751201,0.00006060817,0.0005246928,0.000059178878,0.000009521893,0.000005459769,0.000035745346,0.9343863,0.0013038715,0.005795002,0.056673985,0.00027049438],"about_ca_topic_score_codex":0.000013542153,"about_ca_topic_score_gemma":0.00004142982,"teacher_disagreement_score":0.9488142,"about_ca_system_score_codex":0.000042238233,"about_ca_system_score_gemma":0.000048952534,"threshold_uncertainty_score":0.49544862},"labels":[],"label_agreement":null},{"id":"W2471720700","doi":"10.1080/13658816.2016.1199806","title":"Visual analytics of delays and interaction in movement data","year":2016,"lang":"en","type":"article","venue":"International Journal of Geographical Information Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Computer science; Dynamic time warping; Matching (statistics); Similarity (geometry); Visualization; Pairwise comparison; Computation; Analytics; Artificial intelligence; Algorithm; Computer vision; Data mining; Mathematics","score_opus":0.0300698169696727,"score_gpt":0.3308251255199067,"score_spread":0.300755308550234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2471720700","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037771124,0.000058322436,0.9594274,0.0013023472,0.0010213105,0.000070206945,0.000053988406,0.000010339987,0.00028494405],"genre_scores_gemma":[0.9985915,0.00027700386,0.00084294926,0.00019904271,0.000059451526,6.381576e-7,0.000019719102,0.0000018747412,0.000007867412],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99809396,0.000052050917,0.0010471694,0.00008001023,0.0006452719,0.00008151777],"domain_scores_gemma":[0.9981102,0.000118984986,0.00079472415,0.00019663716,0.00071287376,0.0000665982],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008654575,0.00007125486,0.00016159813,0.00085710624,0.000013663356,0.000183829,0.0008896381,0.00004385065,0.000007556949],"category_scores_gemma":[0.00019740654,0.00004839086,0.000040457973,0.00031010062,0.00004172845,0.0042887074,0.00028722832,0.00007550522,0.0000041205917],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002838107,0.0007084756,0.20807678,0.00015340639,0.0009443525,0.000040371782,0.0015610128,0.0037719507,0.0015063774,0.5331795,0.005084217,0.24468972],"study_design_scores_gemma":[0.0035479306,0.00038619436,0.032408115,0.001050675,0.00003115997,0.0002574612,0.0009200394,0.90840775,0.00054552907,0.0018421634,0.050284874,0.00031811083],"about_ca_topic_score_codex":0.000038757764,"about_ca_topic_score_gemma":0.000007176752,"teacher_disagreement_score":0.9608203,"about_ca_system_score_codex":0.000039346338,"about_ca_system_score_gemma":0.000048990074,"threshold_uncertainty_score":0.31092092},"labels":[],"label_agreement":null},{"id":"W2477444080","doi":"10.4018/978-1-4666-2979-0.ch020","title":"Agent-Based Wellness Indicator","year":2013,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Visualization; Computer science; Software; Human–computer interaction; Process management; Engineering; Data mining","score_opus":0.022427886932664797,"score_gpt":0.26772077403389066,"score_spread":0.24529288710122588,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2477444080","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000003294399,0.00006355553,0.14577428,0.0001330397,0.0005192206,0.00018976149,0.00012354032,0.00026746638,0.85292584],"genre_scores_gemma":[0.069993496,0.000012687642,0.015668605,0.018052533,0.00077377015,0.000044996887,0.00017098026,0.00015013489,0.8951328],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99822235,0.000019754718,0.00035552686,0.0005742173,0.0005317283,0.00029644673],"domain_scores_gemma":[0.9983347,0.000021338494,0.00027966287,0.0010259207,0.00007964782,0.00025869455],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009272342,0.00035406195,0.00032789353,0.000108147084,0.000101917925,0.00039838796,0.0015217175,0.00029408874,0.00030620632],"category_scores_gemma":[0.000010561952,0.0003400389,0.00016808162,0.00003412503,0.00008782399,0.00011018054,0.0003651864,0.00017356343,0.004676959],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010325538,0.000009451462,0.0000044145295,0.000020701751,0.000028413935,0.00002890733,0.000009423313,0.0000029420678,0.0000014113534,0.9537055,0.03272333,0.013464465],"study_design_scores_gemma":[0.00038398636,0.0000540264,0.000014333032,0.00013434998,0.00004516509,0.000010513033,0.0000018667497,0.0051453644,0.00014813106,0.24659665,0.7467557,0.00070992636],"about_ca_topic_score_codex":0.000021583766,"about_ca_topic_score_gemma":0.000008396492,"teacher_disagreement_score":0.71403235,"about_ca_system_score_codex":0.00013192491,"about_ca_system_score_gemma":0.00032978284,"threshold_uncertainty_score":0.99990517},"labels":[],"label_agreement":null},{"id":"W2481070351","doi":"10.4018/978-1-4666-0137-6.ch004","title":"Importance of Interface Design in e-Learning Tools","year":2012,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Interface (matter); Representation (politics); Human–computer interaction; Externalization; Interface design; Focus (optics); Software engineering; Psychology","score_opus":0.049451853606836835,"score_gpt":0.3005039695463428,"score_spread":0.25105211593950594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2481070351","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000016388922,0.00033910712,0.35520864,0.000016064665,0.00013868179,0.00013164859,0.000019744717,0.00006782305,0.6440619],"genre_scores_gemma":[0.72147083,0.000108017586,0.059147242,0.0010777502,0.00031876317,0.00001636344,0.000029509984,0.000115610106,0.21771589],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986361,0.000037996128,0.0004603097,0.00032997952,0.00029175883,0.00024382897],"domain_scores_gemma":[0.9989216,0.000053765165,0.00035274684,0.0004987361,0.000080161815,0.00009303609],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029757034,0.00023037185,0.00034922085,0.000082511506,0.000025131689,0.000098216966,0.0008374173,0.00016027938,0.000029291767],"category_scores_gemma":[0.000052332172,0.00023579516,0.00008279658,0.00004268695,0.00005032399,0.0002030368,0.00035767374,0.00022208125,0.00009104862],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000038953394,0.000007802845,0.00016582254,0.000016802698,0.00001665559,0.000011422407,0.000080779784,0.00011373901,0.00001852716,0.99012256,0.0006231677,0.0088188285],"study_design_scores_gemma":[0.00174663,0.0005809911,0.00055634155,0.0023274946,0.00014402434,0.000112079724,0.0000693195,0.030863436,0.0025238458,0.6373654,0.3207101,0.0030003204],"about_ca_topic_score_codex":0.000008230225,"about_ca_topic_score_gemma":0.000016821981,"teacher_disagreement_score":0.72145444,"about_ca_system_score_codex":0.00011173355,"about_ca_system_score_gemma":0.00013312718,"threshold_uncertainty_score":0.96154475},"labels":[],"label_agreement":null},{"id":"W2485852301","doi":"10.1007/978-3-319-39513-5_17","title":"MEseum: Personalized Experience with Narrative Visualization for Museum Visitors","year":2016,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Narrative; Visualization; World Wide Web; Computer graphics (images); Human–computer interaction; Multimedia; Artificial intelligence; Art; Literature","score_opus":0.020553346130928803,"score_gpt":0.30366115038489244,"score_spread":0.28310780425396365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2485852301","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00003091512,0.000086331725,0.99645054,0.0007861929,0.0008970704,0.00056019134,0.000021951098,0.00018202605,0.0009848031],"genre_scores_gemma":[0.29434887,0.0002181443,0.6856124,0.0076160375,0.002083986,0.00018733718,0.00013597279,0.00026106864,0.0095361965],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99618167,0.00003999326,0.0004955266,0.0015961468,0.0010893121,0.00059736],"domain_scores_gemma":[0.9973375,0.0003801881,0.00041055694,0.001032315,0.00063167803,0.0002077506],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005110208,0.0005464734,0.0005238689,0.00071322307,0.00043284695,0.0007006594,0.002515969,0.00022887919,0.000046335892],"category_scores_gemma":[0.00013599242,0.00039402168,0.000114816205,0.0007181014,0.0009144106,0.0012349837,0.0005593286,0.0002125024,0.000013439137],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000640897,0.0000971901,0.00014339994,0.00011787931,0.00006049642,0.00005357353,0.026605679,0.0037765033,0.00047684388,0.8038481,0.00022763414,0.16452864],"study_design_scores_gemma":[0.0018988021,0.0008877974,0.00004358991,0.0014100227,0.000028813061,0.00007018813,0.000014221811,0.87554556,0.003431718,0.08842865,0.026206637,0.0020339927],"about_ca_topic_score_codex":0.0000037697796,"about_ca_topic_score_gemma":0.00002368886,"teacher_disagreement_score":0.8717691,"about_ca_system_score_codex":0.00026936314,"about_ca_system_score_gemma":0.0006074091,"threshold_uncertainty_score":0.99985117},"labels":[],"label_agreement":null},{"id":"W2486745298","doi":"10.4018/978-1-61350-441-3.ch002","title":"Interactivity of Information Representations in e-Learning Environments","year":2011,"lang":"en","type":"book-chapter","venue":"Advances in game-based learning book series","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Interactivity; Affordance; Computer science; Human–computer interaction; Context (archaeology); Information flow; Multimedia","score_opus":0.012348888675659956,"score_gpt":0.2700821481207247,"score_spread":0.2577332594450647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2486745298","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00018243252,0.0015122688,0.6130002,0.00015232826,0.00037911226,0.00047948846,0.000020946161,0.00018239632,0.38409084],"genre_scores_gemma":[0.31113428,0.031164482,0.047384035,0.0012802164,0.00015664478,0.00016696523,0.0021433763,0.00023298567,0.606337],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984233,0.000102850645,0.0006373479,0.00031682933,0.00032360383,0.00019607326],"domain_scores_gemma":[0.9985856,0.0001708578,0.0007729443,0.000380421,0.000044615223,0.00004556272],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002779775,0.00024319194,0.00034809366,0.00057198387,0.000059449943,0.0000738027,0.000458742,0.00013298946,0.0001827824],"category_scores_gemma":[0.00024974762,0.00027459132,0.00007306074,0.00013000733,0.0001788489,0.0059351963,0.00019661077,0.0006713396,0.00006171255],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018226965,0.0001579307,0.017367747,0.00045354763,0.00005007894,0.000043886717,0.007058487,0.24643005,0.000091513124,0.59650314,0.00007441191,0.13158695],"study_design_scores_gemma":[0.0004234843,0.0001784105,0.0006065378,0.00055137277,0.000009494935,0.0000024329784,0.00010330653,0.009281631,0.0005652337,0.004082393,0.98385024,0.0003454839],"about_ca_topic_score_codex":0.000019684441,"about_ca_topic_score_gemma":0.000038822403,"teacher_disagreement_score":0.9837758,"about_ca_system_score_codex":0.000105486615,"about_ca_system_score_gemma":0.00009320198,"threshold_uncertainty_score":0.9999706},"labels":[],"label_agreement":null},{"id":"W2491094990","doi":"","title":"Augmenting the Visual Presentation of Web Search Results.","year":2011,"lang":"en","type":"article","venue":"Int. J. Web Appl.","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Information retrieval; Web search query; Search engine; Visualization; Redundancy (engineering); Relevance (law); Presentation (obstetrics); Process (computing); Web page; Web query classification; Visual search; World Wide Web; Data mining; Artificial intelligence","score_opus":0.06072689162779663,"score_gpt":0.33761904733490866,"score_spread":0.276892155707112,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2491094990","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11495465,0.00010402444,0.77757806,0.002094872,0.00085332507,0.00072518096,0.000081952734,0.00037557495,0.10323239],"genre_scores_gemma":[0.99471,0.00003856143,0.004302171,0.00020542995,0.000059592225,0.0000060932193,0.000019387526,0.0000066138227,0.0006521261],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988873,0.00008948533,0.00029025454,0.00021196097,0.00035366573,0.0001673044],"domain_scores_gemma":[0.99925643,0.00007626426,0.00011768339,0.0003825506,0.00012282697,0.00004422148],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006343903,0.000074057796,0.0000871132,0.00008386871,0.0000882798,0.00008652006,0.00073632464,0.000033695895,0.000052784773],"category_scores_gemma":[0.00007140179,0.000054680208,0.000038904946,0.00045345744,0.00007447545,0.00027394042,0.0003372855,0.00009177694,0.0001024544],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000119905766,0.0010702616,0.007383019,0.00016250343,0.00020807341,0.00002566371,0.022483783,0.00024968726,0.03707003,0.6878323,0.12708299,0.11631178],"study_design_scores_gemma":[0.0010761591,0.00014744967,0.0035421017,0.000048455502,0.000020504393,0.000005716231,0.0009253149,0.8747891,0.07434856,0.0014619651,0.043386478,0.00024815238],"about_ca_topic_score_codex":0.000073295894,"about_ca_topic_score_gemma":0.000018136021,"teacher_disagreement_score":0.8797554,"about_ca_system_score_codex":0.000011997674,"about_ca_system_score_gemma":0.00008480712,"threshold_uncertainty_score":0.22297941},"labels":[],"label_agreement":null},{"id":"W2492792645","doi":"10.1007/978-3-319-27261-0","title":"Graph Drawing and Network Visualization","year":2015,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Graph drawing; Computer science; Visualization; Graph; Computer graphics (images); Theoretical computer science; Artificial intelligence","score_opus":0.019619820959499268,"score_gpt":0.2916749105686302,"score_spread":0.27205508960913094,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2492792645","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000010197333,0.00060595345,0.9960923,0.00020148407,0.0012514873,0.00017669259,0.0000032950309,0.00016487896,0.0014936941],"genre_scores_gemma":[0.028675698,0.0004790268,0.9507506,0.012818321,0.003621639,0.000016954322,0.00022855634,0.00013178443,0.0032774138],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997039,0.00007109399,0.00040093125,0.0010836981,0.00088238856,0.00052283844],"domain_scores_gemma":[0.998222,0.00019872481,0.00022776495,0.00083402783,0.0002980358,0.00021944485],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0012673765,0.00033766567,0.00038937977,0.0006110704,0.00024849907,0.0011029056,0.0018999873,0.00021314855,0.0000043627483],"category_scores_gemma":[0.0001441803,0.000318271,0.00004792811,0.001994425,0.00042654795,0.00087752036,0.0013712477,0.00032419234,0.000015113753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000049620894,0.00007642161,0.0007321339,0.0001502869,0.00002871684,0.000095399264,0.0025940237,0.17899767,0.00001954305,0.17594475,0.012920888,0.6284352],"study_design_scores_gemma":[0.00016550554,0.00006351963,0.000052206102,0.00022459481,0.000006407078,0.000023925764,1.3725796e-7,0.8057956,0.00002967186,0.18504874,0.008203554,0.0003861538],"about_ca_topic_score_codex":0.0000066474868,"about_ca_topic_score_gemma":0.000031096708,"teacher_disagreement_score":0.6280491,"about_ca_system_score_codex":0.00019719008,"about_ca_system_score_gemma":0.0009937419,"threshold_uncertainty_score":0.999934},"labels":[],"label_agreement":null},{"id":"W2497892641","doi":"10.4018/978-1-60960-521-6.ch001","title":"Visual Support for Use Case Modeling","year":2011,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Use Case Diagram; Unified Modeling Language; Focus (optics); Comprehension; Activity diagram; De facto; Story-driven modeling; Human–computer interaction; Class diagram; Artificial intelligence; Programming language; Software","score_opus":0.07872606198966618,"score_gpt":0.32024019312398583,"score_spread":0.24151413113431963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2497892641","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000005718865,0.000012368479,0.5736666,0.000006049317,0.00028422027,0.00018487043,0.00025906393,0.00014799272,0.42543316],"genre_scores_gemma":[0.14793642,0.000027261269,0.1295919,0.007941884,0.001288908,0.00007103904,0.00033090194,0.0003000505,0.71251166],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983741,0.000009535791,0.00042445646,0.0006010978,0.00026593168,0.00032485538],"domain_scores_gemma":[0.99867356,0.000025176718,0.00018169067,0.0006719833,0.00023205008,0.00021552373],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013373118,0.00034484122,0.00033741677,0.000086922344,0.0001287256,0.00035999547,0.00064381916,0.00027170914,0.000028981156],"category_scores_gemma":[0.000016106793,0.00035054664,0.00022073997,0.000019766252,0.000040027153,0.00026197004,0.0003815173,0.0001230138,0.00014233687],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000061212245,0.000010761526,9.982793e-7,0.00002105002,0.00004408006,0.0005193828,0.000038402548,0.000025772448,4.5424684e-7,0.9889663,0.0029499598,0.007416754],"study_design_scores_gemma":[0.0004807742,0.00020854482,1.0884435e-7,0.00008926999,0.00011861114,0.0011946396,0.0000055732867,0.4975048,0.00001459091,0.36693385,0.13262534,0.0008238905],"about_ca_topic_score_codex":0.00007650396,"about_ca_topic_score_gemma":0.00007058279,"teacher_disagreement_score":0.6220324,"about_ca_system_score_codex":0.00008819928,"about_ca_system_score_gemma":0.00024892524,"threshold_uncertainty_score":0.9998947},"labels":[],"label_agreement":null},{"id":"W2501350279","doi":"10.1201/9780203883020.ch80","title":"Flood risk map perception through experimental graphic semiology","year":2008,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université TÉLUQ","funders":"","keywords":"Semiology; Flood myth; Perception; Cartography; Geography; Computer science; Psychology; Archaeology; Neuroscience","score_opus":0.03620219750715225,"score_gpt":0.2932164911167012,"score_spread":0.2570142936095489,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2501350279","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00003084296,0.00058367685,0.37108424,0.00017602852,0.00055413693,0.00014890757,0.000044770604,0.00034988622,0.6270275],"genre_scores_gemma":[0.0090847,0.009360678,0.041518413,0.003974352,0.00047191008,0.000010926801,0.00076936866,0.00007939513,0.93473023],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985549,0.000039018116,0.00033703976,0.0005944355,0.00026664595,0.00020797322],"domain_scores_gemma":[0.9989353,0.000029290648,0.00019844886,0.00070064975,0.00006008337,0.00007621964],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000086608365,0.00029178857,0.00030801757,0.00014233,0.00016800783,0.00006970624,0.00071472744,0.00029145885,0.0013565996],"category_scores_gemma":[0.000006400583,0.000262329,0.00018196886,0.000050400136,0.00013174412,0.000356356,0.00032831906,0.0002443142,0.0013628888],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000190891,0.000050655235,0.000028121287,0.000008574421,0.000057680794,0.000021022304,0.00059046724,0.000008374155,0.000041662177,0.8877498,0.110256836,0.0011849221],"study_design_scores_gemma":[0.0003675165,0.00018570435,0.00004653835,0.000039264105,0.000030628125,0.000075216456,0.00007149164,0.009613968,0.00010566586,0.012672347,0.9761412,0.0006504713],"about_ca_topic_score_codex":0.00002732388,"about_ca_topic_score_gemma":0.000008719226,"teacher_disagreement_score":0.8750774,"about_ca_system_score_codex":0.00004573023,"about_ca_system_score_gemma":0.000046793033,"threshold_uncertainty_score":0.9999829},"labels":[],"label_agreement":null},{"id":"W2507410144","doi":"10.1007/s11257-016-9179-5","title":"Prediction of individual learning curves across information visualizations","year":2016,"lang":"en","type":"article","venue":"User Modeling and User-Adapted Interaction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visualization; Computer science; Leverage (statistics); Learning curve; Human–computer interaction; Data visualization; Creative visualization; Task (project management); Information visualization; Artificial intelligence; Machine learning","score_opus":0.05117400973619895,"score_gpt":0.3188817769460247,"score_spread":0.26770776720982575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2507410144","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06985585,0.000039426446,0.929121,0.0003078172,0.00023400666,0.00008124739,0.000049903858,0.00017857067,0.00013218766],"genre_scores_gemma":[0.9969111,0.0007144589,0.0017556734,0.00024069031,0.00003439486,0.0000067566843,0.00016176283,0.000007870894,0.00016729913],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988594,0.00006722401,0.00043773084,0.00018277882,0.0003003434,0.00015248836],"domain_scores_gemma":[0.9991437,0.00006007267,0.0002220241,0.0001953758,0.0003186457,0.00006013417],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033253655,0.00011224219,0.0001279113,0.00016939075,0.00017588548,0.0001761284,0.00021350603,0.00006643658,0.000016961983],"category_scores_gemma":[0.00020480467,0.00008954827,0.0000366485,0.0002894673,0.000021350344,0.004106588,0.00014092641,0.00010062627,0.000013563043],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025003913,0.0010161345,0.036775384,0.0012807765,0.00078590575,0.0000036385982,0.037216417,0.26729617,0.015957251,0.20959997,0.02540121,0.4044171],"study_design_scores_gemma":[0.0003880661,0.000085490414,0.00064273644,0.00046568556,0.00001900926,0.000006833389,0.0004695602,0.98528683,0.0007160835,0.000116730815,0.011687234,0.00011574356],"about_ca_topic_score_codex":0.00003474566,"about_ca_topic_score_gemma":0.000008103229,"teacher_disagreement_score":0.9273653,"about_ca_system_score_codex":0.000029976334,"about_ca_system_score_gemma":0.000029619974,"threshold_uncertainty_score":0.36516726},"labels":[],"label_agreement":null},{"id":"W2507669734","doi":"10.1007/978-3-319-45823-6_88","title":"evoVision3D: A Multiscale Visualization of Evolutionary Histories","year":2016,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Visualization; Theoretical computer science; Artificial intelligence; Computer graphics (images)","score_opus":0.01712727842739933,"score_gpt":0.28041394531504127,"score_spread":0.26328666688764196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2507669734","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000054103493,0.0003776587,0.99436,0.00034773347,0.001231666,0.00017499321,0.000023810671,0.000110312176,0.0033684073],"genre_scores_gemma":[0.24392211,0.00037783413,0.7427259,0.0020591891,0.0010600785,0.000013774788,0.00009552095,0.00011748841,0.009628077],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997048,0.00003414206,0.00059578975,0.0009489537,0.0010325358,0.0003405382],"domain_scores_gemma":[0.99761224,0.00028309834,0.00041830077,0.0010738585,0.00049047807,0.0001220244],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004066816,0.0003282847,0.0004123687,0.00086822954,0.00016218075,0.00013786963,0.0021294856,0.00021992052,0.00005570249],"category_scores_gemma":[0.0001797589,0.00027038073,0.0001039174,0.00062391185,0.0007039154,0.0008119524,0.001011063,0.00017963846,0.000034693185],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000060082234,0.00006848905,0.00023982578,0.0000755913,0.000013457859,0.00002024993,0.00075885863,0.003067946,0.00026595153,0.6392103,0.00038189784,0.35589147],"study_design_scores_gemma":[0.0004844678,0.000213952,0.00021955617,0.00081621256,0.000013750257,0.000031409905,2.4196515e-7,0.774726,0.0013086124,0.19454016,0.026830448,0.0008152278],"about_ca_topic_score_codex":0.0000071328195,"about_ca_topic_score_gemma":0.00001595211,"teacher_disagreement_score":0.771658,"about_ca_system_score_codex":0.00032271727,"about_ca_system_score_gemma":0.00054369774,"threshold_uncertainty_score":0.99997485},"labels":[],"label_agreement":null},{"id":"W2509142881","doi":"10.29173/cais882","title":"An Exploration of Approaches to the Support of Serendipity in Digital Environments","year":2016,"lang":"fr","type":"article","venue":"Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Serendipity; Visualization; Computer science; Sociology; Humanities; Epistemology; Art; Artificial intelligence; Philosophy","score_opus":0.12049877742254203,"score_gpt":0.2825536274377581,"score_spread":0.16205485001521605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2509142881","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9668826,0.00007206094,0.017654259,0.0110385865,0.00022989555,0.00054532295,0.0011457648,0.000014855264,0.0024166822],"genre_scores_gemma":[0.99815685,0.000104572886,0.0004843946,0.00009214393,0.000045049295,0.000011770633,0.000010807415,0.000013710247,0.0010807088],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99786234,0.000040085426,0.00079216977,0.00037052628,0.00061115174,0.00032371943],"domain_scores_gemma":[0.9926914,0.000103506034,0.0010049094,0.000403779,0.005665375,0.00013100427],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0008432831,0.00023359935,0.00044594254,0.00017208565,0.00005297674,0.0010313219,0.0026232118,0.00012497032,0.000028051338],"category_scores_gemma":[0.004418405,0.00014771345,0.000119881406,0.0005897359,0.0006064248,0.02735369,0.00086006266,0.00012181047,0.0000057828915],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002272402,0.0019976336,0.32137063,0.0007932923,0.00018376835,0.0000012347887,0.12917131,0.00014105988,0.023276463,0.41439724,0.003006085,0.10543404],"study_design_scores_gemma":[0.0032821419,0.0041947095,0.3021703,0.002831439,0.00031619085,0.000037175665,0.015934374,0.01880661,0.41410354,0.048701704,0.18804067,0.0015811238],"about_ca_topic_score_codex":0.00008761803,"about_ca_topic_score_gemma":0.000034672263,"teacher_disagreement_score":0.3908271,"about_ca_system_score_codex":0.00004793648,"about_ca_system_score_gemma":0.00022596121,"threshold_uncertainty_score":0.99450606},"labels":[],"label_agreement":null},{"id":"W2509947681","doi":"10.1109/tvcg.2016.2598543","title":"Annotation Graphs: A Graph-Based Visualization for Meta-Analysis of Data Based on User-Authored Annotations","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Autodesk (Canada)","funders":"Mitacs; National Organization for Rare Disorders","keywords":"Computer science; Annotation; Visualization; Sensemaking; Information retrieval; Data visualization; Graph; Graph drawing; Data mining; Artificial intelligence; Human–computer interaction; Theoretical computer science","score_opus":0.10887058458608975,"score_gpt":0.36093587672728383,"score_spread":0.2520652921411941,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2509947681","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00027572364,0.000026163985,0.99667114,0.0004040828,0.00023970244,0.00056292035,0.0015400056,0.00027117794,0.0000091029615],"genre_scores_gemma":[0.972313,0.00012684918,0.021363532,0.004247399,0.000030182457,0.00022412774,0.0015577252,0.000063584856,0.00007361123],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9966765,0.000371764,0.00088520104,0.001049657,0.0007210286,0.00029586026],"domain_scores_gemma":[0.9962518,0.0008684037,0.00050031324,0.0014197124,0.0007800304,0.00017974316],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00072891504,0.00039152577,0.0007347892,0.0030004436,0.00040392432,0.00025324663,0.00086594734,0.00017068895,0.000042192165],"category_scores_gemma":[0.000032523203,0.0003104819,0.0006320223,0.0053722467,0.00016598223,0.001075125,0.000012042727,0.000084290135,0.0000025360716],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008218896,0.001071492,0.00009859294,0.00007875278,0.007613382,0.0000010018886,0.0002069546,0.030365111,0.000060214083,0.95609874,0.00084378826,0.0034798067],"study_design_scores_gemma":[0.001233018,0.00045265397,0.00022880225,0.000030549356,0.011460458,4.877033e-7,0.000011945072,0.9827781,0.0012687444,0.0011689069,0.000991833,0.00037450367],"about_ca_topic_score_codex":0.000014886199,"about_ca_topic_score_gemma":0.000071362614,"teacher_disagreement_score":0.9753076,"about_ca_system_score_codex":0.000025258467,"about_ca_system_score_gemma":0.000126164,"threshold_uncertainty_score":0.99993473},"labels":[],"label_agreement":null},{"id":"W250999366","doi":"10.1007/978-3-642-41939-3_37","title":"FractVis: Visualizing Microseismic Events","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Microseism; Computer science; Visualization; Domain (mathematical analysis); Process (computing); Hydraulic fracturing; Data visualization; Data mining; Curse of dimensionality; Data science; Artificial intelligence; Geology; Seismology; Petroleum engineering","score_opus":0.021050463029297476,"score_gpt":0.2906654685272509,"score_spread":0.2696150054979534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W250999366","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000493552,0.0002881737,0.9939642,0.0007181669,0.0014649993,0.00028911058,0.000008792565,0.00020913841,0.0030080897],"genre_scores_gemma":[0.1514756,0.00041432728,0.81596553,0.021903967,0.0011636926,0.00002328478,0.00010193635,0.00018088461,0.008770799],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.996123,0.000036221674,0.0006221386,0.0014957921,0.0010294406,0.0006933889],"domain_scores_gemma":[0.99742043,0.00021954159,0.00037461123,0.0015207602,0.00022848957,0.0002361533],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006235268,0.00054093683,0.0005090406,0.000916216,0.0002680939,0.0009350371,0.004157516,0.0003043563,0.00011672164],"category_scores_gemma":[0.0000813855,0.00050500623,0.00013973891,0.00070886733,0.000348103,0.0012116273,0.0018281788,0.00062953535,0.0007011091],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000025117718,0.00009666312,0.000108864246,0.00008998173,0.00003359702,0.00008403047,0.0008974555,0.007870272,0.00045308901,0.14938414,0.0008408815,0.8401385],"study_design_scores_gemma":[0.00027344067,0.00009357748,0.00011278354,0.00050477614,0.000009885076,0.0000481003,1.8621506e-7,0.8337433,0.00084387575,0.13937138,0.0240882,0.0009104902],"about_ca_topic_score_codex":0.000029896317,"about_ca_topic_score_gemma":0.000011924501,"teacher_disagreement_score":0.83922803,"about_ca_system_score_codex":0.00025159644,"about_ca_system_score_gemma":0.00046003566,"threshold_uncertainty_score":0.9997402},"labels":[],"label_agreement":null},{"id":"W2513074232","doi":"10.1109/tvcg.2016.2598866","title":"Decal-Maps: Real-Time Layering of Decals on Surfaces for Multivariate Visualization","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures; CMG Reservoir Simulation Foundation","keywords":"Visualization; Glyph (data visualization); Computer science; Data visualization; Layering; Computer graphics (images); Multivariate statistics; Set (abstract data type); Information visualization; Artificial intelligence; Data mining; Machine learning","score_opus":0.027267320295959893,"score_gpt":0.31127271587973404,"score_spread":0.28400539558377413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2513074232","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007566277,0.000008369283,0.9911646,0.00009470488,0.000388515,0.00035047403,0.00010490115,0.00027762505,0.00004450582],"genre_scores_gemma":[0.99040574,0.0007515561,0.007404799,0.0009163064,0.00006425202,0.000043492088,0.000050986837,0.00005819479,0.00030466134],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99807024,0.00016248912,0.0005715162,0.00055364624,0.00037695712,0.00026514372],"domain_scores_gemma":[0.9982349,0.0004941018,0.00025551487,0.00042510984,0.00044162507,0.00014874701],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036599225,0.0002700041,0.00032396367,0.0005399244,0.00026442794,0.00015366105,0.00036303297,0.00014591846,0.000017046541],"category_scores_gemma":[0.000021485279,0.00021763457,0.00013009651,0.00082741404,0.00009462409,0.0005511762,0.000010100661,0.000055651344,0.000012751715],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006221249,0.00048284492,0.0000749578,0.000080303056,0.00009394227,0.0000010525005,0.00047037753,0.0015139297,0.0024829283,0.9784548,0.0004285053,0.015854128],"study_design_scores_gemma":[0.0013840768,0.00053946767,0.00021995662,0.00022995032,0.000033672506,0.0000028948525,0.000012490417,0.96710587,0.027105136,0.0014607414,0.0015680098,0.0003377115],"about_ca_topic_score_codex":0.000017077062,"about_ca_topic_score_gemma":0.000009578244,"teacher_disagreement_score":0.9837598,"about_ca_system_score_codex":0.000030875406,"about_ca_system_score_gemma":0.00005225984,"threshold_uncertainty_score":0.887488},"labels":[],"label_agreement":null},{"id":"W2515573129","doi":"10.15353/joci.v12i3.3282","title":"Graphical Perception of Value Distributions: An Evaluation of Non-Expert Viewers' Data Literacy","year":2016,"lang":"en","type":"article","venue":"The Journal of Community Informatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"IDA Ireland; Enterprise Ireland","keywords":"Histogram; Pie chart; Chart; Perception; Computer science; Identification (biology); Field (mathematics); Statement (logic); Plot (graphics); Artificial intelligence; Mathematics; Statistics; Psychology; Linguistics","score_opus":0.08758322501915905,"score_gpt":0.40502416763709076,"score_spread":0.3174409426179317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2515573129","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23550434,0.000025593547,0.7638055,0.00037712426,0.000072988056,0.00006167671,0.0000592154,0.0000048934326,0.00008865998],"genre_scores_gemma":[0.98912805,0.00047440804,0.010132651,0.00017414767,0.0000188577,2.6313262e-7,0.000067473935,0.0000023779162,0.0000017797239],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99731857,0.00090139196,0.00091803476,0.000013485881,0.00076243305,0.000086073815],"domain_scores_gemma":[0.99562925,0.000371675,0.0009798903,0.0014960861,0.0014648207,0.000058271682],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008194066,0.00007437107,0.00018458055,0.00013955876,0.00015543986,0.00005020407,0.0028507712,0.000038794675,0.000019482479],"category_scores_gemma":[0.0006812348,0.000040409355,0.000050758943,0.00035819897,0.00014608179,0.0032714228,0.00052230683,0.00021041298,0.0000031923594],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009863381,0.0018671452,0.0010135815,0.00023724821,0.00027060366,1.8452431e-7,0.23630796,0.0011297307,0.005860076,0.028089713,0.009877348,0.71524775],"study_design_scores_gemma":[0.0016011455,0.0006708917,0.009739641,0.0005771495,0.000212051,0.00006895153,0.019384073,0.9538447,0.0008357193,0.010407122,0.0024842897,0.0001742572],"about_ca_topic_score_codex":0.000022944585,"about_ca_topic_score_gemma":0.0000029058574,"teacher_disagreement_score":0.952715,"about_ca_system_score_codex":0.000038477116,"about_ca_system_score_gemma":0.0001635536,"threshold_uncertainty_score":0.5297489},"labels":[],"label_agreement":null},{"id":"W2516385370","doi":"","title":"Causviz: visual representations of complex causal semantics based on theories of perception","year":2011,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Causality (physics); Semantics (computer science); Computer science; Causal structure; Causal model; Animation; Perception; Graph; Theoretical computer science; Natural language processing; Artificial intelligence; Mathematics; Programming language; Psychology","score_opus":0.06478015949597152,"score_gpt":0.34990205913952516,"score_spread":0.2851218996435536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2516385370","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009747219,6.03592e-7,0.97016263,0.00012528653,0.000063864194,0.00006191458,0.000014894596,0.00004823464,0.019775342],"genre_scores_gemma":[0.9710563,0.000002727449,0.028289651,0.00022033982,0.000009382773,0.0000010279366,0.00003598015,0.00000397073,0.00038062717],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923235,0.000059795428,0.00024458926,0.00014997103,0.00022826542,0.00008504484],"domain_scores_gemma":[0.9992756,0.000060588736,0.000113147136,0.00035077005,0.00016378373,0.000036065692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014795379,0.00006634355,0.00011778793,0.00012430364,0.00003224602,0.000018116152,0.0002727571,0.00002575018,0.00034991035],"category_scores_gemma":[0.00004919914,0.000056341818,0.000041401683,0.00030684232,0.00009273137,0.00017886669,0.00007137276,0.000029798943,0.00001616706],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009787452,0.00035705828,0.00622056,0.000026949165,0.000012951979,0.0000013329362,0.0014637763,0.00023861605,0.0026164416,0.98653585,0.0014989557,0.0010177417],"study_design_scores_gemma":[0.00032101857,0.00026792902,0.03796269,0.000020592588,0.000016466765,0.0000011645524,0.00068405503,0.9469048,0.009823444,0.0036661525,0.00020574708,0.00012594539],"about_ca_topic_score_codex":0.00010447643,"about_ca_topic_score_gemma":0.000021636253,"teacher_disagreement_score":0.9828697,"about_ca_system_score_codex":0.000006885922,"about_ca_system_score_gemma":0.000038112485,"threshold_uncertainty_score":0.38312727},"labels":[],"label_agreement":null},{"id":"W2516807252","doi":"10.1109/tvcg.2016.2598591","title":"Optimizing Hierarchical Visualizations with the Minimum Description Length Principle","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Minimum description length; Computer science; Clutter; Data mining; Visualization; Outlier; Tree (set theory); Data visualization; Feature (linguistics); Set (abstract data type); Hierarchical database model; Artificial intelligence; Pattern recognition (psychology); Radar; Mathematics","score_opus":0.025055373484815756,"score_gpt":0.2798612655801945,"score_spread":0.25480589209537874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2516807252","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036223994,0.00001837308,0.9944753,0.00090074487,0.00030302757,0.0002538484,0.00001688663,0.00034839148,0.000060995586],"genre_scores_gemma":[0.99150896,0.00037327482,0.0046163467,0.0029048936,0.00008269408,0.000042461812,0.000013938928,0.000037285783,0.00042016586],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981338,0.000222837,0.00033939868,0.0005386205,0.00046665047,0.0002987216],"domain_scores_gemma":[0.99871284,0.00021018801,0.00013646361,0.00053872477,0.00022969149,0.00017211761],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027594477,0.00026301996,0.00019300063,0.0003756661,0.00072330324,0.00045991552,0.00049217127,0.000102511476,0.000020504638],"category_scores_gemma":[0.0000055173828,0.00015498717,0.000079096215,0.0011864415,0.00023012937,0.00085800345,0.000015134631,0.00014821212,0.0000148752115],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019591345,0.00022960827,0.00006224607,0.000014600013,0.000061587125,0.000003021546,0.00086931686,0.0006045399,0.00007726537,0.9900772,0.0004688921,0.0075121257],"study_design_scores_gemma":[0.0010547562,0.0003886051,0.00025699625,0.00010345538,0.00004467158,0.00003330188,0.000047213573,0.98374504,0.0012615302,0.00062316685,0.0120651545,0.0003761115],"about_ca_topic_score_codex":0.0000039730767,"about_ca_topic_score_gemma":0.00003016378,"teacher_disagreement_score":0.989859,"about_ca_system_score_codex":0.000034465113,"about_ca_system_score_gemma":0.00007490396,"threshold_uncertainty_score":0.63201934},"labels":[],"label_agreement":null},{"id":"W2518599754","doi":"10.1109/tvcg.2016.2598647","title":"Authoring Data-Driven Videos with DataClips","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":126,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Microsoft Research","keywords":"Computer science; Data visualization; Computer graphics (images); Visualization; Multimedia; Artificial intelligence","score_opus":0.046150180266666944,"score_gpt":0.30429413868809546,"score_spread":0.2581439584214285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2518599754","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005912174,0.0000098351675,0.99807477,0.00030655172,0.0003638082,0.00014444243,0.00009783791,0.00037045518,0.00004105572],"genre_scores_gemma":[0.9825145,0.00064835016,0.013466708,0.0027551118,0.000135006,0.000017679748,0.00010249255,0.00004914074,0.00031099707],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982589,0.00010683634,0.00030066667,0.0007045867,0.00038705228,0.00024196878],"domain_scores_gemma":[0.9983453,0.00012402234,0.00011081539,0.0011056392,0.0001357885,0.00017839274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021303326,0.00022061537,0.00018943322,0.0003539312,0.00031669872,0.0003413736,0.00088456215,0.000078279714,0.000019853675],"category_scores_gemma":[0.0000041012418,0.00015389537,0.000034416553,0.0008346585,0.00010729849,0.001574913,0.000029794612,0.00010122603,0.000024481216],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019444282,0.00026017305,0.00025303478,0.00003122405,0.00010095882,0.000010957396,0.00027763846,0.000311846,0.00003608751,0.95158964,0.0016602183,0.045448776],"study_design_scores_gemma":[0.00078638236,0.00021000038,0.00018649486,0.00012209635,0.00003222257,0.00002714181,0.000011699806,0.9855042,0.00060210255,0.00033032527,0.011870739,0.00031656268],"about_ca_topic_score_codex":0.000006126965,"about_ca_topic_score_gemma":0.000033297278,"teacher_disagreement_score":0.98519236,"about_ca_system_score_codex":0.000017627855,"about_ca_system_score_gemma":0.00005752308,"threshold_uncertainty_score":0.6275671},"labels":[],"label_agreement":null},{"id":"W2522107234","doi":"10.1016/j.procs.2016.09.017","title":"A Review of Latest Web Tools and Libraries for State-of-the-art Visualization","year":2016,"lang":"en","type":"review","venue":"Procedia Computer Science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Acadia University","funders":"","keywords":"Computer science; Visualization; Web application; World Wide Web; Process (computing); Software; Web browser; Web modeling; Interactive visualization; Human–computer interaction; Multimedia; Web page; The Internet; Operating system","score_opus":0.0518667309054764,"score_gpt":0.3484296268695515,"score_spread":0.2965628959640751,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2522107234","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[8.549813e-8,0.576074,0.42287266,0.00009037731,0.00026407267,0.00056169357,0.000077963945,0.000030108811,0.000029025096],"genre_scores_gemma":[0.000001492979,0.9735642,0.025817055,0.00041687602,0.00004936156,0.000037648806,0.000020347545,0.000013038666,0.00007995066],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978123,0.000065799344,0.00079966546,0.0005998944,0.0004606012,0.00026178558],"domain_scores_gemma":[0.99742967,0.00034829788,0.00090476696,0.0007017185,0.0005150219,0.0001005471],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009237024,0.0002479569,0.00085175486,0.0002354263,0.00012795911,0.00031580313,0.0025233522,0.000051232197,0.000002608721],"category_scores_gemma":[0.0005078416,0.00014833422,0.00016767511,0.0020515777,0.00049696374,0.0014863276,0.0012957812,0.00006387968,0.000006251947],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.723037e-7,0.000022263683,0.0000044972667,0.059285156,0.00000975252,1.2759898e-7,0.00004485506,2.9897703e-7,0.0000011153152,0.033487886,0.0044221105,0.90272164],"study_design_scores_gemma":[0.00008084357,0.00005505006,0.0000025881113,0.078337006,0.00004410529,0.000011236121,1.732934e-7,0.0130207,0.000034335473,0.00067548855,0.90753716,0.00020129862],"about_ca_topic_score_codex":1.8266668e-7,"about_ca_topic_score_gemma":2.8503663e-7,"teacher_disagreement_score":0.9031151,"about_ca_system_score_codex":0.000025023252,"about_ca_system_score_gemma":0.0016156267,"threshold_uncertainty_score":0.6048894},"labels":[],"label_agreement":null},{"id":"W2523697008","doi":"10.1109/rweek.2016.7573300","title":"Adapting level of detail in user interfaces for Cybersecurity operations","year":2016,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Office of Naval Research","keywords":"Situation awareness; Computer science; Information overload; Computer security; Intrusion detection system; Firewall (physics); Context (archaeology); Cyber-physical system; User interface; Human–computer interaction; World Wide Web; Engineering","score_opus":0.1455363833729717,"score_gpt":0.35234975219938375,"score_spread":0.20681336882641205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2523697008","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015913755,0.0000044346248,0.9827654,0.0007507843,0.0000411679,0.00005735453,0.000018866906,0.000018697245,0.00042955566],"genre_scores_gemma":[0.9239631,0.000004592778,0.07390218,0.00013213704,0.0000065980234,0.0000035486134,0.0000016258639,0.000001990818,0.0019842167],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99957633,0.0000147929295,0.0001600088,0.00011129888,0.00006121676,0.000076337936],"domain_scores_gemma":[0.9996703,0.000064207576,0.00002333074,0.00015247185,0.00007016177,0.00001950843],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016603053,0.000036746107,0.000063017935,0.000055648663,0.000021542646,0.000033750403,0.00026995008,0.000015875808,0.000033247215],"category_scores_gemma":[0.00010889165,0.000023702121,0.000016284985,0.00012465761,0.000015823618,0.00043908146,0.00009079701,0.000011943485,0.000008438336],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000017545347,0.00006613265,0.0024154373,0.00000913515,0.0000068919585,2.3956358e-7,0.00056133897,0.00012448768,0.0048758634,0.9767636,0.001964364,0.013210767],"study_design_scores_gemma":[0.0017404292,0.00013369422,0.00397798,0.00016738624,0.000007584953,0.000001945261,0.0005101685,0.83197707,0.13758159,0.0044985814,0.019047214,0.00035634858],"about_ca_topic_score_codex":0.000054057782,"about_ca_topic_score_gemma":0.0011766185,"teacher_disagreement_score":0.972265,"about_ca_system_score_codex":0.000009825094,"about_ca_system_score_gemma":0.00003064653,"threshold_uncertainty_score":0.096654445},"labels":[],"label_agreement":null},{"id":"W2524661797","doi":"10.22215/etd/2009-08826","title":"Towards classifying and selecting appropriate security visualization techniques","year":2009,"lang":"en","type":"dissertation","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Library and Archives Canada","funders":"","keywords":"Computer science; Visualization; Artificial intelligence","score_opus":0.018504589311918476,"score_gpt":0.33400636104184445,"score_spread":0.315501771729926,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2524661797","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014024733,0.00017102252,0.9237398,0.00011608242,0.0002868897,0.00032096525,0.0000044256126,0.0012400702,0.07271827],"genre_scores_gemma":[0.57322174,0.004458852,0.36789754,0.005165995,0.0012776292,0.00011265098,0.009387756,0.00028654613,0.03819128],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99849015,0.000065911016,0.0003587628,0.0005254601,0.00034322834,0.00021649343],"domain_scores_gemma":[0.9991093,0.000018520113,0.0002607968,0.00029523126,0.00023353666,0.00008256858],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032660447,0.00024772374,0.00026056488,0.00028533547,0.00018788541,0.00065064686,0.0004382879,0.0002633372,0.000013555104],"category_scores_gemma":[0.00009240195,0.0002363459,0.000048741025,0.0006278309,0.000011370552,0.0005953125,0.00007679637,0.00020028213,0.0000060978728],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007130002,0.00010760634,0.00008709021,0.00035312245,0.00003937703,0.0000063366656,0.0026469957,0.0000016100549,0.00071378116,0.4659287,0.0028893044,0.52721894],"study_design_scores_gemma":[0.0006807725,0.00040346276,0.0017529005,0.0009909401,0.00015959724,0.000040130282,0.0015839135,0.7264399,0.11481918,0.10748137,0.042860016,0.00278784],"about_ca_topic_score_codex":0.000041488434,"about_ca_topic_score_gemma":0.00013363076,"teacher_disagreement_score":0.7264383,"about_ca_system_score_codex":0.000043096206,"about_ca_system_score_gemma":0.00014452625,"threshold_uncertainty_score":0.9637906},"labels":[],"label_agreement":null},{"id":"W2527278991","doi":"10.1109/mcg.2016.90","title":"Sports Tournament Predictions Using Direct Manipulation","year":2016,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Tournament; Computer science; Interface (matter); Focus (optics); League; User interface; Visitor pattern; Human–computer interaction; Multimedia","score_opus":0.030205930113520917,"score_gpt":0.2857579929975708,"score_spread":0.2555520628840499,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2527278991","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0028611647,0.000033549943,0.9959795,0.00043717178,0.00015883513,0.00016739387,0.000016719974,0.0001416809,0.00020400995],"genre_scores_gemma":[0.9726585,0.00034196014,0.026035842,0.00046873032,0.0003286443,0.000038179664,0.000011804699,0.000011551962,0.000104764],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991485,0.000018760353,0.00021020709,0.00030484778,0.00018200952,0.00013567344],"domain_scores_gemma":[0.99927896,0.000039852333,0.000093899274,0.00039306024,0.000089418056,0.00010480983],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011908018,0.00009810998,0.00009369582,0.00015387328,0.0002514721,0.000143928,0.00024833615,0.000038805887,0.000005206857],"category_scores_gemma":[0.0000014407656,0.00007548402,0.000039524504,0.00036128412,0.000047508824,0.00031698582,0.00008695637,0.00003911781,0.0000056818844],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.231661e-7,0.000118196775,0.004527064,0.000010337545,0.00002729918,0.0000018474097,0.00006368978,0.0004998656,0.0004243457,0.9235043,0.0015240086,0.06929834],"study_design_scores_gemma":[0.0002877668,0.000028437336,0.009011637,0.000052140145,0.000026220949,0.000027406575,0.0000032457704,0.9008721,0.00019839931,0.014838344,0.074401975,0.00025228393],"about_ca_topic_score_codex":0.000005681714,"about_ca_topic_score_gemma":0.0000027918054,"teacher_disagreement_score":0.96994364,"about_ca_system_score_codex":0.000019053614,"about_ca_system_score_gemma":0.000023720879,"threshold_uncertainty_score":0.30781493},"labels":[],"label_agreement":null},{"id":"W2534902647","doi":"","title":"Studies on pattern dissemination and reuse to support interaction design","year":2005,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Human–computer interaction; Reuse; Software design pattern; Dissemination; User interface; Variety (cybernetics); Scope (computer science); Interface (matter); Interaction design; Harmony (color); Mainstream; Data science; Software; Engineering; Artificial intelligence","score_opus":0.07904205478790766,"score_gpt":0.4035735529840203,"score_spread":0.32453149819611266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2534902647","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0054962644,0.0000039150354,0.9892582,0.0044426825,0.00010183538,0.000059534184,8.315534e-7,0.00006556735,0.00057115505],"genre_scores_gemma":[0.9722847,0.000027527303,0.021879325,0.0030654918,0.000042411863,0.0000044174963,0.0000049156033,0.0000033289039,0.0026878845],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995602,0.000021501768,0.00010591385,0.00015134626,0.00009957457,0.00006148663],"domain_scores_gemma":[0.9995936,0.000069531205,0.00002774451,0.0002184413,0.000048364902,0.00004232146],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016313899,0.00004944082,0.000050791317,0.00008122787,0.000039528066,0.00010136796,0.00017852463,0.000010723676,0.00002099205],"category_scores_gemma":[0.00013456769,0.000039853454,0.0000073695965,0.000113836766,0.000005823048,0.00039398507,0.00013703777,0.00002199296,0.00012630552],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006384126,0.00014075302,0.00038810557,0.0000119933775,0.000025709835,0.000004760314,0.007317073,0.0009880348,0.00085517153,0.020943422,0.24455917,0.7247594],"study_design_scores_gemma":[0.00044837449,0.0011243406,0.002318638,0.00014629809,0.000019359188,0.000021068548,0.001456151,0.80864805,0.10160011,0.0008441478,0.08280558,0.0005678838],"about_ca_topic_score_codex":9.571921e-7,"about_ca_topic_score_gemma":0.0000094243915,"teacher_disagreement_score":0.9673789,"about_ca_system_score_codex":0.000024412038,"about_ca_system_score_gemma":0.000005135073,"threshold_uncertainty_score":0.16251767},"labels":[],"label_agreement":null},{"id":"W2535433266","doi":"10.1109/infvis.1995.528689","title":"Research report. Interacting with huge hierarchies: beyond cone trees","year":2002,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":102,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Zoom; Visualization; Clutter; Hierarchy; Tree (set theory); Cone (formal languages); Theoretical computer science; Information visualization; Human–computer interaction; Computer graphics (images); Artificial intelligence; Algorithm; Mathematics","score_opus":0.08189140172285958,"score_gpt":0.37092667464420775,"score_spread":0.2890352729213482,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2535433266","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009384417,0.00006373647,0.6341368,0.0052695554,0.00020138912,0.00014960834,0.0000030429514,0.000337633,0.3504538],"genre_scores_gemma":[0.8909969,0.000038812967,0.039943337,0.0007068034,0.00009200274,0.0000066200687,0.00001590134,0.000013345598,0.06818631],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986236,0.000083823754,0.00022095132,0.00032735537,0.00048016052,0.0002640883],"domain_scores_gemma":[0.99875045,0.0002857215,0.0000661628,0.0006041867,0.00019171818,0.00010175277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055562315,0.00007882412,0.000104549574,0.00022290673,0.00018585785,0.00042491144,0.0005724767,0.000023202312,0.0005035747],"category_scores_gemma":[0.00022100586,0.0000576345,0.000020834757,0.000840179,0.00008876378,0.0007111059,0.00027171595,0.0001806059,0.00019166134],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009485992,0.00045437703,0.0034859506,0.000031353153,0.00007890869,0.0013830641,0.0047447104,0.0001269854,0.00063489075,0.70488614,0.23318979,0.050974317],"study_design_scores_gemma":[0.00070612103,0.00037744473,0.0005743894,0.00011635126,0.0000070933497,0.0006218975,0.0016049455,0.6796645,0.002629883,0.0019297323,0.3113136,0.00045408032],"about_ca_topic_score_codex":0.000042650267,"about_ca_topic_score_gemma":0.00008541537,"teacher_disagreement_score":0.8816124,"about_ca_system_score_codex":0.000020988145,"about_ca_system_score_gemma":0.00002469547,"threshold_uncertainty_score":0.55137897},"labels":[],"label_agreement":null},{"id":"W2541234445","doi":"","title":"Expanding the Information Fidelity of Calm Technology Devices Through Techniques of Information Visualization","year":2016,"lang":"en","type":"dissertation","venue":"OCAD University Open Research Repository (OCAD University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario College of Art and Design","funders":"","keywords":"Visualization; Fidelity; Information visualization; Computer science; Human–computer interaction; Reflection (computer programming); Information technology; Engineering; Data science; Artificial intelligence; Telecommunications","score_opus":0.03542419344704046,"score_gpt":0.3502342508792582,"score_spread":0.31481005743221774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2541234445","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01420341,0.000041684154,0.2133595,0.00036593236,0.0003029738,0.0013951156,0.00012790988,0.00019553975,0.7700079],"genre_scores_gemma":[0.9218507,0.0019236495,0.008394551,0.00012096318,0.00008597371,0.0000048384136,0.0020937163,0.00003972689,0.0654859],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974322,0.0005127557,0.0005208112,0.00030435808,0.00091317197,0.00031671065],"domain_scores_gemma":[0.9953789,0.00016347211,0.0010725033,0.00087542314,0.0024290115,0.00008065945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00096896384,0.00021890253,0.00037828574,0.0016069625,0.00093880243,0.00028400496,0.003929411,0.00045142733,0.0000017578465],"category_scores_gemma":[0.00016839601,0.0001965199,0.000114452654,0.0030101188,0.00036493532,0.009554711,0.00080563885,0.00039667322,0.000012766784],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011392345,0.000046230372,0.00042236902,0.00021715621,0.00007108138,0.0000062606623,0.0016364437,0.000006106945,0.0007225576,0.99155545,0.00048732772,0.0047151195],"study_design_scores_gemma":[0.0018650192,0.00065485586,0.0026064832,0.0019555832,0.00019290818,0.000014104136,0.033282187,0.0024454915,0.15901047,0.0022892915,0.79472995,0.00095367926],"about_ca_topic_score_codex":0.0011433084,"about_ca_topic_score_gemma":0.00016463442,"teacher_disagreement_score":0.98926616,"about_ca_system_score_codex":0.00043081254,"about_ca_system_score_gemma":0.0009536833,"threshold_uncertainty_score":0.8013849},"labels":[],"label_agreement":null},{"id":"W2543362121","doi":"10.1109/gem.2014.7048116","title":"Interactive 3D visualisation of playtesting data","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Visualization; Data visualization; Computer graphics (images); Human–computer interaction; Artificial intelligence","score_opus":0.07022185064231913,"score_gpt":0.36219082983827655,"score_spread":0.29196897919595743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2543362121","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011392398,0.0000013484647,0.9885003,0.00009278841,0.00006286669,0.000020370644,0.0000047445737,0.000055307988,0.010123032],"genre_scores_gemma":[0.8976028,0.0000013843988,0.10165687,0.00040432136,0.00003280168,3.1583446e-7,0.0000916934,0.0000027582282,0.00020703848],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99948364,0.000039133964,0.00013863314,0.00016259965,0.000118216005,0.000057777957],"domain_scores_gemma":[0.99914896,0.000110166235,0.00008675718,0.00056451093,0.00006557213,0.00002404048],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029299254,0.000037949878,0.00006105881,0.000048549784,0.000023301642,0.000057796875,0.00073866354,0.000011898844,0.00002939734],"category_scores_gemma":[0.0004098757,0.00003267135,0.0000071817403,0.00017693361,0.000013047513,0.0008228597,0.0004370114,0.000024622452,0.000026464366],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000025786198,0.0001331747,0.0022494576,0.00002819825,0.000022245475,6.353059e-7,0.0007093577,0.0002603489,0.0015527251,0.78462327,0.007943844,0.20247418],"study_design_scores_gemma":[0.00007440165,0.000019016657,0.000503552,0.000010870025,0.000002178266,9.677793e-7,0.000023503879,0.9928813,0.0013539087,0.0004891174,0.0045975004,0.000043712913],"about_ca_topic_score_codex":0.000033255914,"about_ca_topic_score_gemma":0.000005282587,"teacher_disagreement_score":0.99262094,"about_ca_system_score_codex":0.0000047371555,"about_ca_system_score_gemma":0.000015549183,"threshold_uncertainty_score":0.1372633},"labels":[],"label_agreement":null},{"id":"W2545503847","doi":"10.3390/informatics3040020","title":"Supporting Sensemaking of Complex Objects with Visualizations: Visibility and Complementarity of Interactions","year":2016,"lang":"en","type":"article","venue":"Informatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Sensemaking; Computer science; Human–computer interaction; Complementarity (molecular biology); Visualization; Visual analytics; Usability; Visibility; Representation (politics); Information visualization; Data science; Knowledge management; Artificial intelligence","score_opus":0.04186532548949052,"score_gpt":0.37096160492550034,"score_spread":0.32909627943600983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2545503847","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05683346,0.0000021317621,0.9419445,0.00007864411,0.000025295813,0.00009755956,0.000045937748,0.000031548665,0.0009409571],"genre_scores_gemma":[0.9427005,0.000005024384,0.05711953,0.00013162609,0.00000396984,9.2218806e-7,0.00001651061,0.000002615594,0.000019269837],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99900323,0.000025452731,0.00060063193,0.00006778444,0.00019144884,0.000111471156],"domain_scores_gemma":[0.9988102,0.00015387381,0.00050139375,0.00027814636,0.00021566947,0.00004071734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026415745,0.00006977605,0.00015328977,0.00010125136,0.000058755082,0.000038478283,0.00018268141,0.000013359204,0.000030850548],"category_scores_gemma":[0.00010369783,0.000046957277,0.000019153598,0.00025135942,0.000092150476,0.0007985222,0.00017656175,0.000026870068,0.000001827616],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040931653,0.00068338466,0.22258486,0.0018292159,0.00029910496,0.0000037338136,0.043470923,0.00039537824,0.008952446,0.64553225,0.002367212,0.073840566],"study_design_scores_gemma":[0.0021584046,0.00043315729,0.033719756,0.00076967233,0.00006568445,0.000065073415,0.0067112613,0.9267656,0.01671352,0.00412542,0.007967164,0.0005052372],"about_ca_topic_score_codex":0.000019971152,"about_ca_topic_score_gemma":0.00006390224,"teacher_disagreement_score":0.92637026,"about_ca_system_score_codex":0.000017559983,"about_ca_system_score_gemma":0.00004799394,"threshold_uncertainty_score":0.19148622},"labels":[],"label_agreement":null},{"id":"W2546744392","doi":"10.1109/gem.2015.7377210","title":"Uniform vs. non-uniform scaling of shooter games on large displays","year":2015,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Scaling; Computer science; Constant (computer programming); Display size; Mathematics; Geometry; Display device","score_opus":0.029275418194015003,"score_gpt":0.3019294876731757,"score_spread":0.27265406947916065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2546744392","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0049226093,0.000003956562,0.95494556,0.0004528614,0.00015814826,0.00005451521,0.000013651256,0.00006646717,0.039382245],"genre_scores_gemma":[0.973861,0.0000089606565,0.020569982,0.002021286,0.000048864804,0.000001376034,0.00003612059,0.000008785209,0.0034436435],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991005,0.000011331487,0.00021127328,0.000180936,0.00030469807,0.00019123287],"domain_scores_gemma":[0.99923176,0.000023240931,0.00006814871,0.00043603164,0.00010803336,0.0001327973],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031480019,0.00009223598,0.00013396385,0.00010681131,0.00003622882,0.00009053518,0.00055621745,0.00003843152,0.000045330256],"category_scores_gemma":[0.00003909599,0.00006910968,0.00004171295,0.0003094842,0.000021080557,0.00042702493,0.00023190942,0.000054742148,0.00014612742],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013014714,0.0003131418,0.0025302835,0.000032285257,0.000022810704,0.000007677701,0.0012516613,0.00080289494,0.000054233173,0.9532451,0.036353674,0.0053732004],"study_design_scores_gemma":[0.0005808007,0.00012862183,0.0005130906,0.000038159287,0.0000054837246,0.0000024522965,0.00020129334,0.95771414,0.0034952264,0.0014627774,0.035688363,0.00016956386],"about_ca_topic_score_codex":0.00001825575,"about_ca_topic_score_gemma":0.000017494096,"teacher_disagreement_score":0.96893835,"about_ca_system_score_codex":0.000022392831,"about_ca_system_score_gemma":0.000056590838,"threshold_uncertainty_score":0.2818211},"labels":[],"label_agreement":null},{"id":"W2553791450","doi":"10.1007/s11042-016-4038-2","title":"City digital pulse: a cloud based heterogeneous data analysis platform","year":2016,"lang":"en","type":"article","venue":"Multimedia Tools and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Upload; Cloud computing; Data science; Big data; Architecture; Visualization; Data collection; World Wide Web; Data mining","score_opus":0.0681096754440612,"score_gpt":0.31284602557114816,"score_spread":0.24473635012708694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2553791450","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00087112817,0.000030507408,0.99593383,0.0007437682,0.000024910833,0.0001692769,0.0018782209,0.00011362562,0.0002347466],"genre_scores_gemma":[0.9734928,0.000059865037,0.02365295,0.00045106618,0.00014665093,0.00007803638,0.0017611538,0.00000992827,0.0003475276],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989389,0.00000876634,0.00021435136,0.0004865689,0.00017716488,0.00017420184],"domain_scores_gemma":[0.998188,0.0001982874,0.00008011369,0.0013158419,0.00005728322,0.00016047974],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000116799456,0.000110004214,0.00014685944,0.000103226026,0.00013440277,0.00044655584,0.00097042136,0.00004287834,0.00007083669],"category_scores_gemma":[0.000067681925,0.000077552024,0.000048486985,0.0006485083,0.0000719242,0.0008669258,0.0004158776,0.000035954057,0.000073900825],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000033394315,0.00022324224,0.0061267754,0.000008999416,0.00018606186,0.0000029182802,0.000046461155,0.00009222717,0.00023191133,0.009383911,0.0015336624,0.9821605],"study_design_scores_gemma":[0.00047990985,0.00001623344,0.0032005107,0.000007255661,0.00010362655,0.0000032733078,0.0000066378934,0.84003234,0.00042486857,0.00071836245,0.15474546,0.00026152472],"about_ca_topic_score_codex":0.0000074312106,"about_ca_topic_score_gemma":0.00001722794,"teacher_disagreement_score":0.98189896,"about_ca_system_score_codex":0.000014732674,"about_ca_system_score_gemma":0.000038475526,"threshold_uncertainty_score":0.43061483},"labels":[],"label_agreement":null},{"id":"W2558376413","doi":"10.15353/joci.v12i3.3285","title":"Data Murals: Using the Arts to Build Data Literacy","year":2016,"lang":"en","type":"article","venue":"The Journal of Community Informatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":67,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Citizen journalism; Literacy; The arts; Focus (optics); Set (abstract data type); Critical literacy; Digital literacy; Visual arts; Sociology; Mathematics education; Pedagogy; Computer science; Psychology; World Wide Web; Art","score_opus":0.205778547682592,"score_gpt":0.4200238864669845,"score_spread":0.21424533878439253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2558376413","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023328757,0.000037177786,0.96920973,0.0067695216,0.0001825742,0.000063760366,0.00013924537,0.000014289399,0.0002549464],"genre_scores_gemma":[0.83832854,0.00071098655,0.1369127,0.023408812,0.0003420342,3.1197715e-7,0.000102856764,0.000021784503,0.00017198986],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99822855,0.0004491244,0.0007119681,0.000016597303,0.0004356829,0.00015805927],"domain_scores_gemma":[0.9926248,0.001038429,0.0006178924,0.0053388337,0.00028883643,0.00009119047],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.005684808,0.000094278315,0.00014891996,0.000093044204,0.0004888934,0.00043633513,0.015972327,0.000021610793,0.000010928184],"category_scores_gemma":[0.0008538219,0.000038641465,0.000022867436,0.00037641902,0.00007928516,0.005055549,0.00698156,0.00035391471,0.000029456181],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044009343,0.00030837083,0.00022037563,0.000089298075,0.00028090665,0.0000024337644,0.17001969,0.001428751,0.00040713546,0.015151671,0.41533098,0.3967164],"study_design_scores_gemma":[0.00047157964,0.00011666388,0.00016464364,0.0003689523,0.00008572416,0.00043438264,0.011935103,0.41608962,0.00014853796,0.002610996,0.5673744,0.00019937353],"about_ca_topic_score_codex":0.000021018255,"about_ca_topic_score_gemma":0.0000131171955,"teacher_disagreement_score":0.832297,"about_ca_system_score_codex":0.000024843783,"about_ca_system_score_gemma":0.000118478565,"threshold_uncertainty_score":0.98935175},"labels":[],"label_agreement":null},{"id":"W2561057401","doi":"10.5210/ojphi.v8i3.7100","title":"Beyond simple charts: Design of visualizations for big health data","year":2016,"lang":"en","type":"article","venue":"Online Journal of Public Health Informatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Big data; Computer science; Data science; Sensemaking; Variety (cybernetics); Data visualization; Visualization; Population; Human–computer interaction; Data mining; Artificial intelligence; Medicine","score_opus":0.2713751422340808,"score_gpt":0.43823123693547694,"score_spread":0.16685609470139612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2561057401","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000532645,0.00013711514,0.9685667,0.029610207,0.00039306344,0.00023772998,0.00095867296,0.00002500981,0.000018200031],"genre_scores_gemma":[0.0071651656,0.0040610568,0.9680067,0.01914274,0.00065143243,0.0000033844976,0.0007931611,0.000030546933,0.00014584555],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9960392,0.00019350917,0.002672392,0.000100582176,0.0005570497,0.0004372297],"domain_scores_gemma":[0.9941115,0.00036801965,0.003224512,0.0007981517,0.0009766959,0.0005211436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0064602243,0.00013142628,0.00045947163,0.00050258863,0.00016218518,0.00013579299,0.0017972416,0.000048124857,0.000010978737],"category_scores_gemma":[0.0017507623,0.000088624016,0.000060062554,0.00071793277,0.000052248757,0.0025024354,0.0003111702,0.00009415437,0.000003229319],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000067873552,0.00066418864,0.00021865308,0.00063380325,0.00008906931,5.1334774e-7,0.0028878117,0.00027681055,0.0000088177085,0.090834126,0.24254116,0.6618383],"study_design_scores_gemma":[0.0014643456,0.0009873443,0.000087105036,0.00020057565,0.000007372057,0.00004162579,0.0005694275,0.40824893,0.000013253429,0.0022001667,0.5860257,0.00015413114],"about_ca_topic_score_codex":0.000005188335,"about_ca_topic_score_gemma":0.000009841569,"teacher_disagreement_score":0.66168416,"about_ca_system_score_codex":0.000128209,"about_ca_system_score_gemma":0.0045572496,"threshold_uncertainty_score":0.8084365},"labels":[],"label_agreement":null},{"id":"W2562290425","doi":"10.1109/isgt.2016.7781163","title":"Cloud-based visual analytics for smart grids big data","year":2016,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Saudi Arabian Cultural Bureau","keywords":"Smart grid; Big data; Computer science; Analytics; Cloud computing; Visualization; Data visualization; Grid; Data analysis; Visual analytics; Data science; Engineering; Data mining; Operating system","score_opus":0.11143163128122185,"score_gpt":0.35064800827910725,"score_spread":0.2392163769978854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2562290425","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00015487832,0.000006469548,0.99514055,0.0029767123,0.00064780243,0.000094891184,0.00014075064,0.0001713265,0.0006665994],"genre_scores_gemma":[0.6742502,0.00007913418,0.253663,0.021579802,0.0026087263,0.000030819014,0.0011962935,0.00009331053,0.046498723],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988357,0.000026042218,0.00023123625,0.00043767318,0.00022922069,0.00024013118],"domain_scores_gemma":[0.99822146,0.00019806469,0.00006645233,0.0012718401,0.00012294478,0.00011926641],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000385691,0.00011068011,0.00012937767,0.00010597345,0.00007934733,0.00017403257,0.0016787401,0.00004249475,0.000048115304],"category_scores_gemma":[0.00020586596,0.00007003409,0.00004495043,0.00035712362,0.000042648204,0.0004279258,0.00047163173,0.000024261408,0.000119375836],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020557965,0.0003310163,0.0024777392,0.000037307924,0.00006482989,0.0000055331966,0.000018845492,0.000030191599,0.00082315423,0.35803762,0.42377728,0.21437591],"study_design_scores_gemma":[0.0006584521,0.000100902944,0.00008154441,0.000014441636,0.000013568246,8.622423e-7,0.0000044813014,0.6641872,0.0022997623,0.0008329312,0.33163258,0.00017327274],"about_ca_topic_score_codex":0.000007637521,"about_ca_topic_score_gemma":0.000040621464,"teacher_disagreement_score":0.74147755,"about_ca_system_score_codex":0.000020629934,"about_ca_system_score_gemma":0.0001560323,"threshold_uncertainty_score":0.31195447},"labels":[],"label_agreement":null},{"id":"W2563147542","doi":"","title":"Using Physical and Social Sensors in Real-Time Data Streaming for Natural Hazard Monitoring and Response","year":2016,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Institute for Catastrophic Loss Reduction","keywords":"Natural (archaeology); Computer science; Hazard; Natural hazard; Real-time computing; Environmental science; Geography; Meteorology; Chemistry","score_opus":0.16883594586624223,"score_gpt":0.3863591377308927,"score_spread":0.21752319186465047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2563147542","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99202,0.000010024591,0.007408574,0.00022073313,0.00007920224,0.000116837226,0.00006663033,0.000073827905,0.000004155051],"genre_scores_gemma":[0.9983184,0.000020805466,0.0009536738,0.000020655008,0.00008417071,1.8015285e-7,0.000010889242,0.0000147617,0.0005764692],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985818,0.00022644275,0.00013947119,0.0005762083,0.00018791242,0.0002881198],"domain_scores_gemma":[0.9990129,0.00029515152,0.00010048223,0.0004310232,0.00006393231,0.00009649631],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043860966,0.00016620809,0.00021131216,0.000297815,0.00020636068,0.00032778233,0.0007243452,0.00007303631,3.8711178e-7],"category_scores_gemma":[0.000079751255,0.00015572389,0.000029063476,0.0002629122,0.000091076174,0.0031281128,0.001041213,0.00012056205,0.0000042649963],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029089718,0.00007391605,0.92947245,0.000048832597,0.000043289623,0.00013146219,0.0014912073,0.000005135193,0.06314236,0.0006077842,7.805457e-7,0.0046918914],"study_design_scores_gemma":[0.0029824122,0.00010791813,0.98776877,0.00036024879,0.000067441506,0.000033168402,0.00043195282,0.0019678469,0.00501761,0.00018256473,0.00042424304,0.0006558178],"about_ca_topic_score_codex":0.0000027257106,"about_ca_topic_score_gemma":0.00003768803,"teacher_disagreement_score":0.058296327,"about_ca_system_score_codex":0.00012478505,"about_ca_system_score_gemma":0.000064970765,"threshold_uncertainty_score":0.63502353},"labels":[],"label_agreement":null},{"id":"W2565947690","doi":"10.1109/bdva.2016.7787041","title":"An Evaluation of Interaction Methods for Controlling RSVP Displays in Visual Search Tasks","year":2016,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of Toronto","funders":"University of Toronto","keywords":"Rapid serial visual presentation; Computer science; Interface (matter); Visual search; Task (project management); Point (geometry); Computer vision; Identification (biology); Human–computer interaction; Artificial intelligence; Cognition","score_opus":0.126800584129117,"score_gpt":0.5314741742281277,"score_spread":0.4046735900990107,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2565947690","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012866449,0.0000067979827,0.98635817,0.00021200893,0.00010848992,0.00018916882,0.0000035391854,0.000020863426,0.00023449061],"genre_scores_gemma":[0.8855648,0.000004422328,0.11424864,0.00006852135,0.000022756481,0.000013233717,0.000010670178,0.0000036112906,0.00006333759],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99892884,0.00033035036,0.00022857697,0.00018567065,0.0002186314,0.00010792228],"domain_scores_gemma":[0.9990808,0.0003164723,0.00006308499,0.00019069109,0.00031196824,0.000037005233],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032733723,0.000050456696,0.00010287439,0.0001573311,0.000023933211,0.000051074778,0.00022871004,0.000028230119,0.00004472563],"category_scores_gemma":[0.00026186238,0.000033925968,0.00002760646,0.0002045408,0.000014086137,0.0007719233,0.000037391066,0.00002342338,0.0000040619416],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025510139,0.00015830813,0.0007869565,0.00001067885,0.000011797764,8.873256e-8,0.0002958802,0.0012142318,0.06894362,0.086478435,0.00006363674,0.84201086],"study_design_scores_gemma":[0.00090081606,0.00009382808,0.00048371404,0.000019465117,0.000007205902,3.6262279e-7,0.00006281685,0.9635274,0.032978877,0.0016252904,0.00024846353,0.000051749685],"about_ca_topic_score_codex":0.000022372002,"about_ca_topic_score_gemma":0.000026728767,"teacher_disagreement_score":0.9623132,"about_ca_system_score_codex":0.000048113016,"about_ca_system_score_gemma":0.00006448144,"threshold_uncertainty_score":0.13834608},"labels":[],"label_agreement":null},{"id":"W2572544670","doi":"","title":"Joint Action Theory and Pair Analytics: In-vivo Studies of Cognition and Social Interaction in Collaborative Visual Analytics","year":2011,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Analytics; Computer science; Cognition; Cognitive science; Action (physics); MAGIC (telescope); Human–computer interaction; Spatial cognition; Psychology; Data science; Neuroscience","score_opus":0.05967827497854177,"score_gpt":0.3055037839582426,"score_spread":0.24582550897970085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2572544670","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98476946,0.00019423042,0.011485453,0.00028164065,0.00010695859,0.00026872012,0.0004867439,0.000111395406,0.0022953774],"genre_scores_gemma":[0.9988338,0.00012150392,0.0006624266,0.00020361194,0.000023942179,0.000005370748,0.00007168889,0.000013573968,0.00006408424],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99861836,0.00020606612,0.0004796087,0.00032459217,0.00019076548,0.00018061126],"domain_scores_gemma":[0.99931544,0.00017289021,0.0002276573,0.000117009346,0.00009914607,0.000067878704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041602697,0.00017277194,0.00029623494,0.00047836115,0.000066887274,0.00036436834,0.00015102894,0.00008557572,0.00002708234],"category_scores_gemma":[0.0002754042,0.000164185,0.000039007467,0.0008706689,0.00016418485,0.0049577192,0.00026794215,0.00019486781,0.000011274465],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013503613,0.002870256,0.56385326,0.0011044727,0.0007357871,0.00015827297,0.01638845,0.000043700096,0.0027593074,0.34787118,0.0019506419,0.060914263],"study_design_scores_gemma":[0.009339963,0.0022510514,0.22581248,0.0018475224,0.00035614564,0.000065733446,0.049636237,0.09271321,0.1207326,0.48210114,0.01178157,0.0033623513],"about_ca_topic_score_codex":0.0000021620933,"about_ca_topic_score_gemma":0.000013400608,"teacher_disagreement_score":0.3380408,"about_ca_system_score_codex":0.00003356313,"about_ca_system_score_gemma":0.00005995091,"threshold_uncertainty_score":0.669527},"labels":[],"label_agreement":null},{"id":"W2574075402","doi":"","title":"Predicting confusion in information visualization from eye tracking and interaction data","year":2016,"lang":"en","type":"article","venue":"International Joint Conference on Artificial Intelligence","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Confusion; Visualization; Computer science; Focus (optics); Human–computer interaction; Information visualization; Data visualization; Eye tracking; Random forest; User satisfaction; Tracking (education); Data science; Artificial intelligence; Psychology","score_opus":0.15658463720611557,"score_gpt":0.38932103142448754,"score_spread":0.23273639421837197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2574075402","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04679868,0.0000044704093,0.94706583,0.0037194972,0.0008735662,0.00013649804,0.000090960355,0.000107021566,0.0012034717],"genre_scores_gemma":[0.9973936,0.00016377578,0.0015910051,0.0004712204,0.0001001005,0.000006328521,0.00023921432,0.0000062336026,0.000028519547],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981412,0.000083914296,0.00069708575,0.00045364883,0.00045277897,0.00017136137],"domain_scores_gemma":[0.99868923,0.00017050514,0.0002927083,0.0004662681,0.00030729792,0.00007398229],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004431077,0.0001543582,0.00014455144,0.00037717787,0.000075624186,0.00063252554,0.0008946952,0.000074051066,0.00020899196],"category_scores_gemma":[0.00082499813,0.000126851,0.00002181222,0.00024176539,0.00006270061,0.004431931,0.00048259026,0.000119569006,0.0001892423],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029666777,0.000079470796,0.0024198215,0.0000040028126,0.0000121658095,0.0000038217786,0.0008844788,0.0001109268,0.005402787,0.509456,0.000057370566,0.48153952],"study_design_scores_gemma":[0.000102556165,0.000049681767,0.0035980812,0.00039064488,0.0000037700902,0.0000026888874,0.00046630218,0.95390475,0.014160055,0.025739944,0.0013784325,0.00020312384],"about_ca_topic_score_codex":0.0002488962,"about_ca_topic_score_gemma":0.0002601773,"teacher_disagreement_score":0.9537938,"about_ca_system_score_codex":0.00009293894,"about_ca_system_score_gemma":0.00006629489,"threshold_uncertainty_score":0.60994583},"labels":[],"label_agreement":null},{"id":"W2575557354","doi":"10.1109/wi.2016.0127","title":"An Interactive Circular Visual Analytic Tool for Visualization of Web Data","year":2016,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Visual analytics; Session (web analytics); Visualization; Analytics; Web analytics; Data visualization; Web page; Interactive visual analysis; Cultural analytics; Information retrieval; World Wide Web; Semantic analytics; Web modeling; Data mining; Web intelligence","score_opus":0.04208343595782448,"score_gpt":0.377843855377213,"score_spread":0.3357604194193885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2575557354","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003988007,0.0000050096896,0.9951863,0.00017383334,0.00010650055,0.00014103006,0.00009134365,0.00009408449,0.00021387993],"genre_scores_gemma":[0.988269,0.0000146905995,0.010780724,0.00031710928,0.00004896957,0.0000041521125,0.0002462247,0.000010493147,0.00030868623],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988554,0.00005763293,0.00030115605,0.0004207209,0.00021781931,0.00014726892],"domain_scores_gemma":[0.99839854,0.00013313479,0.00014604209,0.0010147673,0.00024510678,0.00006239242],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037727357,0.00009644656,0.00015325977,0.00015499059,0.000042329204,0.000103181555,0.0012112872,0.000037018537,0.00008361095],"category_scores_gemma":[0.0002482103,0.000066572065,0.000037391248,0.00036128174,0.000034761062,0.0022485948,0.00028138564,0.000015838437,0.000020242342],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042923024,0.0010181277,0.0062247566,0.00010757026,0.00020540736,0.0000035776486,0.000383676,0.000061577375,0.07861375,0.8098655,0.013748399,0.08972478],"study_design_scores_gemma":[0.0005639751,0.00015714708,0.00040250015,0.000030023799,0.00002079596,0.0000016909192,0.000033934295,0.98338413,0.0075504384,0.0009043857,0.0067978455,0.00015314069],"about_ca_topic_score_codex":0.0000053634167,"about_ca_topic_score_gemma":0.000007669548,"teacher_disagreement_score":0.9844056,"about_ca_system_score_codex":0.00002418877,"about_ca_system_score_gemma":0.00010613199,"threshold_uncertainty_score":0.271473},"labels":[],"label_agreement":null},{"id":"W2580292168","doi":"10.11606/d.100.2016.tde-24112016-123123","title":"InterVis: um sistema para geração e exploração interativas de visualizações de informação","year":2016,"lang":"pt","type":"dissertation","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Discovery Air (Canada)","funders":"","keywords":"Computer science; Usability; Flexibility (engineering); Perspective (graphical); Visualization; Human–computer interaction; Domain (mathematical analysis); Autonomy; World Wide Web; Information retrieval; Data mining; Artificial intelligence","score_opus":0.05807421003860977,"score_gpt":0.37033606647603234,"score_spread":0.31226185643742255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2580292168","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0042962832,0.00033552074,0.98167646,0.000594486,0.0016003844,0.0005200961,0.00010131334,0.00050839206,0.010367059],"genre_scores_gemma":[0.718071,0.0030050871,0.0132718105,0.009090946,0.0011196918,0.0003918775,0.004542193,0.00036144027,0.25014594],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9941024,0.00050748675,0.0019208906,0.0011746942,0.00093728496,0.0013572448],"domain_scores_gemma":[0.9956302,0.00031965892,0.0010680445,0.0014918981,0.0007629365,0.00072724826],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0010963093,0.0010961452,0.0010517482,0.000898121,0.00048984395,0.0021601804,0.0030541404,0.000686626,0.0017015784],"category_scores_gemma":[0.0004279674,0.0008997872,0.0005703113,0.0009792931,0.000113717935,0.0028624507,0.00073980674,0.0005380701,0.0018784817],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035807333,0.001973824,0.005822684,0.008443182,0.0023473941,0.0004143522,0.21111695,0.00020530605,0.009863606,0.25064245,0.07042389,0.43838826],"study_design_scores_gemma":[0.0028503502,0.0012038121,0.0007073415,0.009557541,0.00041766607,0.00016964672,0.025681483,0.85753584,0.038538426,0.002043279,0.056946103,0.0043485034],"about_ca_topic_score_codex":0.00011397467,"about_ca_topic_score_gemma":0.0002101602,"teacher_disagreement_score":0.96840465,"about_ca_system_score_codex":0.00060512946,"about_ca_system_score_gemma":0.001348292,"threshold_uncertainty_score":0.9993453},"labels":[],"label_agreement":null},{"id":"W2586111535","doi":"10.4018/978-1-5225-2058-0.ch001","title":"Interactive Visual Analytics of Big Data","year":2017,"lang":"en","type":"book-chapter","venue":"Advances in information quality and management","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Visual analytics; Big data; Interactive visual analysis; Variety (cybernetics); Visualization; Data science; Data visualization; Analytics; Interactive visualization; Information retrieval; Data exploration; Information visualization; Data mining; Creative visualization; Artificial intelligence","score_opus":0.10004036548525094,"score_gpt":0.4012229443977909,"score_spread":0.30118257891253997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2586111535","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[6.6408376e-7,0.00022437124,0.5169119,0.00014007329,0.00033236764,0.0001740057,0.00012530986,0.000022024473,0.48206925],"genre_scores_gemma":[0.04945562,0.42475712,0.10648138,0.013048156,0.0007948808,0.00008006815,0.019523438,0.000120192526,0.38573915],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99858606,0.000019053168,0.0007204147,0.00022735453,0.00034162297,0.00010547274],"domain_scores_gemma":[0.99776584,0.000047294645,0.0009554081,0.0010964473,0.00009602762,0.000038955215],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006166553,0.00015773319,0.00027781323,0.0003331994,0.00006714911,0.00018988765,0.0011531,0.00006711176,0.000010577515],"category_scores_gemma":[0.00006406164,0.00015672385,0.000029948644,0.000041031773,0.000098143355,0.0051302407,0.0015827434,0.00011625997,0.000022013124],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000048837605,0.000010802031,0.00000941916,0.00034287164,0.000023052602,0.0000010659376,0.00015803556,0.000044150027,1.5072237e-8,0.66671747,0.00035077572,0.33233747],"study_design_scores_gemma":[0.0003103206,0.00002773007,0.00013785134,0.00028526987,0.000022994094,6.70421e-7,0.00010682552,0.021919416,0.0000020361633,0.030890882,0.9460859,0.00021013377],"about_ca_topic_score_codex":0.000010887964,"about_ca_topic_score_gemma":0.00006457069,"teacher_disagreement_score":0.9457351,"about_ca_system_score_codex":0.00003244639,"about_ca_system_score_gemma":0.000024872366,"threshold_uncertainty_score":0.63910127},"labels":[],"label_agreement":null},{"id":"W2587399391","doi":"","title":"Cognitive Science in the Design of Graphical Images and Interfaces","year":2007,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Cognitive science; Cognition; Communication design; Human–computer interaction; Graphic design; Visualization; Perception; Psychology; Multimedia; Artificial intelligence","score_opus":0.024263240185258456,"score_gpt":0.2736698027491069,"score_spread":0.24940656256384844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2587399391","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2640837,0.00016052907,0.72838044,0.00075574603,0.00006459395,0.00027093018,0.0002649797,0.00011065442,0.0059083956],"genre_scores_gemma":[0.99616635,0.000018556268,0.003192324,0.0005609482,0.000011674966,0.0000015559498,0.000016056196,0.0000064935766,0.000026055566],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987186,0.0000695277,0.00028029154,0.00029362744,0.00038200495,0.00025590629],"domain_scores_gemma":[0.99902993,0.0005154257,0.00008161693,0.00022299183,0.000048829028,0.000101203914],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0010945485,0.00011319994,0.00011896136,0.0003148917,0.00008663112,0.0013628817,0.0010774784,0.000036714646,0.000009852051],"category_scores_gemma":[0.0005037883,0.00007838127,0.00002552105,0.001635438,0.0005174302,0.005148818,0.0003958388,0.0001769832,0.00003254706],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002078795,0.0012431189,0.5310717,0.00012506158,0.000041913667,0.0002146618,0.00154609,0.000024832763,0.003485976,0.3312176,0.001766398,0.12905475],"study_design_scores_gemma":[0.004038386,0.0014138003,0.5236592,0.0010667144,0.00005390755,0.00022741329,0.0035068418,0.027358668,0.2062928,0.21351734,0.016547699,0.0023172062],"about_ca_topic_score_codex":7.45176e-7,"about_ca_topic_score_gemma":3.224743e-7,"teacher_disagreement_score":0.7320826,"about_ca_system_score_codex":0.0000054686266,"about_ca_system_score_gemma":0.0000752423,"threshold_uncertainty_score":0.9996738},"labels":[],"label_agreement":null},{"id":"W2588731222","doi":"10.1145/3022198.3026311","title":"A Collaborative Visualization Tool to Support Doctors' Shared Decision-Making on Antibiotic Prescription","year":2017,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Asynchronous communication; Visualization; Computer-supported cooperative work; Computer science; Medical prescription; Decision support system; Visual analytics; Process (computing); Analytics; Work (physics); Data science; Medicine; Data mining; Nursing; Engineering","score_opus":0.026347725236086368,"score_gpt":0.36587218870547916,"score_spread":0.3395244634693928,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2588731222","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012859157,0.0000018845227,0.97673064,0.00032993214,0.0005743375,0.00032941092,0.00003067979,0.00017858097,0.008965346],"genre_scores_gemma":[0.9681257,0.0000062800164,0.028805722,0.0017479436,0.00006992556,0.000004035016,0.00003376078,0.000011827298,0.0011947893],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99857014,0.000039466282,0.00028728697,0.00045806126,0.00043511105,0.00020994389],"domain_scores_gemma":[0.99831164,0.00006339577,0.00018536563,0.0010334643,0.00030748607,0.00009867714],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00028355655,0.00014486627,0.00015577763,0.00019638638,0.0004839129,0.002144687,0.0010849742,0.000056767356,0.00019083575],"category_scores_gemma":[0.00092364696,0.00012730712,0.000036794463,0.00039645674,0.00002360276,0.0015848213,0.00039919445,0.00004562821,0.00047671332],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055447526,0.00032912355,0.0048499606,0.000024200883,0.000034992983,0.0000333473,0.0017437823,0.0006626913,0.0011191452,0.78609955,0.10183673,0.10321101],"study_design_scores_gemma":[0.0018285371,0.0016890866,0.11347501,0.0008027322,0.00003997332,0.000011938013,0.00026937234,0.74598444,0.009690021,0.005437585,0.119205676,0.001565638],"about_ca_topic_score_codex":0.000007505987,"about_ca_topic_score_gemma":0.000033340963,"teacher_disagreement_score":0.95526654,"about_ca_system_score_codex":0.000057863937,"about_ca_system_score_gemma":0.00009821132,"threshold_uncertainty_score":0.9988912},"labels":[],"label_agreement":null},{"id":"W2589818235","doi":"","title":"Quantitative Reasoning: Exploring Troublesome Thresholds","year":2017,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Psychology","score_opus":0.2958402626661939,"score_gpt":0.3870353841730829,"score_spread":0.09119512150688902,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2589818235","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8900031,0.0000348449,0.10729965,0.00046086762,0.00046859714,0.00013093468,0.000016633003,0.00029637982,0.0012890318],"genre_scores_gemma":[0.99258626,0.00010491251,0.0015771732,0.00024690924,0.00007152327,0.0000013350154,0.000016809747,0.000028813254,0.0053662895],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99791986,0.00014385885,0.00023876269,0.00072464877,0.0004786031,0.00049427425],"domain_scores_gemma":[0.99719995,0.00006613201,0.00036802335,0.0018485168,0.00020489901,0.00031248442],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0004370496,0.00028904263,0.0003093278,0.00041434044,0.0010917966,0.0022856288,0.0039296728,0.00011543969,0.000012342195],"category_scores_gemma":[0.00014980683,0.00032334574,0.00013472216,0.00034668145,0.00016546226,0.011008616,0.0015459456,0.00036069175,0.00033913463],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026400867,0.000074855525,0.91430867,0.000020690137,0.000054113265,0.0002996668,0.0004883006,0.0000265944,0.00017988938,0.08368482,0.0000028415557,0.0008331916],"study_design_scores_gemma":[0.0012481434,0.00016477583,0.98786336,0.00023614135,0.000045133365,0.000028098786,0.00029686908,0.00010815058,0.001790157,0.0007312781,0.006841753,0.0006461551],"about_ca_topic_score_codex":0.000005572395,"about_ca_topic_score_gemma":0.0002782133,"teacher_disagreement_score":0.10572248,"about_ca_system_score_codex":0.00012608281,"about_ca_system_score_gemma":0.00010470302,"threshold_uncertainty_score":0.99992186},"labels":[],"label_agreement":null},{"id":"W2591887453","doi":"","title":"Overcoming the digital tsunami in e-discovery: is visual analysis the answer?","year":2011,"lang":"en","type":"article","venue":"eYLS (Yale Law School)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Context (archaeology); Field (mathematics); Data science; Information retrieval","score_opus":0.021763451534238185,"score_gpt":0.27318193125343726,"score_spread":0.25141847971919906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2591887453","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22642298,0.00054739066,0.69526017,0.004616949,0.00092841475,0.0006751263,0.00017730951,0.000435678,0.070936],"genre_scores_gemma":[0.99323446,0.000018649911,0.0004645735,0.004777651,0.000065516775,0.000007098911,0.000018329118,0.000010412317,0.0014032865],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99847484,0.000103398255,0.00032350226,0.0003921392,0.00038883302,0.00031727736],"domain_scores_gemma":[0.9987073,0.000112245834,0.000116583804,0.00092249503,0.000047405105,0.0000939786],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0004525026,0.00016780342,0.0002057762,0.00012663567,0.00023987368,0.0012200535,0.0015439427,0.00005351144,0.00015283661],"category_scores_gemma":[0.000074868134,0.00010145942,0.00017614894,0.0017586703,0.00012541872,0.0017838887,0.00046807437,0.0002178824,0.00020775151],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016582655,0.00032744507,0.076386325,0.000011179976,0.00049240986,0.000036882277,0.004082611,0.00023934324,0.000040767358,0.9067476,0.0065915766,0.005027329],"study_design_scores_gemma":[0.0016459774,0.00022973782,0.12274803,0.000094249015,0.00055378536,0.000021820835,0.002182839,0.57095057,0.002046449,0.02141414,0.2765476,0.0015648125],"about_ca_topic_score_codex":0.0008985033,"about_ca_topic_score_gemma":0.0008386098,"teacher_disagreement_score":0.8853334,"about_ca_system_score_codex":0.000037644906,"about_ca_system_score_gemma":0.00005829762,"threshold_uncertainty_score":0.9998168},"labels":[],"label_agreement":null},{"id":"W2592360258","doi":"10.3390/ijgi6030076","title":"A Web-Based Visual and Analytical Geographical Information System for Oil and Gas Data","year":2017,"lang":"en","type":"article","venue":"ISPRS International Journal of Geo-Information","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; China Scholarship Council","keywords":"Visualization; Usability; Fossil fuel; Computer science; Set (abstract data type); Data visualization; Data set; Petroleum industry; Petroleum engineering; Data mining; Environmental science; Human–computer interaction; Engineering; Artificial intelligence","score_opus":0.02205895387197214,"score_gpt":0.32903045722827706,"score_spread":0.3069715033563049,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2592360258","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018964132,0.00002191746,0.97104204,0.0075280326,0.0011841587,0.00008411276,0.0003008339,0.000044998855,0.000829769],"genre_scores_gemma":[0.9845824,0.00014299691,0.013526424,0.0011352268,0.00019266416,0.0000037188815,0.0003957675,0.0000044773697,0.000016313646],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982954,0.000027169483,0.0007562206,0.00009840018,0.00067815935,0.00014460951],"domain_scores_gemma":[0.99728435,0.00009183244,0.0010389421,0.00038731305,0.0010533114,0.00014426715],"candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0010005136,0.00012318703,0.00018533586,0.0005305498,0.00026906928,0.002437618,0.0014650485,0.00007940028,0.000004259167],"category_scores_gemma":[0.00073275075,0.000107064814,0.000060457365,0.000083201114,0.00009242572,0.01598069,0.00043365068,0.00012885012,0.000010181362],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000354748,0.00008831463,0.006628341,0.0003272964,0.0003210941,0.000009746206,0.00058465864,0.00038053846,0.000021368736,0.1432239,0.00804473,0.8400153],"study_design_scores_gemma":[0.0021758438,0.000099439654,0.0030619374,0.00012942952,0.000035398753,0.00012073166,0.00013635402,0.9372347,0.00004228691,0.0001717916,0.056666195,0.00012589537],"about_ca_topic_score_codex":0.000015769645,"about_ca_topic_score_gemma":0.0000035672704,"teacher_disagreement_score":0.96561825,"about_ca_system_score_codex":0.000052696592,"about_ca_system_score_gemma":0.00017335382,"threshold_uncertainty_score":0.9985979},"labels":[],"label_agreement":null},{"id":"W2592594555","doi":"10.1177/1473871617693040","title":"A geovisual analytics approach for analyzing event-based geospatial anomalies within movement data","year":2017,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"Fisheries and Oceans Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Geospatial analysis; Visual analytics; Analytics; Data mining; Field (mathematics); Data science; Event (particle physics); Domain (mathematical analysis); Visualization; Cartography","score_opus":0.05867234117495741,"score_gpt":0.35121864530305086,"score_spread":0.29254630412809346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2592594555","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008476299,0.000007955233,0.9973168,0.00020613571,0.00030869097,0.0005006688,0.0002520641,0.00018872111,0.00037133222],"genre_scores_gemma":[0.8702519,0.000015698677,0.110190034,0.0023820102,0.00020606286,0.00006643531,0.016694702,0.000026225898,0.00016693662],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99787873,0.000055847013,0.0008456542,0.00036615212,0.0005646594,0.0002889555],"domain_scores_gemma":[0.99619573,0.000044999833,0.0011717976,0.0019541904,0.0005168172,0.00011648786],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0011194535,0.00022481881,0.00023766723,0.00034423685,0.0009429393,0.002491108,0.002294407,0.000105123305,0.00001187167],"category_scores_gemma":[0.0006983926,0.00022351608,0.00007102464,0.00032583874,0.00006602441,0.008775364,0.00060572533,0.000068352885,0.000020877931],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007768475,0.00044936818,0.010879858,0.00048838934,0.00018138581,0.0000011172377,0.0021330426,0.24263182,0.00008900824,0.71421766,0.009690356,0.019160325],"study_design_scores_gemma":[0.00095209864,0.000090060894,0.0009076298,0.000025999021,0.00003899826,6.7023853e-7,0.00012785458,0.9917413,0.0006574637,0.00032356736,0.004849355,0.0002850116],"about_ca_topic_score_codex":0.000053459615,"about_ca_topic_score_gemma":0.00002753871,"teacher_disagreement_score":0.88712674,"about_ca_system_score_codex":0.00007609033,"about_ca_system_score_gemma":0.0002462158,"threshold_uncertainty_score":0.9985444},"labels":[],"label_agreement":null},{"id":"W2594164625","doi":"10.1145/3025171.3025208","title":"Label-and-Learn","year":2017,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Leverage (statistics); Classifier (UML); Machine learning; Artificial intelligence; Software; Visualization; Data science; Human–computer interaction","score_opus":0.04749049072780054,"score_gpt":0.3425766233070547,"score_spread":0.29508613257925415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2594164625","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010841986,0.000011722492,0.87652797,0.004328749,0.000110136636,0.000018029828,6.7893274e-7,0.00008895684,0.11782958],"genre_scores_gemma":[0.88747716,0.00006499751,0.056826886,0.0028336437,0.000051546165,8.149435e-7,0.0000020575524,0.000004138515,0.05273876],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99977636,0.000004110313,0.000033841647,0.00008371661,0.000051624345,0.00005032592],"domain_scores_gemma":[0.9995369,0.000005370251,0.000022131706,0.00038767233,0.000015018586,0.00003296135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000059986316,0.00002266038,0.000028247518,0.000012001562,0.00016018399,0.0004493352,0.00044720047,0.000009177234,0.00003104084],"category_scores_gemma":[0.000037627608,0.00001787252,0.0000048507895,0.000015658556,0.000020572854,0.000349903,0.0002620112,0.000015510706,0.00011538708],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.819288e-8,0.0000071993563,0.0012022475,0.000001115313,0.0000016248276,0.0000013924948,0.00002628093,1.812192e-7,0.000025166028,0.95488924,0.0055856393,0.03825982],"study_design_scores_gemma":[0.00045841065,0.000034679648,0.01627207,0.000007895159,0.0000033342362,0.00000712133,0.000015883335,0.55880964,0.00077738904,0.011683748,0.41174218,0.00018763334],"about_ca_topic_score_codex":0.000012454727,"about_ca_topic_score_gemma":0.0000060699313,"teacher_disagreement_score":0.94320554,"about_ca_system_score_codex":0.0000012605086,"about_ca_system_score_gemma":0.000006423301,"threshold_uncertainty_score":0.43329495},"labels":[],"label_agreement":null},{"id":"W2594247142","doi":"","title":"Fostering Insight and Collaboration in Long-Term Healthcare through Collection and Visualization of Qualitative Healthcare Data","year":2014,"lang":"en","type":"other","venue":"OCAD University Open Research Repository (OCAD University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Health care; Usability; Scope (computer science); Analytics; Qualitative research; Visualization; Visual analytics; Data visualization; Computer science; Knowledge management; Data science; Data collection; Structuring; Human–computer interaction; Sociology; Business; Data mining","score_opus":0.2117760825751268,"score_gpt":0.4594341350566708,"score_spread":0.247658052481544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2594247142","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0025378177,0.0011253846,0.121390946,0.0023137534,0.00041246234,0.0028820354,0.00040281133,0.00020514037,0.86872965],"genre_scores_gemma":[0.15934858,0.012686708,0.0074922824,0.0002040013,0.00017114359,0.0000019509646,0.002051337,0.00024804784,0.81779593],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99550164,0.0024392663,0.00025675626,0.0009469536,0.0005486938,0.00030670932],"domain_scores_gemma":[0.9978703,0.00015938704,0.00038780886,0.00090666267,0.0004863318,0.0001894813],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009769856,0.0002211851,0.0004476821,0.0012372138,0.0005292147,0.0003221664,0.001737657,0.00032734324,0.000001151521],"category_scores_gemma":[0.00006741253,0.00027802793,0.000022773937,0.0024873766,0.00035027973,0.00192136,0.0033799438,0.00032569465,0.0000023299417],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000090169466,0.00007553908,0.0024559537,0.0005736751,0.000054618533,0.00009691542,0.00612608,0.0000024125543,0.000039861086,0.9861919,0.0036031902,0.00068968156],"study_design_scores_gemma":[0.009552044,0.0023084641,0.00911556,0.006510471,0.00018127158,0.00006377329,0.034011673,0.027037987,0.0004804044,0.0009474534,0.90745294,0.0023379766],"about_ca_topic_score_codex":0.0075566885,"about_ca_topic_score_gemma":0.015298238,"teacher_disagreement_score":0.98524445,"about_ca_system_score_codex":0.000427891,"about_ca_system_score_gemma":0.0007678076,"threshold_uncertainty_score":0.9999672},"labels":[],"label_agreement":null},{"id":"W2594443006","doi":"10.3138/cart.52.1.3820","title":"An Evaluation of a Visual Analytics Prototype for Calendar-Related Spatiotemporal Periodicity Detection and Analysis","year":2017,"lang":"en","type":"article","venue":"Cartographica The International Journal for Geographic Information and Geovisualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Usability; Visual analytics; Learnability; Analytics; Computer science; Visualization; Scale (ratio); Data science; Cultural analytics; Human–computer interaction; Event (particle physics); Geovisualization; Frame (networking); Field (mathematics); Artificial intelligence; Cartography; Information visualization; Geography; The Internet; World Wide Web; Semantic analytics","score_opus":0.024201954297616082,"score_gpt":0.3519265725515373,"score_spread":0.32772461825392124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2594443006","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18441138,0.000069404414,0.8131888,0.00070363254,0.00051510584,0.0008869161,0.00016463177,0.00003486811,0.000025284626],"genre_scores_gemma":[0.99787205,0.00024871467,0.0011356873,0.00019161947,0.000068424604,0.00007364997,0.00039664799,0.000007218531,0.0000060012862],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978729,0.00012290098,0.0007680943,0.00021258768,0.0008503458,0.0001731859],"domain_scores_gemma":[0.99490124,0.00008104149,0.0012866544,0.00036049087,0.0032528383,0.00011771688],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0031972765,0.00016865467,0.00023106807,0.0011809202,0.0012747826,0.00133432,0.0007319889,0.0001224509,0.000007787844],"category_scores_gemma":[0.00057714107,0.00013606381,0.00022193024,0.0005559623,0.00023809755,0.0031147862,0.0000966608,0.000116881136,2.359232e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007657465,0.0005231173,0.18094881,0.00022458033,0.004852786,0.0000010794719,0.006981356,0.009712725,0.00089623156,0.21820915,0.00024822287,0.5766362],"study_design_scores_gemma":[0.0014489858,0.00034933153,0.053258322,0.000024959736,0.0005790184,0.000017179082,0.00025561685,0.9348751,0.00029147096,0.006545852,0.002189472,0.00016470543],"about_ca_topic_score_codex":0.00006647064,"about_ca_topic_score_gemma":0.00015432833,"teacher_disagreement_score":0.9251624,"about_ca_system_score_codex":0.000029813622,"about_ca_system_score_gemma":0.00012243834,"threshold_uncertainty_score":0.9997024},"labels":[],"label_agreement":null},{"id":"W2597453057","doi":"10.29173/cais298","title":"The Visualization of the Citation Patterns of Some Canadian Journals","year":2013,"lang":"fr","type":"article","venue":"Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"Western University","funders":"","keywords":"Citation; Subject (documents); Humanities; Library science; Computer science; Art","score_opus":0.03821450705543486,"score_gpt":0.28287597528539743,"score_spread":0.24466146822996257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2597453057","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96007097,0.0011448899,0.0021684668,0.03165454,0.0011370889,0.0008565066,0.0006306739,0.000019330155,0.002317525],"genre_scores_gemma":[0.9962568,0.0008153894,0.0001346384,0.00048449024,0.000096672906,0.000010457077,0.000005975129,0.000018672887,0.002176848],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99729556,0.00010640912,0.0010345168,0.00026469663,0.00084284163,0.00045597611],"domain_scores_gemma":[0.94047135,0.00023363958,0.0021901994,0.00038455162,0.056521483,0.00019876625],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0011626378,0.00025139807,0.00042905958,0.00023065384,0.0003027458,0.0031689461,0.0034434334,0.00017458275,0.000072168536],"category_scores_gemma":[0.012931515,0.00015994652,0.00022617202,0.0010127423,0.00063550496,0.011362995,0.0006332883,0.00023720588,0.000004291489],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020352125,0.0002214127,0.26816767,0.0008702706,0.00023605576,4.0569154e-7,0.04621922,0.000070725626,0.009133421,0.64142424,0.015114689,0.018521538],"study_design_scores_gemma":[0.001131658,0.0005529457,0.68689847,0.0039655324,0.00037055137,0.00004407649,0.010450609,0.062411144,0.08656584,0.054395594,0.092448756,0.00076480885],"about_ca_topic_score_codex":0.01884117,"about_ca_topic_score_gemma":0.002313441,"teacher_disagreement_score":0.5870286,"about_ca_system_score_codex":0.000082893646,"about_ca_system_score_gemma":0.0009411456,"threshold_uncertainty_score":0.99786586},"labels":[],"label_agreement":null},{"id":"W2597940383","doi":"","title":"Using VisKit: A Manual for Running a Constructive Visualization Workshop","year":2016,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Constructive; Visualization; Computer science; Set (abstract data type); Data visualization; Human–computer interaction; Multimedia; Process (computing); Artificial intelligence; Programming language","score_opus":0.03732485101324698,"score_gpt":0.3207224499319827,"score_spread":0.2833975989187357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2597940383","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015821876,0.00025328796,0.9893129,0.002741819,0.0004196915,0.0005494027,0.0002256356,0.00034013126,0.0045749457],"genre_scores_gemma":[0.26288626,0.00025743863,0.72979534,0.00038576362,0.00013431469,0.00007850568,0.0017875443,0.00010263535,0.0045722364],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99536055,0.001861402,0.00064487115,0.0012375824,0.0004833451,0.0004122624],"domain_scores_gemma":[0.9917393,0.0012949179,0.0008256671,0.003173517,0.002780201,0.00018639956],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0043042186,0.0003602836,0.00040930827,0.00032904136,0.00047002922,0.001133048,0.0033155142,0.00029858146,0.000033318833],"category_scores_gemma":[0.0019565043,0.00035955012,0.00016501479,0.00053842086,0.0002196326,0.00065434666,0.0043211505,0.00027896184,0.000014155873],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007713698,0.00021852502,0.00042584568,0.00014836749,0.00011338154,0.0000026616444,0.0045566033,0.00014748579,0.0006108421,0.9559366,0.0014351233,0.03639684],"study_design_scores_gemma":[0.0006584236,3.3259025e-7,0.00009378647,0.0022095293,0.00006058193,0.000012102114,0.00012501422,0.9537641,0.0059162695,0.02764025,0.00897105,0.000548556],"about_ca_topic_score_codex":0.00007314164,"about_ca_topic_score_gemma":0.00011844809,"teacher_disagreement_score":0.9536166,"about_ca_system_score_codex":0.00015657583,"about_ca_system_score_gemma":0.0005720274,"threshold_uncertainty_score":0.99990386},"labels":[],"label_agreement":null},{"id":"W26047017","doi":"","title":"Evaluation of New Visualization Approaches for Representing Uncertainty in the Recognized Maritime Picture","year":2008,"lang":"en","type":"article","venue":"Defense Technical Information Center (DTIC)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Visualization; Computer science; Workload; Domain (mathematical analysis); Representation (politics); Operations research; Simulation; Human–computer interaction; Data mining; Engineering","score_opus":0.14524018585401288,"score_gpt":0.34264230976922455,"score_spread":0.19740212391521167,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W26047017","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0062922486,0.000017812145,0.98881215,0.0006403359,0.0000914174,0.00089851196,0.000024418428,0.00011069105,0.0031124305],"genre_scores_gemma":[0.9867691,0.000022354936,0.011233543,0.0010974192,0.000042645042,0.0000602108,0.0007357106,0.00000671016,0.00003232487],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979086,0.00019884926,0.00071646326,0.00017391179,0.00081397314,0.00018820056],"domain_scores_gemma":[0.9985638,0.00015970865,0.0003065994,0.0004638132,0.00045884398,0.000047180256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024197823,0.000119578035,0.00016950128,0.00020908071,0.00011020935,0.00011332757,0.0005464021,0.00010208738,0.000017883383],"category_scores_gemma":[0.0013534294,0.00009247684,0.00009024258,0.0007165318,0.000048177193,0.0012842821,0.00011847345,0.00010441212,0.000011300903],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022350314,0.0014397805,0.0074384944,0.00039726894,0.00015422374,0.0000038731146,0.02745321,0.046129484,0.00014177365,0.57280606,0.10556487,0.23824744],"study_design_scores_gemma":[0.001749946,0.000045652465,0.0028397103,0.00004236027,0.00003282354,0.000028069786,0.00024417244,0.9808076,0.00011901849,0.0046694838,0.009275442,0.00014571074],"about_ca_topic_score_codex":0.000016744505,"about_ca_topic_score_gemma":0.000015930615,"teacher_disagreement_score":0.98047686,"about_ca_system_score_codex":0.00006729776,"about_ca_system_score_gemma":0.0001462833,"threshold_uncertainty_score":0.37710962},"labels":[],"label_agreement":null},{"id":"W2607094875","doi":"10.2196/publichealth.7492","title":"Making Air Pollution Visible: A Tool for Promoting Environmental Health Literacy","year":2017,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"U.S. National Library of Medicine","keywords":"Air pollution; Environmental health; Public health; Health literacy; Environmental planning; Environmental science; Political science; Medicine; Biology; Health care; Ecology","score_opus":0.044929853365223135,"score_gpt":0.3731733469672529,"score_spread":0.32824349360202976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2607094875","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021255316,0.00082765,0.842167,0.1333305,0.00044843357,0.0013310661,0.00020232995,0.00023729567,0.00020042008],"genre_scores_gemma":[0.9793129,0.00018224485,0.008242611,0.011834954,0.00012038674,0.00004506424,0.000089120156,0.0000107536935,0.00016198281],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99826545,0.00013967823,0.0003858887,0.00042510204,0.00021195812,0.0005719503],"domain_scores_gemma":[0.99849826,0.0000476556,0.00047209655,0.0006126101,0.000035205838,0.00033416334],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001632312,0.00013149779,0.00023774967,0.00009059114,0.0012980646,0.00088086317,0.0005243453,0.00004035446,0.0000039855686],"category_scores_gemma":[0.00020584387,0.00012617947,0.00003812795,0.00010664833,0.000050655788,0.0011829358,0.00023193014,0.00008720656,0.0000050023436],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006644145,0.0001260725,0.06094356,0.00035783902,0.0000092093,0.0000012993628,0.002119138,0.0000022235497,0.0000060013717,0.022221467,0.005303523,0.908903],"study_design_scores_gemma":[0.00095053075,0.0003206866,0.19754337,0.00006041563,1.5907784e-7,0.000020672813,0.00005965565,0.17890738,0.0000012492242,0.00036925904,0.6214715,0.00029511808],"about_ca_topic_score_codex":0.0000163454,"about_ca_topic_score_gemma":0.000015529786,"teacher_disagreement_score":0.9580576,"about_ca_system_score_codex":0.00010957316,"about_ca_system_score_gemma":0.00045140312,"threshold_uncertainty_score":0.9983794},"labels":[],"label_agreement":null},{"id":"W2607662805","doi":"","title":"Lenticular galaxies: The polyvalent aesthetics of data visualization","year":2010,"lang":"en","type":"article","venue":"OCAD University Open Research Repository (OCAD University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario College of Art and Design","funders":"","keywords":"Cultural studies; Aesthetics; Critical theory; Sociology; Media theory; Art; Anthropology; Epistemology; Philosophy; Media studies","score_opus":0.09828604068910678,"score_gpt":0.35716206908318987,"score_spread":0.2588760283940831,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2607662805","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09556488,0.00007230186,0.23427616,0.0034289446,0.00092751946,0.0016581953,0.00013869442,0.00025657628,0.66367674],"genre_scores_gemma":[0.91772246,0.0003029185,0.003983123,0.000046902314,0.00006787776,1.8289339e-7,0.00013042727,0.0000212513,0.077724844],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99711585,0.0007353024,0.00019998604,0.0006487666,0.0009148625,0.00038521207],"domain_scores_gemma":[0.9961826,0.00015438562,0.00019523971,0.0025089434,0.0007376806,0.00022113607],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0014531679,0.00015438376,0.00020850963,0.00044486253,0.0012346598,0.00045564293,0.009716983,0.00013750362,0.0000030389747],"category_scores_gemma":[0.000093455135,0.00014792432,0.00007374428,0.0019991675,0.0007204524,0.0027262329,0.0040967828,0.00050172425,0.000024435492],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002885757,0.0001761593,0.0023937365,0.00001819004,0.000047792953,0.00010305049,0.00036044995,0.000016146665,0.0016482103,0.99318874,0.00152868,0.00048999826],"study_design_scores_gemma":[0.0012021668,0.00021453327,0.0047169677,0.00007205882,0.00007745494,0.000039728115,0.0022517827,0.06354261,0.0038977505,0.0002395617,0.9233554,0.00038999115],"about_ca_topic_score_codex":0.0006815275,"about_ca_topic_score_gemma":0.00024275263,"teacher_disagreement_score":0.9929492,"about_ca_system_score_codex":0.0001202778,"about_ca_system_score_gemma":0.0006321434,"threshold_uncertainty_score":0.99564093},"labels":[],"label_agreement":null},{"id":"W2608026716","doi":"10.1090/crmp/030/04","title":"On McKay’s connection between the affine 𝐸₈ diagram and the monster","year":2001,"lang":"en","type":"book-chapter","venue":"CRM proceedings & lecture notes","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; Concordia University","funders":"","keywords":"Monster; Connection (principal bundle); Affine transformation; Diagram; Art; Computer science; Mathematics; Pure mathematics; Literature; Geometry; Statistics","score_opus":0.02056099020476468,"score_gpt":0.2534114030827984,"score_spread":0.23285041287803374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2608026716","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00022970569,0.000900836,0.27370107,0.0268724,0.00046566612,0.0009062556,0.000031964362,0.00040276322,0.69648933],"genre_scores_gemma":[0.9847245,0.0007555468,0.00010352219,0.007170465,0.0016157061,0.000025069516,0.00007016294,0.00007723813,0.005457789],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985205,0.000011440419,0.0002894581,0.00054002804,0.00039483598,0.00024374448],"domain_scores_gemma":[0.9986051,0.0005066907,0.00028769486,0.00031910787,0.00020568862,0.00007576474],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036707678,0.00038010016,0.0003621048,0.00013998177,0.00039376813,0.00079910393,0.00078282633,0.00027852485,0.000053513595],"category_scores_gemma":[0.00033238105,0.00020007961,0.0001207568,0.00016020199,0.00025424038,0.00020800738,0.00026500516,0.00057787646,0.00004173408],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011365929,0.0000061943574,0.000058782687,0.000020739586,0.000058375597,0.00000113767,0.00044038368,0.000007580224,0.0000049881514,0.9575282,0.00108787,0.04077442],"study_design_scores_gemma":[0.00061881775,0.0001358356,0.00015388233,0.00018373206,0.00017055294,0.00003116731,0.000010298096,0.0059306757,0.00019072798,0.81915635,0.17297846,0.00043949287],"about_ca_topic_score_codex":0.000008767823,"about_ca_topic_score_gemma":0.0000072950133,"teacher_disagreement_score":0.9844948,"about_ca_system_score_codex":0.00003521461,"about_ca_system_score_gemma":0.00003124891,"threshold_uncertainty_score":0.815901},"labels":[],"label_agreement":null},{"id":"W2610600445","doi":"10.1145/3025453.3025912","title":"Same Stats, Different Graphs","year":2017,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":171,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Autodesk (Canada)","funders":"","keywords":"Computer science; Simulated annealing; Graphical model; Data mining; Constant (computer programming); Outcome (game theory); Graph; Algorithm; Machine learning; Artificial intelligence; Theoretical computer science; Mathematics","score_opus":0.041642506561419164,"score_gpt":0.3265795122978992,"score_spread":0.28493700573648006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2610600445","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0056704185,0.000008382915,0.9700636,0.002082687,0.00026516485,0.000033030312,0.0000041054273,0.00012376199,0.021748826],"genre_scores_gemma":[0.9833079,0.00004124146,0.0066375355,0.0012660456,0.000021041793,0.0000011902791,0.0000067513492,0.0000035061003,0.008714816],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99956965,0.000008420908,0.00007021397,0.00013429616,0.00011934601,0.00009806193],"domain_scores_gemma":[0.9990837,0.000008808018,0.00004681685,0.0007768508,0.00002417676,0.000059669394],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004670401,0.000048395534,0.000057414756,0.000029762936,0.00019499927,0.00059052644,0.0009866558,0.000012684387,0.00007941379],"category_scores_gemma":[0.000025804075,0.000034751465,0.00002487853,0.000028375509,0.000027092146,0.00038235117,0.00029360194,0.000024778108,0.000101401405],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.7212409e-7,0.000023642184,0.0024593899,0.0000017550083,0.0000039138345,0.0000019097433,0.000035796365,6.220848e-7,0.000034644563,0.9793403,0.0075186663,0.010579165],"study_design_scores_gemma":[0.001046745,0.00011515259,0.25420004,0.000030336374,0.000013308992,0.0000066604243,0.00006466437,0.3809961,0.004077169,0.1678091,0.19096102,0.0006796854],"about_ca_topic_score_codex":0.000027451892,"about_ca_topic_score_gemma":0.000033386135,"teacher_disagreement_score":0.97763747,"about_ca_system_score_codex":0.0000043115133,"about_ca_system_score_gemma":0.000009111936,"threshold_uncertainty_score":0.56944597},"labels":[],"label_agreement":null},{"id":"W2610877","doi":"10.4018/978-1-60566-010-3.ch314","title":"Visual Data Mining from Visualization to Visual Information Mining","year":2009,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; University of Ottawa","funders":"","keywords":"Computer science; Association rule learning; Knowledge extraction; Data science; Visualization; Data mining; Concept mining; Data stream mining; Cluster analysis; Process (computing); Data warehouse; Data visualization; Information visualization; The Internet; External Data Representation; Web mining; World Wide Web; Machine learning; Artificial intelligence; Web page","score_opus":0.03582237548817825,"score_gpt":0.31971567325724065,"score_spread":0.2838932977690624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2610877","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000100455334,0.000048243888,0.5278873,0.0001041352,0.00063857116,0.00032855148,0.0005789747,0.00046227124,0.46985152],"genre_scores_gemma":[0.26654762,0.00013808323,0.37180454,0.09888449,0.009055577,0.00008381018,0.047172062,0.0006989637,0.20561486],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.996563,0.000044049357,0.0009839217,0.0009127426,0.0010438893,0.00045236136],"domain_scores_gemma":[0.99724805,0.00006537273,0.00058380334,0.0014424162,0.00029626908,0.00036406377],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0002972711,0.0005763314,0.0005485587,0.00031832507,0.00020852718,0.0012523829,0.0024019857,0.00041598384,0.000044478555],"category_scores_gemma":[0.000142064,0.00063923193,0.00010480702,0.00016174256,0.00004252302,0.0016242982,0.0017091626,0.00016479894,0.0006074049],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016395881,0.000023207527,0.000022074508,0.000018222321,0.00007555912,0.000020071831,0.00047012485,0.00004578664,0.0000074664817,0.8044757,0.024310928,0.17051445],"study_design_scores_gemma":[0.001137636,0.00055594667,0.00014264234,0.0009874338,0.0002199995,0.00003057074,0.00018314653,0.3899795,0.000092205155,0.029109428,0.5752565,0.0023049498],"about_ca_topic_score_codex":0.000055076445,"about_ca_topic_score_gemma":0.00007453429,"teacher_disagreement_score":0.7753663,"about_ca_system_score_codex":0.00022790267,"about_ca_system_score_gemma":0.00037775096,"threshold_uncertainty_score":0.9997844},"labels":[],"label_agreement":null},{"id":"W2611611834","doi":"10.1145/3025453.3025850","title":"Building with Data","year":2017,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Architecture; Process (computing); Data modeling; Data science; Architectural design; Data visualization; Visualization; Design process; Software engineering; Scale (ratio); Work in process; Data mining; Engineering; Programming language","score_opus":0.09818789804779413,"score_gpt":0.3817320511922178,"score_spread":0.2835441531444237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2611611834","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00016014406,0.0000019837769,0.9806806,0.0010037468,0.00003973586,0.000011326772,0.0000024123233,0.000050282808,0.018049795],"genre_scores_gemma":[0.3880286,0.000005427705,0.6082989,0.0007652065,0.00004272582,2.9131743e-7,0.0000117891395,0.000003327444,0.0028437532],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996724,0.0000031164043,0.000033931625,0.0001485297,0.00008359989,0.000058387603],"domain_scores_gemma":[0.99787295,0.0000053567974,0.00003299506,0.0020432996,0.000016909511,0.000028471686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008661381,0.000026098629,0.000029372668,0.000012585018,0.0001645994,0.00064704893,0.0026723251,0.000006018016,0.000016764592],"category_scores_gemma":[0.00003179861,0.00001753233,0.0000028212016,0.00002670315,0.000018673773,0.0011650875,0.00094999454,0.00001528491,0.000034397544],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.1329227e-7,0.00000835048,0.0011906988,0.000001299156,0.000003867976,0.000004580751,0.0000085443535,0.0000034352145,0.00002441746,0.9689659,0.010473688,0.019315023],"study_design_scores_gemma":[0.00016846984,0.000014581027,0.0025542227,0.000009767694,0.000002828269,0.000006030425,0.0000044783797,0.80319303,0.00045364862,0.001545108,0.19194628,0.00010156065],"about_ca_topic_score_codex":0.000019981437,"about_ca_topic_score_gemma":0.000017941982,"teacher_disagreement_score":0.96742076,"about_ca_system_score_codex":0.0000016632847,"about_ca_system_score_gemma":0.000017015273,"threshold_uncertainty_score":0.6239508},"labels":[],"label_agreement":null},{"id":"W2612215771","doi":"10.5555/3076132.3076164","title":"Assessing the Readability of Stacked Graphs","year":2016,"lang":"en","type":"article","venue":"Graphics Interface","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Readability; Computer science; Correctness; Distortion (music); Visualization; Casual; Variety (cybernetics); Information retrieval; Artificial intelligence; Data mining; Theoretical computer science; Algorithm; Programming language","score_opus":0.05089262899001685,"score_gpt":0.3624837412333246,"score_spread":0.31159111224330777,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2612215771","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06949706,0.000049316805,0.927183,0.002056539,0.00018021755,0.000058391044,0.000008775282,0.00006643767,0.0009002906],"genre_scores_gemma":[0.9980112,0.00004530648,0.0016383479,0.00018837609,0.00000716072,0.0000014858098,7.7961926e-7,0.000004475631,0.00010290427],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99902815,0.0001185969,0.00024755814,0.00022163171,0.00024307195,0.00014099246],"domain_scores_gemma":[0.99860024,0.00024591625,0.00013624191,0.00080989575,0.00016727133,0.00004042908],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006286963,0.00008355034,0.00010816107,0.000082621256,0.00007935127,0.00013076821,0.0009996606,0.000036118458,0.000019157373],"category_scores_gemma":[0.00014008739,0.00004260863,0.000068429006,0.0005756309,0.00023320368,0.00059552625,0.00025327504,0.00007152915,0.000009921278],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000020434793,0.000066529254,0.005745905,0.000015712565,0.000027726233,7.2673674e-7,0.0003262003,0.0000057071284,0.0044380045,0.9676509,0.0017099275,0.020010635],"study_design_scores_gemma":[0.00074970676,0.000304736,0.024492487,0.0005423239,0.000058772235,0.00002101551,0.0007969772,0.041945625,0.3382315,0.5479423,0.044004742,0.00090981397],"about_ca_topic_score_codex":0.000013509052,"about_ca_topic_score_gemma":0.000010744714,"teacher_disagreement_score":0.9285141,"about_ca_system_score_codex":0.000011147852,"about_ca_system_score_gemma":0.000038317266,"threshold_uncertainty_score":0.18576346},"labels":[],"label_agreement":null},{"id":"W2612802052","doi":"10.1007/978-3-319-58640-3_53","title":"Case Study: Building UX Design into Citizen Science Applications","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Royal University","funders":"Shell Canada; Mount Royal University; Calgary Foundation; Cenovus Energy","keywords":"Computer science; Human–computer interaction; Citizen science; Software engineering","score_opus":0.05265127933861629,"score_gpt":0.341676094399797,"score_spread":0.2890248150611807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2612802052","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006055771,0.00009204071,0.99633133,0.0002384184,0.0007434113,0.00097373937,0.0000048634133,0.00020705124,0.001348576],"genre_scores_gemma":[0.3233898,0.000022110145,0.67498654,0.0007507506,0.00038673205,0.000041400508,0.0000032846822,0.00003723235,0.00038216333],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9948739,0.000049733357,0.0005899863,0.0022449188,0.0015196918,0.0007217965],"domain_scores_gemma":[0.9946983,0.00037259288,0.00050360995,0.0034475736,0.0006320102,0.000345908],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.002743389,0.000523761,0.0005037369,0.0015302671,0.00214208,0.0033118222,0.008848454,0.00017307082,0.000011719941],"category_scores_gemma":[0.00025659375,0.0004964282,0.00008843865,0.0010596751,0.0021458608,0.0016503467,0.00363956,0.00059401133,0.000054807064],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021967044,0.00013500126,0.00007749931,0.0000375346,0.00001814433,0.0019836412,0.0026984224,0.02165647,0.0002268403,0.066727005,0.000042794712,0.9063944],"study_design_scores_gemma":[0.00037231584,0.00023641778,0.000017985192,0.00019047825,0.000025322568,0.0013916127,0.0000033315878,0.8175332,0.0008644696,0.17576765,0.002574562,0.0010226654],"about_ca_topic_score_codex":0.000094842035,"about_ca_topic_score_gemma":0.00009425807,"teacher_disagreement_score":0.9053718,"about_ca_system_score_codex":0.0004159829,"about_ca_system_score_gemma":0.0017142484,"threshold_uncertainty_score":0.9997487},"labels":[],"label_agreement":null},{"id":"W2613524337","doi":"10.1007/978-3-319-58634-2_13","title":"Four Biases in Interface Design Interactions","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Interface (matter); Interface design; Human–computer interaction; Operating system","score_opus":0.09874358838312612,"score_gpt":0.3482244776977456,"score_spread":0.24948088931461948,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2613524337","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000010707293,0.0001298467,0.99370354,0.000801001,0.0016600795,0.00024026865,0.0000073497617,0.00010509653,0.0033421284],"genre_scores_gemma":[0.27605838,0.00021884919,0.714269,0.0026636184,0.0006254643,0.000016722128,0.00001899924,0.00007572576,0.0060532717],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971416,0.00005352845,0.0004957389,0.0011804191,0.00060082244,0.0005279096],"domain_scores_gemma":[0.99693906,0.0006501673,0.00035474132,0.0017209618,0.00018266322,0.00015242216],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0008944304,0.000402637,0.0004321678,0.0011786507,0.0002582045,0.001288115,0.004444776,0.00016577113,0.000044522392],"category_scores_gemma":[0.00051221135,0.00038034673,0.00009014668,0.00034146235,0.00045145056,0.0013116077,0.0015694164,0.0006697094,0.000115343486],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000093331355,0.000095831,0.000112886366,0.000037557114,0.000019289699,0.00029999015,0.0011886555,0.21793033,0.0001476936,0.0197762,0.0005497594,0.75983244],"study_design_scores_gemma":[0.0001995149,0.00007811549,0.0000664807,0.000808982,0.0000048038605,0.000060261533,2.0157493e-7,0.9526285,0.0008893273,0.039039403,0.005743962,0.00048048442],"about_ca_topic_score_codex":0.00003880349,"about_ca_topic_score_gemma":0.0003888747,"teacher_disagreement_score":0.75935197,"about_ca_system_score_codex":0.00028804122,"about_ca_system_score_gemma":0.000555933,"threshold_uncertainty_score":0.9998648},"labels":[],"label_agreement":null},{"id":"W2617168158","doi":"10.29173/cais635","title":"Can Interactive Map-Based Visualizations Reveal Contexts of Scientific Datasets?","year":2013,"lang":"fr","type":"article","venue":"Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Visualization; Visual analytics; Geovisualization; Computer science; Information visualization; Data science; Data visualization; Scientific visualization; Humanities; Artificial intelligence; Art","score_opus":0.03180771469016852,"score_gpt":0.2933441461934095,"score_spread":0.26153643150324096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2617168158","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88677156,0.0012981024,0.016067328,0.054626927,0.004383988,0.0031251102,0.025917483,0.00018963036,0.0076198718],"genre_scores_gemma":[0.993774,0.00003841037,0.0018139558,0.00046592293,0.00007131716,0.000024006233,0.00022606766,0.000026796468,0.0035595363],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.996757,0.00009723386,0.0010914509,0.00063365675,0.0008543647,0.0005663217],"domain_scores_gemma":[0.926338,0.0002762824,0.0019070683,0.0005912166,0.0706153,0.00027212428],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.00088276836,0.0003888999,0.0006922203,0.00040765695,0.00030098454,0.0067051635,0.003754054,0.00019401712,0.00020937329],"category_scores_gemma":[0.01377629,0.00034104078,0.00023395702,0.0014925359,0.0018249118,0.016897764,0.0013347056,0.00031258783,0.000022913118],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012458336,0.0021934342,0.06399966,0.003312988,0.00049266475,0.0000040426353,0.06403733,0.00010142166,0.030637981,0.51315266,0.30322492,0.01871831],"study_design_scores_gemma":[0.0032861466,0.0014414571,0.051947482,0.006998251,0.0007095191,0.000057790257,0.008075917,0.18420485,0.2352384,0.025092803,0.48104593,0.0019014445],"about_ca_topic_score_codex":0.0011664298,"about_ca_topic_score_gemma":0.0000974257,"teacher_disagreement_score":0.48805985,"about_ca_system_score_codex":0.0000929313,"about_ca_system_score_gemma":0.00095688965,"threshold_uncertainty_score":0.99990416},"labels":[],"label_agreement":null},{"id":"W2617583622","doi":"10.1145/1179622.1179833","title":"Great grids","year":2006,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science","score_opus":0.015280854298980732,"score_gpt":0.2701352265468511,"score_spread":0.2548543722478704,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2617583622","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00024174109,0.0000061573364,0.88125265,0.0004508473,0.00006035455,0.000009589614,5.745539e-7,0.00012679347,0.11785128],"genre_scores_gemma":[0.77456933,0.000009151959,0.10131312,0.004195006,0.00024981366,0.0000020589503,0.00004271056,0.000007989612,0.11961081],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997201,0.00000509917,0.00005472735,0.00008315441,0.00007438779,0.00006253457],"domain_scores_gemma":[0.99977887,0.000005491016,0.000009283443,0.00017187919,0.000017199643,0.000017250766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000033026226,0.000026842166,0.000026892329,0.000025654499,0.000024869973,0.00009032883,0.00023143765,0.000009070331,0.00010228032],"category_scores_gemma":[0.0000027323563,0.000021154694,0.000012395474,0.00015981609,0.000006739942,0.00018558149,0.000057998477,0.000011039851,0.00024837875],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.6722383e-8,0.000008620248,0.00072162953,5.2597414e-7,4.956073e-7,0.0000015180156,0.0000031402092,0.000015549693,0.000026572447,0.92045355,0.07679935,0.0019689994],"study_design_scores_gemma":[0.00019968895,0.000018786679,0.005481807,0.0000028102775,0.000002116581,0.000007879273,0.000004204329,0.32332143,0.002533795,0.022375513,0.6458884,0.00016361858],"about_ca_topic_score_codex":0.000036689096,"about_ca_topic_score_gemma":0.000012324179,"teacher_disagreement_score":0.898078,"about_ca_system_score_codex":0.000004015942,"about_ca_system_score_gemma":0.000007661689,"threshold_uncertainty_score":0.3192489},"labels":[],"label_agreement":null},{"id":"W2618186495","doi":"10.20382/jocg.v8i1a8","title":"A new drawing for simple Venn diagrams based on algebraic construction","year":2016,"lang":"en","type":"article","venue":"Journal of Computational Geometry (Carleton University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Venn diagram; Simple (philosophy); Readability; Mathematics; Diagram; Domain (mathematical analysis); Algebraic number; Algebra over a field; Discrete mathematics; Computer science; Pure mathematics; Mathematics education; Programming language; Statistics; Epistemology","score_opus":0.013859262011055636,"score_gpt":0.2423047760116783,"score_spread":0.22844551400062266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2618186495","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008610179,0.0000071186323,0.98915637,0.0015410751,0.00030579107,0.00006245742,0.000016452599,0.000028482036,0.00027208787],"genre_scores_gemma":[0.8194418,0.000009878584,0.17892517,0.0007305903,0.0002731156,1.1042586e-7,0.000019067194,0.000011913656,0.00058835105],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989715,0.000053849257,0.00025095377,0.00016800231,0.00040438824,0.00015128897],"domain_scores_gemma":[0.99835455,0.00055986736,0.00036428386,0.00013521577,0.0004113222,0.00017478318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021314934,0.00010490257,0.00017472004,0.0009540661,0.000120234625,0.00009408146,0.00049437105,0.000048413815,0.000045720328],"category_scores_gemma":[0.00014128219,0.00008758417,0.0001648954,0.00095406786,0.000038076185,0.000701288,0.000052008247,0.00007094296,0.000009244714],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021755081,0.00021760946,0.004402481,0.00003489834,0.00018460705,0.00009036636,0.00010140361,0.12221601,0.00034710256,0.6233274,0.016086064,0.23277454],"study_design_scores_gemma":[0.0146437865,0.0022314137,0.010656704,0.0004658832,0.00017739245,0.00017063577,0.00023431705,0.50833595,0.0016900431,0.116046235,0.3443659,0.0009817199],"about_ca_topic_score_codex":0.0000019636589,"about_ca_topic_score_gemma":9.1678896e-7,"teacher_disagreement_score":0.8108316,"about_ca_system_score_codex":0.00014215703,"about_ca_system_score_gemma":0.00039024078,"threshold_uncertainty_score":0.3571579},"labels":[],"label_agreement":null},{"id":"W2618693267","doi":"","title":"Studying direct-touch interaction for 2D flow visualization","year":2010,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft; Austrian Science Fund; European Commission","keywords":"Visualization; Human–computer interaction; Computer science; Data visualization; Data exploration; Data science; Process (computing); Multi-touch; Scientific visualization; Information visualization; Artificial intelligence","score_opus":0.03696090821914401,"score_gpt":0.35369401160566255,"score_spread":0.31673310338651856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2618693267","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016798193,0.0000016884973,0.99027175,0.00022781834,0.0010024919,0.00013950841,0.0000034052164,0.000232547,0.0064409534],"genre_scores_gemma":[0.8973502,0.000008112859,0.097553566,0.0010808922,0.0002472763,0.000027564089,0.000104204,0.000016213813,0.0036119577],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99933004,0.00001712864,0.00016443235,0.00022804529,0.00013642215,0.0001239223],"domain_scores_gemma":[0.99940443,0.00007166602,0.000059287613,0.00027326643,0.00014014404,0.000051182382],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018316662,0.00007422808,0.000080617596,0.00009948435,0.00012248688,0.0002921123,0.00031122717,0.00003711383,0.00007929879],"category_scores_gemma":[0.00013829357,0.000066096254,0.000036098958,0.00027986304,0.000009604544,0.0007499501,0.00008744251,0.000053928987,0.000047751142],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008216476,0.0003283046,0.0013220533,0.00003638013,0.00003763101,0.0000012204745,0.0010990691,0.00043271433,0.0108905295,0.83215916,0.035209455,0.11847525],"study_design_scores_gemma":[0.00018567708,0.000030193614,0.0001007589,0.000004468067,0.000004891522,0.0000016058209,0.00005111223,0.9085941,0.0062720003,0.00049940636,0.08415451,0.00010129373],"about_ca_topic_score_codex":0.000008330185,"about_ca_topic_score_gemma":0.000061517414,"teacher_disagreement_score":0.90816134,"about_ca_system_score_codex":0.000011388123,"about_ca_system_score_gemma":0.000023161356,"threshold_uncertainty_score":0.28168458},"labels":[],"label_agreement":null},{"id":"W2620060748","doi":"10.7331/vm.v5i1.106","title":"Adventures in Visual Analysis","year":2017,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Adventure; Context (archaeology); Set (abstract data type); Interpretation (philosophy); Metaphor; Thematic analysis; Computer science; Data science; Subject (documents); Artificial intelligence; Qualitative research; Sociology; Linguistics; Social science; History; World Wide Web","score_opus":0.02092549910697415,"score_gpt":0.3585916254761374,"score_spread":0.3376661263691632,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2620060748","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0072659785,0.000011498616,0.97257996,0.00091146975,0.000073618976,0.000021839529,9.797776e-7,0.000047792233,0.019086894],"genre_scores_gemma":[0.9943995,0.0000061623136,0.0032919832,0.000428824,0.0000115496205,6.1268906e-7,0.0000044395,0.0000010947673,0.0018558186],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99958277,0.000011581065,0.00008572008,0.00013651616,0.00010173424,0.00008167192],"domain_scores_gemma":[0.99941313,0.000008203634,0.000045703622,0.0004831469,0.000017361132,0.000032439544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001107503,0.00003619889,0.000074462754,0.00015156687,0.000085246575,0.00035668872,0.0007440412,0.000015470767,0.000075290365],"category_scores_gemma":[0.000043459248,0.000029811665,0.00003952486,0.00024642947,0.000015062623,0.00041079093,0.0001961581,0.00002390058,0.00004467745],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012066552,0.00015639902,0.26160026,0.000003970793,0.00011457131,0.00002558396,0.00020280936,0.0004240172,0.000041457304,0.70632106,0.0050512613,0.026057433],"study_design_scores_gemma":[0.00013034244,0.000008618378,0.23808846,0.000001977997,0.000014673808,2.5048232e-7,0.000012888962,0.7539707,0.00020784637,0.0010012488,0.0064826817,0.00008031693],"about_ca_topic_score_codex":0.00012221036,"about_ca_topic_score_gemma":0.00032805416,"teacher_disagreement_score":0.98713356,"about_ca_system_score_codex":0.000005941664,"about_ca_system_score_gemma":0.000011489866,"threshold_uncertainty_score":0.34395576},"labels":[],"label_agreement":null},{"id":"W2620338404","doi":"10.29173/cais639","title":"Just What do Scholars do? A Qualitative Exploration of Text Analysis Tools for Information Visualization","year":2013,"lang":"fr","type":"article","venue":"Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Usability; Library science; Sociology; Qualitative analysis; Qualitative research; Visualization; Computer science; Human–computer interaction; Social science; Artificial intelligence","score_opus":0.08200366314899123,"score_gpt":0.3444976675828078,"score_spread":0.2624940044338166,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2620338404","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6247545,0.0014057497,0.35608461,0.010404845,0.00092855823,0.002788524,0.0012344447,0.00009576617,0.0023030262],"genre_scores_gemma":[0.9935527,0.0012641588,0.0040263613,0.00034938304,0.00006166077,0.000085827305,0.0001316783,0.000017793553,0.00051045074],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.996825,0.000119443874,0.0014175212,0.00037805614,0.0008518316,0.00040817077],"domain_scores_gemma":[0.8948515,0.00042410885,0.0026288773,0.00033158192,0.10161127,0.00015263523],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0017055293,0.0003438475,0.00074254564,0.00069329055,0.0001902974,0.0197802,0.0018735233,0.00025560905,0.00007630059],"category_scores_gemma":[0.026373584,0.00030362967,0.0003709351,0.0028194885,0.00047835862,0.20641933,0.0005584368,0.00018850135,0.000012299545],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006923966,0.000275692,0.0032523067,0.0012286205,0.0005907257,7.32234e-8,0.32907146,0.00026178907,0.0014830958,0.6030738,0.0035231507,0.05717005],"study_design_scores_gemma":[0.0030451936,0.0017352964,0.017074876,0.0040995553,0.0027613381,0.000010294352,0.43282598,0.3189478,0.049765944,0.05437729,0.11367693,0.0016795142],"about_ca_topic_score_codex":0.00020657874,"about_ca_topic_score_gemma":0.000011810502,"teacher_disagreement_score":0.5486965,"about_ca_system_score_codex":0.00008837095,"about_ca_system_score_gemma":0.00038747003,"threshold_uncertainty_score":0.9999416},"labels":[],"label_agreement":null},{"id":"W2620803373","doi":"","title":"Sharing Information from Personal Digital Notes using Word-Scale Visualizations","year":2015,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Agence Nationale de la Recherche","keywords":"Computer science; Context (archaeology); Visualization; World Wide Web; Set (abstract data type); Scale (ratio); Word (group theory); Data visualization; Raw data; Information sharing; Information visualization; Data science; Data sharing; Information retrieval; Artificial intelligence; Linguistics","score_opus":0.034730766629636284,"score_gpt":0.27857539837675654,"score_spread":0.24384463174712026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2620803373","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022349259,0.00015745312,0.96707606,0.0017582816,0.00028189513,0.0002162998,0.00041377748,0.0003873222,0.0073596425],"genre_scores_gemma":[0.7493533,0.00014047034,0.23871736,0.00042071138,0.00008920016,0.000029117604,0.0096719,0.000059307844,0.0015186521],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99692726,0.0007653001,0.0006544778,0.0006646549,0.0006738169,0.0003144611],"domain_scores_gemma":[0.9942501,0.00048294937,0.00061430427,0.0017510789,0.0026387032,0.00026282456],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0018974557,0.00032279408,0.0003209358,0.0003153508,0.0003613041,0.003736689,0.0022286293,0.00023969618,0.000069513815],"category_scores_gemma":[0.0014157502,0.00036421735,0.00015710857,0.00067817466,0.0001265909,0.0021440974,0.0036975527,0.00039204577,0.00010279532],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023773924,0.0022422036,0.033612672,0.0005351966,0.0005537677,0.0000140999255,0.17441398,0.006761701,0.00093954476,0.45851833,0.008522241,0.3138625],"study_design_scores_gemma":[0.00029900772,1.9199513e-7,0.0005140022,0.0007036323,0.000028625984,0.000003886342,0.00016847959,0.97931504,0.0013287163,0.008977901,0.008235959,0.00042457742],"about_ca_topic_score_codex":0.0008520075,"about_ca_topic_score_gemma":0.00027936697,"teacher_disagreement_score":0.9725533,"about_ca_system_score_codex":0.0001921937,"about_ca_system_score_gemma":0.0004999142,"threshold_uncertainty_score":0.99988097},"labels":[],"label_agreement":null},{"id":"W2622834624","doi":"","title":"LIVVIL: Logging Interactive Visualizations and Visualizing Interaction Logs","year":2016,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Visualization; Computer science; Usability; Logging; Web application; Process (computing); Data visualization; World Wide Web; Human–computer interaction; Scale (ratio); Data mining","score_opus":0.02215906499644438,"score_gpt":0.2990032049235111,"score_spread":0.27684413992706675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2622834624","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036890763,0.0002861967,0.970829,0.0070026387,0.0004536346,0.00026474477,0.00004786747,0.00045892317,0.016967917],"genre_scores_gemma":[0.94327605,0.0011460847,0.049654353,0.000571659,0.00006812922,0.00005848627,0.0005383608,0.00007114163,0.0046157325],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9945008,0.0030965244,0.00061937876,0.0010348036,0.00040011245,0.0003483607],"domain_scores_gemma":[0.9942344,0.0014760299,0.00071776676,0.0017176822,0.0016354197,0.00021873708],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0026435794,0.00036006462,0.00037320753,0.00045531007,0.0004174414,0.0014498231,0.0014962244,0.00023542013,0.000068989044],"category_scores_gemma":[0.0014758289,0.00036618006,0.00014098127,0.00041777475,0.00018082467,0.0009368172,0.0034847024,0.0004858743,0.000056730343],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000066352172,0.00047952484,0.0010369342,0.00020658289,0.00015028485,0.000008691202,0.013631248,0.000051792766,0.0016727406,0.9012828,0.002252226,0.07922058],"study_design_scores_gemma":[0.0011956395,0.0000020555856,0.0018467103,0.008398176,0.00011717676,0.00006643124,0.00061414996,0.8429668,0.034963585,0.04819544,0.059983406,0.0016504197],"about_ca_topic_score_codex":0.00021352862,"about_ca_topic_score_gemma":0.00020227255,"teacher_disagreement_score":0.939587,"about_ca_system_score_codex":0.0001608136,"about_ca_system_score_gemma":0.000214123,"threshold_uncertainty_score":0.999879},"labels":[],"label_agreement":null},{"id":"W2623977345","doi":"","title":"Creating a Framework for Testing Wellness Visualization Systems","year":2011,"lang":"en","type":"article","venue":"International Conference on eHealth, Telemedicine, and Social Medicine","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Visualization; Computer science; System testing; Human–computer interaction; Software engineering; Artificial intelligence","score_opus":0.1484159885317835,"score_gpt":0.399964311487551,"score_spread":0.2515483229557675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2623977345","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014032784,0.00005244042,0.9701431,0.0054750945,0.0017512816,0.00037626398,0.000019341638,0.00015520581,0.02062399],"genre_scores_gemma":[0.9854137,0.00013041883,0.009174611,0.0031483588,0.0016393895,0.000055215085,0.00010877091,0.000018999006,0.00031054535],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981322,0.000085771266,0.0005621561,0.00040158443,0.00054337294,0.00027486467],"domain_scores_gemma":[0.99824333,0.00045280275,0.00035951543,0.00016996865,0.0006257162,0.00014866472],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007562968,0.00018783161,0.00032666457,0.00023370188,0.0003816402,0.00007899308,0.0005117569,0.00011719348,0.00007114621],"category_scores_gemma":[0.0010836271,0.00015480239,0.000026340476,0.00031273815,0.00016424377,0.00023732499,0.000057138426,0.00017237016,0.0000052863065],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020741922,0.000049259444,0.0007079542,0.00009173892,0.000022351158,0.0000037067964,0.0065511614,0.0000011910934,0.000026895901,0.97248095,0.00062938745,0.019414654],"study_design_scores_gemma":[0.003764155,0.0023311698,0.005178092,0.0023272093,0.00008674963,0.00004165305,0.0158697,0.7856949,0.00008758311,0.16656762,0.017301185,0.0007499519],"about_ca_topic_score_codex":0.00033014617,"about_ca_topic_score_gemma":0.00001553751,"teacher_disagreement_score":0.9840104,"about_ca_system_score_codex":0.00005644154,"about_ca_system_score_gemma":0.00013946793,"threshold_uncertainty_score":0.6312658},"labels":[],"label_agreement":null},{"id":"W2624014580","doi":"10.1145/3064857.3079152","title":"ReflectiveHUD","year":2017,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Alberta Innovates - Technology Futures","keywords":"Undo; Computer science; Representation (politics); Visualization; Human–computer interaction; Nonlinear system; Data visualization; Artificial intelligence; Programming language","score_opus":0.059409957086207964,"score_gpt":0.38578451855666,"score_spread":0.3263745614704521,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2624014580","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009681487,0.0000013647016,0.734714,0.0010248038,0.000076854914,0.000007816696,2.011084e-7,0.000050929404,0.26402724],"genre_scores_gemma":[0.934962,0.0000069339685,0.040379338,0.0012816854,0.000040364073,6.886736e-7,9.694395e-7,0.00000210327,0.023325942],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997797,0.000004010192,0.00003135973,0.000080981554,0.00005503226,0.000048904334],"domain_scores_gemma":[0.9993648,0.0000038486955,0.000025088144,0.0005602712,0.000021790993,0.000024190163],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000510103,0.000020234127,0.000023930677,0.000013575397,0.000182595,0.00039665832,0.0007445281,0.0000076765555,0.000040609502],"category_scores_gemma":[0.000041517236,0.000016102893,0.000009725133,0.00002117393,0.000013586208,0.00045558662,0.00018710141,0.000013341636,0.00019905747],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.66956e-8,0.0000063793264,0.0004852998,3.8916852e-7,0.0000013872371,0.0000012888627,0.000019222114,4.440658e-7,0.00005465335,0.9783174,0.009193247,0.011920216],"study_design_scores_gemma":[0.00042169882,0.000048494167,0.035581205,0.000008558732,0.000003113604,0.0000070082206,0.000018171571,0.3450254,0.008373604,0.056912363,0.5533154,0.00028496183],"about_ca_topic_score_codex":0.000009314949,"about_ca_topic_score_gemma":0.0000063134135,"teacher_disagreement_score":0.9348652,"about_ca_system_score_codex":0.000003121555,"about_ca_system_score_gemma":0.000010019252,"threshold_uncertainty_score":0.38249853},"labels":[],"label_agreement":null},{"id":"W2625298190","doi":"10.1145/3083165.3083179","title":"Seeker","year":2017,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Live streaming; Popularity; Multimedia; The Internet; Publication; World Wide Web; Advertising","score_opus":0.03957436193807088,"score_gpt":0.33947233748735894,"score_spread":0.29989797554928804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2625298190","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00014364076,0.0000012901596,0.8407621,0.001480603,0.00009137084,0.0000069167545,2.5381559e-7,0.000048651156,0.1574652],"genre_scores_gemma":[0.91876316,0.000006400983,0.03667517,0.002202974,0.000044523124,5.049116e-7,0.0000015195799,0.000002125287,0.04230364],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998088,0.000002443583,0.000028873405,0.000064661785,0.000051600102,0.000043623797],"domain_scores_gemma":[0.9993979,0.0000026527346,0.000019504829,0.00054201874,0.000014985472,0.00002297435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000042176962,0.000017354232,0.000020089989,0.000009432635,0.0001299633,0.00040501135,0.0006854761,0.0000066727816,0.000057011493],"category_scores_gemma":[0.000023858935,0.000013569944,0.00000870593,0.000013873483,0.000010924964,0.0004018185,0.0001863495,0.000009978253,0.00036051546],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.3362358e-8,0.000005631848,0.0009869508,4.4025228e-7,0.0000011103101,0.0000012814828,0.000014208267,5.798808e-7,0.000032342767,0.97074986,0.019912422,0.00829516],"study_design_scores_gemma":[0.00018832849,0.000011567196,0.020502944,0.000003624743,0.0000014056232,0.0000032155758,0.0000066067087,0.4001576,0.001929112,0.010212399,0.5668525,0.00013069392],"about_ca_topic_score_codex":0.0000070249653,"about_ca_topic_score_gemma":0.0000036381557,"teacher_disagreement_score":0.96053743,"about_ca_system_score_codex":0.0000015133294,"about_ca_system_score_gemma":0.0000072412076,"threshold_uncertainty_score":0.4633817},"labels":[],"label_agreement":null},{"id":"W2626164772","doi":"10.14714/cp85.1372","title":"An Analysis of Interactive Solar Energy Web Maps for Urban Energy Sustainability","year":2017,"lang":"en","type":"article","venue":"Cartographic Perspectives","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Sustainability; Outreach; Renewable energy; Computer science; Geographic information system; Variety (cybernetics); Data science; Set (abstract data type); Architectural engineering; World Wide Web; Geography; Engineering; Remote sensing; Artificial intelligence","score_opus":0.011453129139568259,"score_gpt":0.3122506605218946,"score_spread":0.30079753138232634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2626164772","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018583935,0.00019542249,0.9791444,0.00046931932,0.00014409897,0.000092798575,0.00018521305,0.000100105324,0.0010847407],"genre_scores_gemma":[0.9983384,0.00009331863,0.0011751215,0.000074121934,0.000056891546,0.000023996228,0.00006601996,0.000009686078,0.00016241368],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99853003,0.00011933189,0.00025044012,0.0006242355,0.00021981625,0.00025612043],"domain_scores_gemma":[0.99670005,0.00009840545,0.00032798544,0.0016660296,0.0010718692,0.00013565796],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029047855,0.00017219683,0.00038253292,0.0008181552,0.00039676277,0.00034704595,0.0014139152,0.00007191795,0.000010111521],"category_scores_gemma":[0.00030406687,0.00016557136,0.00041422024,0.0008492517,0.00037309036,0.0011700405,0.00019499812,0.00005879391,1.3974699e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023960652,0.00041580264,0.016067374,0.0000118317175,0.0007476703,0.0000028689115,0.003806323,0.00010929346,0.0003530154,0.9755237,0.00034329869,0.0025948402],"study_design_scores_gemma":[0.0011651674,0.0008255066,0.058285244,0.000025755433,0.0010419609,0.0000023134876,0.024186067,0.8409777,0.003098198,0.054425865,0.015127881,0.00083830074],"about_ca_topic_score_codex":0.00044697445,"about_ca_topic_score_gemma":0.0007588787,"teacher_disagreement_score":0.9797545,"about_ca_system_score_codex":0.00007233549,"about_ca_system_score_gemma":0.00014596514,"threshold_uncertainty_score":0.67518044},"labels":[],"label_agreement":null},{"id":"W2626368339","doi":"10.1111/cgf.13213","title":"State of the Art in Edge and Trail Bundling Techniques","year":2017,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":82,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Agence Nationale de la Recherche","keywords":"Computer science; Theoretical computer science; Graph; Visualization; Set (abstract data type); Graph Layout; Graph drawing; Data structure; Artificial intelligence; Programming language","score_opus":0.022617232800080978,"score_gpt":0.2859615536406724,"score_spread":0.2633443208405914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2626368339","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011034067,0.000039536975,0.9862125,0.0018692912,0.00025836925,0.00011275676,0.0000067324345,0.000050172617,0.00041660725],"genre_scores_gemma":[0.983683,0.0001206281,0.015059657,0.0009837786,0.00002674366,0.000002810959,0.0000023900282,0.00000756505,0.00011345632],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931157,0.00003337363,0.00018448675,0.0001854441,0.00013328814,0.00015186063],"domain_scores_gemma":[0.99902165,0.000029963614,0.00014618978,0.0007176312,0.000049707483,0.000034863766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003115399,0.00007926955,0.00011817075,0.00011106267,0.00018385962,0.00024818894,0.0011160267,0.000028930657,4.3707476e-7],"category_scores_gemma":[0.000019257714,0.0000601826,0.000043324457,0.00016658753,0.0001522576,0.00037126945,0.00077488687,0.000099163946,0.0000010047095],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002194835,0.00010134379,0.06026475,0.00004813043,0.000019208452,0.000007108946,0.0005350959,0.000019946538,0.000099944744,0.76759547,0.005441594,0.16586524],"study_design_scores_gemma":[0.00043220012,0.000089507186,0.079755716,0.0002327439,0.0000064449205,0.000014294696,0.000009443327,0.78972125,0.0035995287,0.082573496,0.043265328,0.00030005828],"about_ca_topic_score_codex":0.000012742536,"about_ca_topic_score_gemma":0.00010142154,"teacher_disagreement_score":0.9726489,"about_ca_system_score_codex":0.0000046543864,"about_ca_system_score_gemma":0.000025072282,"threshold_uncertainty_score":0.24541752},"labels":[],"label_agreement":null},{"id":"W26305436","doi":"10.1007/978-90-481-8816-1_3","title":"The Concept of Visualization","year":2010,"lang":"en","type":"book-chapter","venue":"Models and modeling in science education","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Visualization; Computer science; Data science; Feature (linguistics); Current (fluid); State (computer science); Data mining; Engineering; Algorithm; Philosophy; Linguistics","score_opus":0.0699187281483069,"score_gpt":0.3492682491841344,"score_spread":0.2793495210358275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W26305436","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002876899,0.0006828981,0.9680012,0.00024871618,0.0006588452,0.00015686025,0.0000032485455,0.000021647,0.029938923],"genre_scores_gemma":[0.9065669,0.0039330046,0.023329627,0.000581202,0.00023801604,0.000018396155,0.00006852931,0.000043944456,0.06522037],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986924,0.0000093950475,0.00035449828,0.00037594154,0.00041766523,0.00015009487],"domain_scores_gemma":[0.9988123,0.00003442898,0.00019585513,0.00047432687,0.00041698987,0.000066078115],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072434713,0.00012308515,0.00013371573,0.00025048165,0.0002654459,0.00026784936,0.0007790982,0.000102215134,0.0000026972025],"category_scores_gemma":[0.000055280838,0.00009677283,0.00002495876,0.00018450258,0.00035083355,0.00075290346,0.00018732743,0.00015439885,0.0000013186825],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.4695662e-7,0.000012019818,8.617214e-7,0.000004847655,8.549484e-7,3.5573464e-8,0.0006580868,0.008218838,0.00006596419,0.96578246,0.000025055817,0.025230514],"study_design_scores_gemma":[0.000033573033,0.000008838785,6.272856e-7,0.000059032347,0.0000029920773,0.0000010647559,0.00003301196,0.79909337,0.00008222865,0.19830349,0.0022908312,0.00009094822],"about_ca_topic_score_codex":0.000036588448,"about_ca_topic_score_gemma":0.00003792592,"teacher_disagreement_score":0.9446716,"about_ca_system_score_codex":0.000034687764,"about_ca_system_score_gemma":0.0012842043,"threshold_uncertainty_score":0.39462814},"labels":[],"label_agreement":null},{"id":"W2664273831","doi":"","title":"Design Considerations for Enhancing Word-Scale Visualizations with Interaction","year":2015,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Focus (optics); Word (group theory); Visualization; Scale (ratio); Human–computer interaction; Reading (process); Space (punctuation); Data visualization; Interaction design; Information visualization; Natural language processing; Artificial intelligence; Linguistics","score_opus":0.048770162838525,"score_gpt":0.30238894749832324,"score_spread":0.25361878465979826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2664273831","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000485042,0.00011017298,0.98797286,0.005484505,0.00026622837,0.0007155041,0.000058818718,0.00040075212,0.004506136],"genre_scores_gemma":[0.20214751,0.00010404962,0.7915772,0.00037862395,0.00004168998,0.00024026178,0.00091549894,0.00005820616,0.004536931],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9953389,0.002554091,0.0005744386,0.00081871625,0.0004100532,0.00030381148],"domain_scores_gemma":[0.9906205,0.0020852454,0.00058346026,0.0018352056,0.004658428,0.00021715698],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.004051645,0.00031114992,0.00033906347,0.00029408964,0.0005102776,0.0014599502,0.001040701,0.00019037368,0.000050844177],"category_scores_gemma":[0.0018242621,0.00031626198,0.00010753041,0.00051739917,0.000116241696,0.0005667617,0.0008823763,0.0003265106,0.000026625612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002841334,0.0015203257,0.00025171626,0.00034337296,0.000291777,0.0000075126004,0.03950044,0.021715108,0.0021134608,0.886571,0.031526197,0.016130691],"study_design_scores_gemma":[0.0007428463,0.0000018478005,0.000050066243,0.001277922,0.000083282284,0.00002155553,0.00027007225,0.92279696,0.033919252,0.029609842,0.0105970595,0.00062928273],"about_ca_topic_score_codex":0.00013847968,"about_ca_topic_score_gemma":0.0024236208,"teacher_disagreement_score":0.90108186,"about_ca_system_score_codex":0.0001609368,"about_ca_system_score_gemma":0.0009405747,"threshold_uncertainty_score":0.99992895},"labels":[],"label_agreement":null},{"id":"W2706146898","doi":"10.1299/jsmecmd.2014.27.202","title":"Information visualization to analyze large scale scientific data","year":2014,"lang":"en","type":"article","venue":"Keisan Rikigaku Koenkai koen ronbunshu/Keisan Rikigaku Kouenkai kouen rombunshuu","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Atomic Energy (Canada)","funders":"","keywords":"Information visualization; Data science; Scale (ratio); Visualization; Computer science; Data visualization; Information retrieval; Data mining; Geography; Cartography","score_opus":0.019885149482660427,"score_gpt":0.295913087365233,"score_spread":0.27602793788257257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2706146898","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05507096,0.00023159091,0.9148903,0.0042129476,0.004369471,0.002455947,0.0018292842,0.0029490413,0.013990451],"genre_scores_gemma":[0.91091496,0.0001552583,0.041782573,0.018235337,0.0016840415,0.0002288005,0.019915303,0.0003926493,0.0066910763],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9855289,0.0011784973,0.0033537098,0.0033187356,0.0035960625,0.003024121],"domain_scores_gemma":[0.98428434,0.00047119058,0.0014956789,0.010161021,0.0014795773,0.0021082184],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.0068640523,0.0017121496,0.002026642,0.0026701528,0.0023862869,0.0063664927,0.011821542,0.00069263595,0.00049712934],"category_scores_gemma":[0.0019651325,0.0016944025,0.0005698519,0.0069186054,0.0005214381,0.012811247,0.005821748,0.00093473814,0.0050208946],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014372064,0.002413795,0.025447665,0.00064200803,0.00070211256,0.000044996945,0.018223945,0.0031693024,0.0016690189,0.39431596,0.5153108,0.03791664],"study_design_scores_gemma":[0.0020864855,0.00036519766,0.010037581,0.00030030668,0.00024645636,0.000051952204,0.0010717735,0.33131284,0.0009731247,0.002236454,0.6489955,0.0023223278],"about_ca_topic_score_codex":0.0002662932,"about_ca_topic_score_gemma":0.00075348915,"teacher_disagreement_score":0.87310773,"about_ca_system_score_codex":0.00049063104,"about_ca_system_score_gemma":0.00076207204,"threshold_uncertainty_score":0.9995625},"labels":[],"label_agreement":null},{"id":"W2715517100","doi":"10.29173/cais218","title":"Visualization of Scientific Knowledge: Integration of the Users’ Needs","year":2013,"lang":"fr","type":"article","venue":"Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Visualization; Comprehension; Computer science; Library science; Political science; Humanities; Art; Artificial intelligence","score_opus":0.042395332936166735,"score_gpt":0.2908408655043593,"score_spread":0.24844553256819255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2715517100","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9810098,0.0005155161,0.005819229,0.003512408,0.0014636334,0.00072785077,0.00022852085,0.000032752832,0.0066903364],"genre_scores_gemma":[0.9923485,0.00011525048,0.00059459714,0.000098715784,0.00006602823,0.000011264521,0.000012287673,0.000019747436,0.0067336312],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99733746,0.000093417744,0.0010544515,0.00036265946,0.00078012823,0.00037185903],"domain_scores_gemma":[0.9131866,0.00014546097,0.0019642746,0.000487042,0.084096685,0.000119945515],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0010754731,0.00029734184,0.0005387019,0.0003936236,0.00020596146,0.0033992906,0.0034956175,0.0002110965,0.00008546224],"category_scores_gemma":[0.012725785,0.00021217072,0.0002662243,0.0029659956,0.0016594055,0.013961484,0.0013090732,0.00022185597,0.000009426088],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025860949,0.000719876,0.058849484,0.0013449998,0.00012861931,9.449313e-8,0.10904021,0.00002883693,0.09425355,0.69846135,0.019338524,0.017808586],"study_design_scores_gemma":[0.001208259,0.0006545594,0.11454208,0.0043847826,0.00041615276,0.00002299721,0.012436783,0.16490218,0.59889853,0.020677919,0.08107365,0.00078213343],"about_ca_topic_score_codex":0.00038842295,"about_ca_topic_score_gemma":0.000034791774,"teacher_disagreement_score":0.6777834,"about_ca_system_score_codex":0.00006169986,"about_ca_system_score_gemma":0.0007067469,"threshold_uncertainty_score":0.9998297},"labels":[],"label_agreement":null},{"id":"W2728444372","doi":"10.1111/cgf.13197","title":"Linear Discriminative Star Coordinates for Exploring Class and Cluster Separation of High Dimensional Data","year":2017,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Discriminative model; Computer science; Linear subspace; Projection (relational algebra); Cluster analysis; Outlier; Class (philosophy); Artificial intelligence; Pattern recognition (psychology); Dimension (graph theory); Set (abstract data type); Data mining; Benchmark (surveying); Data set; Feature vector; Algorithm; Mathematics","score_opus":0.11240782963530994,"score_gpt":0.3558685634375094,"score_spread":0.24346073380219946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2728444372","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021445295,0.000030754338,0.97515535,0.0024331803,0.0005288338,0.00018152676,0.00017650929,0.000035616435,0.000012944842],"genre_scores_gemma":[0.91964906,0.00005080295,0.079245746,0.0004967425,0.0001048601,0.000010987225,0.00038422097,0.000012480491,0.000045085406],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99892557,0.000031187494,0.00024160698,0.00041664692,0.00019446728,0.00019049541],"domain_scores_gemma":[0.99819213,0.00013306594,0.00023362535,0.0011591446,0.00021330334,0.00006870809],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031636425,0.00012848961,0.00019437907,0.000121780744,0.0004043149,0.0002623957,0.0012658499,0.000043993503,7.6952733e-7],"category_scores_gemma":[0.000058913236,0.000115086834,0.00003910723,0.00009029442,0.0001510462,0.0018455507,0.0019099986,0.00006907864,0.0000011411719],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015962018,0.00008451386,0.0015610638,0.000068238514,0.000061076564,0.0000016618964,0.00027537215,0.00013865384,0.000025738287,0.97951686,0.008399175,0.009851684],"study_design_scores_gemma":[0.0005580476,0.00012441039,0.0029887634,0.00004851486,0.000016893911,0.0000020599216,0.000015287242,0.9766255,0.00038981857,0.01437928,0.0047059124,0.00014552707],"about_ca_topic_score_codex":0.000025806503,"about_ca_topic_score_gemma":0.000035178124,"teacher_disagreement_score":0.9764868,"about_ca_system_score_codex":0.0000061612504,"about_ca_system_score_gemma":0.000028992283,"threshold_uncertainty_score":0.4693105},"labels":[],"label_agreement":null},{"id":"W2729703817","doi":"10.1109/re.2017.81","title":"A Visual Narrative Path from Switching to Resuming a Requirements Engineering Task","year":2017,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Visualization; Visual analytics; Task (project management); Human–computer interaction; Process (computing); Creative visualization; Software visualization; Data visualization; Task analysis; Software; Software development; Artificial intelligence; Systems engineering; Component-based software engineering; Engineering","score_opus":0.04066418354582494,"score_gpt":0.3472116467744561,"score_spread":0.30654746322863113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2729703817","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01745939,0.000023701105,0.979573,0.00046979863,0.001037306,0.00022866124,0.00003563597,0.00029485716,0.0008776474],"genre_scores_gemma":[0.8022649,0.000021446282,0.19520465,0.00096959557,0.00039280255,0.000035749177,0.0001914583,0.000038974333,0.0008804053],"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978838,0.000042707074,0.00039674653,0.0008749428,0.00048638324,0.00031544577],"domain_scores_gemma":[0.9980394,0.00005024555,0.00026171468,0.001309697,0.00012029968,0.00021860207],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0003460248,0.00030863218,0.0003467713,0.00021089167,0.00023457152,0.0015536409,0.0021254686,0.00013984673,0.000026717893],"category_scores_gemma":[0.00033056783,0.00030051,0.00009378396,0.0001248878,0.000008408852,0.0005461411,0.0044529526,0.00034163528,0.00007821328],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000105199106,0.0016021534,0.004381607,0.0011836595,0.0032122408,0.0011480211,0.3183973,0.06536542,0.1195252,0.18893427,0.086391635,0.20975327],"study_design_scores_gemma":[0.00021450389,0.000028079898,0.000599811,0.00071906095,0.0000137421775,8.674327e-7,0.00020965285,0.9909726,0.00075270736,0.0013150463,0.0046041585,0.0005697934],"about_ca_topic_score_codex":0.00042137262,"about_ca_topic_score_gemma":0.00003591439,"teacher_disagreement_score":0.92560714,"about_ca_system_score_codex":0.000106872445,"about_ca_system_score_gemma":0.00015453437,"threshold_uncertainty_score":0.9999447},"labels":[],"label_agreement":null},{"id":"W2729788219","doi":"10.1111/cgf.13181","title":"NEREx: Named‐Entity Relationship Exploration in Multi‐Party Conversations","year":2017,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":53,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Sentence; Exploratory search; Reading (process); Process (computing); Exploratory research; Domain (mathematical analysis); Point (geometry); Exploratory data analysis; Thematic analysis; Information retrieval; Natural language processing; Data science; Qualitative research; Linguistics; Data mining","score_opus":0.10417266948073138,"score_gpt":0.3381073165417836,"score_spread":0.23393464706105221,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2729788219","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003513197,0.000017439968,0.9911221,0.0039604716,0.000841568,0.00016203082,0.000010404674,0.00013159584,0.00024117861],"genre_scores_gemma":[0.9755184,0.000035898356,0.023266507,0.0008499418,0.00005254272,0.000012410064,0.00008869144,0.00000988119,0.0001657002],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99870616,0.00008012985,0.00032166077,0.00037980106,0.00024506944,0.0002671651],"domain_scores_gemma":[0.9982797,0.00007271224,0.00023590322,0.0011637779,0.0001444066,0.00010350736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003629166,0.00013947154,0.00015096995,0.00030879167,0.0007155582,0.0009004821,0.0012189574,0.00009270102,0.000005773348],"category_scores_gemma":[0.00012477196,0.00014645248,0.00007874161,0.00037245118,0.00012083984,0.002929761,0.00050899055,0.0001952431,0.00007376364],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010463889,0.00009562573,0.17065302,0.000008066262,0.000008112475,0.000005528595,0.00034595668,0.00024055921,0.0000026940465,0.8234661,0.0038489248,0.0013243465],"study_design_scores_gemma":[0.00057761406,0.000022245938,0.13534229,0.00002744437,0.0000045531533,0.0000019769327,0.000025609625,0.83511364,0.000023247972,0.022396954,0.006281095,0.0001833174],"about_ca_topic_score_codex":0.00006914204,"about_ca_topic_score_gemma":0.0010740942,"teacher_disagreement_score":0.97200525,"about_ca_system_score_codex":0.000032212414,"about_ca_system_score_gemma":0.0000634471,"threshold_uncertainty_score":0.868337},"labels":[],"label_agreement":null},{"id":"W2732748639","doi":"10.1007/978-3-319-63874-4_17","title":"Making Interface Customizations Work: Lessons from a Successful Tailoring Community","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Personalization; Interface (matter); Point (geometry); User interface; Online community; Human–computer interaction; World Wide Web; Work (physics); Software; Scale (ratio); Collaborative filtering; Recommender system","score_opus":0.08682233518944915,"score_gpt":0.3580959267406903,"score_spread":0.27127359155124114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2732748639","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006158954,0.00019109195,0.9907201,0.001174648,0.0015326813,0.00019607299,0.000037152655,0.0002197841,0.005866882],"genre_scores_gemma":[0.7624676,0.000073271534,0.2344973,0.0013023558,0.00043095852,0.000006905111,0.000054790635,0.00005649308,0.0011103327],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99693304,0.0001082051,0.00053931033,0.0010743551,0.0007728246,0.00057226507],"domain_scores_gemma":[0.9951728,0.00059119833,0.0005724608,0.003206215,0.0002943485,0.00016298852],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0009624397,0.0005017603,0.00054907415,0.00069383526,0.0013623044,0.0025952489,0.008344896,0.0002799764,0.000050975057],"category_scores_gemma":[0.00032097616,0.0004979964,0.00012208376,0.00045862392,0.0007693182,0.0013512846,0.004627033,0.0014163062,0.00008659584],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009256461,0.00011928925,0.0008997286,0.00005779043,0.00005973553,0.00008013552,0.004789352,0.08429805,0.000049297643,0.07226232,0.00024318435,0.83713186],"study_design_scores_gemma":[0.0004311159,0.00006159889,0.0005117595,0.0022054925,0.00003216131,0.00001708582,0.0000022049182,0.85586965,0.00050497695,0.12815471,0.010954063,0.0012552126],"about_ca_topic_score_codex":0.00014998436,"about_ca_topic_score_gemma":0.00057309173,"teacher_disagreement_score":0.83587664,"about_ca_system_score_codex":0.00027993968,"about_ca_system_score_gemma":0.00045056897,"threshold_uncertainty_score":0.9999378},"labels":[],"label_agreement":null},{"id":"W2734916492","doi":"10.1145/3079628.3079634","title":"Impact of Individual Differences on User Experience with a Real-World Visualization Interface for Public Engagement","year":2017,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visualization; Computer science; Human–computer interaction; Information visualization; Perception; User interface; Eye tracking; Usability; User experience design; User satisfaction; Data visualization; User interface design; Multimedia; Artificial intelligence; Psychology","score_opus":0.12861582715016606,"score_gpt":0.4179219222526938,"score_spread":0.28930609510252775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2734916492","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21072413,0.0000014337289,0.78681475,0.00014967055,0.00006303466,0.00019080151,0.000017652907,0.00005494731,0.0019835772],"genre_scores_gemma":[0.9939578,0.000009403046,0.0049063843,0.00007845287,0.000016586077,0.000020550635,0.00001661098,0.0000065985114,0.0009876136],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9989665,0.000042941676,0.0001998008,0.00027829147,0.00033305958,0.00017940132],"domain_scores_gemma":[0.99873,0.000069933616,0.0002678557,0.0006982723,0.00015606087,0.000077860546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025985276,0.0001213724,0.00015153123,0.00015696618,0.00026440737,0.00086814485,0.0013615558,0.000021594033,0.00006271354],"category_scores_gemma":[0.0001234611,0.00007824951,0.00004594811,0.00017944086,0.0000818581,0.00096824707,0.00028838386,0.00003811299,0.0000037995615],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003255168,0.00043386532,0.24480797,0.000025638428,0.000113167705,8.9284356e-7,0.0035135658,0.00007952287,0.00015171139,0.73838574,0.0031111813,0.009344178],"study_design_scores_gemma":[0.0017477613,0.002349733,0.8113462,0.0001505459,0.000028436687,0.0000012698522,0.00048802738,0.17261752,0.0071938555,0.0008773613,0.0026361065,0.00056318473],"about_ca_topic_score_codex":0.00009537346,"about_ca_topic_score_gemma":0.0001583974,"teacher_disagreement_score":0.78323364,"about_ca_system_score_codex":0.00002944639,"about_ca_system_score_gemma":0.0000814503,"threshold_uncertainty_score":0.8371541},"labels":[],"label_agreement":null},{"id":"W2735041065","doi":"10.1145/3099023.3099059","title":"Leveraging Pupil Dilation Measures for Understanding Users' Cognitive Load During Visualization Processing","year":2017,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visualization; Pupillary response; Computer science; Bar chart; Human–computer interaction; Pupil; Data visualization; Cognitive load; Graph; Cognition; Artificial intelligence; Psychology; Theoretical computer science","score_opus":0.12461967227297144,"score_gpt":0.3614669554580493,"score_spread":0.23684728318507786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2735041065","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0038373943,0.0000146646635,0.99247223,0.00026826846,0.00013160636,0.00018504946,0.0000034823179,0.0001734526,0.0029138217],"genre_scores_gemma":[0.99534404,0.0000090955255,0.0036635008,0.00015007102,0.00006670604,0.0000081747385,0.000019093826,0.0000122441115,0.00072708353],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989267,0.000022560347,0.00019439944,0.00032011085,0.00033152231,0.00020470507],"domain_scores_gemma":[0.9990985,0.00004522335,0.00023098418,0.00026273786,0.0003021426,0.000060408987],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00035031856,0.000113033784,0.0001112466,0.000097060234,0.0013928397,0.0017050498,0.00042222574,0.00004153217,0.00000699829],"category_scores_gemma":[0.00041034614,0.000110288514,0.00003915034,0.000116409465,0.00004089709,0.0022958731,0.00014571733,0.00003867576,0.0000057603875],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008527521,0.00024941532,0.031002553,0.0005896939,0.0001454517,0.000013742944,0.012464759,0.0007026799,0.004513761,0.88297987,0.0008823504,0.066370435],"study_design_scores_gemma":[0.0011985531,0.000024909878,0.003943036,0.00022718703,0.000026558593,0.0000042537517,0.00097499334,0.9777891,0.006779437,0.008448479,0.00027320467,0.00031028828],"about_ca_topic_score_codex":0.000012987811,"about_ca_topic_score_gemma":0.000025801988,"teacher_disagreement_score":0.99150664,"about_ca_system_score_codex":0.00016796593,"about_ca_system_score_gemma":0.00010910054,"threshold_uncertainty_score":0.9999072},"labels":[],"label_agreement":null},{"id":"W2736696915","doi":"10.1145/3102254.3102287","title":"Discovering the smart forests with virtual reality","year":2017,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Terabyte; Big data; Computer science; Leverage (statistics); Data science; Virtual reality; The Internet; Work (physics); Internet of Things; World Wide Web; Human–computer interaction; Engineering; Artificial intelligence","score_opus":0.03854849807078021,"score_gpt":0.3189647002966833,"score_spread":0.2804162022259031,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2736696915","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0068891943,8.7606605e-7,0.9676176,0.0028810615,0.00007267795,0.00003487126,0.000002029334,0.000046189605,0.022455556],"genre_scores_gemma":[0.99584085,0.0000024779258,0.00088825094,0.00036037725,0.000025049223,0.0000012596641,0.0000022392978,0.0000022542831,0.002877258],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995696,0.000012353038,0.00005951058,0.00012675168,0.00014032733,0.00009146933],"domain_scores_gemma":[0.99892664,0.000017943263,0.000052623825,0.0009478501,0.000022215927,0.000032735952],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014974263,0.000045425844,0.00004398778,0.000009030074,0.0003754609,0.0007605745,0.0010455056,0.00000949816,0.000010054573],"category_scores_gemma":[0.00003670052,0.000022429502,0.0000139130325,0.00003774197,0.00006444885,0.00065415807,0.0003358987,0.000032327865,0.000023420536],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000015726855,0.000013893497,0.014878993,0.0000014981404,0.0000073072238,0.000003269379,0.00012954356,0.00009435414,0.000004992611,0.97520137,0.0035797001,0.0060835257],"study_design_scores_gemma":[0.00049666566,0.0001597733,0.25118527,0.000028564466,0.0000098358505,0.000013286695,0.00016212811,0.69855285,0.00073910516,0.0042511774,0.044118572,0.00028276313],"about_ca_topic_score_codex":0.00013837234,"about_ca_topic_score_gemma":0.0013425407,"teacher_disagreement_score":0.9889516,"about_ca_system_score_codex":0.0000054486727,"about_ca_system_score_gemma":0.000024590756,"threshold_uncertainty_score":0.73342377},"labels":[],"label_agreement":null},{"id":"W2736760681","doi":"","title":"Exploring information visualization use patterns in casual contexts","year":2011,"lang":"en","type":"dissertation","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Casual; Computer science; Visualization; Information visualization; Data science; Human–computer interaction; Psychology; Artificial intelligence; Political science","score_opus":0.12219926445701175,"score_gpt":0.3249473543716792,"score_spread":0.20274808991466747,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2736760681","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.101349,0.000017774835,0.8873761,0.000015860425,0.0020076884,0.00046720204,0.000043681892,0.00042543147,0.008297232],"genre_scores_gemma":[0.966886,0.000906356,0.003043248,0.0011787495,0.00011829209,0.00015948563,0.016477318,0.000063007166,0.0111675775],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9985179,0.00005510998,0.0005968753,0.00026534166,0.00034427978,0.00022049452],"domain_scores_gemma":[0.99897844,0.000033564545,0.00028387582,0.00039467032,0.00023411041,0.000075321885],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017128556,0.00022426217,0.0002221856,0.00070810603,0.000056620094,0.0005605468,0.0005298013,0.00013849072,0.00008507068],"category_scores_gemma":[0.00010865489,0.00022766541,0.000052513264,0.0005431421,0.000005759274,0.009360647,0.00007320099,0.00013997903,0.00017494583],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033265253,0.00023229285,0.00955187,0.00043954258,0.00004858678,0.000021802007,0.024703413,0.00007579265,0.000034011282,0.86062294,0.0017624535,0.102474004],"study_design_scores_gemma":[0.0045672096,0.00048418262,0.489016,0.0028447753,0.00012725643,0.000022833321,0.010382933,0.39213526,0.012213969,0.0027703778,0.080050565,0.0053846315],"about_ca_topic_score_codex":0.00075248757,"about_ca_topic_score_gemma":0.0020287666,"teacher_disagreement_score":0.8843329,"about_ca_system_score_codex":0.0000569352,"about_ca_system_score_gemma":0.0000962404,"threshold_uncertainty_score":0.9283926},"labels":[],"label_agreement":null},{"id":"W2737474671","doi":"","title":"Visualization analysis and design: keynote address","year":2016,"lang":"en","type":"article","venue":"Journal of computing sciences in colleges","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visualization; Computer science; Human–computer interaction; Task (project management); Resource (disambiguation); Space (punctuation); Information visualization; Visual analytics; Data visualization; Data science; Artificial intelligence; Systems engineering","score_opus":0.042275731159824304,"score_gpt":0.3537014500629259,"score_spread":0.3114257189031016,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2737474671","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.039754007,0.00010347148,0.9589423,0.00084097503,0.00018813495,0.000037326554,8.3571774e-7,0.000013846937,0.000119106335],"genre_scores_gemma":[0.9480454,0.000104299164,0.051573038,0.00017979027,0.000044794957,1.3320705e-7,8.936042e-8,0.0000021655583,0.000050319577],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99850625,0.00019779234,0.00046881344,0.0001951587,0.00046127106,0.00017073961],"domain_scores_gemma":[0.99861926,0.0005761197,0.00042996395,0.00012702912,0.00018604082,0.00006161309],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023991223,0.00008185586,0.00023108377,0.0009685016,0.00014965289,0.00026304522,0.0007580087,0.000030100886,0.000006356805],"category_scores_gemma":[0.00034896572,0.000051133567,0.00005325832,0.00315051,0.00015892134,0.00078875595,0.00016341671,0.000046139947,0.0000010967059],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056982157,0.00051005464,0.37020403,0.000058166228,0.0005018426,0.00018161103,0.005289407,0.091712646,0.0036664712,0.37735742,0.005602276,0.14485909],"study_design_scores_gemma":[0.0007790498,0.0003101149,0.032950964,0.0002318987,0.00005521948,0.00005707486,0.00012321844,0.9589593,0.002117961,0.0034923102,0.0007077754,0.00021513096],"about_ca_topic_score_codex":0.0000035338705,"about_ca_topic_score_gemma":0.0000064569813,"teacher_disagreement_score":0.90829134,"about_ca_system_score_codex":0.000033102384,"about_ca_system_score_gemma":0.00013738839,"threshold_uncertainty_score":0.2536551},"labels":[],"label_agreement":null},{"id":"W2739056128","doi":"10.1162/leon_a_01278","title":"Differential Hive Plots: Seeing Networks Change","year":2016,"lang":"en","type":"article","venue":"Leonardo","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"","keywords":"Intersection (aeronautics); Computer science; Similarity (geometry); Differential (mechanical device); Plot (graphics); Algorithm; Artificial intelligence; Pattern recognition (psychology); Data mining; Theoretical computer science; Mathematics; Statistics; Cartography; Image (mathematics); Physics; Geography","score_opus":0.03313933408742976,"score_gpt":0.26920774597397185,"score_spread":0.2360684118865421,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2739056128","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010761851,0.000054224223,0.9941978,0.0034454637,0.00045242632,0.000056627694,0.000006832591,0.00017691424,0.00053351675],"genre_scores_gemma":[0.99553186,0.00010513537,0.0011820736,0.0013611641,0.0004429746,0.000008975922,0.000009687494,0.00001025787,0.0013478659],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992571,0.00003211644,0.000115805626,0.00022732536,0.00015940297,0.00020825253],"domain_scores_gemma":[0.99946815,0.00004061735,0.000048541147,0.0003318649,0.000033801665,0.00007704283],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004676885,0.00008670287,0.000092984825,0.00005116983,0.00006726601,0.000090295245,0.00048749943,0.000039596238,0.0001448459],"category_scores_gemma":[0.000016201706,0.000057949346,0.000041479132,0.0001585935,0.000024785384,0.00042371944,0.00022937419,0.000038588252,0.0001519755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000063106304,0.00009755596,0.004707737,0.000011840538,0.0000436278,0.000039450515,0.0005679646,0.000021751692,0.00060158875,0.49780247,0.015142763,0.48095694],"study_design_scores_gemma":[0.0018965988,0.00017007402,0.021486627,0.0003111111,0.00003293521,0.000025516787,0.00010030552,0.6635169,0.0013438606,0.0035261211,0.30659997,0.0009900159],"about_ca_topic_score_codex":0.0000056573367,"about_ca_topic_score_gemma":0.000004807046,"teacher_disagreement_score":0.9944557,"about_ca_system_score_codex":0.00001914606,"about_ca_system_score_gemma":0.000010082746,"threshold_uncertainty_score":0.23631057},"labels":[],"label_agreement":null},{"id":"W2739232917","doi":"10.3934/bdia.2017003","title":"Rendering website traffic data into interactive taste graph visualizations","year":2017,"lang":"en","type":"article","venue":"Big Data and Information Analytics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario College of Art and Design","funders":"","keywords":"Rendering (computer graphics); Computer science; Computer graphics (images); Graph; World Wide Web; Multimedia; Theoretical computer science","score_opus":0.11087586483674504,"score_gpt":0.35835827069580023,"score_spread":0.24748240585905518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2739232917","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006255824,0.00004138127,0.9952269,0.0009080001,0.00041546108,0.00009909082,0.00061420916,0.000107103544,0.0019622552],"genre_scores_gemma":[0.96121025,0.0019092017,0.015473465,0.0021362738,0.0002051276,0.0000032204046,0.018793108,0.000015847727,0.0002534777],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986678,0.000031539774,0.00047299347,0.00034957816,0.00029882212,0.0001792992],"domain_scores_gemma":[0.995026,0.0000418556,0.00046656825,0.0041526086,0.00016857359,0.00014441808],"candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.00041108424,0.00015801923,0.00017316004,0.0002968484,0.00075044326,0.0027011477,0.004094137,0.000059196373,0.000010785444],"category_scores_gemma":[0.0006013257,0.00015067024,0.000021264506,0.00031851497,0.00010759092,0.022386989,0.004153996,0.000115573974,0.00008557516],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014891075,0.00017857908,0.0014170946,0.00023760609,0.00031774497,0.000009040158,0.0053571537,0.0018809417,0.000026814927,0.18225887,0.10544067,0.7028606],"study_design_scores_gemma":[0.00023972896,0.0000123021655,0.00058383314,0.00002980748,0.000026931586,0.000005383925,0.00029268124,0.7575238,0.000008887144,0.00018284506,0.2409404,0.00015343538],"about_ca_topic_score_codex":0.000029285227,"about_ca_topic_score_gemma":0.00009071533,"teacher_disagreement_score":0.97975343,"about_ca_system_score_codex":0.000019360185,"about_ca_system_score_gemma":0.000098621145,"threshold_uncertainty_score":0.99833417},"labels":[],"label_agreement":null},{"id":"W2741152238","doi":"10.24963/ijcai.2017/217","title":"Further Results on Predicting Cognitive Abilities for Adaptive Visualizations","year":2017,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Generality; Computer science; Gaze; Human–computer interaction; Set (abstract data type); Cognition; Eye tracking; Visualization; Data visualization; Quality (philosophy); User modeling; User interface; Artificial intelligence; Psychology","score_opus":0.07634205449131588,"score_gpt":0.36931894506836305,"score_spread":0.2929768905770472,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2741152238","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006852866,0.0000039057218,0.9596522,0.001113239,0.00017712326,0.00022690561,0.00018903865,0.00014300026,0.03780931],"genre_scores_gemma":[0.9823877,0.0000048915713,0.008177973,0.0005892527,0.0001039881,0.000026000655,0.000055178953,0.000009631112,0.008645385],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999193,0.000027174836,0.00018049669,0.00029234024,0.00015489144,0.0001521094],"domain_scores_gemma":[0.9987257,0.0003233504,0.00015244549,0.00048397583,0.00025917543,0.000055352208],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025108832,0.00008755378,0.000091154216,0.000056601963,0.00055261323,0.00046250498,0.00053733576,0.00003341624,0.00001478031],"category_scores_gemma":[0.0012962766,0.00007422823,0.000043190146,0.000059760077,0.000074485804,0.0005966226,0.0001523266,0.000035904483,0.00003530419],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037645306,0.000099898774,0.00048758756,0.000007377181,0.000030712326,8.5420584e-7,0.0022501566,0.000060645052,0.000006334314,0.98614895,0.004170732,0.006699103],"study_design_scores_gemma":[0.0018075686,0.0005134713,0.0032787458,0.00012987961,0.000020476658,0.0000011888071,0.002134173,0.97187185,0.0013353368,0.010405663,0.008201204,0.00030046754],"about_ca_topic_score_codex":0.000024466079,"about_ca_topic_score_gemma":0.00004108197,"teacher_disagreement_score":0.9817024,"about_ca_system_score_codex":0.000014723978,"about_ca_system_score_gemma":0.000047020356,"threshold_uncertainty_score":0.44599462},"labels":[],"label_agreement":null},{"id":"W2741208289","doi":"10.14714/cp86.1392","title":"Designing a Rule-based Wizard for Visualizing Statistical Data on Thematic Maps","year":2017,"lang":"en","type":"article","venue":"Cartographic Perspectives","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario College of Art and Design","funders":"","keywords":"Wizard; Thematic map; Workflow; Computer science; Set (abstract data type); Data mining; Selection (genetic algorithm); Visualization; Data science; Information retrieval; Database; Artificial intelligence; Cartography; Programming language; World Wide Web; Geography","score_opus":0.09971607546974892,"score_gpt":0.38868558689871274,"score_spread":0.2889695114289638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2741208289","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006434449,0.000097860735,0.9965159,0.00075694325,0.0001418383,0.0002501385,0.00025444347,0.0001522476,0.0011871293],"genre_scores_gemma":[0.84690267,0.0000276492,0.15225902,0.00038180515,0.0001249394,0.00003484438,0.00017776326,0.00002656575,0.00006473058],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99839264,0.0000839378,0.00020691816,0.000699183,0.00031035623,0.00030698627],"domain_scores_gemma":[0.99691564,0.0003937967,0.00018537814,0.0022202677,0.00015609524,0.00012884072],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005927294,0.00018356458,0.00023754555,0.000227599,0.0007866569,0.0009421752,0.0022797429,0.000050908227,0.000011182241],"category_scores_gemma":[0.0011394784,0.00016477017,0.00008169111,0.00018808496,0.0002564828,0.00066982524,0.0003297841,0.00010473771,0.000013531237],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021466698,0.00022436511,0.00075781974,0.00007268111,0.00008049144,0.000014866874,0.0013832635,0.00003952889,0.00038139254,0.9885093,0.0049518114,0.0035630013],"study_design_scores_gemma":[0.0028492028,0.0005884774,0.0034323311,0.00050472276,0.00015446817,0.000010812218,0.005146934,0.91652197,0.0015117291,0.06190107,0.0062906826,0.001087624],"about_ca_topic_score_codex":0.000011589089,"about_ca_topic_score_gemma":0.000008316155,"teacher_disagreement_score":0.92660826,"about_ca_system_score_codex":0.000026504687,"about_ca_system_score_gemma":0.000101930644,"threshold_uncertainty_score":0.90854174},"labels":[],"label_agreement":null},{"id":"W2744428264","doi":"10.1109/mtits.2017.8005715","title":"Dynamic partitioning of urban road networks based on their topological and operational characteristics","year":2017,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Space partitioning; Graph partition; Cluster analysis; Curse of dimensionality; Graph; Network topology; Distributed computing; Data mining; Topology (electrical circuits); Theoretical computer science; Artificial intelligence; Algorithm; Engineering","score_opus":0.024616354289724026,"score_gpt":0.29364435161443975,"score_spread":0.2690279973247157,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2744428264","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02040149,0.0000051562697,0.9769607,0.00093761284,0.00009380653,0.000035084126,0.000010652714,0.00002643726,0.0015290554],"genre_scores_gemma":[0.99460226,0.000010357561,0.0043812045,0.00079298875,0.000020379985,0.0000012971972,0.00003456947,0.0000017965965,0.00015513398],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995721,0.000020858002,0.00011832506,0.00013241784,0.00008159883,0.00007471665],"domain_scores_gemma":[0.99950176,0.00003149514,0.00007798076,0.00030623455,0.000044245546,0.000038259637],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012143727,0.000053134725,0.00008188539,0.000021632593,0.00021166634,0.00025416398,0.00028953515,0.000029604198,0.00004960153],"category_scores_gemma":[0.0000651139,0.000038972204,0.000016307109,0.000026547621,0.000070754024,0.00018453147,0.000095699914,0.000040030252,0.0000027171452],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009496643,0.00017943935,0.074051425,0.000010139349,0.000013995573,0.0000053326266,0.00008833502,0.001787823,0.00012318174,0.9021019,0.0010327732,0.020596195],"study_design_scores_gemma":[0.00009400272,0.000037430833,0.14805634,0.000009722852,0.0000012000426,5.5634285e-7,0.0000037745983,0.8512559,0.00003087366,0.00019833691,0.0002676535,0.000044233053],"about_ca_topic_score_codex":0.0000049754167,"about_ca_topic_score_gemma":0.000004125173,"teacher_disagreement_score":0.9742008,"about_ca_system_score_codex":0.000005534813,"about_ca_system_score_gemma":0.000017807044,"threshold_uncertainty_score":0.24509092},"labels":[],"label_agreement":null},{"id":"W2752241902","doi":"10.5210/ojphi.v9i2.8000","title":"Interactive visualization of public health indicators to support policymaking: An exploratory study","year":2017,"lang":"en","type":"article","venue":"Online Journal of Public Health Informatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; Western University","funders":"","keywords":"Usability; Computer science; Visualization; Learnability; Process (computing); Data science; Interactive visualization; Health care; Health informatics; Health indicator; Human–computer interaction; Public health; Knowledge management; Data mining; Medicine","score_opus":0.19507434597987755,"score_gpt":0.4784536351605938,"score_spread":0.28337928918071625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2752241902","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09500452,0.000014743907,0.8894651,0.01417935,0.0006149227,0.00040422063,0.000078074234,0.00004785195,0.00019125013],"genre_scores_gemma":[0.96811813,0.000114461356,0.022917667,0.008505266,0.00020853062,0.000002788005,0.000086479195,0.000019989566,0.000026677799],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9945059,0.0005658343,0.0030494547,0.00014534935,0.0011346168,0.0005988349],"domain_scores_gemma":[0.9890111,0.00006131252,0.0071737864,0.0010294911,0.0012132779,0.0015110242],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009854096,0.00020686709,0.0006475077,0.0018632439,0.00048784784,0.000973964,0.0025040822,0.00006270177,0.000020797372],"category_scores_gemma":[0.0020131855,0.00018157563,0.00008202107,0.0010029905,0.00007065128,0.0084106475,0.00058064435,0.00031445047,0.000008641306],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013343782,0.0067832386,0.049553704,0.00048592317,0.00024191443,0.000009818962,0.294484,0.00015708027,0.0000021807525,0.04730482,0.012233098,0.5887309],"study_design_scores_gemma":[0.0068255495,0.028454995,0.107212044,0.0006594614,0.000036385805,0.0002364173,0.1704639,0.17187493,0.00003511463,0.00042568258,0.5124656,0.00130995],"about_ca_topic_score_codex":0.00003280146,"about_ca_topic_score_gemma":0.00016791817,"teacher_disagreement_score":0.87311363,"about_ca_system_score_codex":0.00038719992,"about_ca_system_score_gemma":0.006178706,"threshold_uncertainty_score":0.99945533},"labels":[],"label_agreement":null},{"id":"W2752511750","doi":"10.1145/3102071.3102089","title":"Vixen","year":2017,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; USable; Visualization; Data visualization; Human–computer interaction; Process (computing); Focus (optics); Domain (mathematical analysis); Representation (politics); Data science; External Data Representation; Multimedia; Data mining; Artificial intelligence","score_opus":0.04377433604875836,"score_gpt":0.3480795268858432,"score_spread":0.30430519083708485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2752511750","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006435298,0.0000012078882,0.8621941,0.0022413153,0.000064687134,0.0000069847715,1.9064888e-7,0.000048625236,0.13537854],"genre_scores_gemma":[0.9301869,0.000007394393,0.034435783,0.0036550404,0.00004671657,5.640511e-7,0.0000017349207,0.0000021758415,0.031663686],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998103,0.000002382968,0.000029360264,0.00006382669,0.000050909654,0.000043268446],"domain_scores_gemma":[0.9993928,0.0000028089157,0.000020585729,0.00054578914,0.00001416155,0.000023819957],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000043051197,0.000017094715,0.000020341095,0.000009447194,0.00014149185,0.00044182249,0.0007973218,0.0000064141177,0.00005761189],"category_scores_gemma":[0.000023793678,0.000013402973,0.000008534295,0.000013181592,0.000011483135,0.00039816464,0.0001760028,0.0000093617455,0.00031174926],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.995212e-8,0.0000062445242,0.00084878464,4.904865e-7,0.0000012150183,0.0000013774328,0.00001722842,0.000001413975,0.000014556701,0.9632044,0.027200403,0.008703865],"study_design_scores_gemma":[0.00015902561,0.000011094228,0.012640944,0.000002948467,0.0000010767606,0.0000020926723,0.000005543147,0.2880112,0.001567367,0.009849646,0.68764526,0.00010379216],"about_ca_topic_score_codex":0.000011544338,"about_ca_topic_score_gemma":0.0000035043586,"teacher_disagreement_score":0.9533547,"about_ca_system_score_codex":0.0000015957521,"about_ca_system_score_gemma":0.0000074404343,"threshold_uncertainty_score":0.42605042},"labels":[],"label_agreement":null},{"id":"W2753088425","doi":"10.14778/3137628.3137637","title":"I've seen \"enough\"","year":2017,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":69,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Visualization; Usability; Sampling (signal processing); Interactivity; Data mining; Context (archaeology); Speedup; Creative visualization; Data visualization; Sample (material); Machine learning; Data science; Human–computer interaction; World Wide Web; Computer vision; Parallel computing","score_opus":0.026778950403935492,"score_gpt":0.29047185050860946,"score_spread":0.26369290010467394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2753088425","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18039562,0.0003471076,0.06532205,0.06977273,0.0047640875,0.0023406052,0.00008136377,0.0008040913,0.6761723],"genre_scores_gemma":[0.991994,0.000028443792,0.0050943242,0.00035711727,0.00005813189,0.0000061842143,5.0416355e-7,0.000005602105,0.0024556909],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992126,0.000002223446,0.00015636106,0.0001837368,0.00029599539,0.00014904427],"domain_scores_gemma":[0.9991261,0.000007695338,0.00029640953,0.00038947747,0.00013267114,0.000047695285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002094565,0.00008106488,0.00010423144,0.000032362885,0.00030003896,0.00035258944,0.0024872632,0.000022509928,0.000010301957],"category_scores_gemma":[0.00012115489,0.000053990963,0.00006220066,0.00008571981,0.00006633272,0.0005471233,0.0010721808,0.000055440778,0.000022770784],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000037515763,0.00012776059,0.0073667862,0.000062404506,0.000046805384,5.4839114e-7,0.0012650423,0.000005474488,0.009728499,0.9462515,0.026004026,0.009137377],"study_design_scores_gemma":[0.0023728367,0.00026147414,0.03783859,0.00042309592,0.00010198526,0.000032993896,0.0006533157,0.048884388,0.6312818,0.064882815,0.21237074,0.00089596043],"about_ca_topic_score_codex":0.000017570876,"about_ca_topic_score_gemma":9.168307e-7,"teacher_disagreement_score":0.8813687,"about_ca_system_score_codex":0.000022321172,"about_ca_system_score_gemma":0.000019916859,"threshold_uncertainty_score":0.46219954},"labels":[],"label_agreement":null},{"id":"W2753664105","doi":"10.1145/3103010.3103013","title":"MACE","year":2017,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Subtractive color; Set (abstract data type); Context (archaeology); Visualization; Readability; Clutter; Theoretical computer science; Generative grammar; Human–computer interaction; Artificial intelligence; Programming language","score_opus":0.04504198478706526,"score_gpt":0.35258566347848297,"score_spread":0.3075436786914177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2753664105","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00010734106,0.0000017207961,0.83897275,0.0018014783,0.00008386687,0.000006796376,2.5229392e-7,0.000047551977,0.15897825],"genre_scores_gemma":[0.8931677,0.000010759105,0.05279173,0.0020774845,0.0000431856,5.1748907e-7,0.0000014501101,0.0000022393062,0.051904958],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998161,0.0000024255403,0.000026992935,0.00006306639,0.000049389164,0.000042035463],"domain_scores_gemma":[0.9994075,0.000002816565,0.000019752588,0.00053374236,0.000013126688,0.0000230759],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000040446073,0.00001666047,0.000019063713,0.000008810384,0.0001265462,0.0003972942,0.0007597028,0.0000060134494,0.000060475497],"category_scores_gemma":[0.000025376663,0.0000132152345,0.000007826534,0.000013868565,0.000010370627,0.00034895586,0.00019191082,0.000009608258,0.00030675996],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.2727044e-8,0.0000044488934,0.00061999535,4.5097568e-7,8.0874963e-7,0.0000013222924,0.0000112224525,6.2526897e-7,0.000019123327,0.9696016,0.017222453,0.012517947],"study_design_scores_gemma":[0.00017520603,0.000011260893,0.01133955,0.000003627511,0.0000012209048,0.0000031154461,0.0000067242972,0.42420498,0.002184173,0.0100213885,0.5519288,0.000119960554],"about_ca_topic_score_codex":0.000007872746,"about_ca_topic_score_gemma":0.000004049293,"teacher_disagreement_score":0.9595802,"about_ca_system_score_codex":0.0000015575688,"about_ca_system_score_gemma":0.00000675613,"threshold_uncertainty_score":0.3942881},"labels":[],"label_agreement":null},{"id":"W2754529182","doi":"10.1007/s41060-017-0072-z","title":"Visual analytics of high-frequency lake monitoring data","year":2017,"lang":"en","type":"article","venue":"International Journal of Data Science and Analytics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ministry of the Environment, Conservation and Parks; University of Saskatchewan; Nipissing University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canada Foundation for Innovation","keywords":"Visual analytics; Analytics; Data science; Computer science; Remote sensing; Visualization; Geography; Data mining","score_opus":0.12019800888902016,"score_gpt":0.4235599393987042,"score_spread":0.303361930509684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2754529182","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09437887,0.00034293177,0.88877606,0.0082365,0.0050600194,0.00011951674,0.0017183787,0.000036542744,0.0013311856],"genre_scores_gemma":[0.9606281,0.00088630215,0.037850544,0.00010352077,0.0004179081,7.05965e-8,0.000064242806,0.0000056020444,0.00004369256],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9967439,0.000022919778,0.00068872515,0.00043487348,0.0018983557,0.00021119067],"domain_scores_gemma":[0.99421203,0.00008604674,0.0012371952,0.0023002794,0.001971869,0.00019256532],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0025887578,0.00012903701,0.00026710032,0.00048520975,0.00029234987,0.0014877107,0.018061014,0.00003894287,0.00001151492],"category_scores_gemma":[0.002245907,0.00010892889,0.000034063192,0.00038865377,0.0006391804,0.011409043,0.005481088,0.0001708855,0.0000036747253],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000067250396,0.0014374737,0.3335275,0.00010728266,0.001409645,0.0008468797,0.0007100698,0.0007183083,0.010874597,0.26793474,0.009920569,0.37244567],"study_design_scores_gemma":[0.0016894249,0.0002518031,0.070857495,0.00048445768,0.0002332364,0.00032967882,0.00033338848,0.90243083,0.0033431305,0.006408236,0.013059372,0.00057892996],"about_ca_topic_score_codex":0.000055350967,"about_ca_topic_score_gemma":0.000043639262,"teacher_disagreement_score":0.90171254,"about_ca_system_score_codex":0.000040611354,"about_ca_system_score_gemma":0.0007149347,"threshold_uncertainty_score":0.99954885},"labels":[],"label_agreement":null},{"id":"W2757349124","doi":"10.3390/informatics4040033","title":"Health Literacy for the General Public: Making a Case for Non-Trivial Visualizations","year":2017,"lang":"en","type":"article","venue":"Informatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Health literacy; Visualization; Computer science; Literacy; Public health; Data visualization; Data science; Human–computer interaction; Psychology; Health care; Medicine; Artificial intelligence; Pedagogy; Nursing","score_opus":0.07951790359042882,"score_gpt":0.4369266240304251,"score_spread":0.3574087204399963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2757349124","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002024953,0.000011458458,0.99350333,0.0047689797,0.0004557083,0.0005449031,0.00013532279,0.000056314446,0.00032146278],"genre_scores_gemma":[0.4069508,0.000049458078,0.57900524,0.012042062,0.0006126134,0.00018684792,0.0002174397,0.000026646687,0.00090889767],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99897623,0.000012014921,0.00047330078,0.000090063404,0.00015797422,0.00029044325],"domain_scores_gemma":[0.99804837,0.00018038823,0.00051388977,0.0008476645,0.00032641157,0.00008328334],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0005735123,0.00010423057,0.00014096219,0.00008644388,0.0019273924,0.0032379604,0.0011250613,0.000035691854,0.000002863006],"category_scores_gemma":[0.00040686232,0.00007645969,0.00008102872,0.00012362131,0.00004524587,0.0024507407,0.00029038277,0.000050207236,0.000008032652],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003802993,0.00006354488,0.00018472044,0.00023832239,0.000042842188,0.00000383563,0.00859351,0.00039871188,8.623675e-7,0.72669935,0.05063303,0.21313749],"study_design_scores_gemma":[0.0003705247,0.000039418737,0.000028002542,0.000016992157,0.000005978004,0.000059567607,0.00008889102,0.7987932,0.000006332531,0.00079867634,0.19970706,0.00008535255],"about_ca_topic_score_codex":0.0000131736115,"about_ca_topic_score_gemma":0.00004155468,"teacher_disagreement_score":0.7983945,"about_ca_system_score_codex":0.000034594384,"about_ca_system_score_gemma":0.00021626477,"threshold_uncertainty_score":0.99937195},"labels":[],"label_agreement":null},{"id":"W2758238851","doi":"10.18653/v1/w17-4502","title":"Multimedia Summary Generation from Online Conversations: Current Approaches and Future Directions","year":2017,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Asynchronous communication; Variety (cybernetics); Visualization; Conversation; Multimedia; Representation (politics); Human–computer interaction; Domain (mathematical analysis); Social media; Key (lock); World Wide Web; Data visualization; Space (punctuation); Data science; Artificial intelligence","score_opus":0.09814234575045262,"score_gpt":0.32139347644861843,"score_spread":0.22325113069816582,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2758238851","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0060210936,0.0018402762,0.9757422,0.011680856,0.0024392111,0.00019183996,0.00021353092,0.00024039969,0.0016305426],"genre_scores_gemma":[0.24728304,0.020278689,0.70753443,0.0020651147,0.010232024,0.000049512677,0.007118634,0.00004452247,0.0053940443],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99947464,0.000022720762,0.000107912136,0.00022006874,0.00010471151,0.00006995067],"domain_scores_gemma":[0.99935496,0.00001924569,0.00007459189,0.00044644994,0.000041481373,0.000063244515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000061240506,0.00006845606,0.000068393536,0.00003922166,0.00036143092,0.00044537807,0.00030235283,0.000030440644,0.000026167443],"category_scores_gemma":[0.000034526045,0.000058545837,0.000018354876,0.000047427107,0.000042841126,0.0007470161,0.00015534327,0.00005370145,0.000012545457],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.1202435e-7,0.0002089064,0.0048479405,0.000005377127,0.000028925591,9.278861e-7,0.0007939461,0.0000094071565,0.00009556648,0.11677823,0.02100917,0.85622066],"study_design_scores_gemma":[0.00017869675,0.0000048574693,0.013668617,0.000003892317,0.000007822419,4.1898045e-7,0.00005843546,0.7635012,0.000087025306,0.0003102256,0.22209646,0.000082312945],"about_ca_topic_score_codex":0.00008071272,"about_ca_topic_score_gemma":0.0002315172,"teacher_disagreement_score":0.85613835,"about_ca_system_score_codex":0.000009971131,"about_ca_system_score_gemma":0.000026289392,"threshold_uncertainty_score":0.4294791},"labels":[],"label_agreement":null},{"id":"W2762952664","doi":"10.1038/nbt.3986","title":"Scientists need data visualization training","year":2017,"lang":"en","type":"article","venue":"Nature Biotechnology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Children's Hospital","funders":"","keywords":"Visualization; Training (meteorology); Computer science; Data science; Artificial intelligence; Geography","score_opus":0.05820999418349452,"score_gpt":0.37713538346511677,"score_spread":0.31892538928162223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2762952664","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014581837,0.0001922043,0.97939974,0.014758848,0.0015184548,0.00010125957,0.000044054046,0.00065240473,0.0018748272],"genre_scores_gemma":[0.9740352,0.00006145578,0.024232551,0.0009694803,0.00009482051,0.0000012695824,0.00018402215,0.000010196235,0.0004110122],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99881357,0.000019964677,0.00015029895,0.00056676724,0.00021640086,0.00023299802],"domain_scores_gemma":[0.9963084,0.000016804157,0.00019174902,0.0033646186,0.00006953903,0.000048879105],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.00037027357,0.000102633465,0.00013127756,0.00023830637,0.00051402266,0.0005524546,0.0058107893,0.0005734751,0.00001174599],"category_scores_gemma":[0.0010126262,0.00009633182,0.00001910277,0.00035684026,0.00020291976,0.0009863108,0.0021309324,0.00033233804,0.000048687507],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.604341e-7,0.000021966307,0.00017497763,0.000004563257,0.0000090681115,0.000011769134,0.000047483318,9.2087396e-7,0.0016712646,0.9354253,0.008642087,0.053989857],"study_design_scores_gemma":[0.00054002064,0.00004723387,0.0018657742,0.00003388884,0.000012814183,0.000048351365,0.000058354613,0.34675494,0.010216864,0.0077345786,0.63234645,0.0003407228],"about_ca_topic_score_codex":0.000006449157,"about_ca_topic_score_gemma":0.000025775957,"teacher_disagreement_score":0.97257704,"about_ca_system_score_codex":0.000017479364,"about_ca_system_score_gemma":0.000076259304,"threshold_uncertainty_score":0.9995682},"labels":[],"label_agreement":null},{"id":"W2765974701","doi":"10.5703/1288284316433","title":"Collection Dashboards for Selectors","year":2017,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Purdue Pharma (Canada)","funders":"","keywords":"Computer science; Visualization; Visual analytics; Analytics; Data science; Parsing; Data visualization; Selection (genetic algorithm); Data collection; Cultural analytics; Information visualization; World Wide Web; Data mining; Artificial intelligence; The Internet; Semantic analytics","score_opus":0.03857931778285014,"score_gpt":0.3484079909692441,"score_spread":0.30982867318639395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2765974701","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00035361206,0.0000014286929,0.9840102,0.0008216362,0.00024864628,0.00005857201,0.0000017066678,0.00008215816,0.014422],"genre_scores_gemma":[0.83109957,0.000009824256,0.10881988,0.001147431,0.00015491572,0.00001801856,0.000016213504,0.000009258354,0.058724873],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996837,0.0000043548134,0.00005544108,0.00011375809,0.000065776425,0.000077011464],"domain_scores_gemma":[0.9994855,0.000012938661,0.000043305085,0.0003634115,0.00006497358,0.000029856701],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008673882,0.00003277948,0.000040987383,0.000029208673,0.00038213178,0.00042964134,0.0004954746,0.000016160451,0.000018210161],"category_scores_gemma":[0.00009433731,0.000028095767,0.000021805468,0.00005548933,0.000011680184,0.00038058189,0.00007417733,0.000012689592,0.00001932219],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021695523,0.00003402757,0.0014875849,0.0000071840864,0.000011704584,3.8402132e-7,0.00007804306,0.00001012151,0.00019023441,0.77220094,0.21126805,0.014709543],"study_design_scores_gemma":[0.00039279554,0.000060603437,0.0024458505,0.0000033687443,0.000004014535,0.0000015353754,0.0000073333254,0.75794184,0.008303724,0.0041210307,0.22659753,0.000120342294],"about_ca_topic_score_codex":0.000018304263,"about_ca_topic_score_gemma":0.000034374112,"teacher_disagreement_score":0.8751904,"about_ca_system_score_codex":0.000010633162,"about_ca_system_score_gemma":0.000033257867,"threshold_uncertainty_score":0.41430414},"labels":[],"label_agreement":null},{"id":"W2766861616","doi":"10.5687/sss.2017.160","title":"Consecutive Dimensionality Reduction by Canonical Correlation Analysis for Visualization of Convolutional Neural Networks","year":2017,"lang":"en","type":"article","venue":"Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Japan Society for the Promotion of Science; Canadian Institute for Advanced Research","keywords":"Dimensionality reduction; Visualization; Principal component analysis; Canonical correlation; Pattern recognition (psychology); Computer science; Artificial intelligence; Convolutional neural network; Linear subspace; Subspace topology; Benchmark (surveying); Feature (linguistics); Representation (politics); Artificial neural network; Curse of dimensionality; Data visualization; Feature extraction; Mathematics","score_opus":0.01589346132133927,"score_gpt":0.29849663071702803,"score_spread":0.28260316939568875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766861616","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014014634,0.00008364959,0.98317045,0.00085381215,0.00045551587,0.00071361806,0.0002208255,0.00002474351,0.00046275946],"genre_scores_gemma":[0.99917954,0.000011499494,0.000096638636,0.000035845,0.000087670174,0.00013779326,0.00007188329,0.0000067737146,0.00037235807],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99864614,0.00003218068,0.0004722027,0.00034536317,0.00038867776,0.0001154404],"domain_scores_gemma":[0.99733657,0.00032998392,0.0010348775,0.00023018332,0.0010099536,0.000058452144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008467348,0.00012550784,0.00021821438,0.00010435072,0.00056995975,0.00017917682,0.0008439567,0.0000747958,0.000003180561],"category_scores_gemma":[0.0003228896,0.00010103477,0.0001118956,0.00027146435,0.00023222127,0.0004352656,0.00020594429,0.00006758672,5.7957584e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051215862,0.00009218464,0.00044502315,0.00002014617,0.00018522628,5.839144e-9,0.00007749364,0.020380182,0.003605533,0.97485715,0.0002231529,0.000062681174],"study_design_scores_gemma":[0.00035695414,0.000050713028,0.0017118835,0.000057957073,0.00017697518,0.0000059585736,0.00009636861,0.9891334,0.0009274946,0.007092308,0.00026552836,0.00012443955],"about_ca_topic_score_codex":0.000017592827,"about_ca_topic_score_gemma":7.1388985e-7,"teacher_disagreement_score":0.9851649,"about_ca_system_score_codex":0.000054514316,"about_ca_system_score_gemma":0.0000344238,"threshold_uncertainty_score":0.43837273},"labels":[],"label_agreement":null},{"id":"W2767009796","doi":"10.1177/0308518x17739009","title":"Comparative visualizations of transport networks in Calgary using shortest-path trees","year":2017,"lang":"en","type":"article","venue":"Environment and Planning A Economy and Space","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Shortest path problem; Fractal; Transport network; Geography; Computer science; Economic geography; Path (computing); Cartography; Transport engineering; Theoretical computer science; Mathematics; Engineering; Computer network","score_opus":0.04092203028634588,"score_gpt":0.29276120925261384,"score_spread":0.25183917896626795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2767009796","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35249186,0.00047111232,0.6455378,0.00008370387,0.000028447352,0.00007634318,0.0000047334756,0.000008536741,0.001297488],"genre_scores_gemma":[0.9969086,0.00014117801,0.002798328,0.000036740028,0.000013540002,0.0000014165713,0.000013967479,0.0000024625501,0.00008377546],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995464,0.000017569353,0.00013636136,0.0001725913,0.00003371702,0.00009332809],"domain_scores_gemma":[0.999644,0.000028435865,0.000103742124,0.00017316993,0.000002969276,0.000047702633],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000113917886,0.00007755685,0.00015963468,0.000045791407,0.00016284855,0.00006870913,0.00013182685,0.000032403572,0.000006770726],"category_scores_gemma":[0.0000027897868,0.00007795559,0.000013166772,0.000022355456,0.00008605129,0.00034194926,0.00005855884,0.00004754705,3.9606644e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000051269444,0.00004873673,0.9402784,0.0000075654607,0.00001931263,0.000010558104,0.0029672545,0.039385244,0.000018438519,0.016731799,0.00005193647,0.00047564585],"study_design_scores_gemma":[0.00019780106,0.000022199383,0.18087922,0.00003763675,0.0000074778186,0.000002041509,0.00016600911,0.81714696,0.000029665427,0.0001241435,0.001293363,0.00009349019],"about_ca_topic_score_codex":0.000041034607,"about_ca_topic_score_gemma":0.000015562977,"teacher_disagreement_score":0.7777617,"about_ca_system_score_codex":0.000007135684,"about_ca_system_score_gemma":0.000008791423,"threshold_uncertainty_score":0.31789365},"labels":[],"label_agreement":null},{"id":"W2770071766","doi":"10.1109/icebe.2017.27","title":"A Development Framework for Customer Experience Management Applications: Principles and Case Study","year":2017,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Computer science; Purchasing; Personalization; Context (archaeology); Process (computing); Set (abstract data type); Customer relationship management; Product (mathematics); Process management; Knowledge management; Software engineering; World Wide Web; Database; Business; Marketing","score_opus":0.0973322769789561,"score_gpt":0.4013773802973709,"score_spread":0.30404510331841483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2770071766","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010269902,0.000007631463,0.9875844,0.00008811879,0.000033777524,0.0005988979,7.495491e-7,0.000052601747,0.001363891],"genre_scores_gemma":[0.44282106,0.00000795543,0.5556211,0.00015575103,0.000010767261,0.00033598926,9.0093454e-7,0.0000029550633,0.0010435325],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99937516,0.0000057485618,0.00013935298,0.00026798624,0.000108739485,0.000102983635],"domain_scores_gemma":[0.9991297,0.000022278899,0.000074568285,0.0006787424,0.000038150567,0.00005654464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000148445,0.00006557997,0.000063513944,0.000040109768,0.00062263035,0.0005441303,0.00055272464,0.000015149729,0.0000057261636],"category_scores_gemma":[0.00001864553,0.000055179305,0.000009158748,0.000054912052,0.000028827719,0.0002855733,0.0005449688,0.000020477042,0.000014111527],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.536251e-7,0.00015432716,0.0024117942,0.00001801636,0.000018357305,0.000045927136,0.0031138523,0.0000023119972,7.1111833e-7,0.91926885,0.000072327,0.0748929],"study_design_scores_gemma":[0.0011349634,0.00007179715,0.009530024,0.00004776939,0.0000308387,0.00015695348,0.025041131,0.060642272,0.0002975065,0.0045183958,0.8978635,0.00066485576],"about_ca_topic_score_codex":0.000007406756,"about_ca_topic_score_gemma":0.000027841274,"teacher_disagreement_score":0.9147504,"about_ca_system_score_codex":0.000010855222,"about_ca_system_score_gemma":0.000016983688,"threshold_uncertainty_score":0.5247061},"labels":[],"label_agreement":null},{"id":"W2771392591","doi":"10.1109/iemcon.2017.8117201","title":"Marble MLFQ: An educational visualization tool for the multilevel feedback queue algorithm","year":2017,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MacEwan University","funders":"","keywords":"Computer science; Visualization; Algorithm; Queue; Key (lock); Scheduling (production processes); Priority queue; Data visualization; Data mining","score_opus":0.046765632528482426,"score_gpt":0.37389851427985105,"score_spread":0.3271328817513686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2771392591","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00017357296,0.000009847005,0.99481696,0.0030182754,0.00050602166,0.00023338522,0.000027901791,0.00006285577,0.0011511518],"genre_scores_gemma":[0.20277359,0.00009334639,0.72269773,0.008188757,0.0015443566,0.00020554532,0.00067313213,0.00005875653,0.06376478],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99912786,0.00002743297,0.00018266137,0.00028218466,0.0002109595,0.00016890198],"domain_scores_gemma":[0.99844766,0.00013661788,0.00014008234,0.000965273,0.0002478744,0.00006250383],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00034550257,0.00009975701,0.000082338665,0.00004122388,0.0008699111,0.0012238735,0.0014467369,0.000045577857,0.00014317711],"category_scores_gemma":[0.00023048808,0.00007104312,0.000043826396,0.00006915194,0.00005581391,0.001394313,0.00020070739,0.00003854336,0.00006732574],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000025080933,0.00020541556,0.0006284578,0.000011350969,0.000023639941,2.393643e-7,0.00026581637,0.00016184551,0.00006475557,0.75830394,0.042554904,0.1977771],"study_design_scores_gemma":[0.00028379392,0.00002470333,0.010071645,0.000005673525,0.0000070981237,0.0000019656363,0.00003042033,0.95093703,0.00041270652,0.0041767475,0.033918243,0.00012994143],"about_ca_topic_score_codex":0.00008979364,"about_ca_topic_score_gemma":0.000027840142,"teacher_disagreement_score":0.9507752,"about_ca_system_score_codex":0.000022362345,"about_ca_system_score_gemma":0.00014644224,"threshold_uncertainty_score":0.99981296},"labels":[],"label_agreement":null},{"id":"W2775729303","doi":"","title":"Toward graph layout of large data visualization: algorithms, evaluations and application","year":2016,"lang":"en","type":"dissertation","venue":"e-scholar@UOIT (University of Ontario Institute of Technology)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Ontario Institute of Technology","keywords":"Graph Layout; Computer science; Graph drawing; Visualization; Graph; Data mining; Algorithm; Theoretical computer science; Information retrieval","score_opus":0.031084207485633814,"score_gpt":0.30488129131361263,"score_spread":0.27379708382797885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2775729303","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.26818416,0.00071841537,0.72377604,0.0005855322,0.0007681439,0.00089661643,0.0015064979,0.00028957298,0.003275047],"genre_scores_gemma":[0.067110516,0.0014024639,0.9079743,0.000073379786,0.000050147028,0.000005208804,0.016493836,0.00005153609,0.0068386095],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99818486,0.0000122959245,0.00042825338,0.0006866344,0.0004894699,0.00019845944],"domain_scores_gemma":[0.9967257,0.0000036017216,0.0009118474,0.0015704015,0.00071709196,0.000071401075],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005659765,0.0002358448,0.0005142029,0.0009380775,0.0003258878,0.000032724878,0.0027029598,0.0005014724,0.000074742726],"category_scores_gemma":[0.00012392948,0.00027151816,0.000086852255,0.0011458647,0.00018794197,0.0020447462,0.0008305919,0.00036515814,0.0000124389635],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009177887,0.0010983336,0.0015056372,0.0009994364,0.00093392207,0.00002729578,0.007736557,0.000034062723,0.00336723,0.50447786,0.004440841,0.47528705],"study_design_scores_gemma":[0.0015649939,0.00014541316,0.00500566,0.00043677734,0.00036416794,0.000008146284,0.00094222656,0.0056887483,0.0015953083,0.005006439,0.9787585,0.00048358756],"about_ca_topic_score_codex":0.0016847723,"about_ca_topic_score_gemma":0.012892603,"teacher_disagreement_score":0.97431767,"about_ca_system_score_codex":0.00013817161,"about_ca_system_score_gemma":0.0009592854,"threshold_uncertainty_score":0.9999737},"labels":[],"label_agreement":null},{"id":"W2777463893","doi":"10.3138/cart.52.4.2017-0009","title":"A Simulation and Visualization Environment for Spatiotemporal Disaster Risk Assessments of Network Infrastructures","year":2017,"lang":"en","type":"article","venue":"Cartographica The International Journal for Geographic Information and Geovisualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Eidgenössische Technische Hochschule Zürich; European Commission; University of Virginia; TU Graz, Internationale Beziehungen und Mobilitätsprogramme","keywords":"Computer science; Visualization; Component (thermodynamics); Software; Process (computing); Aggregate (composite); Hazard; Simulation modeling; Data mining; Traffic simulation; Dependency (UML); Distributed computing; Software engineering; Microsimulation; Transport engineering; Engineering","score_opus":0.01703650206753511,"score_gpt":0.3379370002310219,"score_spread":0.3209004981634868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2777463893","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02413229,0.000074867305,0.9738395,0.000513251,0.0007452129,0.0005101904,0.00012621986,0.00002470535,0.000033735836],"genre_scores_gemma":[0.9900768,0.0008881305,0.007913098,0.0004593556,0.00020157018,0.00003597741,0.00039669315,0.000010957114,0.000017433214],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983967,0.00007032018,0.0006832527,0.00017591595,0.0004882371,0.00018555248],"domain_scores_gemma":[0.99705714,0.0002387068,0.0015499018,0.0003167386,0.00075059343,0.0000868919],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0011008228,0.00017056506,0.0001779863,0.00036433293,0.0012603312,0.0014863646,0.0006855897,0.000095601,0.0000064828746],"category_scores_gemma":[0.00046026977,0.0001333832,0.0001296736,0.000136938,0.00018632322,0.0026263378,0.00020791261,0.00009618997,3.6656104e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003207951,0.00011037985,0.17770314,0.00015546734,0.0006950921,5.3715536e-7,0.0030811965,0.098490134,0.00003611039,0.5549385,0.0018256144,0.16264303],"study_design_scores_gemma":[0.0014112754,0.00018593286,0.050712157,0.0000538679,0.0000767248,0.000009186742,0.00016274131,0.8773671,0.00002925924,0.028401403,0.04140364,0.00018671628],"about_ca_topic_score_codex":0.000030936782,"about_ca_topic_score_gemma":0.00001687504,"teacher_disagreement_score":0.96594447,"about_ca_system_score_codex":0.000016714928,"about_ca_system_score_gemma":0.000040585914,"threshold_uncertainty_score":0.99955016},"labels":[],"label_agreement":null},{"id":"W2778189778","doi":"10.3138/cart.52.4.2016-0007","title":"An Automated Displaced Proportional Circle Map Using Delaunay Triangulation and an Algorithm for Node Overlap Removal","year":2017,"lang":"en","type":"article","venue":"Cartographica The International Journal for Geographic Information and Geovisualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Algorithm; Symbol (formal); Triangulation; Delaunay triangulation; Computer science; Clutter; Node (physics); Range (aeronautics); Graph; Mathematics; Artificial intelligence; Computer vision; Theoretical computer science; Geometry","score_opus":0.0206625794554279,"score_gpt":0.3624912697424894,"score_spread":0.34182869028706153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2778189778","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.053407155,0.000049983493,0.9433886,0.0011029658,0.0011682514,0.00055906427,0.00016082045,0.00014880583,0.000014392441],"genre_scores_gemma":[0.9193033,0.0002887295,0.07482818,0.002003187,0.00078651204,0.000076513876,0.002639073,0.000035659792,0.000038857677],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981231,0.00008082866,0.00068532414,0.00025902718,0.00060300896,0.0002487288],"domain_scores_gemma":[0.9968854,0.000070176255,0.0009706432,0.0004056757,0.0014750046,0.00019306871],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0014566246,0.00019604147,0.00018108373,0.00061909156,0.0023580894,0.003700386,0.0009029029,0.00012895728,0.000004589729],"category_scores_gemma":[0.00020856327,0.00016800669,0.00013330749,0.00020264836,0.00018028932,0.0069916192,0.00011550059,0.00011818017,6.596552e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005453589,0.00054649636,0.025016718,0.00019027597,0.0008769055,0.000011431787,0.004533954,0.0074424837,0.0018246156,0.4756448,0.00243197,0.480935],"study_design_scores_gemma":[0.0018621563,0.00015850592,0.012787629,0.00004167293,0.000055045988,0.00017511554,0.00025077246,0.96812725,0.000060606857,0.007041527,0.009207597,0.00023214177],"about_ca_topic_score_codex":0.000044830173,"about_ca_topic_score_gemma":0.000022616776,"teacher_disagreement_score":0.9606847,"about_ca_system_score_codex":0.000032682765,"about_ca_system_score_gemma":0.00011211347,"threshold_uncertainty_score":0.9989407},"labels":[],"label_agreement":null},{"id":"W27822636","doi":"10.1007/s10787-016-0295-y","title":"Toward Distributed, Pluggable Tools and Data: Re-Engineering a Data Analysis Architecture","year":2003,"lang":"en","type":"article","venue":"Inflammopharmacology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Architecture; Computer science; Visualization; Plug-in; Software engineering; Data visualization; Data architecture; Data science; Computer architecture; Reference architecture; Software architecture; Data mining; Programming language; Software","score_opus":0.07907290474975917,"score_gpt":0.34773427118764433,"score_spread":0.2686613664378852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W27822636","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0025551405,0.0003205344,0.9941195,0.0009821742,0.00027199966,0.000118131196,0.001202809,0.00015526108,0.00027442808],"genre_scores_gemma":[0.85170835,0.00072879647,0.13258685,0.0033791612,0.00034271117,0.000027221386,0.010797058,0.00004670659,0.00038311986],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983377,0.00010919806,0.00029452165,0.00075293117,0.00017283902,0.0003328019],"domain_scores_gemma":[0.99775785,0.00019842366,0.0000933157,0.0017427026,0.000047872516,0.00015985698],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058020954,0.00016539516,0.00028301933,0.00022850458,0.00008459351,0.000288914,0.002339353,0.00007531201,0.000105884],"category_scores_gemma":[0.00038496588,0.00015891423,0.000029282905,0.0012029925,0.000048713828,0.0010220635,0.0017702442,0.0001981954,0.00001967116],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000106168896,0.00088511704,0.02305703,0.00063462823,0.010951946,0.0022587,0.0022749074,0.2414675,0.017066699,0.34821218,0.27987874,0.07320637],"study_design_scores_gemma":[0.0004923157,0.00001878366,0.00056783616,0.000003945441,0.0003084143,0.000029598492,0.000016372993,0.58956754,0.00042036435,0.0002168697,0.4081213,0.00023664327],"about_ca_topic_score_codex":0.0000107489195,"about_ca_topic_score_gemma":0.000020661875,"teacher_disagreement_score":0.8615327,"about_ca_system_score_codex":0.000020934422,"about_ca_system_score_gemma":0.00008722483,"threshold_uncertainty_score":0.64803344},"labels":[],"label_agreement":null},{"id":"W2782619198","doi":"10.1109/bigdata.2017.8257934","title":"Sanzu: A data science benchmark","year":2017,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Benchmark (surveying); Scalability; Python (programming language); Analytics; Data analysis; Data mining; Macro; Big data; Data modeling; Data science; Machine learning; Database; Operating system","score_opus":0.10436912515128377,"score_gpt":0.3999943821222473,"score_spread":0.29562525697096353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2782619198","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00036164265,0.0000080159925,0.81641656,0.0019165366,0.00032126028,0.000034521865,0.000010007917,0.0000878923,0.18084358],"genre_scores_gemma":[0.91195077,0.000025834092,0.08310133,0.0013708395,0.00006962125,6.200432e-7,0.000022811937,0.0000032797018,0.0034548743],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99909514,0.000005668012,0.000083219784,0.00036985517,0.00028857784,0.00015754387],"domain_scores_gemma":[0.99556845,0.00001090384,0.00006332749,0.0042010113,0.000065002496,0.00009128742],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0005351331,0.000046374076,0.000050667368,0.000055667424,0.00070379797,0.0017990088,0.00956354,0.00001080906,0.0000856597],"category_scores_gemma":[0.00034602016,0.00003720001,0.000008201369,0.00016185356,0.00022501442,0.0046418128,0.0040145614,0.000029841922,0.0001700004],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.7562499e-7,0.000023377528,0.0013821479,0.0000018791926,0.000001994149,0.0000038973685,0.000034860914,0.000001152749,0.00022181842,0.9473734,0.026081078,0.024874214],"study_design_scores_gemma":[0.0001438352,0.000012934118,0.012248941,0.0000081323415,0.0000024537837,0.0000055045284,0.000012601272,0.8313968,0.00090022397,0.0026214311,0.15249354,0.00015359416],"about_ca_topic_score_codex":0.000038299113,"about_ca_topic_score_gemma":0.000017506523,"teacher_disagreement_score":0.944752,"about_ca_system_score_codex":0.000008036112,"about_ca_system_score_gemma":0.0001452743,"threshold_uncertainty_score":0.99923724},"labels":[],"label_agreement":null},{"id":"W2784053634","doi":"10.1145/3164135.3164139","title":"The ubiquity of large graphs and surprising challenges of graph processing","year":2017,"lang":"en","type":"article","venue":"Very Large Data Bases","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":89,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Scalability; Suite; Visualization; Graph; Software; Data science; Call graph; Theoretical computer science; Data visualization; World Wide Web; Data mining; Programming language; Database","score_opus":0.07621659304314052,"score_gpt":0.3534706649777041,"score_spread":0.27725407193456353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2784053634","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2537188,0.048319705,0.67204505,0.0054887873,0.0013630303,0.0007840008,0.013436444,0.00041230163,0.0044318503],"genre_scores_gemma":[0.99487394,0.0035939212,0.0013294574,0.00006610494,0.000012926151,7.379763e-7,0.000102024074,0.0000053030108,0.000015601969],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990513,0.00005607149,0.00021307534,0.00027255152,0.00022292031,0.00018408409],"domain_scores_gemma":[0.9975839,0.000117934695,0.00031152315,0.0018458297,0.00009834743,0.000042425287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010264072,0.00008507412,0.00015458986,0.00006346419,0.0005536725,0.00026103063,0.0019219457,0.000028210092,0.000002364511],"category_scores_gemma":[0.0004061649,0.000061199324,0.00002436123,0.00010918739,0.00014519772,0.0014641768,0.0016810506,0.000051778767,7.2926764e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018878449,0.00050898606,0.022020098,0.00062996754,0.00008771861,0.000013284654,0.0007096767,0.0000013817317,0.00040709187,0.88142884,0.008356789,0.08581729],"study_design_scores_gemma":[0.0047268854,0.00043259567,0.21684611,0.0023029295,0.00031199338,0.000046650428,0.0035909954,0.3251469,0.023823658,0.051754765,0.3691863,0.0018301924],"about_ca_topic_score_codex":0.000032364846,"about_ca_topic_score_gemma":0.00023764804,"teacher_disagreement_score":0.82967407,"about_ca_system_score_codex":0.00000203011,"about_ca_system_score_gemma":0.00005023013,"threshold_uncertainty_score":0.42584568},"labels":[],"label_agreement":null},{"id":"W2788091414","doi":"10.20382/jocg.v9i1a2","title":"Scalable exact visualization of isocontours in road networks via minimum-link paths","year":2016,"lang":"en","type":"article","venue":"Journal of Computational Geometry (Carleton University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Deutsche Forschungsgemeinschaft","keywords":"Heuristics; Scalability; Simple (philosophy); Time complexity; Computer science; Key (lock); Link (geometry); Mathematical optimization; Limit (mathematics); Linear programming; Mathematics; Algorithm; Computer network","score_opus":0.01160676713131791,"score_gpt":0.24497944753088502,"score_spread":0.2333726803995671,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2788091414","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.046069257,0.000061178216,0.95258266,0.00045704446,0.00023346306,0.00005959947,0.0000060006987,0.000016231032,0.0005145403],"genre_scores_gemma":[0.9930031,0.00010298865,0.006220756,0.0001316241,0.000095885225,5.729885e-8,0.000008900752,0.000008379756,0.00042835457],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983925,0.0001569227,0.0005451152,0.0001896815,0.0005229713,0.00019277474],"domain_scores_gemma":[0.9979921,0.00027402418,0.00073229853,0.00016594042,0.00070176006,0.00013387844],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004821947,0.00012997369,0.000305266,0.0014769001,0.00005435708,0.00004848708,0.0007062323,0.00009034704,0.000056119243],"category_scores_gemma":[0.00009667941,0.000112435155,0.00013457949,0.0021543745,0.000067779714,0.0012428103,0.0001367761,0.00010209191,0.0000059763033],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024275288,0.0009236686,0.052964218,0.00007754975,0.00033151684,0.00037466397,0.0006184384,0.5627428,0.0013311044,0.1653641,0.0036397665,0.21138938],"study_design_scores_gemma":[0.00569216,0.0006734048,0.06869555,0.00050752435,0.00006929941,0.00009016405,0.0002313604,0.9050743,0.00057623285,0.0064982143,0.0113347145,0.00055706437],"about_ca_topic_score_codex":0.0000138178275,"about_ca_topic_score_gemma":0.000005034318,"teacher_disagreement_score":0.9469338,"about_ca_system_score_codex":0.00015993736,"about_ca_system_score_gemma":0.00021077359,"threshold_uncertainty_score":0.45849726},"labels":[],"label_agreement":null},{"id":"W2789341774","doi":"10.3390/mti2010010","title":"Discourse with Visual Health Data: Design of Human-Data Interaction","year":2018,"lang":"en","type":"article","venue":"Multimodal Technologies and Interaction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; University of British Columbia","funders":"","keywords":"Computer science; Sensemaking; Visualization; Data science; Human–computer interaction; Data visualization; Process (computing); Task (project management); Artificial intelligence","score_opus":0.13222533292295222,"score_gpt":0.4360434490359025,"score_spread":0.3038181161129503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2789341774","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013497004,0.00004450199,0.98417985,0.0014151856,0.0002249402,0.00016275024,0.00003608807,0.00037263418,0.000067065535],"genre_scores_gemma":[0.9605055,0.00016615857,0.038965736,0.00007364502,0.00004194865,0.0000031550537,0.00020379879,0.000007737456,0.000032352564],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988733,0.000048391135,0.00027102456,0.0004910487,0.00015542832,0.000160815],"domain_scores_gemma":[0.99833786,0.000051406292,0.0002845165,0.0011973467,0.000099627745,0.000029234861],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030253595,0.00012193735,0.00017230997,0.00018744457,0.00016777318,0.00014603135,0.0011457641,0.00006178053,0.000008277917],"category_scores_gemma":[0.00011883255,0.000093131974,0.000009479605,0.00028612217,0.00021383127,0.0024897004,0.0012765934,0.00015334367,0.000007626225],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008080072,0.00039160298,0.0007140635,0.000052700023,0.00007460903,0.0000031308239,0.0004555583,0.0000657366,0.0032534245,0.007234125,0.008788182,0.97888607],"study_design_scores_gemma":[0.00032894942,0.0011618631,0.00039925033,0.00012949898,0.000010447768,0.000021324126,0.0035204198,0.9851886,0.0048411125,0.00020915076,0.004032991,0.00015638293],"about_ca_topic_score_codex":0.0002559275,"about_ca_topic_score_gemma":0.00010588007,"teacher_disagreement_score":0.98512286,"about_ca_system_score_codex":0.000034654062,"about_ca_system_score_gemma":0.00003949602,"threshold_uncertainty_score":0.37978116},"labels":[],"label_agreement":null},{"id":"W2789987714","doi":"10.5220/0006608500740084","title":"A Visual Analytics Framework for Exploring Uncertainties in Reservoir Models","year":2018,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Visual analytics; Computer science; Analytics; Data science; Interactive visual analysis; Visualization; Data mining","score_opus":0.17188750366264696,"score_gpt":0.3784767957541406,"score_spread":0.20658929209149365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2789987714","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005698148,0.000012091585,0.99187917,0.00071659463,0.0001972309,0.00009482719,0.000002709716,0.00011258821,0.0012866625],"genre_scores_gemma":[0.6836496,0.000037369216,0.3141742,0.0009907506,0.00018830507,0.000028379183,0.000007956556,0.000011912865,0.0009115088],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990154,0.00002250085,0.00023141695,0.0002819331,0.0001901058,0.00025863497],"domain_scores_gemma":[0.99922675,0.00013400876,0.00004502753,0.00036896937,0.00015933672,0.00006591806],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028968352,0.00009559723,0.00013210923,0.00019826874,0.000084451036,0.00020479428,0.000608195,0.000049338105,0.000019667512],"category_scores_gemma":[0.00017349658,0.00008583899,0.000041601113,0.00073202903,0.00004972443,0.0009774767,0.00023541253,0.000065705724,0.000022090475],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000048390643,0.000038954557,0.00018609651,0.000009437626,0.000006680516,0.0000010161207,0.00058700884,0.0023181974,0.000005538261,0.99366033,0.0012367674,0.0019451135],"study_design_scores_gemma":[0.000120270815,0.00007301086,0.000028314678,0.000028242917,0.0000020383982,3.447754e-7,0.00021404964,0.8057229,0.00039026418,0.18971314,0.003603661,0.00010379523],"about_ca_topic_score_codex":0.00003569725,"about_ca_topic_score_gemma":0.000108275985,"teacher_disagreement_score":0.8039472,"about_ca_system_score_codex":0.00004103282,"about_ca_system_score_gemma":0.000053896365,"threshold_uncertainty_score":0.35004127},"labels":[],"label_agreement":null},{"id":"W2791982474","doi":"10.1145/3023363","title":"Visual Analysis of Brain Networks Using Sparse Regression Models","year":2018,"lang":"en","type":"article","venue":"ACM Transactions on Knowledge Discovery from Data","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Army Research Office; National Institute of Biomedical Imaging and Bioengineering; DoD Alzheimer's Disease Neuroimaging Initiative; Defense Threat Reduction Agency; Canadian Institutes of Health Research; National Institute on Aging; National Institutes of Health; National Natural Science Foundation of China","keywords":"Visual analytics; Computer science; Discriminative model; Visualization; Artificial intelligence; Machine learning; Intersection (aeronautics); Human–computer interaction","score_opus":0.09753420314028476,"score_gpt":0.3740269390566549,"score_spread":0.27649273591637014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2791982474","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008855609,0.00011062921,0.9886715,0.00012009346,0.0004394872,0.00008018603,0.0015179015,0.00006838386,0.00013620181],"genre_scores_gemma":[0.97287726,0.000077811914,0.024459181,0.00024737572,0.00012531421,0.0000021543437,0.0018889793,0.000019090927,0.00030285443],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981413,0.00014910904,0.0004342823,0.00075222383,0.00028076064,0.00024232024],"domain_scores_gemma":[0.9958083,0.00030555605,0.00017780834,0.0034560263,0.00014746911,0.000104848725],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003019046,0.00020729545,0.00037042462,0.000506204,0.00022882449,0.00024052431,0.0028151916,0.00010216711,0.0001002847],"category_scores_gemma":[0.000057998517,0.0001841209,0.00014322123,0.0025330302,0.0001438186,0.003128313,0.00027933737,0.000142958,0.00002453889],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041949228,0.0082348585,0.001585734,0.00009120104,0.009920169,0.00003076947,0.0057102256,0.6115114,0.005851765,0.023799654,0.02646744,0.3063773],"study_design_scores_gemma":[0.00024719926,0.000056512406,0.00016949244,0.00007731325,0.00052897795,5.8022107e-7,0.000060382303,0.9961469,0.0010608804,0.0006744854,0.0007730899,0.00020418226],"about_ca_topic_score_codex":0.00019510605,"about_ca_topic_score_gemma":0.00048404944,"teacher_disagreement_score":0.9642123,"about_ca_system_score_codex":0.000041993088,"about_ca_system_score_gemma":0.00012162289,"threshold_uncertainty_score":0.75082326},"labels":[],"label_agreement":null},{"id":"W2792276653","doi":"10.1145/3172944.3173009","title":"User-adaptive Support for Processing Magazine Style Narrative Visualizations","year":2018,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Narrative; Set (abstract data type); Style (visual arts); Human–computer interaction; Perception; Process (computing); Exploratory research; Visualization; Multimedia; World Wide Web; Psychology; Artificial intelligence; Linguistics","score_opus":0.03765238327560105,"score_gpt":0.35180836792558823,"score_spread":0.3141559846499872,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2792276653","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00010640831,0.0000042095817,0.9859269,0.00043591822,0.000117931915,0.0001900991,0.000016124632,0.00020850306,0.012993852],"genre_scores_gemma":[0.5079579,0.000006106068,0.4194324,0.004937477,0.00039141052,0.000058075035,0.00019266784,0.000036088215,0.06698792],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907684,0.000023217535,0.00020940336,0.00030864435,0.00017374456,0.00020812057],"domain_scores_gemma":[0.9989509,0.00003178067,0.000092803966,0.00025372274,0.00058613584,0.000084643005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001670179,0.00010837371,0.000115338036,0.00010271601,0.00031434998,0.0002638452,0.00043593516,0.00003633416,0.00024101856],"category_scores_gemma":[0.00006957905,0.00009382905,0.00003515462,0.0005914153,0.00008397404,0.000910483,0.00013128044,0.00002926511,0.00015559538],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000890363,0.00016759612,0.000115733776,0.000018748675,0.00002362396,0.0000013306881,0.006730741,0.000016384021,0.00037672662,0.8653989,0.118494175,0.008647128],"study_design_scores_gemma":[0.00044501488,0.00044045987,0.00013982049,0.000016864982,0.0000108796075,0.000004262766,0.0008398325,0.8033725,0.0029551506,0.0021250392,0.18940566,0.0002445215],"about_ca_topic_score_codex":0.0000024071085,"about_ca_topic_score_gemma":0.00003527871,"teacher_disagreement_score":0.86327386,"about_ca_system_score_codex":0.000022825252,"about_ca_system_score_gemma":0.00015612817,"threshold_uncertainty_score":0.38262376},"labels":[],"label_agreement":null},{"id":"W2792584195","doi":"10.1145/3181669","title":"A Visual Approach for Interactive Keyterm-Based Clustering","year":2018,"lang":"en","type":"article","venue":"ACM Transactions on Interactive Intelligent Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cluster analysis; Computer science; Document clustering; Brown clustering; Flexibility (engineering); Correlation clustering; Task (project management); Relevance (law); Artificial intelligence; Information retrieval; Data mining; Canopy clustering algorithm; Mathematics","score_opus":0.04634535915117807,"score_gpt":0.3484522478146524,"score_spread":0.30210688866347435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2792584195","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00040815515,0.0000135679,0.99434435,0.0001984636,0.002418416,0.0008706636,0.00008239361,0.00028184007,0.0013821357],"genre_scores_gemma":[0.9642499,0.0000063168773,0.03325575,0.0006078339,0.00027254058,0.0003843672,0.000058601927,0.000045318757,0.0011193828],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975549,0.00018941228,0.00063520775,0.0008134256,0.00037767607,0.0004293946],"domain_scores_gemma":[0.9973707,0.00053213944,0.00029575123,0.0009982958,0.0006273015,0.00017576262],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00033513427,0.00036203588,0.00037452366,0.00055847765,0.0003696276,0.00053860963,0.0013604311,0.00011889247,0.00009171301],"category_scores_gemma":[0.00014529128,0.00033842408,0.0002638887,0.00054257084,0.0001122767,0.00096812996,0.00004639977,0.00028525802,0.00021941644],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.007126497,0.021149635,0.00043674387,0.0022037732,0.0047671287,0.000074892436,0.040799595,0.28847146,0.01737053,0.030603895,0.014765723,0.57223016],"study_design_scores_gemma":[0.00048025642,0.00090047513,0.000011570508,0.00020732354,0.00003545565,0.000022751825,0.0011776964,0.9536832,0.029613754,0.00009916813,0.0133877555,0.00038059513],"about_ca_topic_score_codex":0.00008757638,"about_ca_topic_score_gemma":0.000022345213,"teacher_disagreement_score":0.96384174,"about_ca_system_score_codex":0.0003249947,"about_ca_system_score_gemma":0.00009562256,"threshold_uncertainty_score":0.9999068},"labels":[],"label_agreement":null},{"id":"W2793633690","doi":"10.1109/tvcg.2018.2802520","title":"Exploration Strategies for Discovery of Interactivity in Visualizations","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft; Alberta Innovates; Alberta Innovates - Technology Futures","keywords":"Interactivity; Computer science; Visualization; Discoverability; Human–computer interaction; Data visualization; Data science; Set (abstract data type); Interactive visualization; Process (computing); Visual analytics; World Wide Web; Multimedia; Information visualization; Data mining","score_opus":0.0402462888941082,"score_gpt":0.33333501681195365,"score_spread":0.29308872791784546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2793633690","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0062154373,0.0000072422017,0.99281263,0.000054308424,0.0004732629,0.0002688046,0.000030989177,0.0000930773,0.000044269163],"genre_scores_gemma":[0.99673,0.000091520924,0.0025405257,0.00047151357,0.000051345483,0.000032612777,0.00002920122,0.000014598205,0.000038635135],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99874705,0.00010553634,0.0004209391,0.00036052946,0.00020375517,0.00016221788],"domain_scores_gemma":[0.9990789,0.00014406702,0.00015651008,0.00027982017,0.0002890418,0.00005163287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022402094,0.00016315059,0.00020376872,0.0006158546,0.00017912066,0.0003203464,0.00024054709,0.00008227662,0.000004288626],"category_scores_gemma":[0.0000071477707,0.00016800562,0.00006868785,0.0011475163,0.0001321132,0.002515804,0.0000070175506,0.00007354103,0.0000018268119],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022629469,0.0003557868,0.00005370268,0.000043848027,0.000021089632,3.115513e-7,0.0016658433,0.0007553044,0.000086620865,0.9938128,0.00011040632,0.0030716716],"study_design_scores_gemma":[0.00056842517,0.0004240414,0.00015623886,0.00006436901,0.000013006088,0.0000019758513,0.00019573899,0.98488015,0.0053149993,0.0077161924,0.00048148743,0.00018334705],"about_ca_topic_score_codex":0.000021213773,"about_ca_topic_score_gemma":0.00018914288,"teacher_disagreement_score":0.99051464,"about_ca_system_score_codex":0.000019327506,"about_ca_system_score_gemma":0.00007512045,"threshold_uncertainty_score":0.685107},"labels":[],"label_agreement":null},{"id":"W2793816856","doi":"10.1177/1473871618757228","title":"Interactive topic hierarchy revision for exploring a collection of online conversations","year":2018,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Hierarchy; Visual analytics; Asynchronous communication; Analytics; Human–computer interaction; Human-in-the-loop; Data science; Social media; World Wide Web; Visualization; Artificial intelligence","score_opus":0.057960693845268946,"score_gpt":0.35421439275583905,"score_spread":0.2962536989105701,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2793816856","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00688346,0.0000037410032,0.99149597,0.00027601985,0.00046534877,0.0003216872,0.000032919997,0.0001148882,0.00040596828],"genre_scores_gemma":[0.96431154,0.000085581916,0.033028487,0.0008897196,0.00018402604,0.000045927987,0.0012669994,0.0000103705,0.0001773722],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990093,0.000042437554,0.0004999576,0.00011683963,0.00022151701,0.00010996445],"domain_scores_gemma":[0.9982849,0.00007963377,0.00034904722,0.00021840444,0.0010263537,0.00004167711],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002262122,0.00008729853,0.00011961948,0.0004152286,0.00016762604,0.000117493255,0.00022446619,0.000043571465,0.000028801558],"category_scores_gemma":[0.0003926322,0.00008935478,0.000045382112,0.00090287905,0.00003869797,0.0047251806,0.00007002933,0.000033105185,0.000024374856],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000074023235,0.00023320797,0.00092401286,0.00025688694,0.000060482784,1.1080533e-7,0.025808388,0.00045651922,0.00053206366,0.85785705,0.01055721,0.10324006],"study_design_scores_gemma":[0.00069748075,0.00029590694,0.0010630174,0.00008654477,0.000012639486,0.0000016917403,0.000634888,0.9019576,0.0091870995,0.0010701361,0.084851876,0.0001411482],"about_ca_topic_score_codex":0.000012697459,"about_ca_topic_score_gemma":0.000007606652,"teacher_disagreement_score":0.9584675,"about_ca_system_score_codex":0.00007092704,"about_ca_system_score_gemma":0.00008632553,"threshold_uncertainty_score":0.36437818},"labels":[],"label_agreement":null},{"id":"W2794729851","doi":"10.1016/j.infsof.2018.03.001","title":"Special section on Visual Analytics in Software Engineering","year":2018,"lang":"en","type":"article","venue":"Information and Software Technology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Visualization; Visual analytics; Process (computing); Context (archaeology); Data science; Information visualization; Data visualization; Human–computer interaction; Analytics; Creative visualization; Data mining","score_opus":0.008342315570618404,"score_gpt":0.2514719885727999,"score_spread":0.2431296730021815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2794729851","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027379235,0.000004677805,0.97022116,0.0003620265,0.00085132197,0.000085356834,0.0000045743586,0.00074585935,0.00034576873],"genre_scores_gemma":[0.87371844,0.00010175529,0.11945385,0.0038000802,0.0025238711,0.00002650911,0.00013215283,0.000025383813,0.00021794371],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99931407,0.0000070721203,0.00026033272,0.00012198361,0.00013246949,0.00016409022],"domain_scores_gemma":[0.9995636,0.00003104441,0.00007594093,0.0001921594,0.00009938074,0.000037901373],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000119798366,0.000096051226,0.00010751018,0.0008801434,0.00007432722,0.00011408132,0.00023227367,0.00014888594,0.000021670494],"category_scores_gemma":[0.00046001305,0.00009718,0.000015473328,0.0009283386,0.000055818327,0.0009033307,0.00013094246,0.000142034,0.000096546166],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021568687,0.00011609416,0.041713994,0.00006920615,0.000027185528,0.000010244783,0.0015770448,0.0008955877,0.000017884837,0.29141527,0.013815824,0.6503201],"study_design_scores_gemma":[0.0015903276,0.0008521109,0.023239426,0.00011533085,0.000009406675,0.00007328741,0.00025245076,0.41761395,0.0013302083,0.0030122797,0.5512151,0.0006960828],"about_ca_topic_score_codex":0.0000039299243,"about_ca_topic_score_gemma":0.00002029646,"teacher_disagreement_score":0.8507673,"about_ca_system_score_codex":0.00004896263,"about_ca_system_score_gemma":0.00003190463,"threshold_uncertainty_score":0.39628854},"labels":[],"label_agreement":null},{"id":"W2795392050","doi":"10.1145/3173574.3173996","title":"More Text Please! Understanding and Supporting the Use of Visualization for Clinical Text Overview","year":2018,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":54,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"","keywords":"Visualization; Computer science; Process (computing); Data visualization; Field (mathematics); Data science; Clinical Practice; Information visualization; Information retrieval; Medicine; Data mining","score_opus":0.4092592397933965,"score_gpt":0.47921599052909236,"score_spread":0.06995675073569585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795392050","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011023844,0.000040683506,0.99763954,0.0007288821,0.00009798684,0.00014991831,0.00000840629,0.000038880673,0.00019334699],"genre_scores_gemma":[0.9448037,0.0007069732,0.04477973,0.008106926,0.0002384596,0.0000062179106,0.00005550502,0.000023785902,0.0012786619],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99906063,0.00005935362,0.00039853153,0.00020516047,0.00014783883,0.00012850293],"domain_scores_gemma":[0.9989502,0.0003917867,0.00019839179,0.00028218224,0.00012509494,0.0000523311],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006268504,0.000068417256,0.0001260584,0.00004445718,0.00014681184,0.00018987012,0.00024631587,0.00003656833,0.000038366747],"category_scores_gemma":[0.00045783634,0.00004537325,0.000045936195,0.00027576706,0.00014880985,0.0004555167,0.00017255667,0.000027848791,0.0000034189604],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004103005,0.000038289832,0.0036804248,0.000035112495,0.000017243461,2.228952e-7,0.00037030783,0.000006384746,0.000012446166,0.96794003,0.017980993,0.009914412],"study_design_scores_gemma":[0.00031283524,0.0001279543,0.0011541749,0.00004155041,0.000020378162,0.0000024086064,0.00033734782,0.9396086,0.00014594925,0.0030787464,0.055065606,0.00010446967],"about_ca_topic_score_codex":0.000010515297,"about_ca_topic_score_gemma":0.000016303575,"teacher_disagreement_score":0.96486133,"about_ca_system_score_codex":0.000010999745,"about_ca_system_score_gemma":0.000041618994,"threshold_uncertainty_score":0.18502675},"labels":[],"label_agreement":null},{"id":"W2796162634","doi":"10.1145/3170427.3186471","title":"DataInk","year":2018,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Human–computer interaction; Visualization; Data visualization; Graphics; Bridge (graph theory); Graphical user interface; Interface (matter); Point (geometry); User interface; Information visualization; Computer graphics (images); Programming language; Artificial intelligence","score_opus":0.03386072323653286,"score_gpt":0.3289222514085546,"score_spread":0.2950615281720217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2796162634","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000052789124,0.0000012338651,0.9125961,0.0005304791,0.00008044526,0.0000074067925,6.516148e-7,0.000092558774,0.086638354],"genre_scores_gemma":[0.6633142,0.000008859961,0.28155237,0.01830027,0.00040705092,0.0000010537881,0.000030389192,0.0000063524494,0.03637939],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99976367,0.000004912078,0.000038220194,0.000081745566,0.00005754706,0.00005393248],"domain_scores_gemma":[0.99965537,0.0000047176436,0.000007720208,0.00027490538,0.000031273044,0.000025988675],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000053613912,0.000018936495,0.0000187677,0.000019688612,0.000032414926,0.00008005519,0.00038383738,0.0000063566745,0.00021630847],"category_scores_gemma":[0.000013319243,0.000014818669,0.000005323058,0.00015263274,0.000017859757,0.000252052,0.00013925342,0.000008430039,0.001099549],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.9576652e-8,0.00000524461,0.00007043005,2.7936304e-7,8.3446326e-7,3.7757823e-7,0.000026627511,8.3173724e-8,0.000029629527,0.9141994,0.07794362,0.007723405],"study_design_scores_gemma":[0.00005305611,0.000021980155,0.00021688087,0.0000010513457,5.1477514e-7,0.0000017468398,0.000007146408,0.21841815,0.0016995348,0.0037288957,0.7758,0.00005104676],"about_ca_topic_score_codex":0.0000030028825,"about_ca_topic_score_gemma":0.0000037401442,"teacher_disagreement_score":0.91047055,"about_ca_system_score_codex":0.0000020424543,"about_ca_system_score_gemma":0.000010478866,"threshold_uncertainty_score":0.9996782},"labels":[],"label_agreement":null},{"id":"W2798630247","doi":"10.1145/3170427.3188544","title":"Exploration &amp; Anthropomorphism in Immersive Unit Visualizations","year":2018,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Human–computer interaction; Visualization; Virtual reality; Data visualization; Unit (ring theory); Immersion (mathematics); Multimedia; Artificial intelligence; Psychology","score_opus":0.08541912644526621,"score_gpt":0.37517969956702135,"score_spread":0.2897605731217551,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2798630247","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00096507336,0.000006084966,0.9891605,0.001418528,0.00018718021,0.00006676515,0.0000027675865,0.00007307765,0.008120029],"genre_scores_gemma":[0.9571422,0.00010168828,0.03140168,0.003389591,0.00016398524,0.000010358828,0.00022370677,0.00001598388,0.007550815],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992718,0.000048531245,0.00018084008,0.00020669041,0.00015227942,0.00013984482],"domain_scores_gemma":[0.9993865,0.000022255292,0.000048787635,0.0003205787,0.000168824,0.000053040283],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00012737175,0.00007106589,0.00007396071,0.00020589173,0.00011061104,0.00012267429,0.00034642444,0.000032309825,0.00040184928],"category_scores_gemma":[0.000054549702,0.000067920315,0.000016214626,0.0011049944,0.00008557623,0.00108221,0.000121745456,0.000034287455,0.0007881109],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012261485,0.000113197304,0.0011233442,0.0000024539734,0.000004163955,0.0000021464427,0.0019442099,0.00006294446,0.0005545545,0.9774737,0.017264953,0.0014531482],"study_design_scores_gemma":[0.0010048611,0.00018486027,0.002076541,0.00004538123,0.0000088297875,0.000008577788,0.0012942282,0.5761249,0.00972572,0.01911291,0.389822,0.00059116393],"about_ca_topic_score_codex":0.00007056572,"about_ca_topic_score_gemma":0.0005486743,"teacher_disagreement_score":0.95836073,"about_ca_system_score_codex":0.000018822437,"about_ca_system_score_gemma":0.00004875183,"threshold_uncertainty_score":0.99998987},"labels":[],"label_agreement":null},{"id":"W2798663387","doi":"10.1145/3170427.3188664","title":"Detecting Negative Emotion for Mixed Initiative Visual Analytics","year":2018,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Visual analytics; Computer science; Visualization; Analytics; Random forest; Data visualization; Eye tracking; Data analysis; Artificial intelligence; Machine learning; Human–computer interaction; Interactive visual analysis; Data science; Data mining","score_opus":0.056075691097835036,"score_gpt":0.34981287353404644,"score_spread":0.2937371824362114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2798663387","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004558764,0.000001275145,0.9909773,0.000311202,0.00025168344,0.000121680685,0.00000622509,0.00014442118,0.0036274376],"genre_scores_gemma":[0.9110092,0.0000014997285,0.08725999,0.00105149,0.000189663,0.000004765937,0.0000128482025,0.0000073447186,0.00046321322],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99917996,0.00004356344,0.00019156786,0.00025316546,0.00014762017,0.0001841277],"domain_scores_gemma":[0.9990588,0.00018100963,0.00010375255,0.00018446223,0.00040745182,0.00006455736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002478785,0.000092128925,0.00010555293,0.00011681674,0.00020310961,0.0001797018,0.00029505166,0.00003877153,0.0000347302],"category_scores_gemma":[0.00042332843,0.00008231313,0.00004661982,0.00054146495,0.000057925296,0.00054848567,0.00012747689,0.00004105651,0.00006817531],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003942694,0.0004022715,0.0011777261,0.000058381942,0.00023875062,0.0000046849977,0.008031279,0.00018378586,0.0019450777,0.76552963,0.025146363,0.19724262],"study_design_scores_gemma":[0.00033275664,0.00028122508,0.00057495275,0.000010227042,0.000009831711,0.0000014382626,0.00040086263,0.959883,0.0306129,0.00609341,0.0016600994,0.00013932711],"about_ca_topic_score_codex":0.000006149926,"about_ca_topic_score_gemma":0.00003875042,"teacher_disagreement_score":0.95969915,"about_ca_system_score_codex":0.000031434865,"about_ca_system_score_gemma":0.00005208204,"threshold_uncertainty_score":0.3356632},"labels":[],"label_agreement":null},{"id":"W2801003166","doi":"10.2196/humanfactors.9328","title":"The Impact of Visualization Dashboards on Quality of Care and Clinician Satisfaction: Integrative Literature Review","year":2018,"lang":"en","type":"review","venue":"JMIR Human Factors","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":172,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Psychological intervention; Health care; Visualization; Dashboard; Inclusion (mineral); Usability; Medicine; Nursing; Psychology; Computer science; Data science; Data mining","score_opus":0.0884569634965674,"score_gpt":0.5014558538734648,"score_spread":0.4129988903768974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2801003166","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000075077325,0.9977626,0.0004850931,0.0000044645312,0.00015568949,0.0007547691,0.000361931,0.0000367164,0.0003636582],"genre_scores_gemma":[0.00061152014,0.99851716,0.00003344505,0.00002683682,0.00006592975,0.00001696558,0.0006169016,0.000019347786,0.000091902955],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99696183,0.0007684148,0.001214917,0.00044388694,0.0004476486,0.00016327799],"domain_scores_gemma":[0.9962521,0.00037531948,0.0017182538,0.0009562627,0.0006114441,0.00008657321],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057511637,0.00040809935,0.001434479,0.000216441,0.00019734266,0.00019409167,0.00074718386,0.00022251788,0.000019879266],"category_scores_gemma":[0.00030540055,0.00021143525,0.00064257736,0.00096295035,0.00019150309,0.00027610664,0.00019510102,0.00027945967,0.0000040829264],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006671437,0.00012133724,0.0010217224,0.06944665,0.00046322471,0.0000012613806,0.004640752,2.995981e-7,5.277488e-7,0.06464304,0.013308395,0.84634614],"study_design_scores_gemma":[0.0002861854,0.002018739,0.004366721,0.21599412,0.00032274087,0.000003914662,0.00024406688,0.0000430638,0.0000068756362,0.00033585855,0.77552223,0.00085545005],"about_ca_topic_score_codex":0.000033103177,"about_ca_topic_score_gemma":0.00005381686,"teacher_disagreement_score":0.8454907,"about_ca_system_score_codex":0.00011354608,"about_ca_system_score_gemma":0.00021373159,"threshold_uncertainty_score":0.86220795},"labels":[],"label_agreement":null},{"id":"W2801308124","doi":"10.1007/978-981-10-8189-7_2","title":"Directly Interactive Design Gallery Systems: Interaction Terms and Concepts","year":2018,"lang":"en","type":"book-chapter","venue":"KAIST research series","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Human–computer interaction; Representation (politics); Interface (matter); Theoretical computer science","score_opus":0.11842505830736415,"score_gpt":0.4089305950305684,"score_spread":0.2905055367232042,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2801308124","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000041542316,0.0010435574,0.20739695,0.0008154973,0.0021263352,0.0012593435,0.00014451114,0.00047577993,0.7866965],"genre_scores_gemma":[0.012153634,0.0021770934,0.0034192435,0.0001197878,0.00070832565,0.000055388595,0.0001472766,0.00007525476,0.981144],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99754465,0.00027627405,0.00036156166,0.0006869028,0.00076464034,0.00036599694],"domain_scores_gemma":[0.9976804,0.00049330323,0.00019769222,0.0006954951,0.0007467084,0.00018638396],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0009878078,0.00028775516,0.00036323874,0.0004580739,0.00032867346,0.0015520862,0.0008112633,0.00019257417,0.00028590206],"category_scores_gemma":[0.00025569118,0.00025619703,0.000057228892,0.0001240493,0.0006885302,0.0015375008,0.0008668555,0.0005661422,0.0004208838],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002164741,0.000068943125,0.000012864661,0.0004887006,0.00036859204,0.00023100784,0.006154826,0.0000105671825,0.00029690625,0.6801334,0.29919752,0.012820156],"study_design_scores_gemma":[0.00016912304,0.0004756762,0.0000132139485,0.00091601314,0.0000114426975,0.00009481152,0.00040071484,0.007650859,0.00045671765,0.010747064,0.9786664,0.00039794325],"about_ca_topic_score_codex":0.000042173375,"about_ca_topic_score_gemma":0.000029518325,"teacher_disagreement_score":0.67946887,"about_ca_system_score_codex":0.00017911065,"about_ca_system_score_gemma":0.00018763941,"threshold_uncertainty_score":0.99998903},"labels":[],"label_agreement":null},{"id":"W2806416801","doi":"10.63317/5aktrdysie8r","title":"Scalable Visualisation of Sentiment and Stance","year":2018,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Scalability; Visualization; Sentiment analysis; Data visualization; Artificial intelligence; Data science; Human–computer interaction; Database","score_opus":0.021994563627328517,"score_gpt":0.3105197217128845,"score_spread":0.288525158085556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2806416801","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012285459,0.00001130489,0.98084515,0.00018036121,0.00005244342,0.00002351057,0.0000011250676,0.00002881312,0.006571858],"genre_scores_gemma":[0.9646245,0.000014280591,0.032796066,0.00037953292,0.000022003873,4.0364358e-7,0.0000027376257,0.0000016534111,0.0021587878],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996782,0.000010152791,0.00008104526,0.0000895259,0.00009311618,0.000047958976],"domain_scores_gemma":[0.99973685,0.000008022401,0.000031183674,0.00013337741,0.00006778401,0.00002280594],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010036954,0.00002539554,0.000038498467,0.000028149017,0.000025565603,0.000038114387,0.0001025331,0.000008724906,0.000059390066],"category_scores_gemma":[0.000008692451,0.000021562802,0.000005405406,0.00014525166,0.000036856047,0.00022346895,0.000068536356,0.0000069361267,0.00001937659],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000011540867,0.000043037056,0.0020662704,0.000012574401,0.0000064726205,2.1663247e-7,0.00040182107,0.0000026508997,0.0026514402,0.9787022,0.007674151,0.008438041],"study_design_scores_gemma":[0.00033100237,0.00013878918,0.0032579799,0.000021676258,0.000004713129,0.0000018769755,0.00008129134,0.8481102,0.11550167,0.0053549074,0.027067572,0.00012829447],"about_ca_topic_score_codex":0.000007808082,"about_ca_topic_score_gemma":0.0000046483437,"teacher_disagreement_score":0.97334725,"about_ca_system_score_codex":0.000003870106,"about_ca_system_score_gemma":0.000009821209,"threshold_uncertainty_score":0.08793055},"labels":[],"label_agreement":null},{"id":"W2806754601","doi":"10.1109/bdva.2018.8534027","title":"Visual Analytics on Large Displays: Exploring User Spatialization and How Size and Resolution Affect Task Performance","year":2018,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Spatialization; Computer science; Usability; Human–computer interaction; Cluster analysis; Visual analytics; Task (project management); Display size; Analytics; Mobile device; Visualization; Multimedia; Data science; Display device; Artificial intelligence; World Wide Web","score_opus":0.03693070281152191,"score_gpt":0.2891223595834302,"score_spread":0.2521916567719083,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2806754601","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2877339,0.000012656609,0.71113807,0.0003755688,0.00014850471,0.00008491317,0.00000490693,0.00009647362,0.00040500527],"genre_scores_gemma":[0.9956597,0.00019480758,0.0028111706,0.00045276977,0.00012206101,0.0000038987355,0.000015354113,0.000008759054,0.00073146215],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907976,0.000049756836,0.00011238936,0.0003238558,0.00022548967,0.00020874852],"domain_scores_gemma":[0.99945045,0.000072632996,0.00006486709,0.00023553029,0.00008520338,0.00009129688],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028184702,0.0001239134,0.00011448133,0.00010340314,0.00023704217,0.00035618033,0.00015315606,0.000041894935,0.000013114824],"category_scores_gemma":[0.00012677949,0.00010602123,0.0000151093645,0.00036176067,0.000059844355,0.0011400941,0.0001964251,0.000052334442,0.000015411473],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012548314,0.00066810346,0.17124085,0.0003866967,0.00015017166,0.000016182363,0.0045909993,0.00044309814,0.0039194096,0.75693923,0.020073246,0.04144651],"study_design_scores_gemma":[0.000395039,0.00034291396,0.028805213,0.00004491437,0.000011573084,0.000003249759,0.00005337596,0.95912534,0.00170321,0.00004571632,0.009292943,0.0001764864],"about_ca_topic_score_codex":0.0000056685126,"about_ca_topic_score_gemma":0.000034762972,"teacher_disagreement_score":0.95868224,"about_ca_system_score_codex":0.000021151547,"about_ca_system_score_gemma":0.000015955426,"threshold_uncertainty_score":0.43234202},"labels":[],"label_agreement":null},{"id":"W2806823510","doi":"10.1109/mcg.2018.032421650","title":"Observations and Reflections on Visualization Literacy in Elementary School","year":2018,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":60,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Visualization; Computer science; Literacy; Mathematics education; Data visualization; School teachers; Information visualization; Visual literacy; Human–computer interaction; Multimedia; Pedagogy; Artificial intelligence; Psychology","score_opus":0.0489108246076265,"score_gpt":0.3625567480025619,"score_spread":0.31364592339493536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2806823510","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011604126,0.000033172833,0.98695505,0.000671109,0.00010324718,0.00025366514,0.00002314568,0.00009931553,0.0002571879],"genre_scores_gemma":[0.9401624,0.0007705073,0.046254892,0.011573156,0.00070664193,0.00022152644,0.00016486752,0.000024517558,0.00012145873],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99902207,0.00003895828,0.00025336386,0.00038227838,0.00015847367,0.00014484469],"domain_scores_gemma":[0.99919415,0.000062258274,0.000070364404,0.00035916458,0.00020230238,0.000111751],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001775382,0.00011324662,0.00009749795,0.00034147347,0.00033858744,0.00032523402,0.0002453498,0.000044908997,0.0000055613514],"category_scores_gemma":[0.0000071242207,0.00011711974,0.000019827052,0.001066444,0.00009014281,0.00045458178,0.00009966693,0.00009359669,0.000011870645],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010113577,0.00010982681,0.0031227677,0.000008483517,0.000007857446,3.596304e-7,0.00020908771,0.00001443035,0.00009076751,0.98630637,0.0017587834,0.008370247],"study_design_scores_gemma":[0.0005582421,0.0002102064,0.042133167,0.00006060013,0.000013375984,0.000010245026,0.000025280167,0.71883786,0.00019561868,0.04473658,0.1928709,0.00034794345],"about_ca_topic_score_codex":0.000026383634,"about_ca_topic_score_gemma":0.00007612282,"teacher_disagreement_score":0.9415698,"about_ca_system_score_codex":0.000020957583,"about_ca_system_score_gemma":0.00003795854,"threshold_uncertainty_score":0.47760043},"labels":[],"label_agreement":null},{"id":"W2808654760","doi":"","title":"DataTours: A Data Narratives Framework","year":2017,"lang":"en","type":"preprint","venue":"LillOA (Université de Lille (University Of Lille))","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Narrative; Computer science; Data science; Art; Literature","score_opus":0.05325100575135283,"score_gpt":0.28477454662986135,"score_spread":0.23152354087850852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2808654760","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009736034,0.0008662002,0.9450628,0.01038241,0.001061925,0.0004983936,0.002730029,0.00048711107,0.029175086],"genre_scores_gemma":[0.25824627,0.008329189,0.6766044,0.001185826,0.00055722194,9.79936e-7,0.007856103,0.00016441764,0.047055613],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966121,0.00022849932,0.00025602884,0.0016031684,0.00070971187,0.0005905436],"domain_scores_gemma":[0.99101394,0.00015607812,0.0011128192,0.007010685,0.00027470384,0.00043174363],"candidate_categories":["metaepi_narrow","sts","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0005328634,0.00049115863,0.00082565245,0.0005779881,0.0013957588,0.00029059508,0.015171674,0.00068479875,0.0004996654],"category_scores_gemma":[0.00015903208,0.00066254486,0.00029267863,0.0004760265,0.0005472629,0.002219625,0.030816864,0.0008563172,0.00013329746],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031983832,0.0010792186,0.003942281,0.0012428368,0.0027857686,0.0026521503,0.094623335,0.0009328624,0.00034951232,0.4577737,0.40220284,0.03209566],"study_design_scores_gemma":[0.0025706457,0.00025765388,0.0039994833,0.0017300063,0.0005530591,0.000089273635,0.026465736,0.18297149,0.00009516143,0.027178021,0.75133204,0.0027574194],"about_ca_topic_score_codex":0.0007594919,"about_ca_topic_score_gemma":0.0004942248,"teacher_disagreement_score":0.43059567,"about_ca_system_score_codex":0.00032447666,"about_ca_system_score_gemma":0.00067679054,"threshold_uncertainty_score":0.9999043},"labels":[],"label_agreement":null},{"id":"W2809028471","doi":"10.2495/dne-v13-n2-166-175","title":"Visual analysis for conceptual design of complex systems","year":2018,"lang":"en","type":"article","venue":"International Journal of Design & Nature and Ecodynamics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Conceptual design; Systems engineering; Computer science; Engineering; Management science; Architectural engineering; Process management; Human–computer interaction","score_opus":0.03910335471265703,"score_gpt":0.3332498999348191,"score_spread":0.2941465452221621,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2809028471","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016584476,0.00022875918,0.9969782,0.00021907206,0.0007323428,0.00009583177,0.000038128266,0.0000095112655,0.000039707593],"genre_scores_gemma":[0.90812415,0.0001126839,0.09106112,0.00032313223,0.0002861246,0.0000010652893,0.000023868055,0.0000066342113,0.00006122181],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986682,0.000094346695,0.00053620123,0.00015235512,0.00042743658,0.00012145895],"domain_scores_gemma":[0.9973069,0.00033321106,0.0006056134,0.000118724005,0.0015578179,0.000077745004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007209939,0.00010930859,0.00029384234,0.00051850214,0.000052351923,0.00017131866,0.00079397095,0.000112848196,0.000010150028],"category_scores_gemma":[0.0001599334,0.000092353126,0.0001265137,0.00040459092,0.00011553782,0.00041934403,0.000078253404,0.00013385784,0.0000011928528],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011353585,0.0009513202,0.0057055647,0.00007655458,0.011975901,0.00009647,0.0031703955,0.16831177,0.009161657,0.75976664,0.022851257,0.016797116],"study_design_scores_gemma":[0.0005641973,0.00042290607,0.0004423309,0.000027229466,0.00014030778,0.000050566978,0.00011082813,0.9945373,0.00026612033,0.0012209044,0.0021143549,0.00010294494],"about_ca_topic_score_codex":0.0000035879493,"about_ca_topic_score_gemma":0.0000025397194,"teacher_disagreement_score":0.9064657,"about_ca_system_score_codex":0.0000425672,"about_ca_system_score_gemma":0.00011027681,"threshold_uncertainty_score":0.37660512},"labels":[],"label_agreement":null},{"id":"W2810497686","doi":"10.1109/tvcg.2018.2850781","title":"Decal-Lenses: Interactive Lenses on Surfaces for Multivariate Visualization","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Lens (geology); Visualization; Computer graphics (images); Point (geometry); Surface (topology); Context (archaeology); Data visualization; Through-the-lens metering; Computer vision; Artificial intelligence; Optics; Geometry; Mathematics; Physics; Geology","score_opus":0.03285378186025056,"score_gpt":0.3326602116906432,"score_spread":0.29980642983039263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2810497686","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0073283575,0.000010790053,0.99021083,0.000096825876,0.0013542642,0.00045288893,0.000057123143,0.00041479594,0.000074097916],"genre_scores_gemma":[0.99115556,0.0001817192,0.0040531396,0.004051317,0.00016674244,0.000044454122,0.00006923587,0.00004836165,0.00022949369],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978448,0.00020021878,0.0004921035,0.00074911426,0.00038926848,0.0003244866],"domain_scores_gemma":[0.99815494,0.00038150858,0.00022386557,0.00045264975,0.00061615853,0.00017088928],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00028336933,0.00034659254,0.000294571,0.00064658985,0.000694613,0.0005252791,0.0004054944,0.00016163553,0.000023482693],"category_scores_gemma":[0.000022208602,0.00033586076,0.00012962028,0.0010911499,0.00017571115,0.0008167504,0.000011986756,0.00013435683,0.000031732558],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013148488,0.00073642633,0.00004320595,0.000056036017,0.00013381871,0.0000018692959,0.0024234299,0.0006094565,0.00012599831,0.9790039,0.0012699167,0.015464458],"study_design_scores_gemma":[0.0011029895,0.0014220885,0.00019641775,0.000118490934,0.000039427207,0.0000071607706,0.0000734727,0.9769493,0.012350856,0.0012347145,0.006097092,0.00040801664],"about_ca_topic_score_codex":0.000022777027,"about_ca_topic_score_gemma":0.000046240883,"teacher_disagreement_score":0.9861577,"about_ca_system_score_codex":0.000042243028,"about_ca_system_score_gemma":0.00006366163,"threshold_uncertainty_score":0.99990934},"labels":[],"label_agreement":null},{"id":"W2810696192","doi":"10.2196/medinform.9394","title":"Task-Data Taxonomy for Health Data Visualizations: Web-Based Survey With Experts and Older Adults","year":2018,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Bundesministerium für Bildung und Forschung","keywords":"Computer science; Data science; Data visualization; Taxonomy (biology); Task (project management); World Wide Web; Visualization; Data mining","score_opus":0.08506012506686232,"score_gpt":0.3903521432488234,"score_spread":0.30529201818196106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2810696192","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00057749834,0.00003491955,0.9963311,0.0012080941,0.000121259334,0.0006960377,0.00080433686,0.00013243909,0.00009433532],"genre_scores_gemma":[0.21634607,0.00041846858,0.63306266,0.09623572,0.00078100903,0.00042442378,0.052395377,0.000090743044,0.00024554165],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99798036,0.000084388135,0.0006501932,0.00030996243,0.0006564913,0.00031863814],"domain_scores_gemma":[0.99683374,0.0002655722,0.00029734042,0.0019272421,0.00025275833,0.0004233386],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014677073,0.0001638005,0.0002453645,0.00012362892,0.00021715216,0.00029384618,0.0024079888,0.00008929105,0.000043302298],"category_scores_gemma":[0.00053808844,0.00012315775,0.000011238465,0.00051720993,0.00023052767,0.0016313555,0.0010909459,0.000082430415,0.000016843705],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044496162,0.00036206984,0.002328674,0.00055111555,0.000042730157,0.0000018400103,0.0029059884,0.0000027655458,1.2238716e-7,0.0039100205,0.89952713,0.09032303],"study_design_scores_gemma":[0.0013261747,0.00015835503,0.0004032235,0.00023465519,0.0000035893038,0.000005460498,0.0002336116,0.7939484,0.00000220951,0.0000057684742,0.20353161,0.00014693679],"about_ca_topic_score_codex":0.000028142042,"about_ca_topic_score_gemma":0.00030637375,"teacher_disagreement_score":0.79394567,"about_ca_system_score_codex":0.000019950307,"about_ca_system_score_gemma":0.0009341255,"threshold_uncertainty_score":0.5022227},"labels":[],"label_agreement":null},{"id":"W2834516606","doi":"10.1111/cgf.13434","title":"Illustrative Multivariate Visualization for Geological Modelling","year":2018,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Geoscience BC; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; CMG Reservoir Simulation Foundation","keywords":"Visualization; Computer science; Multivariate statistics; Grid; Domain (mathematical analysis); Data mining; Visual analytics; Data visualization; Geology; Machine learning","score_opus":0.05630041469152158,"score_gpt":0.32544514427284726,"score_spread":0.2691447295813257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2834516606","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006935707,0.000013560482,0.997524,0.00047379767,0.00061662076,0.00023944375,0.000013461223,0.00025791998,0.00016761525],"genre_scores_gemma":[0.7039381,0.000020062913,0.29186937,0.0034842128,0.000399924,0.000020529405,0.00012387706,0.000020432204,0.00012342648],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986149,0.00005652491,0.00029527204,0.00047045352,0.00020079312,0.00036203355],"domain_scores_gemma":[0.99882805,0.00010339148,0.00012690705,0.00039202932,0.00044442737,0.000105166204],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026640837,0.00016902301,0.00017833138,0.0001848357,0.00034518723,0.00025164886,0.00070438534,0.00010955135,0.0000069050625],"category_scores_gemma":[0.00002196784,0.00015106644,0.00009868471,0.0006114368,0.00014294709,0.00051350973,0.00030222352,0.00007653203,0.000023253437],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005287871,0.000062847685,0.00022203295,0.0000070045908,0.000021312306,0.0000010150675,0.00027489554,0.0013168096,0.000011194584,0.99368924,0.0026647104,0.0017236779],"study_design_scores_gemma":[0.00036826555,0.00027144095,0.0000916347,0.000015169383,0.0000068112276,0.0000032479559,0.0000121457415,0.9302537,0.00021574128,0.052278023,0.016287424,0.00019641321],"about_ca_topic_score_codex":0.000009160773,"about_ca_topic_score_gemma":0.000008638423,"teacher_disagreement_score":0.9414112,"about_ca_system_score_codex":0.000014282653,"about_ca_system_score_gemma":0.00003937528,"threshold_uncertainty_score":0.6160311},"labels":[],"label_agreement":null},{"id":"W2849310602","doi":"10.1111/cgf.13418","title":"PixelSNE: Pixel‐Aligned Stochastic Neighbor Embedding for Efficient 2D Visualization with Screen‐Resolution Precision","year":2018,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"National Research Foundation of Korea","keywords":"Embedding; Computer science; Visualization; Pixel; Scale (ratio); Range (aeronautics); Tree (set theory); Space (punctuation); Algorithm; Theoretical computer science; Artificial intelligence; Mathematics; Physics","score_opus":0.01824309092424188,"score_gpt":0.2992238744289965,"score_spread":0.28098078350475464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2849310602","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002333991,0.00004151612,0.99535745,0.00030355933,0.0008341314,0.0006449609,0.00003305815,0.00038316147,0.000068190304],"genre_scores_gemma":[0.8664653,0.000009907567,0.13067596,0.0017820406,0.00056207884,0.000045110486,0.00029979355,0.0000637965,0.000096030846],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974392,0.000086264794,0.0004736229,0.0007883545,0.0006029446,0.000609631],"domain_scores_gemma":[0.9977967,0.00018231565,0.0002837605,0.0007889427,0.0007470629,0.00020119308],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005156724,0.00031349866,0.00028569569,0.00053334655,0.0006719896,0.00053809467,0.0009782524,0.00013024487,0.0000075302096],"category_scores_gemma":[0.00006163851,0.00027332664,0.00012287621,0.0015080586,0.00018102268,0.000558943,0.00044666245,0.000078987556,0.000027134944],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007865822,0.00026074503,0.000161706,0.000036244957,0.000057139892,0.0000018061285,0.0004709751,0.01594918,0.00014126136,0.965519,0.0069770208,0.010346249],"study_design_scores_gemma":[0.0009896574,0.0009376638,0.00021899916,0.00016514355,0.000031067008,0.000012708906,0.000022796583,0.98900133,0.0002494466,0.002951779,0.0050362656,0.00038312364],"about_ca_topic_score_codex":0.0000061454753,"about_ca_topic_score_gemma":0.000022611692,"teacher_disagreement_score":0.97305214,"about_ca_system_score_codex":0.000055546072,"about_ca_system_score_gemma":0.000095577525,"threshold_uncertainty_score":0.99997187},"labels":[],"label_agreement":null},{"id":"W2853934102","doi":"10.1111/cgf.13447","title":"State of the Art of Sports Data Visualization","year":2018,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":157,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Université de Lyon; City, University of London; Agence Nationale de la Recherche","keywords":"Visualization; Data science; Computer science; Data visualization; Domain (mathematical analysis); Information visualization; Field (mathematics); Event (particle physics); Data mining","score_opus":0.029333754974387703,"score_gpt":0.30136494827800137,"score_spread":0.27203119330361364,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2853934102","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003128271,0.00001950613,0.9955201,0.000307066,0.0006290515,0.00008937118,0.000043527674,0.000040416682,0.00022269528],"genre_scores_gemma":[0.9866786,0.00006345017,0.011542191,0.0013444365,0.000080093276,6.773651e-7,0.0001207517,0.000012999038,0.00015679424],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987829,0.000047927464,0.00034974818,0.00026937787,0.00039420242,0.00015588987],"domain_scores_gemma":[0.9977296,0.000027392964,0.0002832395,0.0016419656,0.0002772368,0.00004058595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033219962,0.00009106635,0.00014195842,0.00013458465,0.00007860865,0.00004738348,0.0020513881,0.000028718992,0.0000062280674],"category_scores_gemma":[0.000019866751,0.00006863141,0.00005051017,0.0010430674,0.00020463591,0.00034375724,0.0015464913,0.000047285484,0.000005065487],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003402523,0.000120642406,0.0171042,0.00004070095,0.00003716946,0.000001069591,0.0002950264,0.000051554354,0.00006267175,0.8940137,0.06789644,0.020373395],"study_design_scores_gemma":[0.00016692061,0.00006871773,0.008258103,0.00007217363,0.000009844537,0.000003357535,0.000003883189,0.93918604,0.0020759853,0.015558074,0.034485586,0.000111330606],"about_ca_topic_score_codex":0.0000037989082,"about_ca_topic_score_gemma":0.000015323805,"teacher_disagreement_score":0.9839779,"about_ca_system_score_codex":0.0000036400127,"about_ca_system_score_gemma":0.000060939135,"threshold_uncertainty_score":0.3812024},"labels":[],"label_agreement":null},{"id":"W2877520197","doi":"10.1111/cgf.13400","title":"ChangeCatcher: Increasing Inter‐author Awareness for Visualization Development","year":2018,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Autodesk (Canada)","funders":"","keywords":"Workbook; Disk formatting; Computer science; Visualization; Variety (cybernetics); Data science; Human–computer interaction; World Wide Web; Information retrieval; Multimedia; Data mining; Artificial intelligence","score_opus":0.05339487871147814,"score_gpt":0.34099072592544266,"score_spread":0.28759584721396453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2877520197","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0045640785,0.000027779563,0.99293494,0.00064642995,0.001213413,0.00024319824,0.0000074961595,0.00030701267,0.00005564984],"genre_scores_gemma":[0.747574,0.00001668693,0.24497703,0.0059944065,0.0007727804,0.000060996314,0.00033968812,0.000055302608,0.00020911999],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983939,0.00007427688,0.00037539846,0.0004968924,0.0002488356,0.00041067466],"domain_scores_gemma":[0.9986527,0.00008518467,0.00015787133,0.0005040674,0.00046414704,0.00013605488],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006086122,0.00020382354,0.00019939932,0.0003608557,0.0004639277,0.00040382298,0.0009507194,0.00009760476,0.000005765632],"category_scores_gemma":[0.000041067313,0.00020196261,0.00008014025,0.0008557151,0.000087181696,0.0005326855,0.0005568595,0.000062811676,0.000029216237],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017139426,0.00018428931,0.0072062076,0.000079138495,0.000077339726,0.000002268127,0.0022591662,0.000006089401,0.0000655563,0.8909701,0.016664706,0.082467966],"study_design_scores_gemma":[0.0004195505,0.00016107627,0.001232815,0.00008856208,0.000009592745,0.000009530416,0.000033235152,0.77803534,0.0021566998,0.004297226,0.21320409,0.00035227748],"about_ca_topic_score_codex":0.000012529634,"about_ca_topic_score_gemma":0.00006193273,"teacher_disagreement_score":0.8866729,"about_ca_system_score_codex":0.00003987633,"about_ca_system_score_gemma":0.00013261467,"threshold_uncertainty_score":0.82357967},"labels":[],"label_agreement":null},{"id":"W2884085147","doi":"10.1016/j.conengprac.2018.07.005","title":"Design of visualization plots of industrial alarm and event data for enhanced alarm management","year":2018,"lang":"en","type":"article","venue":"Control Engineering Practice","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Visualization; ALARM; Computer science; Visual analytics; Information visualization; Data visualization; Event (particle physics); Data science; Creative visualization; Data mining; Engineering","score_opus":0.055949089628247836,"score_gpt":0.3360120617847156,"score_spread":0.28006297215646775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2884085147","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000041621603,0.00007035736,0.9990438,0.00014491615,0.00022256853,0.00036332908,0.000033961995,0.000038928632,0.000040504],"genre_scores_gemma":[0.88618976,0.000114508555,0.113314375,0.00014634183,0.00011915678,0.00001624023,0.00004726569,0.000015439287,0.00003689155],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991338,0.0000496466,0.00028408377,0.0002303768,0.00018281637,0.00011922759],"domain_scores_gemma":[0.9986015,0.0004011976,0.00022592282,0.00051763875,0.00021209223,0.00004163897],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008407222,0.00008693823,0.00015710772,0.00009949263,0.000028346607,0.000046923356,0.0004784411,0.000042232947,0.0000023312618],"category_scores_gemma":[0.0010503933,0.000089656285,0.00001414675,0.00023178104,0.000020593821,0.00076504727,0.00018349123,0.000037136906,0.0000011834569],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013611808,0.001458417,0.000046888363,0.0010117575,0.0022133782,0.000011687005,0.0020650725,0.3597509,0.046653494,0.40248203,0.00797648,0.17496872],"study_design_scores_gemma":[0.0015301167,0.00020878584,0.000013505235,0.000052000305,0.00009683588,0.0000015758818,0.000017607777,0.97939473,0.004054065,0.000031146843,0.014510437,0.00008918954],"about_ca_topic_score_codex":0.0000031427362,"about_ca_topic_score_gemma":2.4080208e-7,"teacher_disagreement_score":0.88614815,"about_ca_system_score_codex":0.000010616973,"about_ca_system_score_gemma":0.00003082716,"threshold_uncertainty_score":0.36560774},"labels":[],"label_agreement":null},{"id":"W2887447242","doi":"10.18608/jla.2018.52.5","title":"Visualizing Data to Support Judgement, Inference, and Decision Making in Learning Analytics: Insights from Cognitive Psychology and Visualization Science","year":2018,"lang":"en","type":"article","venue":"Journal of Learning Analytics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":75,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Cambridge; McGill University","keywords":"Visual analytics; Computer science; Data science; Visualization; Judgement; Data visualization; Cognition; Inference; Learning analytics; Information visualization; Cognitive science; Human–computer interaction; Psychology; Artificial intelligence; Epistemology","score_opus":0.09089246937351542,"score_gpt":0.44213875999223184,"score_spread":0.35124629061871643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2887447242","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2851625,0.00009390916,0.7141498,0.00008252891,0.00016734243,0.000056210345,0.000003019403,0.000022911561,0.0002617689],"genre_scores_gemma":[0.977316,0.00037939945,0.021566972,0.00052928925,0.00014917925,3.237305e-7,0.000016637116,0.000015268493,0.000026901771],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972374,0.0001947278,0.0008663126,0.0006346252,0.0007350539,0.00033191356],"domain_scores_gemma":[0.9971942,0.0005686931,0.00074591866,0.0003771022,0.00086866587,0.00024547594],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020326339,0.00020256409,0.00040914843,0.0017049933,0.00037084616,0.0007673519,0.0010544071,0.000087349115,0.00002343795],"category_scores_gemma":[0.00402976,0.00019010046,0.000029631217,0.0024180997,0.00030114743,0.0017440061,0.0012095011,0.00045045558,0.000015715268],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026791863,0.0004781558,0.61675626,0.00006393372,0.00030216615,0.00028943107,0.01675769,0.009086748,0.005163581,0.01887263,0.0010250566,0.3309364],"study_design_scores_gemma":[0.000975587,0.0010454193,0.03123028,0.0006287186,0.00009123142,0.00004243965,0.0012974684,0.9579493,0.00013653623,0.002137299,0.0041474756,0.00031828188],"about_ca_topic_score_codex":0.000010880529,"about_ca_topic_score_gemma":0.0000580279,"teacher_disagreement_score":0.9488625,"about_ca_system_score_codex":0.00006374136,"about_ca_system_score_gemma":0.0002499018,"threshold_uncertainty_score":0.7752072},"labels":[],"label_agreement":null},{"id":"W2888029456","doi":"10.1109/tvcg.2018.2865138","title":"Evaluating ‘Graphical Perception’ with CNNs","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":68,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Institutes of Health; National Science Foundation","keywords":"Computer science; Visualization; Convolutional neural network; Perception; Task (project management); Artificial intelligence; Visual perception; Data visualization; Human–computer interaction","score_opus":0.043289634611307,"score_gpt":0.34769999765302995,"score_spread":0.304410363041723,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2888029456","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011415807,0.0000056412905,0.9874315,0.00012336577,0.00037018766,0.00016004013,0.000007891933,0.00035535265,0.00013021452],"genre_scores_gemma":[0.9822559,0.000096152515,0.01386019,0.0034616475,0.00014648089,0.000015363137,0.000015286627,0.000025520936,0.00012348077],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998257,0.0001495877,0.00030191397,0.0005484245,0.00049559184,0.00024748786],"domain_scores_gemma":[0.9988479,0.000070515576,0.00009647987,0.0004341565,0.00037634603,0.00017458014],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028500476,0.00022447358,0.00018023822,0.00046790543,0.0006101022,0.00038934578,0.00034177952,0.000103246646,0.000055873927],"category_scores_gemma":[0.000003263166,0.000196025,0.00006523992,0.0014723429,0.0002468467,0.000543711,0.000007927993,0.00016012126,0.00003366081],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033054188,0.000380284,0.00019972898,0.000027656622,0.00007759252,0.0000038683684,0.0019236455,0.0003668769,0.00006248805,0.9654107,0.00040437735,0.031109694],"study_design_scores_gemma":[0.0006255798,0.00107362,0.0006982736,0.000050404804,0.000029721037,0.000032331893,0.000038034286,0.9949126,0.00036531937,0.0005894098,0.0013028724,0.00028180072],"about_ca_topic_score_codex":0.000009184841,"about_ca_topic_score_gemma":0.000030261483,"teacher_disagreement_score":0.99454576,"about_ca_system_score_codex":0.000018789346,"about_ca_system_score_gemma":0.000058972768,"threshold_uncertainty_score":0.7993668},"labels":[],"label_agreement":null},{"id":"W2888652842","doi":"10.1109/tvcg.2018.2864903","title":"What Do We Talk About When We Talk About Dashboards?","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":374,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Simon Fraser University; Microsoft Research","keywords":"Computer science; Dashboard; Visualization; Documentation; Data science; Data visualization; Scope (computer science); Construct (python library); Human–computer interaction; Data mining","score_opus":0.02315087006402491,"score_gpt":0.29741199435753835,"score_spread":0.27426112429351346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2888652842","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011697662,0.00069837103,0.99343157,0.0007011403,0.0030723445,0.00027486784,0.000033002136,0.0005280989,0.00009085403],"genre_scores_gemma":[0.90736616,0.06407929,0.011166422,0.013195811,0.0011621065,0.00008295398,0.000118470336,0.00018089602,0.0026479142],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99719757,0.00020370237,0.00060926785,0.00087746425,0.0006685198,0.00044349316],"domain_scores_gemma":[0.9980775,0.00010188962,0.00021676219,0.00084114866,0.0004439546,0.00031870865],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00031275296,0.00042145274,0.00035761093,0.000735614,0.0007255534,0.001981026,0.0008020166,0.00022997413,0.00016170979],"category_scores_gemma":[0.00000447498,0.00041840322,0.00017355531,0.0014617462,0.00032105847,0.002221485,0.000028526481,0.0002552167,0.00008232387],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002906009,0.00068229344,0.000028942191,0.0001205127,0.00017168405,0.00001822414,0.006165954,0.0002813627,0.000066030465,0.84224445,0.006751694,0.1434398],"study_design_scores_gemma":[0.0008503002,0.00040221633,0.000070203554,0.00044119015,0.00005078607,0.000044826065,0.00016727038,0.85003746,0.0023919006,0.0043530893,0.14060217,0.0005885758],"about_ca_topic_score_codex":0.000019132487,"about_ca_topic_score_gemma":0.00007521549,"teacher_disagreement_score":0.9822651,"about_ca_system_score_codex":0.000038048256,"about_ca_system_score_gemma":0.00008535756,"threshold_uncertainty_score":0.9998268},"labels":[],"label_agreement":null},{"id":"W2889269664","doi":"10.14778/3229863.3236259","title":"MustaCHE","year":2018,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Cluster analysis; Computer science; Set (abstract data type); Context (archaeology); Visualization; Hierarchical clustering; Range (aeronautics); Artificial intelligence; Data mining","score_opus":0.020014877002886716,"score_gpt":0.27329417948981405,"score_spread":0.2532793024869273,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889269664","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.209643,0.0002608574,0.21481214,0.030370777,0.0039568907,0.001777663,0.000032245163,0.0010144968,0.5381319],"genre_scores_gemma":[0.99090636,0.000009119599,0.0068256743,0.00073893875,0.00008870707,0.000004112209,3.242609e-7,0.00000435234,0.0014224375],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993461,0.00000238026,0.00013805379,0.00014684454,0.00024190213,0.00012474916],"domain_scores_gemma":[0.9995082,0.000007000518,0.00010985813,0.00014904591,0.00018959504,0.000036313413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017415047,0.000061237915,0.000068710775,0.00004006576,0.00008067404,0.00007836564,0.0010195385,0.000017110406,0.000022442822],"category_scores_gemma":[0.000056441222,0.00003919653,0.000041009047,0.00035457299,0.0000711658,0.0002394026,0.00048067275,0.00003691528,0.00003285873],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000028222037,0.000099067074,0.002191163,0.000030905474,0.000023649052,1.128633e-7,0.0011662593,0.0000010490119,0.016648356,0.9297303,0.043906875,0.0061994493],"study_design_scores_gemma":[0.0006322693,0.00021759403,0.0027056772,0.00009315515,0.000028219929,0.000012602052,0.00031601716,0.028770538,0.7474197,0.023917371,0.19560702,0.0002798147],"about_ca_topic_score_codex":0.000006304939,"about_ca_topic_score_gemma":6.648143e-7,"teacher_disagreement_score":0.9058129,"about_ca_system_score_codex":0.000019557927,"about_ca_system_score_gemma":0.000016395483,"threshold_uncertainty_score":0.18945731},"labels":[],"label_agreement":null},{"id":"W2889454307","doi":"10.5539/mas.v12n9p190","title":"An Enhanced Approach for Using Data Visualization for Sentiment Analysis and Auto Summarization Data","year":2018,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Automatic summarization; Computer science; Visualization; Representation (politics); Information retrieval; Recall; Reading (process); Natural language processing; Text graph; The Internet; Artificial intelligence; World Wide Web; Psychology; Cognitive psychology; Linguistics","score_opus":0.10397776609253966,"score_gpt":0.3907941280419423,"score_spread":0.28681636194940263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889454307","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007344754,0.000005546441,0.9982103,0.000023904133,0.00006338053,0.00051485957,0.00023962416,0.00009288286,0.000115045106],"genre_scores_gemma":[0.57474923,0.0000016593738,0.42297962,0.00015167084,0.000055791967,0.000011753451,0.0020234324,0.000007640594,0.000019198631],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975568,0.000020108968,0.0002690949,0.0014114425,0.0004346722,0.0003078643],"domain_scores_gemma":[0.9969902,0.00003047653,0.00017351995,0.0024178715,0.00025694742,0.00013095548],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015655047,0.0001342346,0.00017942679,0.00033946897,0.00068175385,0.0009126901,0.0032076838,0.000041734736,0.0000020392486],"category_scores_gemma":[0.000075908305,0.00013133437,0.000015509999,0.0020530885,0.00033106044,0.0023277984,0.0012779954,0.00002375425,8.337954e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041955445,0.0005333008,0.00032655062,0.00010184755,0.00016403261,1.2611092e-7,0.0023279754,0.0070366524,0.6408457,0.28533167,0.00034300704,0.062947154],"study_design_scores_gemma":[0.00024719076,0.00003046125,0.00007264473,0.0000024973629,0.00011151582,3.030637e-7,0.00004097468,0.9863794,0.011320877,0.0014304238,0.00018651193,0.00017720522],"about_ca_topic_score_codex":0.000010112645,"about_ca_topic_score_gemma":0.000018084897,"teacher_disagreement_score":0.97934276,"about_ca_system_score_codex":0.000038685004,"about_ca_system_score_gemma":0.00017259138,"threshold_uncertainty_score":0.8801092},"labels":[],"label_agreement":null},{"id":"W2889720336","doi":"10.1109/cscwd.2018.8465359","title":"A Collaboration between Visual and Automated Analyses of Complex Flow Patterns","year":2018,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Usability; Visual analytics; Task (project management); Visualization; Process (computing); Data mining; Human–computer interaction; Eye tracking; Artificial intelligence","score_opus":0.07908272915697769,"score_gpt":0.41812851153740127,"score_spread":0.3390457823804236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889720336","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.101315096,0.0000031371862,0.8976204,0.00022866622,0.000031439813,0.000045969813,0.000033419583,0.0002247671,0.00049712823],"genre_scores_gemma":[0.9791348,0.0000033433662,0.020478278,0.00019804145,0.000039591014,4.7687007e-7,0.00006986756,0.0000027122896,0.00007289142],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994053,0.00003830537,0.00018266025,0.00014930955,0.00014417127,0.00008020583],"domain_scores_gemma":[0.9994834,0.000028791064,0.00007085122,0.0001614465,0.00020708721,0.000048440605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009235968,0.000058697253,0.000118291435,0.00009915773,0.000052297117,0.00012831994,0.0001790224,0.000023735405,0.00006703618],"category_scores_gemma":[0.00002336402,0.000049171576,0.0000124363505,0.0005359143,0.00004994528,0.00032187402,0.000113533315,0.0000138796595,0.000014187387],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027057242,0.00083974714,0.5391955,0.0003415882,0.0008138732,0.000013646749,0.0075921407,0.00035156118,0.08115008,0.11570808,0.13090457,0.12306217],"study_design_scores_gemma":[0.00015632785,0.000097468306,0.046442416,0.0000068322793,0.000010535239,4.966015e-7,0.000048369187,0.94403046,0.0084569035,0.000068228146,0.0006166029,0.00006538524],"about_ca_topic_score_codex":0.00004817412,"about_ca_topic_score_gemma":0.00004772755,"teacher_disagreement_score":0.94367886,"about_ca_system_score_codex":0.0000059873164,"about_ca_system_score_gemma":0.000029340574,"threshold_uncertainty_score":0.20051587},"labels":[],"label_agreement":null},{"id":"W2891985485","doi":"10.2196/11826","title":"Data Visualizations to Support Health Practitioners’ Provision of Personalized Care for Patients With Cancer and Multiple Chronic Conditions: User-Centered Design Study","year":2018,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Center for Future Technologies in Cancer Care, Boston University; Gordon and Betty Moore Foundation","keywords":"Multiple Chronic Conditions; Cancer; Medicine; Health care; Computer science; Nursing; Family medicine; Chronic disease; Internal medicine","score_opus":0.11230668996931374,"score_gpt":0.4338126998777568,"score_spread":0.321506009908443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891985485","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5187611,0.000026972271,0.47208807,0.000118040676,0.00014035423,0.004738939,0.004008067,0.00011054627,0.0000079305355],"genre_scores_gemma":[0.9934202,0.0000060738885,0.0024678886,0.0001493743,0.000031545034,0.000086914384,0.0037380764,0.000017361599,0.000082585546],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99866456,0.00008230353,0.00028663193,0.0004590122,0.0003140844,0.00019342259],"domain_scores_gemma":[0.99850667,0.000052951083,0.0002597207,0.00056842685,0.0004755978,0.00013664781],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013388984,0.00014033428,0.00020414239,0.00018156989,0.0004339848,0.00013821555,0.00049584144,0.000026515898,0.00004999417],"category_scores_gemma":[0.000058514514,0.000116671436,0.000017536466,0.00032450617,0.000075550335,0.00078531646,0.00022913604,0.00003670365,0.0000022967884],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023336275,0.006646649,0.79813206,0.0008498487,0.0004423182,0.0000017472199,0.11118389,0.00015588914,0.0003792019,0.008043096,0.06826432,0.0056675994],"study_design_scores_gemma":[0.027640613,0.0455077,0.693231,0.00093766104,0.00024699303,0.000001578083,0.02217338,0.040994357,0.0008982818,0.00009605192,0.16633385,0.0019385271],"about_ca_topic_score_codex":0.00012913719,"about_ca_topic_score_gemma":0.000927163,"teacher_disagreement_score":0.47465912,"about_ca_system_score_codex":0.000120672965,"about_ca_system_score_gemma":0.00029813603,"threshold_uncertainty_score":0.47577232},"labels":[],"label_agreement":null},{"id":"W2892575549","doi":"10.1155/2018/2084950","title":"5G Visualization: The METIS-II Project Approach","year":2018,"lang":"en","type":"article","venue":"Mobile Information Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Horizon 2020 Framework Programme; Samsung; Ministry of Economy, Trade and Industry; Technische Universität Kaiserslautern","keywords":"Metis; Visualization; Computer science; Human–computer interaction; Virtual reality; Data visualization; Multimedia; World Wide Web; Artificial intelligence","score_opus":0.025391086056600586,"score_gpt":0.3016868380012164,"score_spread":0.2762957519446158,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892575549","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002949784,0.000041762178,0.9500162,0.000055903452,0.00071493426,0.0007314745,0.000014266759,0.0002759264,0.04785454],"genre_scores_gemma":[0.9931521,0.000028063112,0.0019750108,0.0013635185,0.00047979355,0.00042831185,0.0002819729,0.000011974521,0.0022793012],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99856126,0.000108174085,0.00051566714,0.0001441818,0.00048319373,0.00018752892],"domain_scores_gemma":[0.9985845,0.00002812911,0.00027749606,0.0006401334,0.0004243471,0.00004539131],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073829485,0.00012214393,0.00013187241,0.00017592667,0.0005123035,0.00090909726,0.0008558221,0.00005858843,0.000016301528],"category_scores_gemma":[0.00004799604,0.000080679245,0.00004136381,0.0011115224,0.00007160092,0.0027697023,0.00018988938,0.000056367626,0.00041668714],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000040818104,0.0000816961,0.0001557748,0.000108254455,0.00004465752,3.1140712e-7,0.01858544,0.0017048588,0.0000147510455,0.82782626,0.14169967,0.009774265],"study_design_scores_gemma":[0.0001084585,0.000058890477,0.000018034967,0.000009479918,0.0000022985257,0.00001382852,0.00076940586,0.44096273,0.000072434,0.000013572733,0.55789,0.00008088495],"about_ca_topic_score_codex":0.000045387955,"about_ca_topic_score_gemma":0.0000012736629,"teacher_disagreement_score":0.9928571,"about_ca_system_score_codex":0.000040402654,"about_ca_system_score_gemma":0.00009734444,"threshold_uncertainty_score":0.8766446},"labels":[],"label_agreement":null},{"id":"W2892938424","doi":"10.1109/bigdata.2018.8622095","title":"Predicting computational reproducibility of data analysis pipelines in large population studies using collaborative filtering","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Compute Canada","keywords":"Reproducibility; Computer science; Pipeline transport; Population; Process (computing); Set (abstract data type); Pipeline (software); Data mining; Relevance (law); Speedup; Variance (accounting); Statistics; Mathematics; Parallel computing; Engineering","score_opus":0.18909310364366497,"score_gpt":0.4506390377404407,"score_spread":0.26154593409677573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892938424","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14380747,0.00015122016,0.85481864,0.00008451045,0.00021641827,0.00019523517,0.0006277337,0.000066223096,0.000032534062],"genre_scores_gemma":[0.7005914,0.000027424216,0.29709944,0.000038195165,0.00008447874,0.000002150472,0.0021338824,0.0000060268217,0.000017021497],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99635106,0.00024820105,0.0010060113,0.0018053454,0.00042397698,0.00016541706],"domain_scores_gemma":[0.9948638,0.00015508146,0.0007112644,0.0032604346,0.0009752482,0.00003415614],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035780966,0.00018827061,0.00060582865,0.0005532008,0.000088043606,0.00013622054,0.0012054947,0.00008779803,0.000013852692],"category_scores_gemma":[0.0016800128,0.00017968692,0.00006419496,0.002220969,0.00005677084,0.0007759637,0.0058860956,0.00013551382,8.1614024e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000063918246,0.0001718023,0.5800842,0.00027191246,0.0007659906,0.0000021452724,0.0019319927,0.41387913,0.000015221202,0.0022132653,0.00018019683,0.0004777279],"study_design_scores_gemma":[0.0001196358,0.000008290408,0.040607132,0.00011710085,0.0001399656,3.01015e-7,0.00027947137,0.95557374,0.000048159272,0.002945714,0.000009507625,0.00015098353],"about_ca_topic_score_codex":0.0003806814,"about_ca_topic_score_gemma":0.0011010206,"teacher_disagreement_score":0.55771923,"about_ca_system_score_codex":0.00009346738,"about_ca_system_score_gemma":0.0001770011,"threshold_uncertainty_score":0.73365974},"labels":[],"label_agreement":null},{"id":"W2893385070","doi":"10.1016/j.visinf.2018.09.002","title":"The efficacy of stacked bar charts in supporting single-attribute and overall-attribute comparisons","year":2018,"lang":"en","type":"article","venue":"Visual Informatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MacEwan University","funders":"MacEwan University","keywords":"Bar chart; Chart; Bar (unit); Visualization; Computer science; Pie chart; Data mining; Statistics; Artificial intelligence; Mathematics","score_opus":0.04260661857385285,"score_gpt":0.3383269532057595,"score_spread":0.29572033463190667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2893385070","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.57241815,0.000035213252,0.42585278,0.00050831935,0.00027111196,0.0002745543,0.00004082077,0.0000902805,0.0005087912],"genre_scores_gemma":[0.9954439,0.000034529432,0.0039615966,0.00040114392,0.0000424305,0.0000018645178,0.00004060634,0.000006545557,0.000067419656],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982947,0.000048503527,0.0008810888,0.00010953717,0.00031784698,0.00034828376],"domain_scores_gemma":[0.9986601,0.00026939393,0.00042678084,0.00035337207,0.00018902548,0.00010134422],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007526328,0.00013564296,0.00023312418,0.00012305945,0.00020813194,0.0003114126,0.00052044116,0.000053922526,0.000009059465],"category_scores_gemma":[0.00032450937,0.00010391884,0.00003685265,0.00045673168,0.00019356278,0.0007535881,0.00043610513,0.000114725706,0.000033579876],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001427594,0.0026002123,0.15973037,0.0008605269,0.0004059409,0.000022672531,0.07799377,0.0010247934,0.0018414805,0.573307,0.11107239,0.07099808],"study_design_scores_gemma":[0.001446615,0.0005060678,0.017990522,0.0001140654,0.000015788179,0.000009973344,0.0012540447,0.9385148,0.0052068033,0.00018141624,0.034430444,0.00032943656],"about_ca_topic_score_codex":0.000010449631,"about_ca_topic_score_gemma":0.000015859758,"teacher_disagreement_score":0.93749005,"about_ca_system_score_codex":0.000029789562,"about_ca_system_score_gemma":0.0000719132,"threshold_uncertainty_score":0.42376876},"labels":[],"label_agreement":null},{"id":"W2893678799","doi":"10.1109/mcg.2018.053491726","title":"Data Tectonics: A Framework for Building Physical and Immersive Data Representations","year":2018,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Materiality (auditing); Computer science; Context (archaeology); Representation (politics); External Data Representation; Data science; Data visualization; Human–computer interaction; Computer graphics (images); Visualization; Artificial intelligence; Geology","score_opus":0.08496562910253126,"score_gpt":0.3989050245696182,"score_spread":0.31393939546708693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2893678799","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005855907,0.000073155126,0.99713147,0.0010101559,0.000104460305,0.00032875224,0.0006814784,0.000060548537,0.000024413235],"genre_scores_gemma":[0.18400003,0.00034904582,0.81127566,0.001759238,0.001539457,0.000096294105,0.0009403158,0.000023161154,0.00001681447],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99874187,0.000020211299,0.00016944388,0.0007803008,0.00012260927,0.00016556152],"domain_scores_gemma":[0.99718326,0.00032493778,0.000093495444,0.0021532013,0.00013756,0.000107571956],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019200041,0.00011218813,0.00012935873,0.000099995916,0.00045238127,0.000378592,0.0016885845,0.0000456477,7.877564e-7],"category_scores_gemma":[0.00002403328,0.0001105758,0.000019504629,0.00047554538,0.00021189771,0.0005685645,0.0013400633,0.00009603813,0.0000038433445],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.0035664e-7,0.000057248984,0.000065169894,0.000012547695,0.000029648585,1.8273491e-7,0.00014039976,0.000003913015,0.00006125344,0.9808283,0.0042460905,0.014554431],"study_design_scores_gemma":[0.0001342945,0.000032372445,0.00019198106,0.000014322761,0.000027733578,0.0000054441907,0.000017001159,0.82914585,0.00006599168,0.10087362,0.06936041,0.00013097803],"about_ca_topic_score_codex":0.000009374241,"about_ca_topic_score_gemma":0.000009274324,"teacher_disagreement_score":0.8799547,"about_ca_system_score_codex":0.0000036186627,"about_ca_system_score_gemma":0.000035901034,"threshold_uncertainty_score":0.450915},"labels":[],"label_agreement":null},{"id":"W2894104460","doi":"10.1093/bioinformatics/bty832","title":"A systematic method for surveying data visualizations and a resulting genomic epidemiology visualization typology: GEViT","year":2018,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Centre for Disease Control; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; University of British Columbia; Canada Research Chairs; Michael Smith Health Research BC; Fred Hutchinson Cancer Research Center","keywords":"Typology; Visualization; Data science; Computer science; Data visualization; Computational biology; Data mining; Biology; Geography; Archaeology","score_opus":0.1553546717332538,"score_gpt":0.43647967099048524,"score_spread":0.28112499925723144,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2894104460","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00011409666,0.0001208863,0.99812746,0.0002397149,0.0002548275,0.0005857986,0.00012480203,0.00016933237,0.00026310954],"genre_scores_gemma":[0.0068171183,0.00009682871,0.98969877,0.0021755507,0.0001491582,0.000029212342,0.0008813883,0.000022425205,0.00012952494],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976291,0.000415345,0.0011308566,0.0003524909,0.00013108269,0.00034112917],"domain_scores_gemma":[0.99615395,0.0016444843,0.00065687456,0.0011291017,0.0003022366,0.000113344155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005356327,0.00017475773,0.00044860778,0.00024131437,0.000389926,0.00020037654,0.0010466286,0.00011815676,0.000004454809],"category_scores_gemma":[0.0068359585,0.00015411967,0.00003603243,0.0005176798,0.00010619156,0.0010067194,0.00081907725,0.000054634886,0.000036699057],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010485557,0.00006290025,0.0012005715,0.0070962743,0.00017091217,6.0589815e-7,0.0042115175,0.000089385496,0.000098053875,0.97354376,0.009072015,0.0044434997],"study_design_scores_gemma":[0.00030999206,0.00007651251,0.0001644334,0.0003025629,0.000051239436,0.000023504148,0.00031421095,0.9950775,0.0000260769,0.0012870826,0.002181514,0.00018536758],"about_ca_topic_score_codex":0.00001727821,"about_ca_topic_score_gemma":0.000029961706,"teacher_disagreement_score":0.99498814,"about_ca_system_score_codex":0.000035662688,"about_ca_system_score_gemma":0.00010211098,"threshold_uncertainty_score":0.81837744},"labels":[],"label_agreement":null},{"id":"W2895515925","doi":"10.3138/cart.53.3.2017-0021","title":"Scaling the Interactive Dot Map","year":2018,"lang":"en","type":"article","venue":"Cartographica The International Journal for Geographic Information and Geovisualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Interactivity; Zoom; Visualization; Computer science; Context (archaeology); Interactive visualization; Categorical variable; Information visualization; Data science; Data visualization; Geovisualization; Human–computer interaction; Cartography; World Wide Web; Artificial intelligence; Geography; Machine learning; Engineering","score_opus":0.012496062056471496,"score_gpt":0.30574453722714257,"score_spread":0.2932484751706711,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2895515925","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005728882,0.000119972334,0.97533834,0.014135581,0.0036750762,0.00035391227,0.00003128019,0.000098980425,0.00051796326],"genre_scores_gemma":[0.9833311,0.00073616166,0.0017178508,0.012916905,0.00092336425,0.00004150308,0.00019911656,0.000012979573,0.000121047975],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983492,0.000092118695,0.0005654618,0.00015317263,0.00061390427,0.0002261813],"domain_scores_gemma":[0.9970291,0.00023950555,0.00047259746,0.0002756029,0.001891287,0.00009188966],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0012766605,0.00015992185,0.00011149113,0.0005569186,0.0012003544,0.0021529042,0.0012979545,0.00006728776,0.000026982936],"category_scores_gemma":[0.000323842,0.00009598642,0.00016110584,0.000685203,0.00028699692,0.0025183891,0.00023135857,0.00019556087,0.000018834213],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000095032796,0.00005714337,0.0023813285,0.000018743944,0.00036626428,0.000001262846,0.0066349753,0.00016729024,0.00006059015,0.8918023,0.023744455,0.07467058],"study_design_scores_gemma":[0.00087338267,0.00014703305,0.0019706576,0.00006272377,0.000044510733,0.00017493527,0.0015101498,0.21360521,0.00021960118,0.024710909,0.75644195,0.00023892858],"about_ca_topic_score_codex":0.000019607227,"about_ca_topic_score_gemma":0.000021125317,"teacher_disagreement_score":0.9776022,"about_ca_system_score_codex":0.000023121782,"about_ca_system_score_gemma":0.000064998385,"threshold_uncertainty_score":0.99888295},"labels":[],"label_agreement":null},{"id":"W2896357116","doi":"10.1007/978-3-030-01388-2_4","title":"Interaction for Immersive Analytics","year":2018,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":54,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Human–computer interaction; Visual analytics; Analytics; Visualization; Data science; Data visualization; Data exploration; Artificial intelligence","score_opus":0.03413281021332345,"score_gpt":0.31604194512284145,"score_spread":0.281909134909518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2896357116","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000053380954,0.000049567032,0.9947647,0.0005347984,0.002077651,0.00027597608,0.00001836781,0.000055540248,0.0022180546],"genre_scores_gemma":[0.042180233,0.00012984374,0.9409476,0.0087531,0.0026107735,0.000017248976,0.00014605447,0.00009766356,0.0051174974],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974896,0.00001417251,0.00042366647,0.0010877027,0.00055994734,0.00042493548],"domain_scores_gemma":[0.9977022,0.00032525655,0.0003154922,0.0010042996,0.00051951513,0.00013323723],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00053796114,0.00034080842,0.0003522378,0.00079798466,0.00020772872,0.0005869302,0.0023143382,0.000202156,0.00005759039],"category_scores_gemma":[0.00014244458,0.00032166694,0.00013759783,0.0005293817,0.00042259775,0.00072296156,0.00076946884,0.0002935895,0.00008816621],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002865535,0.00012714512,0.000045768553,0.00017268657,0.000104334,0.00005641272,0.003035839,0.03056982,0.0003614152,0.2542542,0.004711746,0.706532],"study_design_scores_gemma":[0.00018809138,0.00017909824,0.0000052580317,0.00016813938,0.000013601749,0.000017253999,4.645513e-7,0.87722206,0.0015657928,0.09588159,0.024358636,0.00040001312],"about_ca_topic_score_codex":0.000004347246,"about_ca_topic_score_gemma":0.000034827593,"teacher_disagreement_score":0.84665227,"about_ca_system_score_codex":0.0002455984,"about_ca_system_score_gemma":0.00034923237,"threshold_uncertainty_score":0.9999235},"labels":[],"label_agreement":null},{"id":"W2896550038","doi":"10.1007/978-3-030-01388-2_9","title":"Just 5 Questions: Toward a Design Framework for Immersive Analytics","year":2018,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Visual analytics; Workspace; Analytics; Human–computer interaction; Visualization; Fidelity; Interactive visual analysis; Data science; Data visualization; Presentation (obstetrics); Artificial intelligence","score_opus":0.07155882250079762,"score_gpt":0.3373596401715792,"score_spread":0.26580081767078156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2896550038","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[6.009319e-7,0.00022018801,0.99594903,0.0011762985,0.0016374781,0.00053437066,0.000029106546,0.000098616954,0.00035433267],"genre_scores_gemma":[0.0031678383,0.00010288575,0.9919037,0.0035005445,0.0007540969,0.000013248253,0.000022125187,0.000037588918,0.0004979237],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.996571,0.00004102586,0.0005508618,0.0014245906,0.0007826555,0.0006298747],"domain_scores_gemma":[0.996271,0.0010329369,0.00037254,0.0014001073,0.00070354156,0.00021987465],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010017349,0.0004868894,0.0005094397,0.0008677443,0.00031594315,0.0008359098,0.0035280806,0.0004114595,0.000053074935],"category_scores_gemma":[0.0006246215,0.00045880157,0.00016976947,0.00092482415,0.00076325395,0.0005977956,0.00091659056,0.00048597454,0.00009087892],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016803806,0.00008467143,0.000012577769,0.00012394848,0.00006698352,0.000048351587,0.0029990706,0.03918909,0.00003419949,0.8185058,0.0017746211,0.13714388],"study_design_scores_gemma":[0.00012119056,0.00019187065,0.000003319846,0.0003394364,0.000020868532,0.000012907008,7.011327e-7,0.5850285,0.00043436367,0.40988937,0.0035414558,0.00041598955],"about_ca_topic_score_codex":0.0000048932307,"about_ca_topic_score_gemma":0.000008579061,"teacher_disagreement_score":0.5458394,"about_ca_system_score_codex":0.00027196817,"about_ca_system_score_gemma":0.0008169972,"threshold_uncertainty_score":0.9997864},"labels":[],"label_agreement":null},{"id":"W2896743066","doi":"10.1007/978-3-030-01388-2_5","title":"Immersive Human-Centered Computational Analytics","year":2018,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Analytics; Human–computer interaction; Computer graphics (images); Data science","score_opus":0.03971296169331512,"score_gpt":0.31184910683891703,"score_spread":0.2721361451456019,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2896743066","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000027934158,0.00007156083,0.9937983,0.00046576106,0.0010106224,0.00020483662,0.00002719125,0.00010417119,0.00428963],"genre_scores_gemma":[0.19257984,0.00007031856,0.7884995,0.011372733,0.0019477138,0.0000070721526,0.0004031021,0.0001313954,0.004988386],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99610955,0.000033093816,0.00063805433,0.001427934,0.0012167131,0.0005746816],"domain_scores_gemma":[0.9973197,0.00021555905,0.0004075048,0.0012201854,0.0006138396,0.00022318577],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00057340576,0.000493578,0.00049393007,0.0010572782,0.0003753303,0.00079963,0.0035698528,0.00024640365,0.00018984672],"category_scores_gemma":[0.00006560044,0.00048426527,0.00015537356,0.00081932225,0.0009840291,0.0006627976,0.0015620257,0.00047039444,0.00024316879],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014229075,0.00031482044,0.00034807817,0.0001608009,0.00018598344,0.00038752906,0.0038566377,0.19708553,0.00021689956,0.6071632,0.0048074084,0.1854589],"study_design_scores_gemma":[0.0003119714,0.00014292091,0.000066514775,0.00020317812,0.000013300932,0.000031270138,3.6241303e-7,0.79451895,0.00021182085,0.20015575,0.0037750911,0.0005689011],"about_ca_topic_score_codex":0.0000075985668,"about_ca_topic_score_gemma":0.000034667828,"teacher_disagreement_score":0.5974334,"about_ca_system_score_codex":0.00029001027,"about_ca_system_score_gemma":0.00050183444,"threshold_uncertainty_score":0.9997609},"labels":[],"label_agreement":null},{"id":"W2898395619","doi":"10.1145/3242671.3242678","title":"Characterizing and Modeling the Effects of Local Latency on Game Performance and Experience","year":2018,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Latency (audio); Lag; Computer science; Time lag; Lag time; Affect (linguistics); Human–computer interaction; Psychology; Computer network; Telecommunications","score_opus":0.021531046779217324,"score_gpt":0.28053959827249886,"score_spread":0.25900855149328156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2898395619","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.58064467,0.000012521228,0.41891515,0.00008096967,0.000041885458,0.000025318046,1.203598e-7,0.000013563348,0.0002657756],"genre_scores_gemma":[0.9986045,0.00009469449,0.00064359076,0.00056965125,0.000016557355,0.0000012291389,2.8108263e-7,0.0000017927964,0.000067702786],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996278,0.000012080188,0.00007196863,0.00012454922,0.00008662789,0.00007696347],"domain_scores_gemma":[0.9997239,0.000032152104,0.000024962454,0.00016183352,0.000029686149,0.000027435486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007350363,0.000046439243,0.000054198885,0.000023896797,0.00006516339,0.00005336376,0.00016771475,0.000013108701,0.0000024894966],"category_scores_gemma":[0.000014982578,0.000028424194,0.000005639615,0.000093748524,0.00009531431,0.0002693825,0.00012201735,0.00002668459,0.0000031839395],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035067194,0.00018152999,0.008453999,0.0005141751,0.00003700443,0.000007130281,0.0451567,0.00032186837,0.04156718,0.37166768,0.0002811988,0.5317765],"study_design_scores_gemma":[0.00007363742,0.00010928247,0.0011828435,0.000041697123,0.0000011718997,0.0000024648573,0.00007303761,0.9854354,0.01284422,0.000052229545,0.00014095643,0.0000430083],"about_ca_topic_score_codex":0.0000048587826,"about_ca_topic_score_gemma":7.0338336e-7,"teacher_disagreement_score":0.98511356,"about_ca_system_score_codex":0.000002339313,"about_ca_system_score_gemma":0.0000062511435,"threshold_uncertainty_score":0.1159105},"labels":[],"label_agreement":null},{"id":"W2898731212","doi":"10.1093/llc/fqy051","title":"In defense of sandcastles: Research thinking through visualization in digital humanities","year":2018,"lang":"en","type":"article","venue":"Digital Scholarship in the Humanities","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Visualization; Interpretation (philosophy); Epistemology; Argument (complex analysis); Terminology; Information visualization; Discipline; Praxis; Ontology; Computer science; Data science; Humanities; Sociology; Social science; Philosophy; Linguistics; Artificial intelligence","score_opus":0.19189528529168076,"score_gpt":0.3977230538410073,"score_spread":0.20582776854932655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2898731212","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7854337,0.00036504306,0.008634006,0.00020135826,0.00028737917,0.0005331307,0.00007220075,0.0001121544,0.20436104],"genre_scores_gemma":[0.9986501,0.000020837988,0.00009596932,0.0005649768,0.000084081956,0.00001149989,0.000042583346,0.000014672828,0.0005153238],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977137,0.00022091971,0.0005305939,0.00030872424,0.0008245688,0.00040147986],"domain_scores_gemma":[0.9987048,0.0004318065,0.00010932498,0.00046728418,0.0002710717,0.000015697626],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0016473574,0.00015759034,0.00020465534,0.0006164577,0.00024293388,0.0036377648,0.0015127648,0.000073874835,0.0000242083],"category_scores_gemma":[0.00070148904,0.0001325665,0.00004460166,0.0012221634,0.0006315155,0.008543706,0.00044764444,0.00034525196,0.000054499003],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010191145,0.00017556056,0.012326122,0.000033668464,0.000003855724,0.00002189703,0.05117988,0.000008580156,0.000004708774,0.93572444,0.00015751281,0.00035359728],"study_design_scores_gemma":[0.0009495893,0.0004063387,0.010437099,0.00071664585,0.0000031760896,0.000022556153,0.030285554,0.001772624,0.00041756095,0.9353121,0.019188488,0.0004882934],"about_ca_topic_score_codex":0.00009493377,"about_ca_topic_score_gemma":0.0007891815,"teacher_disagreement_score":0.21321635,"about_ca_system_score_codex":0.000100679164,"about_ca_system_score_gemma":0.00008854626,"threshold_uncertainty_score":0.9973965},"labels":[],"label_agreement":null},{"id":"W2899027031","doi":"10.22501/jss.511242","title":"Sonifying for Public Engagement: A Context-Based Model for Socially Relevant Data","year":2018,"lang":"en","type":"article","venue":"Journal of sonic studies","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Public engagement; Data science; Computer science; Psychology; Sociology; Political science; Public relations; Geography","score_opus":0.4562638318407072,"score_gpt":0.45446713537136346,"score_spread":0.001796696469343717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2899027031","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00014469071,0.0011287157,0.98846763,0.009598225,0.0003905381,0.00015575028,0.00005696094,0.000020799154,0.000036699268],"genre_scores_gemma":[0.6351972,0.00060387637,0.3589423,0.0039225444,0.00085849885,0.00001574711,0.000016608847,0.000022601944,0.00042063225],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988133,0.00003847187,0.00045017598,0.0001940296,0.0002646843,0.00023935609],"domain_scores_gemma":[0.99756956,0.00038440034,0.00048001576,0.0003548584,0.0011513205,0.000059849623],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019917176,0.000101905964,0.0002744058,0.00011830544,0.00042540155,0.00019686231,0.0011910294,0.000027714192,0.0000020311454],"category_scores_gemma":[0.0017002113,0.000079740275,0.00010189964,0.000153723,0.00009278289,0.00072674453,0.0003583637,0.00007887712,0.000002187818],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001041362,0.0004013536,0.00016131708,0.00034096255,0.0014824225,0.0000059398835,0.0073765144,0.0005200118,0.00015389707,0.48105595,0.40761703,0.10078048],"study_design_scores_gemma":[0.0012562481,0.00023743587,0.000009194728,0.00007417278,0.00006115125,0.0000022260951,0.00085322675,0.939816,0.000058765425,0.009373264,0.048156098,0.00010224888],"about_ca_topic_score_codex":5.1882984e-7,"about_ca_topic_score_gemma":0.000051301548,"teacher_disagreement_score":0.93929595,"about_ca_system_score_codex":0.00007087717,"about_ca_system_score_gemma":0.0006204856,"threshold_uncertainty_score":0.32718876},"labels":[],"label_agreement":null},{"id":"W2900510420","doi":"10.1109/bdva.2018.8534019","title":"Multiple Workspaces in Visual Analytics","year":2018,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Workspace; Computer science; Visual analytics; Visualization; Exploratory analysis; Analytics; Human–computer interaction; Process (computing); Data visualization; Exploratory research; Work (physics); Interactive visual analysis; Path (computing); Data science; Data mining; Artificial intelligence; Engineering","score_opus":0.02759077134307323,"score_gpt":0.3255944979311638,"score_spread":0.29800372658809055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2900510420","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009037778,0.000008067288,0.9817063,0.00051961746,0.00013750118,0.00003508382,6.5602865e-7,0.0001085506,0.008446437],"genre_scores_gemma":[0.9726694,0.000008128793,0.02433923,0.0009849003,0.00006800861,7.867492e-7,0.000003897581,0.000003547262,0.0019221039],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99936473,0.000021244132,0.00013491612,0.0001857044,0.00013722316,0.00015619224],"domain_scores_gemma":[0.99958134,0.000043243064,0.000029116414,0.00023445136,0.000057293553,0.000054571457],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001464764,0.000060773466,0.000075693104,0.00013549022,0.000038958242,0.00014612169,0.00040422604,0.000029371577,0.000085201566],"category_scores_gemma":[0.000077409655,0.000051983912,0.00001787465,0.00076558854,0.00004313392,0.0003422015,0.00016953643,0.00003991118,0.000257928],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011074046,0.0006351263,0.25359687,0.000015796892,0.00003516902,0.000034075994,0.0017983647,0.00039973712,0.000462147,0.62924033,0.05285808,0.060913254],"study_design_scores_gemma":[0.00019151597,0.000038455008,0.0044283615,0.0000069576595,0.0000010537498,9.0185955e-7,0.00006069392,0.979508,0.0007658331,0.00054049987,0.014363557,0.00009418527],"about_ca_topic_score_codex":0.000032371125,"about_ca_topic_score_gemma":0.00047224373,"teacher_disagreement_score":0.9791083,"about_ca_system_score_codex":0.000014240629,"about_ca_system_score_gemma":0.000027331755,"threshold_uncertainty_score":0.33152285},"labels":[],"label_agreement":null},{"id":"W2903161160","doi":"10.1007/s11023-018-9484-3","title":"Peeking Inside the Black Box: A New Kind of Scientific Visualization","year":2018,"lang":"en","type":"article","venue":"Minds and Machines","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; University of Pittsburgh","keywords":"Visualization; Computer science; sort; Theory of computation; Scientific visualization; Philosophy of science; Coding (social sciences); Function (biology); Black box; Data science; Computational model; Human–computer interaction; Theoretical computer science; Epistemology; Artificial intelligence; Algorithm; Mathematics; Information retrieval; Biology; Philosophy","score_opus":0.02450880691181074,"score_gpt":0.3110524630839154,"score_spread":0.28654365617210464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2903161160","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20693354,0.00011368805,0.78915673,0.0011509801,0.00040321163,0.000093837654,0.0000051862426,0.00004065565,0.0021021743],"genre_scores_gemma":[0.9953763,0.000008662594,0.002124838,0.000324852,0.00012046342,4.364301e-7,0.000011275142,0.0000042571883,0.002028922],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994036,0.000027076368,0.00013968135,0.00017611065,0.00016005631,0.00009347133],"domain_scores_gemma":[0.9995059,0.000024172416,0.00007847504,0.0002563805,0.00009164797,0.00004346051],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023748666,0.000063399944,0.00007422343,0.000085211905,0.000181934,0.00030438884,0.00029886892,0.000020017873,0.000025955585],"category_scores_gemma":[0.000058095433,0.000041188105,0.000019229476,0.00045029307,0.00018963411,0.00022156336,0.00017960713,0.000024500001,0.000010121959],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011738255,0.00014764073,0.016262911,0.00007517161,0.00004727011,0.0000032016646,0.019802839,0.000040149116,0.010047937,0.55902237,0.052614607,0.3419242],"study_design_scores_gemma":[0.00047723288,0.00013959037,0.010435297,0.00006112388,0.00002476024,0.00001023606,0.00014550435,0.8307054,0.009063696,0.00995931,0.13875343,0.00022441438],"about_ca_topic_score_codex":0.000056617082,"about_ca_topic_score_gemma":0.00009351424,"teacher_disagreement_score":0.83066523,"about_ca_system_score_codex":0.0000029860475,"about_ca_system_score_gemma":0.00004953161,"threshold_uncertainty_score":0.29352286},"labels":[],"label_agreement":null},{"id":"W2903881814","doi":"10.1109/tvcg.2018.2874730","title":"The 2018 Visualization Career Award","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Visualization; Computer science; Data visualization; Information visualization; Graphics; Human–computer interaction; Geovisualization; Data science; World Wide Web; Computer graphics (images); Artificial intelligence","score_opus":0.028017543542245282,"score_gpt":0.29519429428401106,"score_spread":0.2671767507417658,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2903881814","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00072361535,0.000034401197,0.9964611,0.0002427738,0.0018065549,0.00019437005,0.0000120451905,0.0003755223,0.00014965293],"genre_scores_gemma":[0.9904934,0.0010887522,0.0012456251,0.005867876,0.00040261511,0.000031264717,0.000034437657,0.000052560994,0.00078346644],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998068,0.00019003062,0.00041795813,0.0005076171,0.0004965111,0.0003199218],"domain_scores_gemma":[0.9985036,0.00013991224,0.00014391151,0.0006105818,0.00043294445,0.00016901336],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0003727124,0.00024962434,0.00017323418,0.00031699988,0.0013675368,0.0007982179,0.0006000909,0.00012485971,0.000015578493],"category_scores_gemma":[0.000007788413,0.00020105712,0.00009108913,0.0014369475,0.00030206554,0.00058372517,0.000015831081,0.00013497703,0.00006167595],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010258334,0.00011845088,0.00005017131,0.000011152533,0.000047749487,0.0000012104839,0.0006553944,0.00006801579,0.000011647228,0.9824819,0.004768469,0.01177557],"study_design_scores_gemma":[0.0003907898,0.00030418724,0.00017305514,0.00002912612,0.000023056262,0.0000125445185,0.000039998657,0.93725497,0.0019806821,0.0010886595,0.058429632,0.0002733081],"about_ca_topic_score_codex":0.000015260523,"about_ca_topic_score_gemma":0.00007099108,"teacher_disagreement_score":0.9952154,"about_ca_system_score_codex":0.000031407293,"about_ca_system_score_gemma":0.00006496239,"threshold_uncertainty_score":0.9999325},"labels":[],"label_agreement":null},{"id":"W2905269564","doi":"10.1609/aimag.v39i4.2825","title":"Human Computation for Image and Video Analysis (GroupSight)","year":2018,"lang":"en","type":"article","venue":"AI Magazine","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Crowdsourcing; Computation; Computer science; Data science; Image (mathematics); Artificial intelligence; Multimedia; World Wide Web; Algorithm","score_opus":0.02022637091902564,"score_gpt":0.33411592507963234,"score_spread":0.3138895541606067,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2905269564","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0029570616,0.000010814769,0.994494,0.0010100638,0.00005233493,0.00007482128,0.000010468158,0.000079931284,0.0013105121],"genre_scores_gemma":[0.91612583,0.0000036966405,0.07948852,0.0026640808,0.00015127397,0.0000059323297,0.00015255618,0.000008639884,0.0013994827],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993532,0.00001955002,0.00015519133,0.00024671174,0.0001065257,0.00011885278],"domain_scores_gemma":[0.9994527,0.000027177695,0.000060411865,0.00021631991,0.00018709082,0.000056277444],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001630616,0.00007282428,0.00012239747,0.00017357536,0.00016005646,0.00023525015,0.0002041102,0.000022662061,0.000030306623],"category_scores_gemma":[0.000021327023,0.000067207446,0.000043156906,0.00064808823,0.00007208548,0.00042402963,0.0001024463,0.00002455161,0.00006670784],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012344057,0.00029230077,0.0041041574,0.000095148345,0.0006577052,0.00001270851,0.0014076297,0.00016201213,0.015762206,0.611934,0.325973,0.03958679],"study_design_scores_gemma":[0.00046245623,0.00015560574,0.011411972,0.0000047942876,0.00012232114,0.0000022125391,0.0000066701923,0.94951296,0.0005397464,0.00652711,0.031095656,0.00015848257],"about_ca_topic_score_codex":0.0000050657304,"about_ca_topic_score_gemma":0.0000380956,"teacher_disagreement_score":0.94935095,"about_ca_system_score_codex":0.000008635239,"about_ca_system_score_gemma":0.000009517955,"threshold_uncertainty_score":0.274064},"labels":[],"label_agreement":null},{"id":"W2910652915","doi":"10.1109/iemcon.2018.8614978","title":"Retrofitting Realities: Affordances and Limitations in Porting an Interactive Geospatial Visualization from Augmented to Virtual Reality","year":2018,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Affordance; Computer science; Augmented reality; Visualization; Virtual reality; Human–computer interaction; Geospatial analysis; Big data; Context (archaeology); Cloud computing; Mobile device; Visual analytics; Interactive visualization; Data visualization; Interactive visual analysis; Analytics; Data science; Multimedia; World Wide Web; Artificial intelligence","score_opus":0.06339116498653302,"score_gpt":0.35613344027764315,"score_spread":0.29274227529111013,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2910652915","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18486929,0.0000021925653,0.8115931,0.0003687955,0.00014716307,0.00010693604,0.000021422578,0.000121118566,0.002769987],"genre_scores_gemma":[0.9814067,0.00001048131,0.017129796,0.0009477668,0.00012441329,0.000006481186,0.00016638087,0.000007425143,0.00020059722],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986394,0.0001383993,0.00041387195,0.00041432254,0.00020900607,0.00018501798],"domain_scores_gemma":[0.99906397,0.00020065426,0.00016381209,0.00027595137,0.00018121286,0.00011441215],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041665122,0.00010887515,0.00014037456,0.00017207123,0.00014034643,0.00028591708,0.0002737319,0.000039139442,0.000026228096],"category_scores_gemma":[0.0006836417,0.00010736256,0.0000146699485,0.00055850844,0.00004620962,0.0014013146,0.00021141703,0.000055126195,0.000010058341],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009699219,0.00042980883,0.03426526,0.000021274698,0.0000639614,0.0000112534,0.08970049,0.00050431606,0.00242838,0.68245465,0.002231292,0.1877923],"study_design_scores_gemma":[0.00038759384,0.0003892977,0.02612474,0.000078401616,0.0000058830465,0.0000010789544,0.009896113,0.95527035,0.0021088242,0.0042388565,0.0012483817,0.0002504508],"about_ca_topic_score_codex":0.0017278565,"about_ca_topic_score_gemma":0.009073717,"teacher_disagreement_score":0.95476604,"about_ca_system_score_codex":0.00005215013,"about_ca_system_score_gemma":0.000046693123,"threshold_uncertainty_score":0.50633466},"labels":[],"label_agreement":null},{"id":"W2911014696","doi":"10.1111/cgf.13596","title":"MyEvents: A Personal Visual Analytics Approach for Mining Key Events and Knowledge Discovery in Support of Personal Reminiscence","year":2019,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"FP7 Information and Communication Technologies; Engineering and Physical Sciences Research Council; Horizon 2020 Framework Programme; European Commission; Queen's University; Queen's University Belfast","keywords":"Reminiscence; Event (particle physics); Recall; Computer science; Analytics; Human–computer interaction; Process (computing); Visual analytics; Data science; Visualization; World Wide Web; Psychology; Artificial intelligence; Cognitive psychology","score_opus":0.022680003278810264,"score_gpt":0.2931121402544004,"score_spread":0.27043213697559015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2911014696","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08157194,0.00007980756,0.91732097,0.00016209189,0.00030629477,0.00029985048,0.000055322886,0.000032179156,0.00017151922],"genre_scores_gemma":[0.9692354,0.000040561445,0.029557029,0.00058390404,0.000057299523,0.00001034646,0.00013477339,0.000019642799,0.00036104684],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99814165,0.000057455134,0.0004533002,0.0005984566,0.00033119202,0.0004179657],"domain_scores_gemma":[0.9991367,0.00013838884,0.00019647856,0.00027806137,0.00013658754,0.000113784896],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005168088,0.00022373494,0.0003734408,0.0004332473,0.00007809103,0.00013309527,0.0006174078,0.00010435598,0.0000033984131],"category_scores_gemma":[0.000021903543,0.0002212769,0.0001532121,0.00076453737,0.00009357968,0.0007621462,0.0005538756,0.00013774271,0.0000025778686],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013483441,0.0021822378,0.6339441,0.0011268236,0.00028354325,0.000012027796,0.012768506,0.00021355956,0.000119924814,0.32707125,0.0109103825,0.011232854],"study_design_scores_gemma":[0.0010501683,0.00041262998,0.0062971185,0.00008411153,0.000015651643,0.000014074303,0.00026341033,0.9892535,0.000031687123,0.0004543494,0.0018465917,0.00027666945],"about_ca_topic_score_codex":0.0000046550394,"about_ca_topic_score_gemma":0.000008729972,"teacher_disagreement_score":0.98903996,"about_ca_system_score_codex":0.00002767903,"about_ca_system_score_gemma":0.0001675697,"threshold_uncertainty_score":0.90234107},"labels":[],"label_agreement":null},{"id":"W2912481189","doi":"10.1109/mcg.2019.2898941","title":"A Walk Among the Data","year":2019,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Virtual reality; Human–computer interaction; Data visualization; Visualization; Unit (ring theory); Data exploration; Multimedia; Computer graphics (images); Artificial intelligence","score_opus":0.02973118019729208,"score_gpt":0.2870278564335315,"score_spread":0.2572966762362394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912481189","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002810756,0.00005988925,0.99534327,0.0009282213,0.0001289843,0.0002509862,0.000025945703,0.00008335799,0.00036859815],"genre_scores_gemma":[0.97759646,0.00041944828,0.0156106,0.0052166474,0.00042001976,0.00006840035,0.00019931966,0.000018620663,0.0004504857],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992093,0.000023132088,0.00013969047,0.00036769017,0.00013993241,0.000120262266],"domain_scores_gemma":[0.998132,0.00007760747,0.000060659317,0.0016165281,0.00005260983,0.00006061821],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020050061,0.00008143956,0.00007989752,0.000057836973,0.00017993254,0.00033883206,0.0016996884,0.000029817993,0.0000045989864],"category_scores_gemma":[0.0000013016667,0.000058410813,0.000022514956,0.00043795432,0.00007701447,0.0003291115,0.0005535991,0.00009373396,0.000062467116],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.4702066e-7,0.000032224056,0.0024550231,0.0000074753575,0.000013968422,2.561424e-7,0.000056127374,0.000032772685,0.000009639703,0.9733716,0.00791064,0.01611012],"study_design_scores_gemma":[0.00008917463,0.000009421977,0.0047194734,0.000005123715,0.000006056803,0.0000038991757,0.000004880008,0.76578045,0.000008452054,0.0061026188,0.22317636,0.000094105126],"about_ca_topic_score_codex":0.000014101836,"about_ca_topic_score_gemma":0.000010675545,"teacher_disagreement_score":0.97973263,"about_ca_system_score_codex":0.0000024781903,"about_ca_system_score_gemma":0.000019650754,"threshold_uncertainty_score":0.32673654},"labels":[],"label_agreement":null},{"id":"W2912769923","doi":"10.1111/j.1740-9713.2019.01229.x","title":"Visualising the<i>Titanic</i>Disaster","year":2019,"lang":"en","type":"article","venue":"Significance","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Tragedy (event); History; Visualization; Data science; Computer science; Literature; Art; Artificial intelligence","score_opus":0.015684330440939965,"score_gpt":0.2773413171302379,"score_spread":0.26165698668929793,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912769923","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014605065,0.00013706682,0.9517248,0.0023562324,0.0009983113,0.0002862073,0.000008279899,0.00023815119,0.02964588],"genre_scores_gemma":[0.9900898,0.000011760458,0.0020857714,0.00317664,0.000069329275,0.000004117607,0.000004300648,0.000008528659,0.0045497804],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991591,0.00004760851,0.00014102932,0.0002516529,0.0002211601,0.00017946919],"domain_scores_gemma":[0.9991369,0.00006621914,0.000063577965,0.0006437316,0.000047611396,0.00004192657],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00021940461,0.00008006836,0.00008453851,0.000027321563,0.000074145624,0.00024572073,0.0008405646,0.000021997623,0.00011475345],"category_scores_gemma":[0.000021459795,0.000056568468,0.000036754165,0.0003621219,0.000032428394,0.00040639518,0.00013470792,0.000068743044,0.0011548814],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000031913207,0.00005304307,0.001723322,0.000022663728,0.000017069839,0.0000047169797,0.0012518397,0.00020247384,0.008385138,0.9637468,0.016057065,0.008532714],"study_design_scores_gemma":[0.0007172134,0.00012905749,0.0030106867,0.00008233052,0.000014272547,0.000014673681,0.0006740978,0.26566663,0.0102905,0.009067419,0.7096071,0.00072595186],"about_ca_topic_score_codex":0.000006991272,"about_ca_topic_score_gemma":0.0000026287883,"teacher_disagreement_score":0.9754847,"about_ca_system_score_codex":0.000017106044,"about_ca_system_score_gemma":0.000041143947,"threshold_uncertainty_score":0.9996228},"labels":[],"label_agreement":null},{"id":"W2912962050","doi":"10.1109/beliv.2018.8634420","title":"How to Evaluate an Evaluation Study? Comparing and Contrasting Practices in Vis with Those of Other Disciplines : Position Paper","year":2018,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Checklist; Position (finance); Position paper; Resource (disambiguation); Empirical research; Psychology; Qualitative research; Engineering ethics; Management science; Sociology; Applied psychology; Social science; Computer science; Epistemology; Engineering; Cognitive psychology; Business; World Wide Web","score_opus":0.1263585004118408,"score_gpt":0.4299767174871811,"score_spread":0.3036182170753403,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912962050","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7966839,0.0000040473674,0.20166782,0.00082779105,0.000023037577,0.0002790387,8.0025e-7,0.000020953978,0.0004926272],"genre_scores_gemma":[0.98850274,4.1840698e-7,0.011191688,0.00023271095,0.000022362383,0.000008085694,0.0000027732851,0.000004033671,0.000035201647],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99905396,0.00016268772,0.00014023902,0.00023169213,0.00032468632,0.0000867443],"domain_scores_gemma":[0.99923915,0.000053217147,0.00017295624,0.00020624757,0.00028604807,0.00004240163],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010848107,0.00006847282,0.000111665904,0.00009363568,0.00005833755,0.00026016196,0.00015432881,0.0000118267735,0.000010494737],"category_scores_gemma":[0.00016238721,0.00004729886,0.000005125428,0.0002989776,0.000024890567,0.0014415313,0.00009022477,0.000023878973,0.000001293339],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000111186586,0.0013084619,0.89516556,0.000030120244,0.000081034246,0.0000023904033,0.020936528,0.0009754171,0.00874747,0.016966583,0.00008287666,0.05559239],"study_design_scores_gemma":[0.00071356114,0.0005059071,0.19102122,0.000040549097,0.00002514465,0.0000011882505,0.0015262146,0.80542827,0.00043618248,0.00019155986,0.000023741371,0.00008644402],"about_ca_topic_score_codex":0.00013829287,"about_ca_topic_score_gemma":0.0023790037,"teacher_disagreement_score":0.80445284,"about_ca_system_score_codex":0.000012281938,"about_ca_system_score_gemma":0.000029549396,"threshold_uncertainty_score":0.2508748},"labels":[],"label_agreement":null},{"id":"W2913222940","doi":"","title":"Revised Selected Papers of the 23rd International Symposium on Graph Drawing and Network Visualization - Volume 9411","year":2015,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Graph drawing; Visualization; Computer science; Volume (thermodynamics); Graph; Computer graphics (images); Artificial intelligence; Theoretical computer science","score_opus":0.016122305798521325,"score_gpt":0.269704205921023,"score_spread":0.2535819001225017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2913222940","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012559266,0.000057422796,0.95302343,0.004251737,0.0014300819,0.00031027623,0.000009017284,0.0002588534,0.02809992],"genre_scores_gemma":[0.9932843,0.00005499952,0.002371572,0.0019391825,0.00010928554,0.000002490814,0.000037478163,0.000009581267,0.0021911487],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99912983,0.00007724612,0.00019291394,0.0001840707,0.00030881198,0.00010713712],"domain_scores_gemma":[0.9993481,0.000027331145,0.00010790437,0.00024060154,0.00021411164,0.00006194957],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024214618,0.00007640815,0.000091670416,0.00004348169,0.000066602595,0.00012880407,0.00044430888,0.000031625525,0.000018593208],"category_scores_gemma":[0.000107627304,0.000054393084,0.00002671872,0.00075778796,0.000037282512,0.00023042211,0.00016712706,0.00004220874,0.0000044276544],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024756004,0.00017650591,0.069443144,0.000031374024,0.00010680405,0.0000019388233,0.0014810202,0.012433159,0.0014427543,0.82661813,0.083330855,0.004909538],"study_design_scores_gemma":[0.0006877714,0.00011111551,0.009576164,0.000100765785,0.00001843919,0.000004927612,0.00006307022,0.9337396,0.0008562024,0.0011760746,0.053452346,0.00021354096],"about_ca_topic_score_codex":0.000011129403,"about_ca_topic_score_gemma":0.000006969228,"teacher_disagreement_score":0.980725,"about_ca_system_score_codex":0.000019754176,"about_ca_system_score_gemma":0.00004497371,"threshold_uncertainty_score":0.22180855},"labels":[],"label_agreement":null},{"id":"W2913302869","doi":"","title":"Proceedings of the Ninth annual IEEE conference on Information visualization","year":2003,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Ninth; Visualization; Computer science; Data science; Telecommunications; World Wide Web; Political science; Business; Artificial intelligence","score_opus":0.019851236920620956,"score_gpt":0.27860960541915186,"score_spread":0.2587583684985309,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2913302869","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009314513,9.816771e-7,0.8666241,0.0003449496,0.00025958547,0.00016156925,0.000009394769,0.000094000614,0.12319087],"genre_scores_gemma":[0.9965422,0.0000048279426,0.0015451811,0.0010195991,0.000006427039,0.000001937495,0.0000034515324,0.0000020177615,0.00087435497],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99941236,0.000011233861,0.0001777438,0.00007920367,0.00024273359,0.000076738805],"domain_scores_gemma":[0.9993902,0.00000931309,0.00012334721,0.00012197643,0.00032947055,0.000025691683],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015549554,0.000055871813,0.00005630652,0.00006172055,0.00005433658,0.000109110806,0.00034582175,0.000025977435,0.000030397767],"category_scores_gemma":[0.0000940523,0.00003678684,0.00002039766,0.0004656878,0.000025425701,0.0011774867,0.00003491228,0.000032082848,0.000030139032],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.231763e-7,0.000019423955,0.0002714335,0.00000710255,0.0000017707717,9.2066506e-9,0.00049361493,0.000027243444,0.00010078812,0.99177605,0.006817922,0.00048411227],"study_design_scores_gemma":[0.0011439644,0.00035792723,0.0045508845,0.00014761512,0.000018046234,0.000010582526,0.0023164486,0.6280659,0.2252638,0.01850934,0.11904617,0.0005693346],"about_ca_topic_score_codex":0.0000026730493,"about_ca_topic_score_gemma":8.5234257e-7,"teacher_disagreement_score":0.9872277,"about_ca_system_score_codex":0.000011130689,"about_ca_system_score_gemma":0.000046154564,"threshold_uncertainty_score":0.15001237},"labels":[],"label_agreement":null},{"id":"W2913406170","doi":"10.1002/pra2.2018.14505501129","title":"Bibliomaps ‐ a software to create web‐based interactive maps of science: The case of UX map","year":2018,"lang":"en","type":"article","venue":"Proceedings of the Association for Information Science and Technology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MacEwan University","funders":"","keywords":"Computer science; Metadata; Visualization; World Wide Web; Software; Similarity (geometry); Information retrieval; Interactive visualization; Scale (ratio); Data science; Data mining; Image (mathematics)","score_opus":0.011767626837194962,"score_gpt":0.2968086482535875,"score_spread":0.28504102141639254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2913406170","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92241037,0.000012984984,0.046580557,0.023014618,0.0008071063,0.0016635974,0.0002780579,0.00023519646,0.004997539],"genre_scores_gemma":[0.9937768,0.0000022040495,0.005878191,0.00028441963,0.000007011098,0.000014460288,9.530264e-7,0.0000015697589,0.00003442004],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987689,0.0000032264172,0.0003705832,0.00014046357,0.0005311794,0.00018563986],"domain_scores_gemma":[0.99252415,0.000082988874,0.0009183889,0.00018299505,0.006256005,0.0000354564],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002485672,0.000066194865,0.00012467641,0.0023764693,0.0004711139,0.00017899447,0.0014452875,0.000053622207,0.0000010323885],"category_scores_gemma":[0.004894305,0.000042653563,0.000028289262,0.012670937,0.0012538948,0.0030668268,0.00053578516,0.000057491463,0.000002749908],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025577032,0.00007434723,0.012106829,0.00014586098,0.000025559384,1.1225843e-7,0.0061489544,0.000012642747,0.030134225,0.91797364,0.010072803,0.02327944],"study_design_scores_gemma":[0.0008817403,0.0005186398,0.0014348006,0.00012308161,0.00003213647,0.000038926904,0.00541241,0.07935359,0.87158895,0.019299334,0.021116072,0.00020032644],"about_ca_topic_score_codex":0.000010165536,"about_ca_topic_score_gemma":0.000003673493,"teacher_disagreement_score":0.8986743,"about_ca_system_score_codex":0.00009497344,"about_ca_system_score_gemma":0.00033073899,"threshold_uncertainty_score":0.6087965},"labels":[],"label_agreement":null},{"id":"W2913767699","doi":"10.1109/tvcg.2019.2898186","title":"Aggregated Dendrograms for Visual Comparison between Many Phylogenetic Trees","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Phylogenetic tree; Tree (set theory); Tree rearrangement; Benchmark (surveying); Artificial intelligence; Visualization; Domain (mathematical analysis); Theoretical computer science; Biological data; Machine learning; Data mining; Mathematics; Biology; Bioinformatics; Geography","score_opus":0.025583604238574382,"score_gpt":0.3095388435255826,"score_spread":0.2839552392870082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2913767699","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03700838,0.00004465524,0.96142787,0.000050214818,0.00058447855,0.00050220406,0.00003502715,0.00032697557,0.000020191272],"genre_scores_gemma":[0.99591756,0.00010971108,0.0027877064,0.0007855965,0.00007682441,0.000028658978,0.000101872065,0.000033579505,0.00015848978],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980716,0.000115142655,0.0005029498,0.0006200236,0.0003611896,0.00032909468],"domain_scores_gemma":[0.99885684,0.00017599939,0.00018252395,0.0003994207,0.00019974893,0.00018543727],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00020524532,0.00029168473,0.00037193697,0.00047996393,0.00029251768,0.00043134336,0.0004483309,0.00016136952,0.000017499835],"category_scores_gemma":[0.0000024981955,0.00029673357,0.00015121701,0.0010444109,0.000073746494,0.00036183,0.000010607127,0.00014544395,0.000033401448],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056442637,0.0013328877,0.009803781,0.00022979722,0.00041071002,0.0000030842975,0.0014226356,0.005289365,0.00014026208,0.8387846,0.00084459933,0.14168186],"study_design_scores_gemma":[0.0011138244,0.00069317507,0.0013633049,0.00005739141,0.000053722033,0.0000046386185,0.000029547722,0.9893998,0.0022115419,0.00043970242,0.004262221,0.0003711175],"about_ca_topic_score_codex":0.000008210884,"about_ca_topic_score_gemma":0.000015700061,"teacher_disagreement_score":0.9841105,"about_ca_system_score_codex":0.000022770404,"about_ca_system_score_gemma":0.000041027233,"threshold_uncertainty_score":0.9999485},"labels":[],"label_agreement":null},{"id":"W2913986028","doi":"10.22230/src.2019v10n1a339","title":"Special Issue: Altmetrics","year":2019,"lang":"en","type":"article","venue":"Scholarly and Research Communication","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Altmetrics; Computer science; World Wide Web; Internet privacy; Information retrieval","score_opus":0.0897808304484677,"score_gpt":0.41345933752282565,"score_spread":0.32367850707435797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2913986028","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.036695465,0.0045816493,0.07058485,0.04544634,0.0015165578,0.0014894122,0.000021024909,0.0004297349,0.83923495],"genre_scores_gemma":[0.9038495,0.012095277,0.042972203,0.0015711647,0.0018551251,0.000022408625,0.00013874951,0.000029074135,0.03746652],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99839836,0.0004654003,0.00013353101,0.000195606,0.00062050764,0.00018657072],"domain_scores_gemma":[0.99789083,0.00024879878,0.000034813045,0.0011693599,0.0005616323,0.000094594616],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003012007,0.000051379324,0.00007334845,0.0003427151,0.0003502362,0.0017613127,0.0014419205,0.00005910683,0.00015549979],"category_scores_gemma":[0.00059911644,0.000046544825,0.000016926537,0.0013286509,0.000077980214,0.0028861153,0.0010491188,0.00050506194,0.00084550865],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000060713846,0.000113056485,0.004104103,0.000025679426,0.000012761475,0.0000012739683,0.0009805341,0.0000032144756,0.0002572068,0.6927504,0.08803744,0.21370828],"study_design_scores_gemma":[0.0002488748,0.00006600159,0.007130714,0.000022226464,0.0000010786255,0.0000023760683,0.00016707595,0.008270264,0.00017718051,0.0069663175,0.9768627,0.000085137915],"about_ca_topic_score_codex":0.000025316773,"about_ca_topic_score_gemma":0.000008489786,"teacher_disagreement_score":0.8888253,"about_ca_system_score_codex":0.00003204996,"about_ca_system_score_gemma":0.00006843981,"threshold_uncertainty_score":0.99993247},"labels":[],"label_agreement":null},{"id":"W2914351552","doi":"10.48550/arxiv.1902.01108","title":"2-D Embedding of Large and High-dimensional Data with Minimal Memory and Computational Time Requirements","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Embedding; Visualization; Clustering high-dimensional data; Big data; Multidimensional data; Dimensionality reduction; Graph; MNIST database; Theoretical computer science; Algorithm; Data mining; Artificial intelligence; Deep learning; Cluster analysis","score_opus":0.07453010131495667,"score_gpt":0.2471603090474955,"score_spread":0.17263020773253884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2914351552","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3803221,0.00003484771,0.61872244,0.00006458606,0.000088484856,0.00014579727,0.00037960592,0.00004295814,0.00019918698],"genre_scores_gemma":[0.98752564,0.000019662508,0.011063796,0.0001019374,0.000014626967,6.411233e-8,0.0005998413,0.0000083855575,0.000666048],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987351,0.00006026309,0.00015384975,0.00076045864,0.00014129275,0.00014904025],"domain_scores_gemma":[0.9987497,0.00007362992,0.00022740533,0.00073378417,0.00012832787,0.00008719253],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023443109,0.00016106703,0.0002420165,0.00015944293,0.000073898475,0.0000704371,0.0008010115,0.00008179233,0.000028172051],"category_scores_gemma":[0.000015393665,0.00016540606,0.000019134213,0.00018613653,0.000119689445,0.0005333233,0.0038431762,0.00012970496,0.000013987804],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012645694,0.00042957766,0.013423421,0.000519306,0.00058777584,0.00022175857,0.00038846064,0.7228607,0.00009266608,0.25632143,0.004423071,0.0006053447],"study_design_scores_gemma":[0.00073228596,0.000044594057,0.001670571,0.00010984218,0.000054515564,0.000004892425,0.000021555783,0.9950315,0.000014510277,0.0020435639,0.00008397419,0.00018819745],"about_ca_topic_score_codex":0.000021195377,"about_ca_topic_score_gemma":0.0000039322854,"teacher_disagreement_score":0.6076586,"about_ca_system_score_codex":0.0000231852,"about_ca_system_score_gemma":0.00015072942,"threshold_uncertainty_score":0.67450637},"labels":[],"label_agreement":null},{"id":"W2914667513","doi":"10.1109/beliv.2018.8634072","title":"A Micro-Phenomenological Lens for Evaluating Narrative Visualization","year":2018,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Narrative; Computer science; Visualization; Context (archaeology); Phenomenology (philosophy); Set (abstract data type); Narrative inquiry; Human–computer interaction; User experience design; Data science; Epistemology; Artificial intelligence","score_opus":0.12215381635497205,"score_gpt":0.4192655422254594,"score_spread":0.2971117258704874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2914667513","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005132845,0.0000072581265,0.98912257,0.0005216995,0.00014299288,0.00016787645,0.0000034976752,0.00016574372,0.004735496],"genre_scores_gemma":[0.60266334,0.0000072137773,0.38766673,0.005249132,0.00028094798,0.00003461989,0.000076859505,0.000014367481,0.0040068175],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991867,0.00004977819,0.00017960457,0.00027250435,0.00014116697,0.00017027286],"domain_scores_gemma":[0.999281,0.00006253054,0.00007041542,0.00021624191,0.0003328044,0.000037028058],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003286082,0.000078419005,0.00009100961,0.000062494815,0.00022232751,0.00015624193,0.00034971227,0.00003838645,0.00014740671],"category_scores_gemma":[0.00020980719,0.000063069056,0.000029809578,0.00032264413,0.000057983045,0.00039952056,0.00012364931,0.000022189055,0.00007578306],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000053618983,0.00006198539,0.00008835405,0.0000056875037,0.000012857968,2.3044582e-7,0.0045225928,0.000010183399,0.0039507416,0.979629,0.0071649347,0.004548093],"study_design_scores_gemma":[0.00055170374,0.0006534631,0.000100439545,0.000010173627,0.0000073028273,0.0000028451996,0.0007959265,0.95976096,0.005691456,0.011553064,0.020670274,0.00020240441],"about_ca_topic_score_codex":0.0000018659357,"about_ca_topic_score_gemma":0.0000049757077,"teacher_disagreement_score":0.96807593,"about_ca_system_score_codex":0.000023318555,"about_ca_system_score_gemma":0.000046762536,"threshold_uncertainty_score":0.25718814},"labels":[],"label_agreement":null},{"id":"W2914885989","doi":"10.1109/mlui52768.2018.10075559","title":"Speculative Execution for Guided Visual Analytics","year":2018,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Deutsche Forschungsgemeinschaft","keywords":"Computer science; Analytics; Visual analytics; Visualization; State (computer science); Human–computer interaction; Data science; Artificial intelligence; Programming language","score_opus":0.05728401426596396,"score_gpt":0.3786440452116918,"score_spread":0.32136003094572785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2914885989","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00072730694,0.0000020965022,0.9858174,0.00044895126,0.00017606479,0.00009664751,0.0000041822536,0.000116788295,0.012610617],"genre_scores_gemma":[0.74637353,0.0000056859167,0.23810229,0.003325405,0.00048393346,0.0000067485785,0.000068255926,0.0000125426695,0.011621588],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931717,0.000015083006,0.00016479591,0.00021356967,0.00014192925,0.00014746188],"domain_scores_gemma":[0.99933565,0.000031001655,0.000054572436,0.00023583864,0.0002831695,0.000059782422],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001611693,0.000070685666,0.00008174534,0.00008067294,0.00010170343,0.00013481236,0.00031129975,0.000029369841,0.00007659706],"category_scores_gemma":[0.00008026273,0.00006073319,0.000043344175,0.00036677785,0.000049007263,0.0003246532,0.00010365712,0.000018242534,0.00012726491],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021588194,0.00004409294,0.00011870812,0.0000035095195,0.000015755555,5.111565e-7,0.00014796066,0.000017870396,0.0003213219,0.937813,0.058494687,0.003020431],"study_design_scores_gemma":[0.00023379824,0.00012391592,0.0002514928,0.0000039545985,0.0000071504255,0.0000017085839,0.00003070931,0.93272626,0.007022523,0.007066477,0.05242159,0.00011043554],"about_ca_topic_score_codex":0.0000056558915,"about_ca_topic_score_gemma":0.000009299839,"teacher_disagreement_score":0.9327084,"about_ca_system_score_codex":0.000024253668,"about_ca_system_score_gemma":0.00003888034,"threshold_uncertainty_score":0.24766277},"labels":[],"label_agreement":null},{"id":"W2915817106","doi":"10.5281/zenodo.13681","title":"rletters: v2.0.0","year":2015,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science","score_opus":0.08013290710744612,"score_gpt":0.2872036796203245,"score_spread":0.20707077251287836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2915817106","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009245397,0.00004369383,0.8302662,0.0042893616,0.00021269357,0.00018290334,0.000055237586,0.00174513,0.16228025],"genre_scores_gemma":[0.9484073,0.000120861776,0.024529465,0.010102787,0.0008903358,6.111154e-8,0.0044644913,0.0029844514,0.0085002715],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99867827,0.00019295762,0.00017087469,0.00031819724,0.00038900928,0.00025072263],"domain_scores_gemma":[0.99863553,0.000009708675,0.00006529307,0.0005796153,0.0004599638,0.0002498974],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00061682396,0.000090729925,0.000087998815,0.00017136573,0.0007098203,0.0014751652,0.0018446113,0.000032734963,0.0012979492],"category_scores_gemma":[0.00045049097,0.00009294597,0.000029513834,0.00068672444,0.000069334696,0.0006436329,0.0015243541,0.00011734114,0.01323492],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005191043,0.0000779907,0.0000024804006,0.000010061129,0.000013483743,0.00001424581,0.001015357,0.00006156703,0.0003570822,0.09233473,0.84395874,0.062149044],"study_design_scores_gemma":[0.0003035959,0.00008531034,0.000039860042,0.000007667529,0.000002949084,0.0000520538,0.00011101495,0.011312441,0.00018210505,0.0006691357,0.9871147,0.00011915077],"about_ca_topic_score_codex":0.000004542831,"about_ca_topic_score_gemma":6.446051e-8,"teacher_disagreement_score":0.94748276,"about_ca_system_score_codex":0.00007913067,"about_ca_system_score_gemma":0.000004883337,"threshold_uncertainty_score":0.999615},"labels":[],"label_agreement":null},{"id":"W2916045436","doi":"10.1145/3251351","title":"Session details: Application track A2: context awareness","year":2009,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Session (web analytics); Track (disk drive); Computer science; Context (archaeology); Context awareness; Multimedia; World Wide Web; Operating system; Geology","score_opus":0.03153283561306323,"score_gpt":0.3300389368297955,"score_spread":0.29850610121673227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2916045436","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001805815,0.000022700522,0.99185055,0.0014084172,0.00005161068,0.00006774773,0.0000011351215,0.00021511344,0.0045768837],"genre_scores_gemma":[0.98914057,0.00001330998,0.0063573862,0.0033729111,0.000028896837,0.0000024355973,0.000022696257,0.0000024876,0.0010593117],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99935263,0.000021934738,0.00014603246,0.00021772142,0.00015201936,0.00010965355],"domain_scores_gemma":[0.9994266,0.0000173833,0.000048742175,0.00037495626,0.000068433415,0.0000639004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011307404,0.00006730319,0.0000773364,0.000047793055,0.00007852106,0.00014230353,0.00045157477,0.000033485805,0.00003280099],"category_scores_gemma":[0.000013865311,0.000054716722,0.00002535188,0.0003019442,0.000009779712,0.0004897446,0.000039604965,0.000034026692,0.00020114287],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000015775852,0.00010163472,0.00043683,0.0000034206814,0.0000022753513,0.0000012022153,0.00011472152,0.00004731626,0.0011898945,0.49088955,0.0071535558,0.500058],"study_design_scores_gemma":[0.00039990703,0.00007786365,0.004491473,0.00001711917,0.000005557212,0.0000063303546,0.00009726144,0.87160677,0.0111518195,0.0084591545,0.10342698,0.00025977212],"about_ca_topic_score_codex":0.000011000085,"about_ca_topic_score_gemma":0.000010786893,"teacher_disagreement_score":0.9873347,"about_ca_system_score_codex":0.000013267541,"about_ca_system_score_gemma":0.00003387339,"threshold_uncertainty_score":0.25853518},"labels":[],"label_agreement":null},{"id":"W2916502341","doi":"10.5281/zenodo.14918","title":"feelpp: Feel++ 0.100.0 Beta 3","year":2015,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Canadian Military Institute","funders":"","keywords":"BETA (programming language); Computer science","score_opus":0.08520681964997878,"score_gpt":0.29442424175452775,"score_spread":0.20921742210454897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2916502341","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001281336,0.00009652299,0.66541773,0.003632879,0.00031116625,0.0002926569,0.000112747155,0.0024403837,0.3264146],"genre_scores_gemma":[0.9555688,0.00016881422,0.015344399,0.0034575367,0.00073579326,7.215294e-8,0.0049102427,0.002789049,0.017025309],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99831396,0.00023851452,0.00022169045,0.00040558938,0.00050293247,0.00031730667],"domain_scores_gemma":[0.99815077,0.000013296978,0.000089871086,0.0007322262,0.0006738092,0.00034002168],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007751203,0.000119931756,0.00012049344,0.00021763827,0.0009617714,0.001693854,0.0022655828,0.000046472724,0.0018758938],"category_scores_gemma":[0.0004507123,0.00012309756,0.000039542578,0.0009291803,0.0000872406,0.00071291375,0.001961935,0.00015372621,0.016574463],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000793819,0.00013124742,0.0000045836305,0.00001559993,0.000022265822,0.000022177852,0.0010602347,0.00008421461,0.00028180037,0.1695521,0.7452848,0.083533034],"study_design_scores_gemma":[0.00037793376,0.00012177196,0.000076226526,0.000009976024,0.0000049285354,0.000073950905,0.00012507125,0.011023505,0.00027538495,0.0007379695,0.98701763,0.00015563448],"about_ca_topic_score_codex":0.000009018377,"about_ca_topic_score_gemma":1.7185764e-7,"teacher_disagreement_score":0.95428747,"about_ca_system_score_codex":0.000100117126,"about_ca_system_score_gemma":0.000009070453,"threshold_uncertainty_score":0.9993425},"labels":[],"label_agreement":null},{"id":"W2917889041","doi":"10.5281/zenodo.14911","title":"feelpp: Feel++ 0.100.0 Beta 2","year":2015,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Canadian Military Institute","funders":"","keywords":"Computer science","score_opus":0.08387944784165778,"score_gpt":0.294272060975161,"score_spread":0.21039261313350321,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2917889041","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012742073,0.00009819043,0.65866727,0.003658384,0.0003123854,0.00029434927,0.00011289136,0.0024608239,0.33312148],"genre_scores_gemma":[0.95492065,0.00017427588,0.015524946,0.0035340565,0.0007536701,7.366801e-8,0.005115312,0.0028451195,0.017131869],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99831426,0.00023865292,0.00022169031,0.00040547436,0.0005027227,0.00031722212],"domain_scores_gemma":[0.9981578,0.00001323304,0.00008997369,0.0007319568,0.0006670045,0.00034000457],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00077156664,0.000119912416,0.000120509096,0.00021757485,0.0009619124,0.001694005,0.0022657448,0.000046476627,0.0018864218],"category_scores_gemma":[0.00044583637,0.0001230897,0.0000395379,0.0009288372,0.000087233755,0.0007128543,0.0019629924,0.00015372282,0.016253369],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007738899,0.00012932671,0.0000043789746,0.000015256485,0.000021953887,0.000022150727,0.0010453279,0.00008331132,0.0002681933,0.1703852,0.74478996,0.08322721],"study_design_scores_gemma":[0.00037595088,0.0001220955,0.00007561339,0.000009894452,0.000004959342,0.00007483684,0.00012459692,0.010953692,0.00026875583,0.00074223924,0.98709184,0.00015550654],"about_ca_topic_score_codex":0.0000090071335,"about_ca_topic_score_gemma":1.7171091e-7,"teacher_disagreement_score":0.9536465,"about_ca_system_score_codex":0.000099777404,"about_ca_system_score_gemma":0.00000902883,"threshold_uncertainty_score":0.9993423},"labels":[],"label_agreement":null},{"id":"W2918215490","doi":"","title":"WESt: Visualizing non-Emergency Surgery Waiting Times","year":2015,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Emergency surgery; Computer science; Medicine; Medical emergency; Surgery","score_opus":0.03154456339617047,"score_gpt":0.2737966343610597,"score_spread":0.24225207096488927,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2918215490","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016682023,0.0002994721,0.9208605,0.0056581353,0.00033386287,0.00010963339,0.000008129968,0.00037819435,0.05567],"genre_scores_gemma":[0.94178855,0.00022299844,0.04572096,0.0002618875,0.0000386528,0.000011600955,0.00016902253,0.000030045465,0.011756248],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9966559,0.0015863428,0.0004783196,0.0004784697,0.00046164833,0.00033935023],"domain_scores_gemma":[0.996,0.00063867343,0.00029622705,0.0012668784,0.0015105486,0.0002876782],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0053604455,0.00018061306,0.0002230629,0.00021426541,0.00028466267,0.00040868908,0.0012178305,0.00007310603,0.00014296865],"category_scores_gemma":[0.0018869482,0.00019053105,0.00011988757,0.0009729284,0.00006859492,0.00071501377,0.0006559188,0.00013886395,0.00024259243],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002948643,0.0005451599,0.0125426315,0.00006231402,0.00005117947,0.000014716937,0.01090407,0.00005623634,0.0012001644,0.83679295,0.05089832,0.08692931],"study_design_scores_gemma":[0.0004954985,6.178339e-7,0.0024866285,0.00057840446,0.00002236376,0.000023125911,0.0004921345,0.8918545,0.027531957,0.0052733673,0.07053155,0.00070983364],"about_ca_topic_score_codex":0.000268314,"about_ca_topic_score_gemma":0.00017164103,"teacher_disagreement_score":0.9251066,"about_ca_system_score_codex":0.00005213903,"about_ca_system_score_gemma":0.0002359973,"threshold_uncertainty_score":0.7769631},"labels":[],"label_agreement":null},{"id":"W2921044872","doi":"10.4324/9781315153582-7","title":"Visual Data Mining with Virtual Reality Spaces","year":2017,"lang":"en","type":"book-chapter","venue":"Auerbach Publications eBooks","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Virtual reality; Computer science; Human–computer interaction; Computer graphics (images)","score_opus":0.10918361619299091,"score_gpt":0.350210228194204,"score_spread":0.2410266120012131,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2921044872","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000020004225,0.000027842898,0.258243,0.0019172261,0.00012479261,0.00023279035,0.0002820969,0.00037272405,0.73879755],"genre_scores_gemma":[0.0026246393,0.00003197141,0.009502866,0.0005048688,0.00026477495,0.000022996737,0.0034255378,0.000062991385,0.98355937],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99729735,0.00003822816,0.00045746853,0.0011967744,0.0006761918,0.00033399384],"domain_scores_gemma":[0.99211556,0.0001155059,0.0007763283,0.006286008,0.00045274224,0.0002538817],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0005776665,0.00039619653,0.0003863078,0.0003378456,0.0006706716,0.002178831,0.005744882,0.00024983755,0.00007748616],"category_scores_gemma":[0.00014982127,0.00035736797,0.00006504003,0.000046066114,0.00033870034,0.0012361135,0.0021856527,0.00032349356,0.00016857784],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000018839819,0.000023994213,0.000018859038,0.000012041077,0.00009476126,0.0000047005115,0.00012719566,0.000001942405,0.0000016074908,0.89817363,0.06328136,0.038258],"study_design_scores_gemma":[0.00021816837,0.000103708364,0.000046672216,0.00010153502,0.00007101492,0.00002286505,0.000019446315,0.017482478,0.000007375875,0.0026276817,0.97879386,0.0005051898],"about_ca_topic_score_codex":0.000035441724,"about_ca_topic_score_gemma":0.00024448748,"teacher_disagreement_score":0.9155125,"about_ca_system_score_codex":0.000060746654,"about_ca_system_score_gemma":0.00084008975,"threshold_uncertainty_score":0.9998878},"labels":[],"label_agreement":null},{"id":"W2921184145","doi":"10.1186/s41256-019-0095-1","title":"Optimizing data visualization for reproductive, maternal, newborn, child health, and nutrition (RMNCH&amp;N) policymaking: data visualization preferences and interpretation capacity among decision-makers in Tanzania","year":2019,"lang":"en","type":"article","venue":"Global Health Research and Policy","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Johns Hopkins Bloomberg School of Public Health; Global Affairs Canada; Tanzania Commission for Science and Technology; Johns Hopkins University","keywords":"Reproductive health; Government (linguistics); Child health; Snowball sampling; Public health; Medicine; Environmental health; Nursing; Pediatrics; Population","score_opus":0.1770375326194011,"score_gpt":0.4991860953202507,"score_spread":0.32214856270084957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2921184145","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20725422,0.003626152,0.77379084,0.009407226,0.00024305623,0.003204875,0.0020587218,0.00013603299,0.00027888885],"genre_scores_gemma":[0.9387215,0.013867376,0.04125532,0.0020423802,0.00035423314,0.000040837596,0.0036462226,0.000027750719,0.000044388904],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99645627,0.0004933124,0.00062003644,0.0012260603,0.000552773,0.00065156],"domain_scores_gemma":[0.99755746,0.00022458255,0.00027361632,0.0012140044,0.00027341422,0.00045694603],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028914667,0.0001913768,0.00033917255,0.00055423804,0.000463494,0.0007287426,0.0009109001,0.000097308926,0.0000027523445],"category_scores_gemma":[0.001337054,0.00018960201,0.000011382576,0.0014960554,0.00020218884,0.002405021,0.0012666266,0.00017209994,0.0000036644797],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00066543225,0.0005471339,0.055727974,0.0029546292,0.000056085883,0.0000016822985,0.0067424844,0.00009509504,0.00001518487,0.40691042,0.014736723,0.51154715],"study_design_scores_gemma":[0.002893763,0.0012856155,0.05311028,0.0022400946,0.0000060392317,0.000052684492,0.00095689954,0.8604015,0.0000137459365,0.039436214,0.03914558,0.00045758017],"about_ca_topic_score_codex":0.006349108,"about_ca_topic_score_gemma":0.0035986013,"teacher_disagreement_score":0.8603064,"about_ca_system_score_codex":0.00021619056,"about_ca_system_score_gemma":0.00066001446,"threshold_uncertainty_score":0.95979947},"labels":[],"label_agreement":null},{"id":"W2921869280","doi":"10.1145/3294109.3295627","title":"You say Potato, I say Po-Data","year":2019,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; Alberta Innovates - Technology Futures","keywords":"Visualization; Computer science; Leverage (statistics); Annotation; Human–computer interaction; Data visualization; Block (permutation group theory); Information visualization; Fidelity; Usability; World Wide Web; Computer graphics (images); Multimedia; Artificial intelligence","score_opus":0.034638465513602855,"score_gpt":0.3087285460835585,"score_spread":0.27409008056995565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2921869280","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008830479,0.000028132357,0.90677756,0.0036758885,0.00041949507,0.00008377996,0.000023317854,0.00023525023,0.087873556],"genre_scores_gemma":[0.47626162,0.00009196757,0.13622211,0.054652214,0.00029032803,0.0000030194442,0.0008983554,0.0000443626,0.33153602],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999147,0.000023381936,0.00013268962,0.00033739014,0.0002053522,0.00015417454],"domain_scores_gemma":[0.9983043,0.000027320437,0.000036009835,0.0015215089,0.000039154536,0.00007172322],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00021189253,0.00007091794,0.00008602579,0.00005360602,0.000032584263,0.00021262535,0.0017991648,0.000025803822,0.0007389658],"category_scores_gemma":[0.00003033747,0.00005718168,0.000019419162,0.00028568727,0.000011285027,0.00075280824,0.00085737987,0.000044155357,0.0036000926],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.904334e-7,0.000077225726,0.0035321896,0.000012020049,0.000017916336,0.0000055756122,0.00012705545,0.00003738957,0.00016596822,0.69710076,0.27999538,0.018927531],"study_design_scores_gemma":[0.00025416783,0.000028078497,0.0010200896,0.000008363608,0.000004032563,0.0000043894006,0.000039701266,0.5386345,0.00040151022,0.0020736766,0.4573357,0.00019578486],"about_ca_topic_score_codex":0.00002201808,"about_ca_topic_score_gemma":0.000010039512,"teacher_disagreement_score":0.77055544,"about_ca_system_score_codex":0.000006056332,"about_ca_system_score_gemma":0.000045099183,"threshold_uncertainty_score":0.9971757},"labels":[],"label_agreement":null},{"id":"W2922207040","doi":"10.1145/3295750.3298914","title":"Relevance-driven Clustering for Visual Information Retrieval on Twitter","year":2019,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Cluster analysis; Relevance (law); Information retrieval; Ranking (information retrieval); Metric (unit); Matching (statistics); Visualization; Task (project management); Learning to rank; Data mining; Artificial intelligence","score_opus":0.021478513558595473,"score_gpt":0.3050415692701416,"score_spread":0.2835630557115461,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2922207040","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0072898106,6.261356e-7,0.9844513,0.0004857739,0.00034297325,0.00018235434,0.0000029187456,0.00011286359,0.0071314084],"genre_scores_gemma":[0.9319414,0.000010342363,0.050344523,0.010779344,0.000119920434,0.000006103091,0.00011073743,0.000011914819,0.006675712],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999405,0.000008939766,0.00016398239,0.00012272959,0.000172163,0.00012713499],"domain_scores_gemma":[0.99955153,0.00005631058,0.00005886106,0.00022438761,0.00007210243,0.000036816797],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000103082944,0.00006448155,0.0000728868,0.000082596714,0.00003825039,0.00018998224,0.0002732862,0.00003152981,0.000048008806],"category_scores_gemma":[0.00004826559,0.00005470333,0.000032377822,0.00016748373,0.0000055709356,0.0011176986,0.000102981176,0.000037387625,0.00070252037],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025429914,0.00023714508,0.0025968656,0.0003521513,0.000075194985,0.0000019641996,0.0030300522,0.016787473,0.0026738136,0.79868275,0.10862459,0.06668371],"study_design_scores_gemma":[0.0003885041,0.00015095706,0.00013250472,0.000013998897,0.0000013524066,7.9350264e-7,0.000040702686,0.9130293,0.0011972876,0.00016028064,0.08479042,0.00009388773],"about_ca_topic_score_codex":9.972551e-7,"about_ca_topic_score_gemma":7.2507765e-7,"teacher_disagreement_score":0.93410677,"about_ca_system_score_codex":0.000023910528,"about_ca_system_score_gemma":0.000020413481,"threshold_uncertainty_score":0.9029712},"labels":[],"label_agreement":null},{"id":"W2922208991","doi":"10.1016/j.cose.2019.03.005","title":"An evaluation framework for network security visualizations","year":2019,"lang":"en","type":"article","venue":"Computers & Security","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Visualization; Network security; Categorization; Taxonomy (biology); Ranking (information retrieval); Data science; Data mining; Audit; Data visualization; Computer security; Information retrieval; Artificial intelligence","score_opus":0.027225201343472772,"score_gpt":0.35597988501045824,"score_spread":0.32875468366698546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2922208991","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0074536656,0.00011470314,0.988533,0.00043478646,0.0019213224,0.0007978935,0.00002697178,0.00034238186,0.0003752335],"genre_scores_gemma":[0.8813972,0.000017516406,0.115383275,0.0021934821,0.0005094292,0.00003499409,0.00042625208,0.00002254715,0.000015317455],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977949,0.0002609546,0.000363683,0.0006659099,0.000507181,0.00040733194],"domain_scores_gemma":[0.99779505,0.00026843324,0.00019376936,0.0011025391,0.00044504227,0.00019519294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010965419,0.00020926469,0.0002581053,0.00010423733,0.00025085898,0.0005031822,0.0012064421,0.00014363219,0.00007669268],"category_scores_gemma":[0.00010010823,0.00022367436,0.00011437678,0.0007846269,0.000036998066,0.001025191,0.00024455905,0.00015887481,0.000082473794],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005398852,0.00019450007,0.0013917383,0.000038317154,0.000026235015,5.7036897e-7,0.0014778029,0.0093677025,0.0000065284535,0.9726348,0.011900743,0.0029556472],"study_design_scores_gemma":[0.00032781024,0.000104145205,0.0004087741,0.00003774625,0.000016811586,0.0000016718585,0.000024993113,0.70562756,0.000028795597,0.27915138,0.014058161,0.00021217126],"about_ca_topic_score_codex":0.000007771665,"about_ca_topic_score_gemma":0.000011723684,"teacher_disagreement_score":0.8739435,"about_ca_system_score_codex":0.0000761519,"about_ca_system_score_gemma":0.00014658213,"threshold_uncertainty_score":0.91211754},"labels":[],"label_agreement":null},{"id":"W2923430727","doi":"10.5753/sibgrapi.est.2020.12995","title":"Visualization of Multivariate Data on Surfaces","year":2020,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures; CMG Reservoir Simulation Foundation","keywords":"Computer science; Visualization; Multivariate statistics; Rendering (computer graphics); Data visualization; Focus (optics); Context (archaeology); Computer graphics (images); Data science; Artificial intelligence; Machine learning; Geology","score_opus":0.10057468751735535,"score_gpt":0.3663377616322531,"score_spread":0.26576307411489775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2923430727","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004870629,0.000005220674,0.99510986,0.0012675581,0.00004518111,0.0000368181,0.000017094868,0.00009310879,0.0029380769],"genre_scores_gemma":[0.9742073,0.000015900228,0.022093382,0.003210086,0.000025960082,2.5166688e-7,0.00019053138,0.0000054242787,0.0002511601],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993936,0.000030344052,0.00013993485,0.00021283462,0.00016518754,0.000058120586],"domain_scores_gemma":[0.99936575,0.000032731412,0.000059375114,0.00044993398,0.00004326972,0.000048966318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000099408026,0.000046260906,0.000072786795,0.000024271092,0.000019938396,0.00005149186,0.00091462483,0.00001527132,0.00004632332],"category_scores_gemma":[0.00013340868,0.000037969392,0.000009324676,0.00034192504,0.0000107171745,0.000406021,0.00037983558,0.000017684657,0.000055478136],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000031437567,0.00007187756,0.000405482,0.000017776374,0.000011685878,0.0000010473234,0.00033613804,0.0010543268,0.0014136592,0.9815358,0.011746374,0.0034026692],"study_design_scores_gemma":[0.0001247278,0.000040810388,0.00027852406,0.000004822597,0.0000020371488,8.747918e-8,0.000011460224,0.9808859,0.003453549,0.00010446954,0.015043321,0.00005027743],"about_ca_topic_score_codex":0.000012602149,"about_ca_topic_score_gemma":0.0000018926911,"teacher_disagreement_score":0.98143137,"about_ca_system_score_codex":0.000002135377,"about_ca_system_score_gemma":0.000020744588,"threshold_uncertainty_score":0.16996157},"labels":[],"label_agreement":null},{"id":"W2940472653","doi":"10.1145/3290605.3300417","title":"Automating the Intentional Encoding of Human-Designable Markers","year":2019,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"ENCODE; Encoding (memory); Computer science; Overlay; Tree (set theory); Quality (philosophy); Artificial intelligence; Human–computer interaction; Multimedia; Programming language; Mathematics","score_opus":0.0280723387972699,"score_gpt":0.3008729520147728,"score_spread":0.27280061321750293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2940472653","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027357409,0.00001098949,0.8901208,0.0003875256,0.00016467212,0.000102209066,0.0000011556716,0.00010864627,0.08174658],"genre_scores_gemma":[0.9846824,0.0000012774005,0.008525606,0.00028229045,0.0000086962955,8.440554e-7,0.000002815005,0.0000022272457,0.0064938897],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99950254,0.00002733823,0.00013883588,0.00009559131,0.0001584305,0.00007725459],"domain_scores_gemma":[0.9995923,0.000057491994,0.000065450724,0.00021814957,0.000051561787,0.000015066441],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033203265,0.000036151374,0.000053262287,0.00003845264,0.00006005164,0.000073263676,0.00046039905,0.0000114333725,0.00044476255],"category_scores_gemma":[0.000022894963,0.000023599301,0.000030492392,0.0001933061,0.000017025983,0.00025193597,0.00014849407,0.000030007113,0.000070101814],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.3394485e-7,0.000017697845,0.0040614554,0.000015919364,0.000011261057,2.3878778e-7,0.00012232353,0.0001214297,0.0071430667,0.98384935,0.0031461327,0.0015108117],"study_design_scores_gemma":[0.00018760045,0.000043941545,0.00464464,0.000046311314,0.0000039152033,0.000002434101,0.0003659811,0.98639023,0.004087146,0.0030508756,0.001078816,0.000098083925],"about_ca_topic_score_codex":0.00001221069,"about_ca_topic_score_gemma":0.0000012036303,"teacher_disagreement_score":0.9862688,"about_ca_system_score_codex":0.000008271956,"about_ca_system_score_gemma":0.000021218515,"threshold_uncertainty_score":0.4869838},"labels":[],"label_agreement":null},{"id":"W2941610467","doi":"10.1145/3290605.3300423","title":"A Lie Reveals the Truth","year":2019,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Leverage (statistics); Computer science; Perception; Exaggeration; Presentation (obstetrics); Human–computer interaction; Context (archaeology); Range (aeronautics); Chart; Artificial intelligence; Psychology; Mathematics","score_opus":0.02160802881580311,"score_gpt":0.28708637996077296,"score_spread":0.26547835114496987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2941610467","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010511163,0.000021919972,0.8586841,0.0037942466,0.0005757115,0.00009441841,0.0000016241768,0.00016963374,0.12614717],"genre_scores_gemma":[0.9629302,0.000007784974,0.0046768766,0.0045577013,0.000031537216,9.695005e-7,0.0000023411465,0.0000025808758,0.027789982],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996636,0.0000165311,0.000060918916,0.00009455967,0.00009662296,0.000067802255],"domain_scores_gemma":[0.9994926,0.00006712329,0.000018139188,0.00038358598,0.0000183465,0.000020191701],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00012700133,0.000028639131,0.000035665616,0.000015077783,0.00002539752,0.000117252115,0.00051759375,0.000009190281,0.00023566931],"category_scores_gemma":[0.000027770384,0.000015436572,0.000016869406,0.00017246681,0.0000065755858,0.00015427392,0.00011558241,0.000022407223,0.0018180166],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.0236846e-8,0.0000053765216,0.00030317172,0.0000011096522,0.0000016830286,2.0854569e-7,0.00004699198,0.000003737519,0.000029321933,0.9816526,0.016916778,0.0010389414],"study_design_scores_gemma":[0.00044339694,0.000075658274,0.008878162,0.00001758901,0.000005797718,0.000010321726,0.00015333114,0.434929,0.0011380047,0.030636579,0.52342755,0.0002846356],"about_ca_topic_score_codex":0.0000024002763,"about_ca_topic_score_gemma":6.646531e-7,"teacher_disagreement_score":0.95241904,"about_ca_system_score_codex":0.0000031374282,"about_ca_system_score_gemma":0.000011769788,"threshold_uncertainty_score":0.9989592},"labels":[],"label_agreement":null},{"id":"W2941752661","doi":"10.1145/3290605.3300771","title":"Saliency Deficit and Motion Outlier Detection in Animated Scatterplots","year":2019,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Outlier; Artificial intelligence; Computer science; Motion (physics); Anomaly detection; Computer vision; Visualization; Pattern recognition (psychology); Position (finance); Multivariate statistics; Salient; Machine learning","score_opus":0.011111353170032895,"score_gpt":0.25784608438183043,"score_spread":0.24673473121179754,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2941752661","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.47262216,0.0000074234085,0.5249549,0.00012034984,0.000090434085,0.00007009159,6.062223e-7,0.00009697601,0.002037005],"genre_scores_gemma":[0.9981292,0.0000073092647,0.0012076898,0.00026043138,0.0000046325617,0.0000010167671,0.000003420427,0.0000032241194,0.00038308627],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99949855,0.000020896869,0.00011140095,0.00018514467,0.00009061567,0.00009337017],"domain_scores_gemma":[0.99975055,0.000009795236,0.000026335203,0.00016306767,0.000023268942,0.00002699295],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001088529,0.00004995902,0.00005862647,0.000115355,0.000020092082,0.00010245869,0.00012430517,0.000026712305,0.000035993176],"category_scores_gemma":[0.000010332385,0.00004481576,0.000008611765,0.0003129263,0.000006788694,0.0004540455,0.0000724708,0.000031885174,0.00017127128],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013698107,0.0004183144,0.41447398,0.00011581493,0.000017679034,0.000008848969,0.0016335023,0.00052347843,0.0459744,0.27504942,0.00057614536,0.26119474],"study_design_scores_gemma":[0.00039324202,0.00005689901,0.11399286,0.0000138067335,0.0000019015864,0.000007087544,0.00006470156,0.8799641,0.003908814,0.0007782621,0.0006720287,0.00014630487],"about_ca_topic_score_codex":0.00003544044,"about_ca_topic_score_gemma":0.00005410451,"teacher_disagreement_score":0.8794406,"about_ca_system_score_codex":0.000014906786,"about_ca_system_score_gemma":0.000006086484,"threshold_uncertainty_score":0.2201403},"labels":[],"label_agreement":null},{"id":"W2942053434","doi":"10.3233/978-1-61499-951-5-325","title":"Challenges in Displaying Health Data on Small Smartwatch Screens","year":2019,"lang":"en","type":"article","venue":"Studies in health technology and informatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Smartwatch; Computer science; Human–computer interaction; Global Positioning System; Accelerometer; Gyroscope; Visualization; Key (lock); Wearable computer; Data science; Computer security; Embedded system; Artificial intelligence; Engineering; Telecommunications","score_opus":0.22984448490093295,"score_gpt":0.422252618308351,"score_spread":0.19240813340741802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2942053434","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17016983,0.123591885,0.116455995,0.55968976,0.0043442515,0.005704955,0.00024586005,0.0021013431,0.017696109],"genre_scores_gemma":[0.7147457,0.2176501,0.053020455,0.0143290125,0.000030011428,0.000028791217,0.00008049903,0.000018056304,0.000097389886],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99847645,0.000051110073,0.00073081715,0.00023136938,0.00011930476,0.00039096398],"domain_scores_gemma":[0.9986038,0.00013016797,0.00025049722,0.00093753234,0.000030455687,0.00004754203],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014123062,0.00012755021,0.00037589148,0.0006302277,0.00012276728,0.000020119794,0.00082192675,0.00008772951,6.470195e-7],"category_scores_gemma":[0.00019935748,0.00011106766,0.000007941773,0.0007396492,0.00011407974,0.00040364545,0.0012782615,0.0003169444,0.00002021197],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000049153255,0.00008327602,0.02748664,0.0016543339,0.000020309932,0.0000026842695,0.008563728,0.00008477124,6.680578e-8,0.68250376,0.0012305852,0.27836493],"study_design_scores_gemma":[0.0037669556,0.0026031549,0.028010696,0.0047755125,0.0000049959503,0.000065459004,0.08664657,0.6563998,0.000010690437,0.026079327,0.19059771,0.0010391154],"about_ca_topic_score_codex":0.000022012659,"about_ca_topic_score_gemma":0.0005197207,"teacher_disagreement_score":0.65642446,"about_ca_system_score_codex":0.00008162155,"about_ca_system_score_gemma":0.0001070342,"threshold_uncertainty_score":0.45292076},"labels":[],"label_agreement":null},{"id":"W2942658839","doi":"10.1109/mcg.2019.2914844","title":"Broadening Intellectual Diversity in Visualization Research Papers","year":2019,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Visualization; Computer science; Diversity (politics); Data science; Information visualization; Data visualization; Creative visualization; Human–computer interaction; Artificial intelligence; Sociology","score_opus":0.058744361171354884,"score_gpt":0.34124879793544255,"score_spread":0.28250443676408765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2942658839","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.032314327,0.000040660998,0.96608275,0.00016960887,0.000093328876,0.00029134992,0.0000035576486,0.000076071265,0.0009283547],"genre_scores_gemma":[0.99724144,0.0002244719,0.0018775384,0.00041853913,0.00006370653,0.000018288905,0.000020422945,0.0000067596948,0.00012886089],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989045,0.00007725787,0.00016781781,0.00038155649,0.00027201526,0.0001968362],"domain_scores_gemma":[0.99919754,0.00021010397,0.00003864324,0.0003527961,0.00012408517,0.00007683139],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040197952,0.000084093575,0.000103959916,0.00040541243,0.00030500581,0.0001984875,0.00055313547,0.000056508492,0.000011472884],"category_scores_gemma":[0.000007757512,0.0000880093,0.000026905975,0.0013479721,0.000071995666,0.0002392315,0.0006015803,0.0001669317,0.0000516453],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000013792321,0.0000848724,0.010084136,0.000019985662,0.000008435422,9.477502e-7,0.0011325019,0.00018825878,0.00012094333,0.9732706,0.0009742213,0.0141137],"study_design_scores_gemma":[0.0004023698,0.00007150349,0.0074420935,0.00003427626,0.0000036693712,0.000005369905,0.00008734642,0.92867446,0.00011714602,0.009244081,0.05367476,0.00024292905],"about_ca_topic_score_codex":0.00003141134,"about_ca_topic_score_gemma":0.0000191282,"teacher_disagreement_score":0.9649271,"about_ca_system_score_codex":0.000019496056,"about_ca_system_score_gemma":0.000027639466,"threshold_uncertainty_score":0.35889152},"labels":[],"label_agreement":null},{"id":"W2945063489","doi":"","title":"A Constructive Classroom Exercise for Teaching InfoVis","year":2016,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"U.S. Consumer Product Safety Commission","keywords":"Visualization; Computer science; Constructive; Class (philosophy); Software deployment; Human–computer interaction; Multimedia; Mathematics education; Artificial intelligence; Process (computing); Software engineering; Psychology; Programming language","score_opus":0.015358916115727192,"score_gpt":0.2660995136534438,"score_spread":0.2507405975377166,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2945063489","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009434502,0.00020937051,0.96420884,0.0074892375,0.00045021257,0.0005324195,0.00021811428,0.00037534145,0.025572987],"genre_scores_gemma":[0.25969532,0.0005660257,0.71729225,0.0005672998,0.00011136875,0.00026996876,0.0010083478,0.00009429431,0.020395137],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9957384,0.0019936305,0.000558917,0.00092076533,0.00040494665,0.0003833271],"domain_scores_gemma":[0.9931121,0.0014465272,0.0006256639,0.0026059148,0.0019979589,0.00021186641],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.004150855,0.00033662116,0.00041134722,0.00026688902,0.0004433712,0.0009118865,0.002765067,0.00025994578,0.00003459449],"category_scores_gemma":[0.0019516682,0.00031729502,0.00024634445,0.00023593752,0.00025121585,0.00044932507,0.0027451538,0.00045165615,0.000041798583],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000044767057,0.00016934288,0.00028785793,0.00011378158,0.000051075775,0.0000014234112,0.0044079316,0.000009599562,0.00019230765,0.8714339,0.004798661,0.11852964],"study_design_scores_gemma":[0.002913426,0.0000016962083,0.0007796033,0.010260876,0.00018222202,0.000025106083,0.0004239775,0.4188906,0.031518873,0.28064215,0.25210503,0.0022564433],"about_ca_topic_score_codex":0.00009519411,"about_ca_topic_score_gemma":0.000099737874,"teacher_disagreement_score":0.59079176,"about_ca_system_score_codex":0.000120823606,"about_ca_system_score_gemma":0.00044575974,"threshold_uncertainty_score":0.99992794},"labels":[],"label_agreement":null},{"id":"W2946002390","doi":"10.1117/12.2519882","title":"Deep learning visual programming","year":2019,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Moncton","funders":"","keywords":"Computer science; Python (programming language); Deep learning; Artificial intelligence; Toolbox; Artificial neural network; Machine learning; Deep neural networks; Software; Software engineering; Programming language","score_opus":0.013006452836806912,"score_gpt":0.29803277795077393,"score_spread":0.285026325113967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2946002390","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003489931,0.00000987967,0.98398894,0.00010026391,0.000100087986,0.000047267145,2.1846487e-8,0.00024351734,0.012020073],"genre_scores_gemma":[0.9336075,0.0000052325554,0.052771665,0.00055395014,0.000030067133,0.0000016076073,0.0000089124715,0.0000062454915,0.013014805],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994841,0.000018627074,0.00008146057,0.00015528355,0.00013247425,0.00012801126],"domain_scores_gemma":[0.9997429,0.000017597604,0.000026425081,0.00013986572,0.000030854655,0.000042356747],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00010721993,0.000045658107,0.00005307989,0.000044201464,0.000040163784,0.00020246614,0.00027288988,0.000017474891,0.0001702577],"category_scores_gemma":[0.00001838764,0.00003895179,0.000021052661,0.00024532145,0.0000060182674,0.00033567275,0.00014181467,0.000052285133,0.0010926194],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.680074e-7,0.000070402,0.019554978,0.000015056471,0.000011349763,0.00000389709,0.00037146942,0.00080744346,0.00024309143,0.48101214,0.00034807547,0.4975613],"study_design_scores_gemma":[0.00009354134,0.000045228855,0.00035094886,0.0000033338201,8.810713e-7,0.000001946047,0.00007016964,0.88703215,0.00017781352,0.00008073474,0.112066984,0.00007625558],"about_ca_topic_score_codex":0.0000037887612,"about_ca_topic_score_gemma":0.0000017026775,"teacher_disagreement_score":0.9312173,"about_ca_system_score_codex":0.0000070078645,"about_ca_system_score_gemma":0.000011114756,"threshold_uncertainty_score":0.99968517},"labels":[],"label_agreement":null},{"id":"W2948762444","doi":"10.1145/3299869.3320232","title":"GraphWrangler","year":2019,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Scripting language; SQL; Relational database management system; Visualization; Programming language; Data visualization; Graph; Pipeline (software); Analytics; Software; Process (computing); Relational database; Database; Theoretical computer science; Data mining","score_opus":0.013744559453490382,"score_gpt":0.2676976218942785,"score_spread":0.2539530624407881,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2948762444","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016822343,0.0000054395146,0.8521418,0.0003904782,0.00014871985,0.000023709428,2.9783115e-7,0.00011742367,0.14548993],"genre_scores_gemma":[0.9187689,0.0000076243828,0.028368268,0.00533912,0.000019461555,7.166625e-7,0.000006938488,0.0000037848463,0.047485184],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99975985,0.000004558504,0.00003774887,0.00007940195,0.00006747893,0.00005098612],"domain_scores_gemma":[0.99973446,0.0000059042604,0.000007752406,0.00021657118,0.000014616348,0.000020679014],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000036268983,0.000021128873,0.000025686923,0.000029881143,0.00000894421,0.000052113068,0.00025237506,0.000007753184,0.00050897204],"category_scores_gemma":[0.000002379281,0.000016321288,0.000013637259,0.00017097982,0.0000029373746,0.00020205523,0.000055819848,0.000011710577,0.001961747],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.8010006e-8,0.000007108877,0.0017661119,9.745783e-7,0.0000013416792,2.8572455e-7,0.000018118486,0.000004106846,0.00006571004,0.98367155,0.012418273,0.0020463655],"study_design_scores_gemma":[0.00031727372,0.000035590027,0.0037411356,0.000004560822,0.0000013607506,0.0000033869585,0.000022614222,0.3284062,0.0012724146,0.009659133,0.65635574,0.00018060333],"about_ca_topic_score_codex":0.0000019147874,"about_ca_topic_score_gemma":7.8675765e-7,"teacher_disagreement_score":0.97401243,"about_ca_system_score_codex":0.000001582145,"about_ca_system_score_gemma":0.000005993547,"threshold_uncertainty_score":0.99881536},"labels":[],"label_agreement":null},{"id":"W2948783326","doi":"","title":"Research Guides: NOVA Reads (NOVA Online) 2018-2019: Useful Websites","year":2019,"lang":"en","type":"libguides","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Nova (rocket); Nova scotia; Computer science; Geography; Engineering; Aeronautics","score_opus":0.17680736149308027,"score_gpt":0.4252342641557368,"score_spread":0.24842690266265652,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2948783326","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00005262967,0.0017517117,0.19197837,0.014924071,0.014129757,0.0011778192,0.002052037,0.0014515462,0.7724821],"genre_scores_gemma":[0.00009548884,0.0015560339,0.038407065,0.005830015,0.0021146545,0.0000046252167,0.0047855945,0.00011369685,0.94709283],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9938446,0.000336188,0.0010715071,0.0015390778,0.0021509137,0.0010576958],"domain_scores_gemma":[0.99338454,0.0007066392,0.00034660613,0.003632738,0.0016255574,0.00030393308],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002080257,0.0005691205,0.0007759128,0.0014846904,0.00019636915,0.0016341992,0.0064266967,0.0005967492,0.005266532],"category_scores_gemma":[0.00070893846,0.00048286404,0.00024104095,0.0020073086,0.00026815067,0.0011855683,0.0028879899,0.0011455951,0.020175036],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002142837,0.000108506,0.00009349325,0.00012914374,0.00006509496,0.00001898956,0.00010055509,0.000011090866,0.0000143476045,0.033829004,0.9632542,0.0023734143],"study_design_scores_gemma":[0.0002520021,0.00013496165,0.0000610187,0.00030122572,0.000018685614,0.000012491141,0.00011282353,0.017171606,0.00010578887,0.0008329515,0.98036903,0.0006274103],"about_ca_topic_score_codex":0.0010376853,"about_ca_topic_score_gemma":0.0006021442,"teacher_disagreement_score":0.17461076,"about_ca_system_score_codex":0.0001869682,"about_ca_system_score_gemma":0.0014038581,"threshold_uncertainty_score":0.9997623},"labels":[],"label_agreement":null},{"id":"W2949910996","doi":"","title":"Perception-action coupling in a prediction motion task","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer vision; Ball (mathematics); Computer science; Artificial intelligence; Mathematics; Trajectory; Perception; Psychology; Geometry","score_opus":0.0321094143362258,"score_gpt":0.2966363299735697,"score_spread":0.2645269156373439,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949910996","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.060003523,0.0000019265954,0.9380697,0.0003503464,0.00015995865,0.000084466476,8.524155e-7,0.00014957145,0.0011796372],"genre_scores_gemma":[0.9937786,0.000020040045,0.005215164,0.00022877834,0.000038970786,0.000010717461,0.000028227769,0.000002917995,0.0006766113],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99947774,0.000011013327,0.00014054052,0.00015822606,0.00012185576,0.000090600166],"domain_scores_gemma":[0.999718,0.000008585298,0.000028068836,0.00015713563,0.000054095948,0.000034123404],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010426825,0.000046427343,0.000044585857,0.000114351526,0.00004200237,0.00015589107,0.00013201644,0.000031668213,0.00024602914],"category_scores_gemma":[0.00001576044,0.00004309283,0.000014756809,0.00030230902,0.000007652923,0.0012225227,0.0000370537,0.000044936132,0.00040653732],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006325241,0.0010542611,0.23706745,0.000109645785,0.000034867342,0.000005424702,0.0032354465,0.07906304,0.06121099,0.2128416,0.055772986,0.34959796],"study_design_scores_gemma":[0.000097978955,0.000011673973,0.065449424,0.000005348576,7.314647e-7,0.0000012471669,0.00014617642,0.93309385,0.00005245403,0.0005479844,0.00054966746,0.00004346177],"about_ca_topic_score_codex":0.00016422551,"about_ca_topic_score_gemma":0.000019403788,"teacher_disagreement_score":0.93377507,"about_ca_system_score_codex":0.000048173304,"about_ca_system_score_gemma":0.000010612147,"threshold_uncertainty_score":0.522535},"labels":[],"label_agreement":null},{"id":"W2950318938","doi":"10.1007/978-3-030-22514-8_26","title":"On Visualization of Movements for Monitoring Older Adults","year":2019,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Movement (music); Wearable computer; Granularity; Visualization; Sample (material); Population; Tracking (education); Residence; Human–computer interaction; Artificial intelligence; Embedded system","score_opus":0.01977603093422682,"score_gpt":0.302466458360422,"score_spread":0.2826904274261952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950318938","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00013050462,0.000057264544,0.9968392,0.000043467684,0.0016778838,0.0004906496,0.00001542912,0.000055063898,0.0006904887],"genre_scores_gemma":[0.6460616,0.0001653727,0.3449621,0.0032269692,0.0010804214,0.000029810819,0.00015665275,0.00015627944,0.0041607968],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975308,0.000013406824,0.00045609538,0.00089848845,0.00078692153,0.00031426593],"domain_scores_gemma":[0.99807525,0.0002560592,0.0003604992,0.00087793556,0.00035639424,0.00007383878],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003997152,0.00029365058,0.00035048113,0.0006524621,0.00008924239,0.00020067517,0.0017524557,0.00016727588,0.00000896439],"category_scores_gemma":[0.000102204256,0.00027585265,0.000093,0.00041355647,0.00012519734,0.0003966382,0.00047629053,0.00015503076,0.00001639974],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024492965,0.00015187621,0.00038007856,0.0003829212,0.000028057124,0.0000057199886,0.001462489,0.03825327,0.00012386338,0.5321906,0.000088631845,0.426908],"study_design_scores_gemma":[0.0006647754,0.0003025346,0.00015144766,0.0016128722,0.0000060528923,0.0000015551982,3.262488e-7,0.9589339,0.0052044378,0.032154743,0.0005404854,0.0004268531],"about_ca_topic_score_codex":0.0000038058515,"about_ca_topic_score_gemma":0.000002897882,"teacher_disagreement_score":0.92068064,"about_ca_system_score_codex":0.00012281381,"about_ca_system_score_gemma":0.00024738384,"threshold_uncertainty_score":0.99996936},"labels":[],"label_agreement":null},{"id":"W2950847613","doi":"10.1109/icde.2019.00220","title":"IVLG: Interactive Visualization of Large Graphs","year":2019,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Visualization; Search engine indexing; Aggregate (composite); Schema (genetic algorithms); User interface; Graph; Abstraction; Information retrieval; Data mining; Theoretical computer science","score_opus":0.012764457545929293,"score_gpt":0.32365316222217455,"score_spread":0.31088870467624524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950847613","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009617797,0.0000056798604,0.96913457,0.00007936602,0.00018092403,0.00006613728,0.0000041355656,0.00006917078,0.02084224],"genre_scores_gemma":[0.99530053,0.000007113441,0.0023757874,0.0005397004,0.000004836749,6.278574e-7,0.000023102115,0.0000033528563,0.0017449531],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994645,0.000025678832,0.00014024894,0.0001402372,0.0001437183,0.00008558165],"domain_scores_gemma":[0.99950826,0.00002727314,0.00007492356,0.0002593236,0.00010331657,0.000026905906],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011055893,0.000048364902,0.00008157537,0.000108782624,0.000015069336,0.00003980972,0.00030288548,0.00001997101,0.0003013626],"category_scores_gemma":[0.000021214302,0.000041334137,0.000031586642,0.00041554682,0.000007213506,0.00051683484,0.00012962124,0.00002166681,0.0001753711],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010391935,0.000063033025,0.0041762176,0.000008057802,0.000007644269,2.1157975e-7,0.0002451275,0.000010312127,0.00054097024,0.99302644,0.0014882745,0.00043265466],"study_design_scores_gemma":[0.00089011213,0.00017167973,0.0053558364,0.000047673868,0.000008379618,0.0000027866229,0.00035257885,0.91874945,0.029062241,0.010162112,0.03491659,0.00028053814],"about_ca_topic_score_codex":0.000007235117,"about_ca_topic_score_gemma":0.0000040822815,"teacher_disagreement_score":0.9856827,"about_ca_system_score_codex":0.0000064868073,"about_ca_system_score_gemma":0.000017813249,"threshold_uncertainty_score":0.32997093},"labels":[],"label_agreement":null},{"id":"W2951048064","doi":"10.1103/physreve.99.062701","title":"Machine learning topological defects of confined liquid crystals in two dimensions","year":2019,"lang":"en","type":"article","venue":"Physical review. E","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Compute Canada","keywords":"Artificial neural network; Computer science; Lattice (music); Liquid crystal; Sorting; Topology (electrical circuits); Topological sorting; Artificial intelligence; Topological defect; Square lattice; Field (mathematics); Algorithm; Physics; Statistical physics; Optics; Condensed matter physics; Mathematics; Combinatorics","score_opus":0.026102187097586816,"score_gpt":0.37031237204369283,"score_spread":0.344210184946106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951048064","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91218954,0.0077329595,0.064812444,0.0020791152,0.00020554052,0.0008361106,0.000013598648,0.00019504165,0.011935676],"genre_scores_gemma":[0.9971353,0.0014264805,0.00045975987,0.0008517755,0.000015304451,0.0000033266745,0.000013411146,0.0000039848615,0.000090656635],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990935,0.0001502047,0.00022532619,0.00021314992,0.00017630159,0.00014155476],"domain_scores_gemma":[0.99933195,0.00017499889,0.000100420926,0.00028821416,0.00004609783,0.000058304133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022294461,0.00008745405,0.00033969316,0.000035929075,0.00001841297,0.000013859472,0.00031947184,0.0000110964975,0.00007335893],"category_scores_gemma":[0.0002947875,0.00006541062,0.00008662567,0.00040055808,0.000028235057,0.000118251824,0.00022184793,0.00012521265,0.00014354342],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000082200495,0.00036584502,0.0036945818,0.00037214736,0.000011379666,0.0000073627743,0.00010699807,0.00044475164,0.026274161,0.9666707,0.0002502411,0.0017936077],"study_design_scores_gemma":[0.0018792808,0.0013507823,0.0027913982,0.002843024,0.00006743458,0.000009465514,0.000019802981,0.89263296,0.011936877,0.019523554,0.06615229,0.0007931568],"about_ca_topic_score_codex":0.000015076162,"about_ca_topic_score_gemma":0.0000027496228,"teacher_disagreement_score":0.94714713,"about_ca_system_score_codex":0.000009161665,"about_ca_system_score_gemma":0.000022456097,"threshold_uncertainty_score":0.26673675},"labels":[],"label_agreement":null},{"id":"W2951156811","doi":"10.48550/arxiv.1205.2651","title":"Seeing the Forest Despite the Trees: Large Scale Spatial-Temporal\\n Decision Making","year":2012,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Scale (ratio); Temporal scales; Environmental resource management; Geography; Computer science; Environmental science; Cartography; Ecology","score_opus":0.07346166479597925,"score_gpt":0.23735575965303848,"score_spread":0.16389409485705925,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951156811","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07732009,0.0002288076,0.9185865,0.00024470003,0.001538421,0.00061347906,0.00007108146,0.00013594046,0.0012609928],"genre_scores_gemma":[0.99550134,0.0005920332,0.0010800853,0.0007613413,0.00040140125,0.0000014548808,0.00005697952,0.000049204933,0.001556185],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9954916,0.00071168435,0.0006814427,0.0015871533,0.00043681602,0.0010912637],"domain_scores_gemma":[0.99393,0.0008356954,0.0010044776,0.0035264206,0.0003971264,0.0003062927],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0021082908,0.00070605107,0.00055620354,0.00032663607,0.0020223837,0.0011139446,0.0059414003,0.00039455073,0.0002976947],"category_scores_gemma":[0.00017958543,0.0005162142,0.0005664924,0.0020029133,0.0004468141,0.001247603,0.006904858,0.0010332448,0.0005507971],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016403376,0.0008560005,0.2904381,0.00016357866,0.00042077553,0.00027890707,0.0075633326,0.36486012,0.000011028112,0.304947,0.0025537366,0.027743438],"study_design_scores_gemma":[0.00056886766,0.00004048312,0.017782602,0.0005112323,0.00028583664,0.000012310086,0.0009473372,0.94364405,0.000009310682,0.010703766,0.024833903,0.00066027953],"about_ca_topic_score_codex":0.00036856515,"about_ca_topic_score_gemma":0.0045048986,"teacher_disagreement_score":0.91818124,"about_ca_system_score_codex":0.0002717238,"about_ca_system_score_gemma":0.0003382314,"threshold_uncertainty_score":0.999923},"labels":[],"label_agreement":null},{"id":"W2952651124","doi":"10.1145/3331156","title":"Tangible BioNets","year":2019,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Excellence Research Chairs, Government of Canada; Canada Foundation for Innovation; Ontario Ministry of Research, Innovation and Science; Canada Research Chairs; National Science Foundation","keywords":"Computer science; Usability; Process (computing); Biological network; Human–computer interaction; Biological data; Data science; Bioinformatics","score_opus":0.045309125682246085,"score_gpt":0.3326112583374098,"score_spread":0.2873021326551637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952651124","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.956494,0.000010983484,0.016418543,0.0038280305,0.0033976457,0.00047188124,0.0000041457697,0.0003232132,0.019051567],"genre_scores_gemma":[0.99031126,0.000003477868,0.0071874065,0.00088121026,0.00015409154,0.0000033423955,0.000003046367,0.000011147189,0.0014450168],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989662,0.000007480169,0.00025566708,0.00031176023,0.00030861152,0.00015026634],"domain_scores_gemma":[0.9988478,0.000036642905,0.00028115368,0.0006024861,0.00019576802,0.000036142268],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017068326,0.00012385058,0.00014192902,0.00017126498,0.000091745176,0.00023756061,0.0024927622,0.000044200067,0.0000527254],"category_scores_gemma":[0.000052800748,0.00009064163,0.00010209391,0.0003617664,0.000020585541,0.0009255819,0.0010687152,0.00014406479,0.00021933348],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040751856,0.00069688895,0.00964612,0.00026352121,0.00014420695,8.639019e-7,0.0021848523,0.00050611113,0.11275988,0.67013294,0.17351164,0.030112203],"study_design_scores_gemma":[0.0018854135,0.0012557467,0.019822787,0.0011573075,0.000049629063,0.00006900433,0.00025557377,0.4161047,0.40372136,0.039709657,0.11492734,0.0010414873],"about_ca_topic_score_codex":0.000007499655,"about_ca_topic_score_gemma":4.7329118e-7,"teacher_disagreement_score":0.6304233,"about_ca_system_score_codex":0.000048045702,"about_ca_system_score_gemma":0.0000094160905,"threshold_uncertainty_score":0.46322137},"labels":[],"label_agreement":null},{"id":"W2953170629","doi":"","title":"Visualisation interactive de données budgétaires","year":2019,"lang":"fr","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Humanities; Political science; Philosophy","score_opus":0.020450999997808996,"score_gpt":0.28036731376695423,"score_spread":0.25991631376914526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953170629","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03479098,0.002500655,0.9379258,0.019729175,0.0012357498,0.00071227987,0.00011928475,0.00069913967,0.002286894],"genre_scores_gemma":[0.8736687,0.0013714115,0.0785436,0.012645959,0.00054074306,0.00013515317,0.0001574637,0.000116780684,0.032820243],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99624836,0.00050550443,0.0007119195,0.0008327021,0.0005975394,0.0011039609],"domain_scores_gemma":[0.9970248,0.00030887732,0.0004799026,0.0013415929,0.0003559158,0.0004889418],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0011343793,0.00050465256,0.00049863325,0.00057259516,0.00026540432,0.0012963563,0.0013940331,0.00044311958,0.0004863418],"category_scores_gemma":[0.00041773973,0.0005674109,0.00026338882,0.0011972587,0.00016998255,0.0027088241,0.00070763764,0.0006025175,0.0005559507],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007650366,0.0008056475,0.042079374,0.0002557097,0.00016845885,0.000108645014,0.00412057,0.007075884,0.004883658,0.8500224,0.027476404,0.06292675],"study_design_scores_gemma":[0.0005786296,0.00027565582,0.013242717,0.00037700628,0.00005758349,0.00017043125,0.00044487658,0.8920041,0.008885943,0.007850992,0.075442955,0.00066913577],"about_ca_topic_score_codex":0.014571863,"about_ca_topic_score_gemma":0.0024092442,"teacher_disagreement_score":0.88492817,"about_ca_system_score_codex":0.0010448914,"about_ca_system_score_gemma":0.00077486405,"threshold_uncertainty_score":0.9997404},"labels":[],"label_agreement":null},{"id":"W2953333724","doi":"10.7155/jgaa.00474","title":"Experimental Analysis of the Accessibility of Drawings with Few Segments","year":2018,"lang":"en","type":"article","venue":"Journal of Graph Algorithms and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Deutsche Forschungsgemeinschaft; Netherlands eScience Center","keywords":"Computer science; Line drawings; Graph drawing; Line segment; Graph; Dense graph; Shortest path problem; Theoretical computer science; Combinatorics; Line graph; Artificial intelligence; Mathematics; Pathwidth; Engineering drawing","score_opus":0.01542996390512583,"score_gpt":0.3150062101701762,"score_spread":0.29957624626505036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953333724","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14210284,0.00009478046,0.8574259,0.00013001342,0.00002402957,0.00007750482,0.000016374259,0.0000036681977,0.00012487176],"genre_scores_gemma":[0.9811734,0.000020790587,0.01869156,0.00006711493,0.000025169358,0.0000023839584,0.0000013932889,0.000001990437,0.000016199412],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992776,0.000020587719,0.00031026624,0.00010149334,0.00023277837,0.00005730727],"domain_scores_gemma":[0.9988845,0.000020717895,0.00048488964,0.00028044972,0.0002810066,0.00004842147],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019084559,0.00005260463,0.0001643322,0.00016587244,0.000095355455,0.00003974829,0.00046380292,0.000016520118,0.000008836145],"category_scores_gemma":[0.0000049054256,0.000030888245,0.000090307854,0.001525734,0.00019558067,0.00021789208,0.00008972471,0.000041629883,1.494141e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000104993815,0.006107617,0.48491094,0.00016789895,0.0073575904,0.0000038403077,0.010382639,0.0006448926,0.07859538,0.24095121,0.0021933527,0.16857967],"study_design_scores_gemma":[0.002297614,0.0011152807,0.61439633,0.00016075098,0.0019080649,0.000047620575,0.0018409943,0.12797233,0.23753871,0.007428404,0.0048004114,0.0004934886],"about_ca_topic_score_codex":0.000009924774,"about_ca_topic_score_gemma":0.0000033219787,"teacher_disagreement_score":0.83907056,"about_ca_system_score_codex":0.000007103261,"about_ca_system_score_gemma":0.000038425613,"threshold_uncertainty_score":0.1259586},"labels":[],"label_agreement":null},{"id":"W2954024736","doi":"10.1609/aiide.v15i1.5219","title":"Automatic Abstraction and Refinement for Simulations with Adaptive Level of Detail","year":2019,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Scope (computer science); Context (archaeology); Abstraction; Graphics; Human–computer interaction; Computer graphics; Interactive simulation; Data science; Artificial intelligence; Simulation; Programming language; Computer graphics (images)","score_opus":0.10877689287641408,"score_gpt":0.3203551584741755,"score_spread":0.21157826559776144,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2954024736","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84002775,0.000005213921,0.15586205,0.0007941677,0.00009839498,0.0007355666,0.000100591154,0.000019269532,0.0023569937],"genre_scores_gemma":[0.9987406,0.0000072242337,0.0009531973,0.00007035401,0.00000575335,0.000011493052,0.000003672537,0.0000049271925,0.00020276807],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991235,0.000003922615,0.0003104511,0.0002426938,0.00020795548,0.00011146463],"domain_scores_gemma":[0.99907035,0.00010075553,0.00032002063,0.00010440416,0.00036638687,0.000038101218],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000080963415,0.000121153855,0.00016315887,0.00008072792,0.00005170362,0.00019009819,0.0002484821,0.000023302451,0.000020186595],"category_scores_gemma":[0.000070588474,0.000082112914,0.00003862721,0.000120771634,0.0000892976,0.00080910063,0.00012890092,0.00006312956,0.000003519595],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031099626,0.0005755941,0.0019959284,0.00016575614,0.0001402183,1.2881372e-7,0.0034806768,0.0002663589,0.011659029,0.78837013,0.00004770015,0.19298746],"study_design_scores_gemma":[0.00016370724,0.0016340555,0.0013577121,0.000613467,0.00002840039,0.000003305386,0.004312912,0.78994334,0.18449378,0.01706518,0.00017374339,0.00021036598],"about_ca_topic_score_codex":0.000008565601,"about_ca_topic_score_gemma":0.000004579092,"teacher_disagreement_score":0.789677,"about_ca_system_score_codex":0.000028619637,"about_ca_system_score_gemma":0.000026571759,"threshold_uncertainty_score":0.33484674},"labels":[],"label_agreement":null},{"id":"W2954949039","doi":"10.1344/thj.2019.1.3","title":"Public data art’s potential for digital placemaking","year":2019,"lang":"en","type":"article","venue":"Tourism & Heritage Journal","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Placemaking; Exhibition; Public space; Sculpture; Context (archaeology); Storytelling; Relation (database); Space (punctuation); Visual arts; Architecture; Sociology; Aesthetics; Computer science; Urban design; Art; History; Engineering; Architectural engineering; Archaeology; Database","score_opus":0.05661132546302079,"score_gpt":0.29494799251516235,"score_spread":0.23833666705214157,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2954949039","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003148959,0.00008247839,0.9894304,0.0025160832,0.0010909253,0.00014105294,0.00008558788,0.00009096742,0.0034135194],"genre_scores_gemma":[0.9113449,0.00006435623,0.06248359,0.001745814,0.001929861,0.0000035902835,0.00040316395,0.00005632129,0.02196839],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99852175,0.000034009092,0.00034162952,0.00033558725,0.00039657977,0.00037041958],"domain_scores_gemma":[0.9985378,0.000050422426,0.00021566663,0.000858356,0.00014027672,0.00019747904],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0005371172,0.00013457848,0.00017810016,0.00012938303,0.00019843213,0.0030168481,0.0020654346,0.000058258353,0.00024430355],"category_scores_gemma":[0.00013369453,0.000121494355,0.00008434611,0.0002073416,0.00002104116,0.0044144057,0.00071844854,0.00021213721,0.00031595354],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037167545,0.00043150637,0.0015975708,0.00008324629,0.00021940196,0.0003840542,0.0004206618,0.0002961993,0.00068184204,0.042340633,0.8817587,0.07174901],"study_design_scores_gemma":[0.0010664741,0.00011687046,0.00016274312,0.00003974278,0.00001346842,0.0003878589,0.00011585531,0.48665807,0.000017883205,0.0025214457,0.50860846,0.00029112786],"about_ca_topic_score_codex":5.113932e-7,"about_ca_topic_score_gemma":9.834955e-7,"teacher_disagreement_score":0.9269468,"about_ca_system_score_codex":0.000032400432,"about_ca_system_score_gemma":0.00015287979,"threshold_uncertainty_score":0.99801815},"labels":[],"label_agreement":null},{"id":"W2955088171","doi":"","title":"Who Rules Infovis? Unwrapping the Conference Organization","year":2015,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science","score_opus":0.027036334099530112,"score_gpt":0.24692675569126232,"score_spread":0.21989042159173222,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2955088171","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0060712444,0.00008944739,0.9464577,0.015367838,0.000089804256,0.00010845182,0.000006669322,0.00022892354,0.031579927],"genre_scores_gemma":[0.94382286,0.00017992423,0.045389865,0.0010240468,0.000023216819,0.000008019714,0.00021805207,0.000022803502,0.0093111945],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997261,0.0015956612,0.00026827626,0.00030907735,0.0003704173,0.00019556555],"domain_scores_gemma":[0.9952271,0.0003925502,0.00020081777,0.0012796096,0.0027502615,0.0001496403],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028524513,0.00012784563,0.00012540864,0.00009004876,0.0003265386,0.0009288437,0.0016867385,0.000056626406,0.000044506756],"category_scores_gemma":[0.0020506817,0.00010610684,0.000034817265,0.0009555445,0.00013092159,0.0005918946,0.0006447672,0.00012855227,0.00014389826],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.924804e-7,0.00007013022,0.001325161,0.000006948208,0.000010532143,8.386325e-7,0.0074980427,0.000030540235,0.0001996711,0.9731094,0.004640857,0.013107378],"study_design_scores_gemma":[0.0011131959,0.000001051356,0.0066412953,0.0005708055,0.000029413952,0.000029059576,0.00093379355,0.7304723,0.033842202,0.02069607,0.20497651,0.0006942815],"about_ca_topic_score_codex":0.00013888431,"about_ca_topic_score_gemma":0.00014776817,"teacher_disagreement_score":0.9524133,"about_ca_system_score_codex":0.000043356245,"about_ca_system_score_gemma":0.00026171643,"threshold_uncertainty_score":0.8956861},"labels":[],"label_agreement":null},{"id":"W2955789822","doi":"10.5281/zenodo.3266480","title":"Ruthwell Cross - Main","year":2019,"lang":"en","type":"article","venue":"Figshare","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Polygon (computer graphics); Resolution (logic); High resolution; Mathematics; Low resolution; Computer science; Artificial intelligence; Geography; Remote sensing; Telecommunications","score_opus":0.03479440192434198,"score_gpt":0.31172098693475386,"score_spread":0.2769265850104119,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2955789822","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0024482457,0.00038555986,0.02454115,0.0016169847,0.0013870359,0.0010047649,0.6895429,0.0020602155,0.27701312],"genre_scores_gemma":[0.60447955,0.0000048028255,0.0065730517,0.0109454,0.00038356968,0.00005121656,0.28526402,0.000059121772,0.09223925],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99950063,0.000010870701,0.00007571163,0.00016530084,0.0001263055,0.000121169374],"domain_scores_gemma":[0.9994829,0.000025186366,0.000032368203,0.00037339478,0.000038526996,0.000047604877],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000027463231,0.000051281524,0.000051206847,0.000029247944,0.000029265278,0.0002666165,0.0005948164,0.000027663546,0.12938024],"category_scores_gemma":[0.00008847405,0.000047729565,0.000026990225,0.00018888507,0.0000014032146,0.00034733463,0.00023013324,0.000039767845,0.039670885],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.2182226e-7,0.000014263371,0.0002361731,0.00003518297,0.0000029058913,0.0000070776014,0.00005645091,0.0000706765,0.000022885424,0.008175391,0.9903515,0.0010271532],"study_design_scores_gemma":[0.00014187032,0.000013408215,0.001912664,0.0001170463,3.867825e-7,0.0000037974794,0.0000038336066,0.071039714,0.0004793982,0.00020975024,0.92595875,0.000119404795],"about_ca_topic_score_codex":7.4460354e-7,"about_ca_topic_score_gemma":7.057758e-7,"teacher_disagreement_score":0.60203135,"about_ca_system_score_codex":0.0000098494,"about_ca_system_score_gemma":0.000031607033,"threshold_uncertainty_score":0.96107686},"labels":[],"label_agreement":null},{"id":"W2957222340","doi":"10.22215/etd/2015-11133","title":"ACH Walkthrough: Designing and Building a Web Application for Collaborative Sensemaking","year":2015,"lang":"en","type":"dissertation","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Sensemaking; Software walkthrough; Computer science; Intelligence analysis; Data science; Human–computer interaction; World Wide Web; Software; Software development","score_opus":0.03782813021565749,"score_gpt":0.36982138487110633,"score_spread":0.3319932546554488,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2957222340","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00064343825,0.00023788013,0.9942957,0.000117084244,0.00019240355,0.0005563994,0.000025809866,0.00015864088,0.0037726571],"genre_scores_gemma":[0.17335063,0.00014718971,0.8131172,0.0006252014,0.00029625132,0.00031576448,0.0026960915,0.00008315425,0.00936853],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988244,0.000038300223,0.00026075757,0.00047421147,0.00023572078,0.00016657029],"domain_scores_gemma":[0.99866503,0.00010662173,0.00025949313,0.00027370505,0.0006158618,0.00007929047],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037498682,0.00018919562,0.00023175815,0.00015643214,0.00017234619,0.00037977277,0.0003168155,0.00014785277,0.0000018366079],"category_scores_gemma":[0.00012332735,0.00018357024,0.000030300582,0.00052482774,0.000013213909,0.00043798267,0.000057400655,0.00008052301,0.000005398859],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033648615,0.00006584478,0.000038608483,0.00040930702,0.00010958692,0.0000030046226,0.00580825,0.000116005845,0.019101353,0.86469907,0.019611515,0.090003796],"study_design_scores_gemma":[0.0007706964,0.000108358094,0.00002047621,0.0001830951,0.000081104285,0.0000054896973,0.0039616725,0.90379035,0.009736747,0.019249786,0.06140069,0.00069150585],"about_ca_topic_score_codex":0.000009968997,"about_ca_topic_score_gemma":0.000091502196,"teacher_disagreement_score":0.90367436,"about_ca_system_score_codex":0.000054485972,"about_ca_system_score_gemma":0.0003384536,"threshold_uncertainty_score":0.7485777},"labels":[],"label_agreement":null},{"id":"W2958881837","doi":"","title":"A Novel Interaction Paradigm For Exploring Spatio-Temporal Data","year":2018,"lang":"en","type":"preprint","venue":"Open Archive Toulouse Archive Ouverte (University of Toulouse)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Centre National de la Recherche Scientifique","keywords":"Computer science; Visualization; Human–computer interaction; Data visualization; Robot; Data exploration; Augmented reality; Data science; Artificial intelligence","score_opus":0.17961411618704254,"score_gpt":0.32862712318368764,"score_spread":0.1490130069966451,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2958881837","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020303696,0.000012474326,0.98476213,0.0010313396,0.00096030574,0.0015151888,0.006533644,0.0001895389,0.0029650163],"genre_scores_gemma":[0.03582749,0.0005526367,0.94393927,0.00047965784,0.00040031926,0.000020672403,0.016720623,0.00012824441,0.0019311131],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9962001,0.00024779118,0.0005445873,0.0019020353,0.0005282219,0.0005772871],"domain_scores_gemma":[0.99412674,0.00040038145,0.0010325091,0.0038945721,0.00020432775,0.0003415006],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0006720134,0.0005426403,0.00089792325,0.0006198332,0.00062720827,0.0006044189,0.013327767,0.00014564503,0.000122000965],"category_scores_gemma":[0.00015675245,0.00067118235,0.00030998024,0.0003259413,0.00036422486,0.0031013875,0.027919779,0.0005819893,0.000083558865],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002536286,0.0037555564,0.002127144,0.0020164896,0.0033026007,0.00020802561,0.061238483,0.006145481,0.0009078919,0.18233062,0.6651166,0.0703148],"study_design_scores_gemma":[0.0019628445,0.00033757434,0.001091886,0.00064899016,0.00020657304,0.00001552792,0.00091430376,0.7577549,0.000066350025,0.018243682,0.21779558,0.00096177246],"about_ca_topic_score_codex":0.0055891504,"about_ca_topic_score_gemma":0.010182622,"teacher_disagreement_score":0.75160944,"about_ca_system_score_codex":0.0001340784,"about_ca_system_score_gemma":0.00071073085,"threshold_uncertainty_score":0.99957395},"labels":[],"label_agreement":null},{"id":"W2958922780","doi":"","title":"Unifying the Framework of Multi-Layer Network and Visual Analytics","year":2019,"lang":"en","type":"preprint","venue":"SERVAL (Université de Lausanne)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Visual analytics; Computer science; Analytics; Layer (electronics); Data science; Visualization; Data mining; Nanotechnology; Materials science","score_opus":0.03577915787664386,"score_gpt":0.2869827454634733,"score_spread":0.2512035875868294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2958922780","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03991808,0.00095894677,0.95612806,0.0011190681,0.0005403196,0.0002595492,0.000042589363,0.000107929314,0.00092545396],"genre_scores_gemma":[0.9158578,0.0016683962,0.07525499,0.0019958804,0.0002634053,0.000001616011,0.000117419164,0.000048194153,0.004792305],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99848944,0.00014836724,0.00022892078,0.0004749503,0.0003173862,0.00034095938],"domain_scores_gemma":[0.99840724,0.00020194697,0.00032946456,0.0007742189,0.00016328419,0.00012383208],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037566514,0.00023986153,0.0003524363,0.000116448704,0.00023547797,0.0001564318,0.0013796509,0.00031656233,0.00004367858],"category_scores_gemma":[0.000040030012,0.00021501309,0.00012883049,0.0005622025,0.00010195595,0.00020888534,0.004384645,0.0005317353,0.000021691712],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000106397645,0.00036027204,0.08337919,0.0013561388,0.0015243492,0.0001973623,0.015363666,0.3254337,0.00019248028,0.5280827,0.02371592,0.020287817],"study_design_scores_gemma":[0.00024642667,0.000038760536,0.010192951,0.00033020208,0.00011472998,0.0000063001835,0.0003411961,0.9793941,0.000038982806,0.0031530268,0.0058538965,0.0002894467],"about_ca_topic_score_codex":0.000107349704,"about_ca_topic_score_gemma":0.00008030119,"teacher_disagreement_score":0.8808731,"about_ca_system_score_codex":0.000106441454,"about_ca_system_score_gemma":0.0001519469,"threshold_uncertainty_score":0.876798},"labels":[],"label_agreement":null},{"id":"W2959416902","doi":"10.1111/cgf.13715","title":"Segmentifier: Interactive Refinement of Clickstream Data","year":2019,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Mitacs","keywords":"Computer science; Clickstream; Visual analytics; Glyph (data visualization); Process (computing); Data mining; Visualization; Path (computing); Set (abstract data type); Downstream (manufacturing); Human–computer interaction; Theoretical computer science; Programming language; The Internet; World Wide Web","score_opus":0.02750749594206824,"score_gpt":0.30023123754657277,"score_spread":0.2727237416045045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2959416902","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0035287226,0.000041154148,0.9932504,0.00059562095,0.0010765782,0.000164115,0.00007835639,0.00009145503,0.0011735895],"genre_scores_gemma":[0.91291666,0.0003228543,0.080013484,0.0044929907,0.00014792441,0.000005931082,0.0012434322,0.00003511321,0.00082158356],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985898,0.00004461952,0.00033855278,0.0004977706,0.00030078462,0.00022847566],"domain_scores_gemma":[0.99750763,0.00006525444,0.000196674,0.002030012,0.0001301064,0.000070344715],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025559342,0.00013363479,0.00020195938,0.00035282588,0.00004682078,0.000126396,0.0022431507,0.000045245262,0.00003499851],"category_scores_gemma":[0.000008954888,0.00012395279,0.00006588809,0.0008340844,0.000041950443,0.0007421398,0.0023441142,0.00011100151,0.00007843611],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001075824,0.00047873627,0.019723497,0.000091193586,0.00021569805,0.000007177589,0.00032924657,0.0000900134,0.00017669224,0.7581897,0.17910862,0.041578677],"study_design_scores_gemma":[0.00048944564,0.00016538595,0.0013076463,0.0000721043,0.000012784281,0.00000523213,0.000035778776,0.8874493,0.00069436285,0.0025921238,0.10696098,0.00021484887],"about_ca_topic_score_codex":0.000018397359,"about_ca_topic_score_gemma":0.000011995935,"teacher_disagreement_score":0.9132369,"about_ca_system_score_codex":0.000009705497,"about_ca_system_score_gemma":0.00004173043,"threshold_uncertainty_score":0.50546485},"labels":[],"label_agreement":null},{"id":"W2959839175","doi":"","title":"Fireflies: Biomimicry-Inspired InfoVis for Exploring Public Opinion about an Infectious Disease","year":2016,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Biomimetics; Infectious disease (medical specialty); Computer science; Data science; Disease; Artificial intelligence; Medicine; Pathology","score_opus":0.04717162427357215,"score_gpt":0.27615666225522445,"score_spread":0.2289850379816523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2959839175","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019079525,0.000120923854,0.9670829,0.010604,0.00029443196,0.000259531,0.000067631416,0.00053457764,0.001956485],"genre_scores_gemma":[0.9701788,0.0006862798,0.026726289,0.0003549983,0.00004761448,0.0001432622,0.0002671041,0.000033721,0.0015619511],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974101,0.0010247519,0.0003716236,0.0005591795,0.0002823034,0.00035203557],"domain_scores_gemma":[0.99575585,0.00069455133,0.00023355876,0.0016919608,0.0012460824,0.00037797852],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020117532,0.00018855155,0.0001711684,0.00024387996,0.00043022828,0.00073590415,0.0013672911,0.000060193193,0.000043951877],"category_scores_gemma":[0.0018689104,0.00016118941,0.00011004208,0.0006016125,0.00012329602,0.001979211,0.00045901712,0.000064268446,0.00004664925],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000063538123,0.00043516487,0.0034323018,0.00005341298,0.000026432746,9.542969e-7,0.0022250214,0.0000047894505,0.0020304765,0.7395818,0.0012374592,0.25096583],"study_design_scores_gemma":[0.0040794364,0.0000067291403,0.014077515,0.0016819956,0.00003817912,0.000009600166,0.00018752983,0.26635894,0.041706037,0.016397513,0.65399766,0.0014588294],"about_ca_topic_score_codex":0.000065719054,"about_ca_topic_score_gemma":0.0001407921,"teacher_disagreement_score":0.9510993,"about_ca_system_score_codex":0.000085000975,"about_ca_system_score_gemma":0.00020453335,"threshold_uncertainty_score":0.70963407},"labels":[],"label_agreement":null},{"id":"W2964938859","doi":"10.48550/arxiv.1908.00215","title":"Illusion of Causality in Visualized Data","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Causality (physics); Causation; Illusion; Interpretation (philosophy); Bar chart; Psychology; Causal reasoning; Visualization; Cognitive psychology; Correlation; Cognition; Computer science; Social psychology; Artificial intelligence; Mathematics; Statistics; Epistemology","score_opus":0.1784209683597186,"score_gpt":0.2778278528546118,"score_spread":0.09940688449489321,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2964938859","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09014406,0.000031416443,0.9073116,0.00005856166,0.00041753027,0.0002175077,0.00018793548,0.000082301194,0.0015490605],"genre_scores_gemma":[0.9974399,0.00024170766,0.00095874706,0.000084910775,0.000015950172,7.5497226e-8,0.0003943204,0.000008667024,0.00085570826],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982391,0.00019135959,0.00028399366,0.0009767205,0.00011855335,0.00019030093],"domain_scores_gemma":[0.99635714,0.0000772698,0.0003177098,0.0030553339,0.000117812364,0.00007470491],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0005253426,0.00018105019,0.00036359773,0.0003058944,0.000030013613,0.0000560641,0.0037466825,0.00018716817,0.000039193343],"category_scores_gemma":[0.00008229648,0.0002061762,0.00006923504,0.0007635962,0.00006749064,0.0005254807,0.008967021,0.00026172126,0.000052782245],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054392134,0.00065855595,0.032535903,0.00060422753,0.00012264666,0.00022693184,0.0005264479,0.14894462,0.00013466015,0.8128576,0.002381515,0.0009524713],"study_design_scores_gemma":[0.00051093055,0.000016397928,0.0025996205,0.000120459714,0.000024153487,5.672664e-7,0.000038886992,0.9884623,0.00005287625,0.0064052315,0.0015300008,0.00023854562],"about_ca_topic_score_codex":0.0004146222,"about_ca_topic_score_gemma":0.00012221707,"teacher_disagreement_score":0.9072958,"about_ca_system_score_codex":0.00008414849,"about_ca_system_score_gemma":0.00026010655,"threshold_uncertainty_score":0.9990483},"labels":[],"label_agreement":null},{"id":"W2966373506","doi":"","title":"Speculative Execution for Guided Visual Analytics","year":2018,"lang":"en","type":"preprint","venue":"KOPS (University of Konstanz)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Deutsche Forschungsgemeinschaft","keywords":"Computer science; Visual analytics; Analytics; Visualization; State (computer science); Human–computer interaction; Data science; Artificial intelligence; Programming language","score_opus":0.04779898995771891,"score_gpt":0.30399982677594,"score_spread":0.2562008368182211,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2966373506","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0052222265,0.000020784417,0.98891425,0.00046013336,0.00037559553,0.0003067221,0.00024072835,0.00010807828,0.0043514506],"genre_scores_gemma":[0.4282689,0.00025388235,0.55888504,0.00040003142,0.00036580776,0.0000012314539,0.0014882458,0.000048446862,0.0102883885],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998593,0.00006669663,0.00022414897,0.0005457822,0.00034711233,0.0002233052],"domain_scores_gemma":[0.9980212,0.00006330347,0.00044746895,0.0006668562,0.00067961094,0.00012156916],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003214318,0.00019971737,0.00037165647,0.0003363094,0.00019669758,0.00008211852,0.0012565932,0.00021673444,0.00007698618],"category_scores_gemma":[0.000073804746,0.00025720912,0.00024185443,0.0004326129,0.00023027055,0.0003239423,0.001384911,0.00014846667,0.000029374882],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011631199,0.0006756595,0.00093426905,0.0007172857,0.00088714925,0.000058715435,0.0058169765,0.002996343,0.00046187392,0.67675304,0.30013376,0.0104485955],"study_design_scores_gemma":[0.000835215,0.00015981159,0.0008034712,0.00019559659,0.0001832521,0.0000036314748,0.00077397906,0.95581466,0.00033294535,0.016037056,0.024355968,0.0005043976],"about_ca_topic_score_codex":0.00006081762,"about_ca_topic_score_gemma":0.00005459812,"teacher_disagreement_score":0.95281833,"about_ca_system_score_codex":0.00014866189,"about_ca_system_score_gemma":0.00032007325,"threshold_uncertainty_score":0.999988},"labels":[],"label_agreement":null},{"id":"W2966541941","doi":"10.1109/tvcg.2019.2934283","title":"What is Interaction for Data Visualization?","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":105,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Visualization; Computer science; Visual analytics; Information visualization; Human–computer interaction; Data visualization; Context (archaeology); Data science; Confusion; Field (mathematics); Artificial intelligence; Psychology; Mathematics","score_opus":0.04465670589119501,"score_gpt":0.34599591985587613,"score_spread":0.3013392139646811,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2966541941","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00094076194,0.00005349346,0.9948789,0.00024275538,0.0029864132,0.0005106048,0.000063619045,0.00029276716,0.000030709645],"genre_scores_gemma":[0.9521146,0.005457739,0.009642761,0.02880273,0.00035672545,0.00009396996,0.0012713069,0.00015050739,0.0021096582],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979616,0.00009754726,0.00045373215,0.0008582175,0.00037718387,0.00025175945],"domain_scores_gemma":[0.99813193,0.0001712392,0.0001808584,0.0010858285,0.0002917834,0.00013838022],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00032271267,0.00026127184,0.00024976273,0.00049732166,0.00029775346,0.0011865807,0.00080726726,0.00013631566,0.00006165023],"category_scores_gemma":[0.0000039602087,0.00026969158,0.00008909055,0.00097096147,0.00004653813,0.0036303818,0.000027856651,0.00012393699,0.000054407257],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028594355,0.00041394195,0.00009393998,0.00012161627,0.00011247926,7.932875e-7,0.0011725568,0.00053136284,0.00002093969,0.9692522,0.0046763886,0.023575187],"study_design_scores_gemma":[0.00075911894,0.00023362046,0.000028431004,0.00009706818,0.00003195588,0.000009271131,0.000105518695,0.9621944,0.0009076289,0.00082825444,0.03449262,0.00031215636],"about_ca_topic_score_codex":0.000007528031,"about_ca_topic_score_gemma":0.000010302941,"teacher_disagreement_score":0.9852361,"about_ca_system_score_codex":0.000025989588,"about_ca_system_score_gemma":0.000058238784,"threshold_uncertainty_score":0.9999755},"labels":[],"label_agreement":null},{"id":"W2968598704","doi":"10.22215/etd/2015-10921","title":"Crowd Shape as a Visual Feedback Mechanism in Human-Computer Interaction","year":2015,"lang":"en","type":"dissertation","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Human–computer interaction; Crowd simulation; Computer science; Mechanism (biology); Artificial intelligence; Computer graphics (images); Computer vision; Crowds; Epistemology; Computer security","score_opus":0.029025944627040792,"score_gpt":0.3725625282689501,"score_spread":0.3435365836419093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2968598704","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16190484,0.00009830858,0.6624294,0.00046428165,0.010451098,0.0012074406,0.00001923331,0.0013654648,0.16205992],"genre_scores_gemma":[0.81371343,0.00009642633,0.02620357,0.0045745578,0.0013774968,0.00009008201,0.009604973,0.00020167457,0.1441378],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99800533,0.00007500931,0.0005064687,0.0006324638,0.0005136427,0.0002670979],"domain_scores_gemma":[0.99893135,0.000026889666,0.0002435258,0.00040036786,0.00026490612,0.00013297904],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00029307572,0.0002998337,0.00032737275,0.00055760506,0.00007306202,0.00059785164,0.00087153935,0.00026590558,0.0005256618],"category_scores_gemma":[0.000029057215,0.00029657516,0.0000905015,0.0005526047,0.000009054221,0.00089267263,0.00016873765,0.00030924525,0.00077758403],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046476034,0.0008891598,0.00003797729,0.00022878501,0.00010905286,0.00012891805,0.0051709316,0.00015083268,0.0018313031,0.83536756,0.05659895,0.09944007],"study_design_scores_gemma":[0.0010097101,0.00038419254,0.0003595457,0.00034258695,0.000027317166,0.00002051189,0.0009977886,0.9481412,0.0034688287,0.032589715,0.011669639,0.0009889512],"about_ca_topic_score_codex":0.00017470065,"about_ca_topic_score_gemma":0.0005554505,"teacher_disagreement_score":0.94799036,"about_ca_system_score_codex":0.00013655215,"about_ca_system_score_gemma":0.00020154633,"threshold_uncertainty_score":0.9999486},"labels":[],"label_agreement":null},{"id":"W2969174528","doi":"10.1007/978-3-319-50832-0","title":"Advances in Visual Computing","year":2016,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Google (Canada)","funders":"","keywords":"Las vegas; Computer science; Computer graphics (images); Set (abstract data type); Volume (thermodynamics); Artificial intelligence; Programming language","score_opus":0.012709739973195851,"score_gpt":0.30869911657802,"score_spread":0.29598937660482416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2969174528","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000015563632,0.0006293536,0.9927233,0.00037469916,0.0015014459,0.00019476961,0.0000047523417,0.0001482287,0.0044079237],"genre_scores_gemma":[0.1765649,0.0016189623,0.8025575,0.011452162,0.00361928,0.000017332928,0.00008113801,0.0001663349,0.003922373],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99611324,0.00008128097,0.0006289571,0.0014507711,0.00095525326,0.00077049056],"domain_scores_gemma":[0.9978909,0.0005730511,0.00030216516,0.00091074186,0.00016846652,0.00015467363],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010349767,0.0004268885,0.0005168518,0.0012245934,0.00015795136,0.00057120464,0.003686198,0.00022043285,0.000013485258],"category_scores_gemma":[0.00018073329,0.0003495058,0.000082510756,0.0018091507,0.0004944427,0.0014976794,0.001726622,0.0005034753,0.000078047306],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016415245,0.000044517685,0.0002784581,0.000043426764,0.000001965472,0.00006365829,0.00031813476,0.009788132,0.000017917715,0.009804968,0.000107723376,0.97952944],"study_design_scores_gemma":[0.00037893007,0.0000942096,0.00012153748,0.0009283399,0.0000022374904,0.000023797254,1.8742712e-7,0.92706734,0.0002566834,0.05736829,0.0131236175,0.0006348235],"about_ca_topic_score_codex":0.0000048368133,"about_ca_topic_score_gemma":0.00007629334,"teacher_disagreement_score":0.97889465,"about_ca_system_score_codex":0.00047947292,"about_ca_system_score_gemma":0.0011205473,"threshold_uncertainty_score":0.9998957},"labels":[],"label_agreement":null},{"id":"W2969737323","doi":"10.1109/tvcg.2019.2934399","title":"Illusion of Causality in Visualized Data","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":71,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Causality (physics); Visualization; Computer science; Causation; Illusion; Bar chart; Causal reasoning; Interpretation (philosophy); Data visualization; Cognition; Cognitive psychology; Psychology; Artificial intelligence; Statistics; Mathematics","score_opus":0.037454337811717565,"score_gpt":0.3289071690966643,"score_spread":0.2914528312849467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2969737323","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024017042,0.000023169965,0.9750159,0.000043872533,0.00047163753,0.00021928655,0.00004246657,0.00010290947,0.000063712556],"genre_scores_gemma":[0.9970761,0.00034851467,0.0015554896,0.0008381009,0.00001579438,0.0000033772378,0.00007513381,0.000014940324,0.000072564646],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982313,0.00017808427,0.0004884311,0.00055299886,0.0003697249,0.0001794558],"domain_scores_gemma":[0.99858075,0.00010807709,0.00014958448,0.0009535058,0.00012211376,0.000085945256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045300781,0.00017383718,0.0002778863,0.0005405603,0.00007875603,0.00010560757,0.0007086295,0.00010455653,0.000033723503],"category_scores_gemma":[0.0000046378154,0.00017303019,0.000047739697,0.0013559567,0.000062674706,0.0007316373,0.000035419052,0.00013184376,0.000013205464],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028028671,0.00068605907,0.0013499563,0.0001298133,0.000040763454,0.0000031609848,0.0008101076,0.0009405242,0.00010884021,0.9875593,0.00018776089,0.008155667],"study_design_scores_gemma":[0.000898033,0.0001387962,0.0013197728,0.000077192664,0.000010468946,0.0000043708737,0.000027428014,0.9948155,0.0007246446,0.0004908454,0.0012965623,0.00019634812],"about_ca_topic_score_codex":0.000050144503,"about_ca_topic_score_gemma":0.00005065067,"teacher_disagreement_score":0.993875,"about_ca_system_score_codex":0.000016199929,"about_ca_system_score_gemma":0.00005730883,"threshold_uncertainty_score":0.7055966},"labels":[],"label_agreement":null},{"id":"W2970198235","doi":"10.1007/978-3-030-29829-6_24","title":"Constructing Belief: Using Bayesian Belief Networks to Measure and Manage Uncertainty in Digital Design","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Inro Consultants (Canada)","funders":"","keywords":"Bayesian network; Computer science; Risk analysis (engineering); Inference; Bayesian inference; Outcome (game theory); Knowledge management; Management science; Bayesian probability; Artificial intelligence; Engineering; Business; Mathematics","score_opus":0.03781406733060042,"score_gpt":0.25967166872017894,"score_spread":0.22185760138957852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2970198235","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000004256718,0.0000702428,0.8520855,0.00008669303,0.0001612557,0.00028858832,0.000015499823,0.00007591739,0.14721206],"genre_scores_gemma":[0.09700533,0.00027176042,0.37755564,0.008104758,0.00079939316,0.000008674839,0.00044748996,0.0003689521,0.515438],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982905,0.000019113808,0.0004086305,0.0006513358,0.00032192472,0.0003085049],"domain_scores_gemma":[0.9989393,0.00010914647,0.0001583171,0.0005272005,0.000100980316,0.00016510494],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003125491,0.00032256282,0.00039526165,0.00032053422,0.00007606173,0.0007450311,0.00057972176,0.00021895685,0.00004253953],"category_scores_gemma":[0.00003976709,0.00031363813,0.000055852477,0.00016274747,0.000058251797,0.0005179445,0.0005844731,0.00024862197,0.00002645308],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004702227,0.000009546325,0.00017290346,0.000029501418,0.000039099483,0.00003862868,0.000097164535,0.019001588,0.0000010365741,0.90978247,0.00057712366,0.07024625],"study_design_scores_gemma":[0.00026342875,0.00004561964,0.000006672487,0.00040739408,0.000016899972,0.000034047076,0.00004458088,0.9857195,0.0000016516482,0.0057491674,0.0071661607,0.00054489943],"about_ca_topic_score_codex":0.000021859505,"about_ca_topic_score_gemma":0.00006444581,"teacher_disagreement_score":0.9667179,"about_ca_system_score_codex":0.00011768806,"about_ca_system_score_gemma":0.000107770844,"threshold_uncertainty_score":0.9999316},"labels":[],"label_agreement":null},{"id":"W2970404470","doi":"10.1007/s11257-019-09244-5","title":"Gaze analysis of user characteristics in magazine style narrative visualizations","year":2019,"lang":"en","type":"article","venue":"User Modeling and User-Adapted Interaction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Human–computer interaction; Visualization; Eye tracking; Task (project management); Reading (process); Gaze; Set (abstract data type); Narrative; User interface; User modeling; User experience design; Artificial intelligence","score_opus":0.02552047626472859,"score_gpt":0.3119476732779864,"score_spread":0.2864271970132578,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2970404470","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.48750356,0.000012040688,0.5118655,0.000084524116,0.00016596749,0.00009013312,0.000019112886,0.00004738654,0.00021176734],"genre_scores_gemma":[0.9960167,0.00012302694,0.0025365483,0.00019346492,0.000019287074,0.0000048005195,0.00023160376,0.000013277395,0.00086133525],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99854285,0.00008877285,0.00056832813,0.00038824618,0.00023663047,0.00017514743],"domain_scores_gemma":[0.9989303,0.00006965775,0.00024032213,0.00039631347,0.00029689693,0.00006655113],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022388513,0.00016372553,0.00037170452,0.0008054193,0.000062819025,0.0001544331,0.00024324958,0.00008083697,0.000114044764],"category_scores_gemma":[0.00006971573,0.00016250226,0.0000779166,0.0014161507,0.000015139834,0.001061787,0.00011626798,0.00015317828,0.000020368067],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023345508,0.0015533101,0.11672775,0.00023829544,0.0018244731,0.0000136083745,0.03267816,0.6849193,0.0147264395,0.14066738,0.0015945365,0.0048232703],"study_design_scores_gemma":[0.00030493818,0.000055883127,0.0048585297,0.00009000716,0.000101258556,0.000001385593,0.0007953578,0.9912841,0.00011083929,0.000038672166,0.0021857987,0.00017324489],"about_ca_topic_score_codex":0.00012001464,"about_ca_topic_score_gemma":0.00017244865,"teacher_disagreement_score":0.50932896,"about_ca_system_score_codex":0.00005356424,"about_ca_system_score_gemma":0.00003859919,"threshold_uncertainty_score":0.662665},"labels":[],"label_agreement":null},{"id":"W2971876502","doi":"10.1109/scivis.2018.8823618","title":"3De Interactive Lenses for Visualization in Virtual Environments","year":2018,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Visualization; Computer science; Lens (geology); Focus (optics); Virtual reality; Context (archaeology); Data visualization; Computer graphics (images); Domain (mathematical analysis); Augmented reality; Human–computer interaction; Computer vision; Artificial intelligence; Optics; Physics","score_opus":0.023781503441774425,"score_gpt":0.3310667017197559,"score_spread":0.30728519827798145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2971876502","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004263423,0.0000016637907,0.9939257,0.00010850426,0.0001521268,0.000093727846,0.0000039792226,0.000034582,0.0014162837],"genre_scores_gemma":[0.98781186,0.000008379893,0.0059427647,0.0014603146,0.000069121284,0.000009548229,0.00003548852,0.0000067337437,0.004655788],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994653,0.000023721586,0.00013692518,0.00016276648,0.00009972411,0.000111583686],"domain_scores_gemma":[0.9996926,0.000047731064,0.000042603606,0.00016419472,0.000023561117,0.000029297576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009930942,0.000059151433,0.00006333879,0.00009596856,0.000041994845,0.00007534524,0.00024880614,0.000023462238,0.0000609931],"category_scores_gemma":[0.000063602376,0.00005426191,0.000017070626,0.00017650909,0.000031114763,0.000570776,0.00010411128,0.00001781722,0.000103651786],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018211875,0.00025733912,0.0012053353,0.000004572127,0.000014791821,9.712402e-7,0.0022846665,0.000046841942,0.0028081904,0.9612986,0.00732578,0.024734695],"study_design_scores_gemma":[0.0010405689,0.00060840975,0.002032034,0.00002720279,0.000005162241,0.0000020772434,0.0004772797,0.78546035,0.05437858,0.003174073,0.15250508,0.00028916803],"about_ca_topic_score_codex":0.000007081894,"about_ca_topic_score_gemma":0.000027108188,"teacher_disagreement_score":0.9879829,"about_ca_system_score_codex":0.000030348647,"about_ca_system_score_gemma":0.000014612778,"threshold_uncertainty_score":0.22127365},"labels":[],"label_agreement":null},{"id":"W2972234946","doi":"10.1177/0306312719871356","title":"Medium, calculation, play: On digital images in scientific practice","year":2019,"lang":"en","type":"article","venue":"Social Studies of Science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Sociology; Negotiation; Work (physics); Epistemology; Digital media; Orientation (vector space); Mediation; Value (mathematics); Action (physics); Immutability; Readability; Mathematics; Social science; Geometry; World Wide Web; Physics","score_opus":0.03712835895151081,"score_gpt":0.3749062829960865,"score_spread":0.33777792404457574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2972234946","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87251556,0.0005866803,0.022063382,0.0217085,0.0054508597,0.00088586984,0.00007387364,0.00025255585,0.07646272],"genre_scores_gemma":[0.9984051,0.000012713784,0.000785722,0.00022087374,0.000026167387,0.000001509551,0.0000017062317,0.0000022163836,0.0005439696],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9983728,0.000022937082,0.00020841404,0.0003564278,0.00082774356,0.000211669],"domain_scores_gemma":[0.9989295,0.00018404744,0.0001434012,0.00021720924,0.0004898365,0.000036004927],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010836807,0.00007124819,0.000138396,0.00020573197,0.00045005904,0.00036189612,0.0008047149,0.000017651297,0.000003093083],"category_scores_gemma":[0.001454221,0.00006180728,0.000026856915,0.0021071562,0.0016545105,0.002335999,0.00043336293,0.000059606602,0.000068740716],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026074213,0.0007798942,0.023048272,0.000097237535,0.00005864931,0.00001653935,0.062324695,0.00083307194,0.006791332,0.8576466,0.026536176,0.02184148],"study_design_scores_gemma":[0.007364538,0.0018091203,0.45463595,0.0009712351,0.000085624866,0.000023585497,0.12498511,0.08091435,0.045323506,0.05704217,0.22272637,0.004118448],"about_ca_topic_score_codex":0.000008602445,"about_ca_topic_score_gemma":0.000006095572,"teacher_disagreement_score":0.8006044,"about_ca_system_score_codex":0.00008664314,"about_ca_system_score_gemma":0.00021478685,"threshold_uncertainty_score":0.60961133},"labels":[{"model":"gemma","categories":["sts"],"domain":null,"study_design":"qualitative","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high"},{"model":"gpt","categories":["sts","scholarly_communication"],"domain":null,"study_design":"qualitative","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high"}],"label_agreement":"split"},{"id":"W2976983092","doi":"10.1109/iccse.2019.8845345","title":"Proposing a Pareto-VIKOR Ranking Method for Enhancing Parallel Coordinates Visualization","year":2019,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Visualization; Computer science; Parallel coordinates; Metric (unit); Ranking (information retrieval); Plot (graphics); Sorting; Pairwise comparison; Data mining; Pareto principle; Multi-objective optimization; Data visualization; Contour line; Mathematical optimization; Algorithm; Artificial intelligence; Mathematics; Machine learning; Statistics","score_opus":0.01842503554552514,"score_gpt":0.3391844588951215,"score_spread":0.32075942334959634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2976983092","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00046057755,0.000025978754,0.9969149,0.00029783358,0.00023449102,0.0004340949,0.0000024141061,0.0002464235,0.0013832855],"genre_scores_gemma":[0.23306048,0.000008935306,0.76172,0.0014924746,0.000065413566,0.000027914124,0.000069155765,0.000024284862,0.003531358],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99879104,0.00007121935,0.00029108167,0.00038461105,0.00020773333,0.00025429804],"domain_scores_gemma":[0.9991309,0.00017830194,0.00012524234,0.0003271247,0.0001805504,0.000057874753],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064745103,0.00012757217,0.00018757416,0.00012310022,0.00013284408,0.00037876726,0.00043541926,0.000051283052,0.000050505303],"category_scores_gemma":[0.000111117726,0.0001106899,0.000065158325,0.00043194983,0.000009315118,0.00073432206,0.00013812458,0.000040292023,0.000055819495],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000078762305,0.000055230335,0.00090567,0.00011369437,0.000028173225,7.5271095e-7,0.0005660818,0.0013867656,0.007680506,0.97510844,0.0012221663,0.01292461],"study_design_scores_gemma":[0.0005074417,0.00006305618,0.000032158303,0.00004934863,0.000009832603,0.000003233588,0.00010906002,0.9718037,0.014692034,0.00393509,0.008599668,0.00019537641],"about_ca_topic_score_codex":0.00001770866,"about_ca_topic_score_gemma":0.000023004213,"teacher_disagreement_score":0.9711734,"about_ca_system_score_codex":0.000033912194,"about_ca_system_score_gemma":0.00006263801,"threshold_uncertainty_score":0.4513803},"labels":[],"label_agreement":null},{"id":"W2978716154","doi":"10.1109/tvcg.2019.2934415","title":"Evaluating an Immersive Space-Time Cube Geovisualization for Intuitive Trajectory Data Exploration","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":125,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Computer science; Zoom; Human–computer interaction; Geovisualization; Usability; Visualization; Cube (algebra); Trajectory; Desk; Workload; Artificial intelligence; Information visualization","score_opus":0.09336402127289002,"score_gpt":0.3753260117945121,"score_spread":0.2819619905216221,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2978716154","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0055559543,0.000019560977,0.99230516,0.00008783569,0.00075818616,0.00083995966,0.00014221048,0.00026010815,0.000031025145],"genre_scores_gemma":[0.964444,0.000488551,0.025904173,0.0044256626,0.00035813006,0.00013158792,0.0034603123,0.00014793561,0.0006396786],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973725,0.0003096317,0.0004981249,0.0010090325,0.0005099284,0.00030077403],"domain_scores_gemma":[0.9978607,0.0002272063,0.00025607925,0.0009914509,0.00048743293,0.00017711468],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007186144,0.00031137755,0.00030485186,0.0005737524,0.00042480364,0.0005047111,0.0007405787,0.00015968122,0.000042302945],"category_scores_gemma":[0.000015717818,0.00033385478,0.000081851285,0.0010384928,0.00006757672,0.0033632575,0.000025160005,0.00014330397,0.000040526604],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009885117,0.0008735197,0.00005923527,0.00016236589,0.00018172128,0.0000015062478,0.0046964274,0.017444158,0.00087596674,0.9476838,0.0009252272,0.026997223],"study_design_scores_gemma":[0.0011365998,0.00093597785,0.000048193622,0.00006391618,0.000058191963,0.0000049974315,0.0001900043,0.99314487,0.0019318911,0.0010346585,0.0010439216,0.00040676034],"about_ca_topic_score_codex":0.000012431338,"about_ca_topic_score_gemma":0.000015009067,"teacher_disagreement_score":0.97570074,"about_ca_system_score_codex":0.00004422721,"about_ca_system_score_gemma":0.0001265033,"threshold_uncertainty_score":0.99991137},"labels":[],"label_agreement":null},{"id":"W2981828859","doi":"10.1109/ithings/greencom/cpscom/smartdata.2019.00212","title":"Big Data Analysis and Services: Visualization on Smart Data to Support Healthcare Analytics","year":2019,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Big data; Data science; Computer science; Variety (cybernetics); Visual analytics; Visualization; Data visualization; Analytics; Health care; Data analysis; World Wide Web; Data mining; Artificial intelligence","score_opus":0.13643544424291953,"score_gpt":0.38259885112220593,"score_spread":0.2461634068792864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2981828859","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0035572245,0.0000141862665,0.99161,0.0023711983,0.00027924892,0.00022824637,0.00068633945,0.00016959541,0.0010839716],"genre_scores_gemma":[0.91280097,0.00019265793,0.02300797,0.031335395,0.00016501501,0.0000024913738,0.028320797,0.000034111064,0.004140612],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997718,0.00007274709,0.00036137566,0.0011098967,0.00048670196,0.0002513279],"domain_scores_gemma":[0.99435955,0.00005861958,0.00011365544,0.005081415,0.00013340331,0.0002533772],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006600266,0.00016325203,0.00028168224,0.00053994276,0.000085061925,0.0005070746,0.0032492029,0.00005824989,0.00009755797],"category_scores_gemma":[0.00003944674,0.00014426427,0.000023937055,0.0028744654,0.000012773183,0.00102501,0.00313702,0.00006363339,0.00033610582],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039690083,0.0006956685,0.5093279,0.00073544466,0.0015394541,0.000029680252,0.0016281705,0.0020647284,0.00014680151,0.31373182,0.0535222,0.116538495],"study_design_scores_gemma":[0.00017285395,0.00012489448,0.006788047,0.000017356762,0.0001109824,0.0000014170868,0.00010247298,0.9357782,0.00003067666,0.00006534735,0.056594193,0.00021358575],"about_ca_topic_score_codex":0.00047166616,"about_ca_topic_score_gemma":0.002414478,"teacher_disagreement_score":0.968602,"about_ca_system_score_codex":0.000021927479,"about_ca_system_score_gemma":0.00009610789,"threshold_uncertainty_score":0.60378814},"labels":[],"label_agreement":null},{"id":"W2982503935","doi":"10.2196/14019","title":"Visual Analytic Tools and Techniques in Population Health and Health Services Research: Protocol for a Scoping Review","year":2019,"lang":"en","type":"review","venue":"JMIR Research Protocols","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Regional Municipality of Waterloo; Canadian Institute for Health Information; University of Waterloo; BC Centre for Disease Control; University of British Columbia; McMaster University; University of Calgary; Canadian Institutes of Health Research; Impact; Université de Sherbrooke; University of Toronto; University Health Network; Institute of Health Services and Policy Research; Ontario Neurotrauma Foundation; Toronto Rehabilitation Institute","funders":"","keywords":"Protocol (science); Population health; Population; Computer science; Data science; Psychology; Applied psychology; Medical education; Medicine; Alternative medicine; Environmental health","score_opus":0.7429640043698736,"score_gpt":0.7362142141202958,"score_spread":0.006749790249577892,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2982503935","genre_codex":"protocol","genre_gemma":"protocol","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"protocol","genre_consensus":"protocol","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[2.5411966e-9,0.18029307,0.00082264707,0.00060772424,0.000002005955,0.81813425,0.00002575401,0.00008450734,0.000030023133],"genre_scores_gemma":[4.3781e-9,0.37070525,0.0013748215,0.00038934633,0.00004728746,0.627249,0.00012587906,0.000034671673,0.00007373936],"study_design_codex":"design_other","study_design_gemma":"systematic_review","domain_scores_codex":[0.9906721,0.003542867,0.0017153684,0.0013837565,0.0014620923,0.0012238038],"domain_scores_gemma":[0.9963707,0.0007764511,0.0007401196,0.0010884866,0.00052806357,0.0004962232],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.019673942,0.00041235157,0.0021122757,0.0016657001,0.0004659709,0.0014770014,0.0013705387,0.00023797667,0.000008011516],"category_scores_gemma":[0.0002617165,0.0003350102,0.00013180704,0.003049618,0.00012786148,0.0011070494,0.0013851604,0.0010500477,0.000014692959],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006077212,0.000093752096,0.00002111786,0.4919656,0.0000050398908,0.0000011165921,0.000057293764,1.332376e-8,1.7205863e-8,0.0017050437,0.0017216367,0.5044233],"study_design_scores_gemma":[0.00027694288,0.00088210887,0.000005144858,0.50371945,0.0000010347487,0.0000051019074,0.00000822301,0.0003452733,2.2813589e-7,0.0001750975,0.49442428,0.00015707497],"about_ca_topic_score_codex":0.00011313342,"about_ca_topic_score_gemma":0.00012474504,"teacher_disagreement_score":0.5042662,"about_ca_system_score_codex":0.0005427733,"about_ca_system_score_gemma":0.0038389901,"threshold_uncertainty_score":0.9999102},"labels":[],"label_agreement":null},{"id":"W2983086841","doi":"10.1080/00401706.2019.1629751","title":"Continuous Time Modeling in the Behavioural and Related Sciences","year":2019,"lang":"en","type":"article","venue":"Technometrics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"","keywords":"Mathematics; Econometrics; Computer science","score_opus":0.04476352215554825,"score_gpt":0.28303700426560124,"score_spread":0.238273482110053,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2983086841","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93489563,0.0003220707,0.059039004,0.0006883155,0.000075166456,0.00017715376,0.0000028848801,0.0001730913,0.004626695],"genre_scores_gemma":[0.9974406,0.000024207835,0.0021825063,0.00013121095,0.0000018182014,0.0000010504313,0.0000022511708,0.0000022243084,0.00021413378],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99932617,0.000015872882,0.00013584578,0.00017623589,0.00022100267,0.00012486838],"domain_scores_gemma":[0.9996345,0.000055350716,0.000037888927,0.00023290257,0.000022939646,0.00001639396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006858565,0.00005169813,0.0000798034,0.00061312504,0.000058702593,0.00019188764,0.00072742364,0.000037149664,0.000010303371],"category_scores_gemma":[0.0000927158,0.000036279762,0.000013116361,0.004245044,0.000040917566,0.00028224482,0.0001608311,0.00008964349,0.00006217897],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000015426946,0.00025234287,0.20726238,0.000020356594,0.000009546621,0.000028734215,0.001341717,0.0024563235,0.00022678671,0.73062825,0.00058231375,0.057189703],"study_design_scores_gemma":[0.00014433678,0.000039422826,0.0011990789,0.000006514501,0.0000018973652,0.000009676102,0.00008331461,0.99591154,0.000013318132,0.0023798374,0.00014219926,0.00006886331],"about_ca_topic_score_codex":0.000016872958,"about_ca_topic_score_gemma":6.458071e-7,"teacher_disagreement_score":0.99345523,"about_ca_system_score_codex":0.000010972281,"about_ca_system_score_gemma":0.000015272031,"threshold_uncertainty_score":0.2039603},"labels":[],"label_agreement":null},{"id":"W2983752450","doi":"10.1007/s10664-019-09784-9","title":"An experimental scrutiny of visual design modelling: VCL up against UML+OCL","year":2019,"lang":"en","type":"article","venue":"Empirical Software Engineering","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Unified Modeling Language; Visual modeling; Comprehension; Notation; Software engineering; Programming language; Software; Mathematics","score_opus":0.04332768921336913,"score_gpt":0.3190907181283654,"score_spread":0.27576302891499627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2983752450","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.112167425,0.000074829215,0.8869577,0.00001966959,0.00030635504,0.000101513564,0.000003489614,0.0003457574,0.000023225686],"genre_scores_gemma":[0.8812183,0.000004647366,0.1184016,0.00018418909,0.00006196895,0.0000037550062,0.000020861327,0.000023688412,0.00008096311],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987023,0.000034800418,0.000294838,0.00035536778,0.0003336121,0.00027907683],"domain_scores_gemma":[0.9991958,0.000097141405,0.0000627945,0.00041348135,0.000058724032,0.00017206391],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018924916,0.00017573024,0.0002232057,0.00012361213,0.000038644477,0.00009662232,0.0005948724,0.000078296915,0.000036217883],"category_scores_gemma":[0.000055332115,0.00017502489,0.00007028312,0.00040111493,0.000015920083,0.0005164545,0.0001535487,0.000118331205,0.00006395774],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000061812902,0.00016211985,0.0030099335,0.00003077604,0.000018750896,0.0000055163796,0.0006646753,0.98837566,0.0047406075,0.0011390607,0.0003944028,0.0014522866],"study_design_scores_gemma":[0.00024590164,0.0001354892,0.00014295221,0.000027809427,0.000002814278,0.0000018647047,0.000021304897,0.97882414,0.01879715,0.00001657391,0.0015639064,0.00022009038],"about_ca_topic_score_codex":0.000003019139,"about_ca_topic_score_gemma":4.180457e-8,"teacher_disagreement_score":0.7690509,"about_ca_system_score_codex":0.00004841543,"about_ca_system_score_gemma":0.0000482726,"threshold_uncertainty_score":0.7137308},"labels":[],"label_agreement":null},{"id":"W2985091509","doi":"10.1109/mlui52769.2019.10075563","title":"Shall we play? – Extending the Visual Analytics Design Space through Gameful Design Concepts","year":2019,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Visual analytics; Workflow; Analytics; Human–computer interaction; Context (archaeology); Data science; Point (geometry); Visualization; Artificial intelligence","score_opus":0.06991903238041558,"score_gpt":0.3516262037949849,"score_spread":0.2817071714145693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2985091509","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001709613,0.00015812615,0.99215144,0.0019459616,0.00033210026,0.00034257316,0.0000023652294,0.0002199483,0.0046765464],"genre_scores_gemma":[0.6260986,0.00065596827,0.3423904,0.0061817477,0.00020783696,0.000014316432,0.000016806514,0.00005469811,0.02437965],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99792147,0.00029374176,0.000319443,0.0005163768,0.00051533093,0.000433622],"domain_scores_gemma":[0.9982071,0.000613379,0.00015619732,0.00080362766,0.00011482164,0.00010489699],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007815418,0.00023386645,0.00024532885,0.00008388608,0.00017715941,0.0005865343,0.0014420856,0.00008171837,0.0004497632],"category_scores_gemma":[0.00008804284,0.00015752521,0.00008932065,0.00080893893,0.00008683257,0.00095992093,0.00037716486,0.00016283647,0.001087074],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014839951,0.00015821223,0.00047652476,0.000021829477,0.000102618,0.000024352934,0.0025059707,0.026682975,0.00084392674,0.9079771,0.05639074,0.004800916],"study_design_scores_gemma":[0.0003731961,0.00015815174,0.00008557055,0.000033780525,0.000020404857,0.0000141714,0.00040451184,0.9599245,0.003531328,0.0036976472,0.031450912,0.0003058257],"about_ca_topic_score_codex":0.000015594189,"about_ca_topic_score_gemma":0.0000029246805,"teacher_disagreement_score":0.93324155,"about_ca_system_score_codex":0.000053216037,"about_ca_system_score_gemma":0.00014257355,"threshold_uncertainty_score":0.9996907},"labels":[],"label_agreement":null},{"id":"W2985723853","doi":"10.1145/3311957.3359441","title":"Mapping the \"How\" of Collaborative Action","year":2019,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Sociotechnical system; Computer-supported cooperative work; Crowds; Workflow; Process (computing); Computer science; Data science; Space (punctuation); Collaborative software; Focus (optics); Knowledge management; Sociology; Engineering","score_opus":0.04868269135984792,"score_gpt":0.31016521707838973,"score_spread":0.2614825257185418,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2985723853","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007160252,0.000009076069,0.9735264,0.0027041237,0.00023989103,0.00007513357,0.000001614873,0.000033672368,0.016249832],"genre_scores_gemma":[0.9850413,0.000012102599,0.004670787,0.0005170612,0.000012081283,7.4638416e-7,0.0000023992889,0.0000014019083,0.009742098],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99973816,0.000020406313,0.000048530055,0.00006435501,0.00008984666,0.000038716193],"domain_scores_gemma":[0.99965715,0.000025188176,0.000041693813,0.00019182728,0.000075019714,0.000009112626],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008743832,0.000023189286,0.000036591005,0.00002617631,0.000020637082,0.000054495074,0.00022959165,0.000009101425,0.00005175832],"category_scores_gemma":[0.000011657784,0.000013706981,0.000010135731,0.00043215224,0.00000943825,0.00024018672,0.000059236776,0.000017321605,0.0000499869],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010205408,0.000028361994,0.0017615958,0.000015741285,0.000019858504,2.2393286e-7,0.0017871888,0.000109513145,0.0069738105,0.95386183,0.023009064,0.012431793],"study_design_scores_gemma":[0.00034765506,0.0000702757,0.004434145,0.000020620526,0.0000030208485,0.0000018003774,0.0056242826,0.61700296,0.030437127,0.0019915572,0.3399112,0.00015533996],"about_ca_topic_score_codex":0.0000027837539,"about_ca_topic_score_gemma":0.0000028672985,"teacher_disagreement_score":0.9778811,"about_ca_system_score_codex":0.0000047664344,"about_ca_system_score_gemma":0.000023859679,"threshold_uncertainty_score":0.06424971},"labels":[],"label_agreement":null},{"id":"W2989690241","doi":"10.22215/etd/2019-13597","title":"Data Visualization of Geospatial Data for Future Business Investments","year":2019,"lang":"en","type":"dissertation","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Geospatial analysis; Computer science; Workload; Data science; Asset (computer security); Order (exchange); Asset management; Visualization; Knowledge management; Data mining; Business; Finance","score_opus":0.06582469208491032,"score_gpt":0.37650516423380137,"score_spread":0.31068047214889105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2989690241","genre_codex":"methods","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00015017625,0.00013579224,0.98969364,0.00010295366,0.0028987122,0.0005674551,0.0051258025,0.00008671976,0.0012387299],"genre_scores_gemma":[0.001571182,0.0003980208,0.040404387,0.0006044032,0.00052414316,0.000010670958,0.9428331,0.000056267447,0.0135978],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979666,0.000036350684,0.0005008918,0.00086847774,0.00045831915,0.00016936251],"domain_scores_gemma":[0.99451894,0.000045798795,0.0005345019,0.0042683524,0.0005793025,0.000053091142],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.00031306886,0.00022388173,0.00033781922,0.00019162687,0.000060769486,0.00019814476,0.0058361413,0.00021199751,0.000047610487],"category_scores_gemma":[0.00020641061,0.00020376126,0.000027673077,0.000646533,0.000011883113,0.0016699311,0.0010295834,0.000059445265,0.000024302592],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006343001,0.0005895428,0.00036895098,0.0031493695,0.00033740207,0.0000017140393,0.00075887726,0.00007764642,0.00017060153,0.56138295,0.38381702,0.04928249],"study_design_scores_gemma":[0.00062601164,0.000036864865,0.0015480618,0.00015099785,0.0001141499,6.859065e-7,0.00028592587,0.8316825,0.00021470572,0.00044945875,0.1644834,0.00040724993],"about_ca_topic_score_codex":0.000056150388,"about_ca_topic_score_gemma":0.00029757657,"teacher_disagreement_score":0.94928926,"about_ca_system_score_codex":0.000014234093,"about_ca_system_score_gemma":0.0004721483,"threshold_uncertainty_score":0.9995428},"labels":[],"label_agreement":null},{"id":"W2990089916","doi":"","title":"Affordance Networks: An Approach for Linking IT features-in-use to Their Effects","year":2019,"lang":"en","type":"article","venue":"Journal of the Association for Information Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Affordance; Computer science; Human–computer interaction; Knowledge management","score_opus":0.014200280131236183,"score_gpt":0.26301638971148816,"score_spread":0.248816109580252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2990089916","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027472747,0.000021395317,0.99362344,0.00035227655,0.0018492059,0.0010025632,0.000019371622,0.000018236966,0.0003662475],"genre_scores_gemma":[0.9860586,0.000008559354,0.010496266,0.0018201073,0.00030235766,0.000036439164,0.00005235217,0.000009929367,0.0012154236],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986403,0.00009915785,0.0006278259,0.00007380772,0.00038039725,0.00017849423],"domain_scores_gemma":[0.99733806,0.0003524233,0.0013852258,0.000250567,0.0006164775,0.000057220317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021059671,0.00009163247,0.00022418764,0.00019024572,0.000098569166,0.0007983503,0.00071148574,0.00008635285,1.28049e-7],"category_scores_gemma":[0.00044176422,0.00006202241,0.00013235421,0.00044907222,0.0000023323378,0.003777534,0.000056238492,0.00010793788,0.0000033482006],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000067207,0.00008817946,0.0176432,0.0003899315,0.00012271704,8.393968e-8,0.006937482,0.85417014,0.000054298573,0.09162972,0.025192125,0.0037049272],"study_design_scores_gemma":[0.0010984238,0.00012456777,0.004476785,0.00019147727,0.000011521464,0.0000063602984,0.00046553297,0.9188067,0.00007502913,0.0001015338,0.07451562,0.00012649904],"about_ca_topic_score_codex":0.000003383924,"about_ca_topic_score_gemma":0.0000023166501,"teacher_disagreement_score":0.9833113,"about_ca_system_score_codex":0.00029472995,"about_ca_system_score_gemma":0.00006216827,"threshold_uncertainty_score":0.769851},"labels":[],"label_agreement":null},{"id":"W2990531070","doi":"10.5753/cbie.sbie.2019.1741","title":"Teachers' Perceptions on Traditional and Non-Traditional Data Visualization for Pedagogical Decision-Making","year":2019,"lang":"pt","type":"article","venue":"Anais do XXX Simpósio Brasileiro de Informática na Educação (SBIE 2019)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Fundação de Amparo à Pesquisa do Estado de Alagoas; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Canadian Bureau for International Education","keywords":"Visualization; Computer science; Context (archaeology); Perception; Variety (cybernetics); Data visualization; Point (geometry); Graphics; Information visualization; Affect (linguistics); Mathematics education; Multimedia; Psychology; Artificial intelligence","score_opus":0.130803576143818,"score_gpt":0.40081880009120857,"score_spread":0.2700152239473906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2990531070","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21633802,0.00027297824,0.7662702,0.0015173255,0.0029602405,0.0020966826,0.0069947657,0.0002671409,0.0032826224],"genre_scores_gemma":[0.9747474,0.00034066086,0.010655585,0.005484531,0.0010026784,0.000055320532,0.0058303336,0.00010371701,0.0017797278],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9940298,0.00015529268,0.0014086433,0.0016804592,0.0015663493,0.0011594445],"domain_scores_gemma":[0.9933485,0.0026791259,0.0005709805,0.0021600337,0.0004705617,0.00077083794],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001524616,0.0008082805,0.000790494,0.0008409146,0.00092588103,0.0019862931,0.0027335405,0.00060228474,0.0028312446],"category_scores_gemma":[0.001474869,0.0008079619,0.00030629896,0.0010405969,0.00032411783,0.0035165981,0.0008932051,0.0006862829,0.0010242987],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040653697,0.003817552,0.050458487,0.00052265526,0.0005134831,0.000027594853,0.013672394,0.0015529868,0.00030074202,0.24750394,0.5862581,0.094965525],"study_design_scores_gemma":[0.0033606365,0.0017073709,0.15509951,0.0014951852,0.00032260892,0.000195017,0.004647077,0.795478,0.000037519174,0.007922965,0.027723687,0.0020104663],"about_ca_topic_score_codex":0.000025117726,"about_ca_topic_score_gemma":0.000015915914,"teacher_disagreement_score":0.793925,"about_ca_system_score_codex":0.0003411936,"about_ca_system_score_gemma":0.0014088332,"threshold_uncertainty_score":0.99975353},"labels":[],"label_agreement":null},{"id":"W2990841712","doi":"10.20380/gi2019.12","title":"Controlling Procedural Modelling Interactively with Guiding Curves","year":2019,"lang":"en","type":"article","venue":"Canada Human-Computer Communications Society","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Probabilistic logic; Constraint (computer-aided design); Set (abstract data type); Space (punctuation); Monte Carlo method; Function (biology); Theoretical computer science; Artificial intelligence; Algorithm; Machine learning; Programming language; Mathematics","score_opus":0.052110855835335285,"score_gpt":0.2855826971218953,"score_spread":0.23347184128656004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2990841712","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0025485542,0.00039516875,0.9910332,0.004275818,0.00012373822,0.00029316425,0.00000913445,0.00014709849,0.0011741071],"genre_scores_gemma":[0.7242446,0.00022562049,0.26477394,0.009953312,0.000054962686,0.00002264731,0.00013688847,0.000025292138,0.00056274794],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99860036,0.00007998598,0.00034045515,0.00035413355,0.00034629577,0.00027874298],"domain_scores_gemma":[0.99740344,0.00016356626,0.00021475552,0.0017742474,0.00034006135,0.00010392082],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022739482,0.00018800118,0.00024591488,0.000038526225,0.00051175826,0.00026845856,0.0025893548,0.000038229053,0.000013883179],"category_scores_gemma":[0.00000545048,0.000174945,0.00008994687,0.00039910965,0.000066080815,0.00074571377,0.0006817225,0.00020754072,0.000007888687],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000111801,0.0005115719,0.0034199145,0.000839861,0.0011142812,0.0000076231263,0.009218364,0.14361997,0.00071678037,0.546844,0.28907758,0.004618905],"study_design_scores_gemma":[0.00036350486,0.000023012122,0.000059783353,0.000285791,0.00001478881,0.000005923507,0.00014809414,0.96726376,0.00006033249,0.00013064759,0.031391267,0.00025310367],"about_ca_topic_score_codex":0.013391485,"about_ca_topic_score_gemma":0.013551663,"teacher_disagreement_score":0.8236438,"about_ca_system_score_codex":0.0002448883,"about_ca_system_score_gemma":0.0006236038,"threshold_uncertainty_score":0.9931784},"labels":[],"label_agreement":null},{"id":"W2991285952","doi":"10.3389/frobt.2019.00128","title":"Task Dependent Group Coupling and Territorial Behavior on Large Tiled Displays","year":2019,"lang":"en","type":"article","venue":"Frontiers in Robotics and AI","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Human–computer interaction; Sensemaking; Task (project management); Visual analytics; Analytics; Visualization; Data visualization; Process (computing); Space (punctuation); Data science; World Wide Web; Artificial intelligence","score_opus":0.007393682761218173,"score_gpt":0.25296968169089945,"score_spread":0.24557599892968127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2991285952","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.039073948,0.00011785054,0.9564951,0.00021878863,0.0037797268,0.0001780776,0.000023730696,0.000030217003,0.0000825651],"genre_scores_gemma":[0.9816424,0.00012500156,0.017244112,0.00042974856,0.00015780468,0.0000044630415,0.000040577062,0.000011492155,0.00034437756],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992213,0.000012338166,0.00014859624,0.00027238767,0.00016435458,0.0001809883],"domain_scores_gemma":[0.99965304,0.000014417695,0.000041268017,0.00020311336,0.000015675434,0.000072483424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000148807,0.000097861936,0.00014897413,0.000092583075,0.000059123173,0.00019902967,0.00019599231,0.000058087415,0.000003001252],"category_scores_gemma":[0.000009254016,0.00009080503,0.000016871309,0.00009913913,0.000017529783,0.00019968674,0.00015525018,0.00011162319,0.00000453334],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003591596,0.0006793899,0.7535743,0.00008563771,0.000040110255,0.000064484295,0.00065593177,0.010248781,0.0003112099,0.21363084,0.0133236395,0.007349736],"study_design_scores_gemma":[0.0011185827,0.00010429835,0.008213512,0.00004399033,0.000013801913,0.0000022346896,0.0000763081,0.9862671,0.000023195718,0.0005189887,0.0034262617,0.00019175233],"about_ca_topic_score_codex":0.0000066185457,"about_ca_topic_score_gemma":0.000009060558,"teacher_disagreement_score":0.9760183,"about_ca_system_score_codex":0.000020912512,"about_ca_system_score_gemma":0.000012293998,"threshold_uncertainty_score":0.37029216},"labels":[],"label_agreement":null},{"id":"W2991332254","doi":"10.5194/nhess-20-1557-2020","title":"Enhancing the operational value of snowpack models with visualization design principles","year":2020,"lang":"en","type":"article","venue":"Natural hazards and earth system sciences","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Simon Fraser University","keywords":"Snowpack; Visualization; Workflow; Computer science; Terrain; Data visualization; Field (mathematics); Snow; Data science; Data mining; Meteorology; Database; Cartography","score_opus":0.047097741772846674,"score_gpt":0.2829808021925496,"score_spread":0.23588306041970294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2991332254","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015015352,0.00029856968,0.98308223,0.00084817666,0.00008560029,0.00016002428,0.0000042253646,0.00005015674,0.0004556892],"genre_scores_gemma":[0.9749365,0.000016058437,0.024614124,0.0003438917,0.00004071886,0.0000022588345,0.00000265102,0.0000025615786,0.000041236533],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987288,0.00011793929,0.0002322257,0.00026310293,0.00052772794,0.00013020333],"domain_scores_gemma":[0.9994768,0.000078984776,0.00012242782,0.000113385206,0.00014596268,0.00006246557],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000652043,0.00008927852,0.00013131736,0.00004266709,0.00033654616,0.0003309001,0.00044595424,0.000023456267,0.000002092127],"category_scores_gemma":[0.00003890381,0.000047356654,0.000019954688,0.0006518835,0.00014567179,0.00082610874,0.00010006517,0.000048976515,0.0000022388067],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000045197726,0.000005784209,0.00006686814,0.000051251496,0.000008326218,9.2828367e-7,0.001104061,0.04850829,0.0006114572,0.9477069,0.000047983613,0.001883654],"study_design_scores_gemma":[0.00009969731,0.000116500996,0.00010634496,0.00006919437,0.000004896333,0.000009931211,0.00051467144,0.9947729,0.0039786836,0.00008703898,0.00016267475,0.00007746495],"about_ca_topic_score_codex":0.000017502112,"about_ca_topic_score_gemma":0.0000074407135,"teacher_disagreement_score":0.9599211,"about_ca_system_score_codex":0.0000055514706,"about_ca_system_score_gemma":0.000203773,"threshold_uncertainty_score":0.3190877},"labels":[],"label_agreement":null},{"id":"W2996118209","doi":"10.1109/visual.2019.8933542","title":"Uncovering Data Landscapes through Data Reconnaissance and Task Wrangling","year":2019,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Data science; Computer science; Task (project management); Domain (mathematical analysis); Visualization; Set (abstract data type); Data visualization; Data mining; Systems engineering; Engineering","score_opus":0.08160704378035767,"score_gpt":0.330723064920984,"score_spread":0.24911602114062636,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2996118209","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00329235,0.00034524553,0.98101693,0.000848337,0.0002786024,0.00008139607,0.00013638394,0.00015880907,0.01384197],"genre_scores_gemma":[0.7879972,0.0011501451,0.20129448,0.0041214093,0.00030065668,0.0000011348881,0.0018189854,0.00002613102,0.0032898793],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99905276,0.000017062159,0.00013474835,0.0005271637,0.00013463887,0.00013360065],"domain_scores_gemma":[0.99747527,0.000055309312,0.000044654793,0.0023662415,0.000021341122,0.00003716612],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027054895,0.0000749898,0.0001024937,0.000030896408,0.000051216703,0.00030795843,0.0022649567,0.000022171134,0.0000462438],"category_scores_gemma":[0.000083833766,0.000063533334,0.000005581144,0.00023270973,0.000012549828,0.0029775742,0.0029347248,0.00004771591,0.000097269905],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001515419,0.0001856458,0.04555943,0.00035653083,0.00018184437,0.00003540106,0.00178685,0.0014667333,0.0009848734,0.6343236,0.14967488,0.16542907],"study_design_scores_gemma":[0.00019530559,0.000009412099,0.00014097511,0.00002536114,0.0000032100609,0.00000558924,0.00004338612,0.7336282,0.00006341393,0.0010173157,0.2647475,0.000120359306],"about_ca_topic_score_codex":0.00004922354,"about_ca_topic_score_gemma":0.000056553166,"teacher_disagreement_score":0.7847048,"about_ca_system_score_codex":0.0000046592863,"about_ca_system_score_gemma":0.000041426218,"threshold_uncertainty_score":0.42088908},"labels":[],"label_agreement":null},{"id":"W2997617508","doi":"10.13140/rg.2.2.33547.21281","title":"Analytics and Visualization of Spatial Models as a Service","year":2019,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; DEVS; Visualization; Graphical user interface; Web service; Analytics; User interface; Service (business); Software; Software engineering; Interface (matter); Conceptual architecture; Architecture; Human–computer interaction; World Wide Web; Database; Operating system; Modeling and simulation; Simulation; Data mining","score_opus":0.024248649078345376,"score_gpt":0.29654360913858113,"score_spread":0.27229496006023574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2997617508","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014451597,0.000008528241,0.97559476,0.00020193117,0.000047087076,0.00006232534,0.000002052274,0.00004501411,0.009586694],"genre_scores_gemma":[0.99319756,0.000022150589,0.004650933,0.0012142301,0.000008608054,3.8891335e-7,0.00001457057,0.0000043572904,0.00088718353],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99941355,0.000016977116,0.00015429349,0.00016112873,0.00017852323,0.00007555022],"domain_scores_gemma":[0.999468,0.000020268644,0.00006504853,0.00025781157,0.00014499307,0.000043833556],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009633616,0.000056986635,0.000098368764,0.00008167259,0.000016238788,0.00006277196,0.00023122127,0.000028860039,0.000069028356],"category_scores_gemma":[0.000010504949,0.000050814462,0.000014051324,0.0003585575,0.000008786684,0.000456556,0.00015822363,0.000017942099,0.000038804446],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016764506,0.000032773067,0.0015703789,0.000033405817,0.000009346794,3.2960745e-7,0.0002737418,0.0030641558,0.00023981582,0.99329674,0.00013120209,0.0013464277],"study_design_scores_gemma":[0.00017939734,0.00003661618,0.0002716535,0.00000936405,0.000004823378,0.000001717274,0.00003097997,0.9920303,0.0008627489,0.0059993854,0.0005061847,0.000066827844],"about_ca_topic_score_codex":0.00020150728,"about_ca_topic_score_gemma":0.000037747126,"teacher_disagreement_score":0.98896617,"about_ca_system_score_codex":0.0000052129267,"about_ca_system_score_gemma":0.000037242688,"threshold_uncertainty_score":0.20721537},"labels":[],"label_agreement":null},{"id":"W2998073349","doi":"10.1109/vahc47919.2019.8945039","title":"PADE: Supporting Collaborative Visual Analysis of Patient Administrative Systems Data with a Large Touch Display System","year":2019,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"European Commission; Strategiske Forskningsråd","keywords":"Computer science; Padé approximant; Human–computer interaction; Visualization; Computer graphics (images); Artificial intelligence; Mathematics","score_opus":0.0210311037787432,"score_gpt":0.3392476650014512,"score_spread":0.318216561222708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2998073349","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1082409,0.00003429176,0.8849816,0.00006865446,0.00019177004,0.0006355757,0.0012835878,0.00014608317,0.00441759],"genre_scores_gemma":[0.99643046,0.0000018854379,0.002314337,0.00006465316,0.000010126709,0.000007385846,0.0007795281,0.000007661334,0.00038395607],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978223,0.00015100806,0.0005955044,0.0005858256,0.0005806462,0.00026470996],"domain_scores_gemma":[0.9975919,0.00012489178,0.00059212133,0.0011596518,0.00042003384,0.00011137486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038885963,0.00016890353,0.0004972078,0.00025435875,0.00007051029,0.0002537529,0.0009235577,0.000046361747,0.000041766903],"category_scores_gemma":[0.00004081204,0.00011820034,0.00005424938,0.0031142996,0.00002791375,0.0008049888,0.00048881606,0.00006234199,0.00002631313],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054902426,0.00069342594,0.09355172,0.00043585207,0.003909583,0.000050122766,0.0054087015,0.0031366295,0.0001613218,0.8900309,0.0021502108,0.00041661132],"study_design_scores_gemma":[0.00031472437,0.00035177055,0.0006616223,0.00007478647,0.00027816815,0.0000029166429,0.013752081,0.98270667,0.00030257896,0.0000010237922,0.0013617062,0.00019195942],"about_ca_topic_score_codex":0.00006608926,"about_ca_topic_score_gemma":0.000092742885,"teacher_disagreement_score":0.97957003,"about_ca_system_score_codex":0.000044382068,"about_ca_system_score_gemma":0.00027738974,"threshold_uncertainty_score":0.482007},"labels":[],"label_agreement":null},{"id":"W3000988915","doi":"10.1145/3241380","title":"A Visual Analytics Approach for Interactive Document Clustering","year":2019,"lang":"en","type":"article","venue":"ACM Transactions on Interactive Intelligent Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cluster analysis; Computer science; Visual analytics; Analytics; Visualization; Data mining; Set (abstract data type); Process (computing); Key (lock); Document clustering; Information retrieval; Machine learning","score_opus":0.03359866520823913,"score_gpt":0.33494963901087926,"score_spread":0.30135097380264014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3000988915","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008428596,0.000024511557,0.99328107,0.00016295357,0.0023979433,0.0012814223,0.00005578177,0.00019458911,0.0017589006],"genre_scores_gemma":[0.9765475,0.000033786117,0.017810797,0.00033113622,0.0001003694,0.00027656285,0.00006790931,0.0000447325,0.004787202],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973935,0.00015890696,0.0007192438,0.00083921046,0.00045936633,0.00042976512],"domain_scores_gemma":[0.9973384,0.00067670434,0.0003303326,0.0010903878,0.00039460298,0.00016953617],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003685283,0.0003735707,0.00046132877,0.000548444,0.000177151,0.00059244165,0.0013236433,0.00011514642,0.00013242749],"category_scores_gemma":[0.00008052364,0.00034671163,0.0003145206,0.0005467867,0.000035294594,0.0012640851,0.000070892915,0.00035244337,0.00038390618],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017678655,0.005400411,0.00035835608,0.0012230366,0.0040766518,0.000022626444,0.01238576,0.8272731,0.0032434005,0.036908302,0.0027003489,0.10464017],"study_design_scores_gemma":[0.00053035293,0.0007565391,0.000011278535,0.00021244856,0.00005277712,0.000031788746,0.003091688,0.9747273,0.0074430644,0.0002344116,0.0124664055,0.00044196213],"about_ca_topic_score_codex":0.000086078326,"about_ca_topic_score_gemma":0.000009324389,"teacher_disagreement_score":0.97570467,"about_ca_system_score_codex":0.00047462448,"about_ca_system_score_gemma":0.00007314712,"threshold_uncertainty_score":0.9998985},"labels":[],"label_agreement":null},{"id":"W3001738025","doi":"10.1109/mcg.2020.2968906","title":"PixelClipper: Supporting Public Engagement and Conversation About Visualizations","year":2020,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of Calgary","funders":"H2020 Marie Skłodowska-Curie Actions; Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures","keywords":"Computer science; Facilitator; Visualization; Conversation; Data visualization; Bridge (graph theory); World Wide Web; Public engagement; Information visualization; Human–computer interaction; Function (biology); Annotation; Data science; Multimedia; Artificial intelligence","score_opus":0.05245772478856532,"score_gpt":0.30798934242104775,"score_spread":0.25553161763248244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3001738025","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0022285043,0.00008082012,0.9910805,0.0059684208,0.000058762576,0.0002758221,0.000018454315,0.00019452443,0.00009414511],"genre_scores_gemma":[0.97280866,0.0005968619,0.018694693,0.0074430658,0.00024260349,0.00007090252,0.00011432781,0.000014741704,0.000014118386],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988639,0.000054477016,0.0002982914,0.0004303306,0.00017099209,0.00018205369],"domain_scores_gemma":[0.99914956,0.00006872036,0.00013575472,0.0002652891,0.00013743182,0.00024325683],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022284937,0.00012819962,0.0001309865,0.000121088335,0.0003867805,0.0005598754,0.00033163594,0.00004583724,0.000007641369],"category_scores_gemma":[0.000012305868,0.00013374248,0.000033205186,0.00064216426,0.000086778855,0.00041997805,0.00022645126,0.00010758797,0.000012863567],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.814355e-7,0.00004013678,0.0019217544,0.000030552663,0.000019126062,5.474301e-7,0.00059487,0.000026739232,0.000091159134,0.9796153,0.0011519047,0.016507642],"study_design_scores_gemma":[0.00027068955,0.00004287946,0.0017104138,0.000007403319,0.000015927295,0.0000044328362,0.000052297797,0.84617263,0.00006452641,0.0030955062,0.14835641,0.0002069024],"about_ca_topic_score_codex":0.000003195882,"about_ca_topic_score_gemma":0.000002216052,"teacher_disagreement_score":0.97651976,"about_ca_system_score_codex":0.000006548682,"about_ca_system_score_gemma":0.000040053448,"threshold_uncertainty_score":0.545386},"labels":[],"label_agreement":null},{"id":"W3003076508","doi":"10.24908/iqurcp.10641","title":"7. Shape and Motion Integration in People Perception Depends on the Action of the Performer","year":2018,"lang":"en","type":"article","venue":"Inquiry Queen s Undergraduate Research Conference Proceedings","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Motion (physics); Perception; Action (physics); Performing arts; Object (grammar); Biological motion; Kinematics; Communication; Artificial intelligence; Motion capture; Computer vision; Psychology; Computer science; Physics; Visual arts; Art; Classical mechanics","score_opus":0.1470669104366305,"score_gpt":0.3956191493023162,"score_spread":0.24855223886568567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3003076508","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9178874,0.0000035844957,0.044936635,0.034448776,0.00015413565,0.00042132614,0.0000018740003,0.000038842194,0.002107413],"genre_scores_gemma":[0.9990578,0.0001882755,0.00019226567,0.00015495553,0.000081493505,0.000023987459,0.0000035630221,0.0000072821954,0.00029035655],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981836,0.00014008084,0.0002542936,0.00035799175,0.00078437454,0.0002796405],"domain_scores_gemma":[0.9984847,0.00011897036,0.00011659356,0.0002434645,0.0009799897,0.000056322413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017154678,0.00011878595,0.0001194277,0.0002949762,0.00035241654,0.00041210494,0.0007010827,0.00007797384,0.000035436948],"category_scores_gemma":[0.000489805,0.00007159475,0.00003066927,0.0012929622,0.0004762935,0.00095497776,0.0003178864,0.00039226105,0.000028711765],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044745604,0.00014225973,0.015863696,0.0000656228,0.0000119954975,2.615719e-7,0.015777357,0.0000024633762,0.024130244,0.8212624,0.0025231338,0.12017578],"study_design_scores_gemma":[0.00049982435,0.0006223767,0.13330029,0.0004718607,0.0000087828475,0.000010596188,0.011312867,0.7581927,0.024296233,0.070303135,0.00070735003,0.00027395174],"about_ca_topic_score_codex":0.00016780481,"about_ca_topic_score_gemma":0.0001927297,"teacher_disagreement_score":0.7581903,"about_ca_system_score_codex":0.00011784141,"about_ca_system_score_gemma":0.00012430853,"threshold_uncertainty_score":0.39739373},"labels":[],"label_agreement":null},{"id":"W3003718360","doi":"10.1177/1473871619896101","title":"Visualization in the preprocessing phase: Getting insights from enterprise professionals","year":2020,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Canadian Bureau for International Education","keywords":"Computer science; Visualization; Data science; Workflow; Data visualization; Process (computing); Raw data; Scope (computer science); Set (abstract data type); Data pre-processing; Preprocessor; Data mining; Knowledge management; Database; Artificial intelligence","score_opus":0.027544756766617464,"score_gpt":0.3509752933536995,"score_spread":0.32343053658708204,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3003718360","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016209107,0.000053429652,0.98081344,0.0013224512,0.00015164382,0.00038537174,0.000014954568,0.00024369165,0.00080593437],"genre_scores_gemma":[0.9802658,0.000022347924,0.0014925009,0.016510284,0.000117005,0.000032620173,0.0015395092,0.000010391563,0.000009517674],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977802,0.00026067984,0.0008281396,0.00025987212,0.0006877872,0.00018330608],"domain_scores_gemma":[0.9987587,0.0001148933,0.0004878959,0.00030968877,0.00024625086,0.00008261196],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034141407,0.00017510806,0.00016604265,0.00022907117,0.00024144842,0.0008369617,0.00077758514,0.00009254856,0.000038458034],"category_scores_gemma":[0.0005134888,0.00013913967,0.00004133217,0.001735752,0.000024039253,0.006954621,0.00016137518,0.0001173514,0.0001255743],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008148435,0.0009856316,0.004668306,0.00039655407,0.000051727275,0.00001001683,0.33067492,0.0057030516,0.001473254,0.5826398,0.014796079,0.05851915],"study_design_scores_gemma":[0.0010178131,0.00005224855,0.0006119727,0.00010226353,0.000007918192,0.0000012139604,0.0020333817,0.97617173,0.0011527194,0.0009822287,0.017656285,0.0002102166],"about_ca_topic_score_codex":0.000018704603,"about_ca_topic_score_gemma":0.0000049502446,"teacher_disagreement_score":0.97932094,"about_ca_system_score_codex":0.000044856784,"about_ca_system_score_gemma":0.00010904022,"threshold_uncertainty_score":0.80708414},"labels":[],"label_agreement":null},{"id":"W3005749067","doi":"10.5753/sibgrapi.est.2020.12991","title":"Preprocessing Profiling Model for Visual Analytics","year":2020,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Government of Canada","keywords":"Computer science; Preprocessor; Visual analytics; Visualization; Data pre-processing; Profiling (computer programming); Data visualization; Data science; Data mining; Raw data; Analytics; Process (computing); Scope (computer science); Artificial intelligence","score_opus":0.09200503410435676,"score_gpt":0.3606945119934958,"score_spread":0.268689477889139,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3005749067","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00023297081,0.00000835193,0.9969232,0.0013874465,0.00002229232,0.00009234239,0.000003842991,0.00021172188,0.0011178197],"genre_scores_gemma":[0.48806682,0.0000028920635,0.5055281,0.0055194353,0.00006804539,0.0000051427082,0.00002107396,0.000009209378,0.0007792783],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992822,0.000006012244,0.0001627093,0.00027534683,0.0001351775,0.00013856115],"domain_scores_gemma":[0.9995844,0.00002158538,0.00004802853,0.00014156563,0.000101795995,0.00010265456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009832024,0.00006923989,0.00008986682,0.000029974804,0.00007564765,0.00022534213,0.0003843739,0.000024463572,0.0000046655778],"category_scores_gemma":[0.000109897315,0.000061745624,0.00003855246,0.0003022641,0.0000106533535,0.00043882747,0.0001394681,0.000033711458,0.000013333619],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012744494,0.00013434154,0.0006712025,0.00026386,0.00004092024,0.0000023877196,0.001852994,0.15970396,0.0028065764,0.8062808,0.008652284,0.019577939],"study_design_scores_gemma":[0.0001380576,0.000024277542,0.0000016196119,0.00000378704,0.0000056671734,3.0684137e-7,0.000032038377,0.99387544,0.00381859,0.001443491,0.00056472677,0.00009201995],"about_ca_topic_score_codex":3.31191e-7,"about_ca_topic_score_gemma":4.2153852e-7,"teacher_disagreement_score":0.8341715,"about_ca_system_score_codex":0.0000076995075,"about_ca_system_score_gemma":0.00008790351,"threshold_uncertainty_score":0.25179136},"labels":[],"label_agreement":null},{"id":"W3006254691","doi":"10.1145/3334480.3382864","title":"Capturing the Practices, Challenges, and Needs of Transportation Decision-Makers","year":2020,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Workflow; Interoperability; Government (linguistics); Agency (philosophy); Quality (philosophy); Work (physics)","score_opus":0.0637426416145598,"score_gpt":0.3039755185858082,"score_spread":0.2402328769712484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3006254691","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008382452,0.0011521104,0.9640405,0.022808991,0.000055458167,0.00008215237,0.000004340626,0.000061800776,0.0034121673],"genre_scores_gemma":[0.98965144,0.0010373963,0.008159173,0.0010972449,0.000015882044,6.279009e-7,0.0000034681138,0.0000024709009,0.000032300206],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99960846,0.000015765063,0.00011792212,0.00008242159,0.00012757574,0.000047876318],"domain_scores_gemma":[0.99955803,0.00012539007,0.00011234846,0.00012829596,0.000032668293,0.000043272357],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000115267074,0.000038240443,0.00005436416,0.000023753928,0.000026916976,0.00003619662,0.00022362104,0.000014560665,0.000009556103],"category_scores_gemma":[0.00008602109,0.000024950949,0.00001340334,0.00017583347,0.000016944226,0.00032395782,0.000022287291,0.000033632674,0.0000033699716],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000833224,0.000029644818,0.00025369282,0.000046122506,0.000024353936,0.0000033957372,0.022472728,0.00015719749,0.00010138878,0.7880266,0.0016946135,0.18718196],"study_design_scores_gemma":[0.0013294365,0.000264708,0.016271086,0.00008875255,0.00007629114,0.000010695389,0.023132592,0.6487357,0.0019791366,0.006616228,0.30102938,0.00046600096],"about_ca_topic_score_codex":0.000014006215,"about_ca_topic_score_gemma":0.00002318853,"teacher_disagreement_score":0.981269,"about_ca_system_score_codex":0.000001685227,"about_ca_system_score_gemma":0.000016219723,"threshold_uncertainty_score":0.10174701},"labels":[],"label_agreement":null},{"id":"W3007795301","doi":"10.3390/data5010020","title":"VARTTA: A Visual Analytics System for Making Sense of Real-Time Twitter Data","year":2020,"lang":"en","type":"article","venue":"Data","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Microblogging; Computer science; Social media; Analytics; Visual analytics; Data science; Aggregate (composite); Data analysis; Social media analytics; Visualization; World Wide Web; Data mining","score_opus":0.16399634951439704,"score_gpt":0.38296479146433393,"score_spread":0.2189684419499369,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3007795301","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00029851287,0.000012963757,0.9933121,0.00091378106,0.00009852275,0.00015450716,0.0046935854,0.00013628378,0.00037969637],"genre_scores_gemma":[0.62905544,0.0000644067,0.3123728,0.005331211,0.0010525173,0.0000063446187,0.05157403,0.000089271416,0.00045397252],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99851936,0.00005132235,0.00036181798,0.0006146462,0.00026787183,0.00018499824],"domain_scores_gemma":[0.99677473,0.00010812807,0.00018841495,0.0027481387,0.000089327164,0.000091230366],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045693104,0.000112920054,0.00023934539,0.000056768688,0.00005435259,0.00017344282,0.0030576228,0.000038840735,0.000014403614],"category_scores_gemma":[0.00023375206,0.00010597931,0.000025016701,0.00044037678,0.000028160706,0.00080982543,0.0035998183,0.00004821237,0.00009317207],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045137218,0.00018658092,0.0004075659,0.0010581943,0.00027645243,0.00008961341,0.000933192,0.00017808305,0.0031299654,0.030732697,0.95852536,0.0044371793],"study_design_scores_gemma":[0.00023761835,0.000038693634,0.000020216201,0.000047845588,0.000048551672,0.0000065448944,0.000082252875,0.9460851,0.00014579676,0.0000137531515,0.05315562,0.000118000564],"about_ca_topic_score_codex":0.000009804568,"about_ca_topic_score_gemma":0.0000018709391,"teacher_disagreement_score":0.945907,"about_ca_system_score_codex":0.000011563181,"about_ca_system_score_gemma":0.0000831193,"threshold_uncertainty_score":0.5681875},"labels":[],"label_agreement":null},{"id":"W3010016343","doi":"10.1145/3377325.3377517","title":"Understanding the effectiveness of adaptive guidance for narrative visualization","year":2020,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visualization; Computer science; Narrative; Adaptation (eye); Human–computer interaction; Comprehension; Process (computing); Salient; Information visualization; Storytelling; Gaze; Multimedia; World Wide Web; Artificial intelligence; Psychology; Linguistics","score_opus":0.13667634096325823,"score_gpt":0.34525326380487104,"score_spread":0.2085769228416128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3010016343","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000094496514,0.000011724856,0.99780893,0.0004888481,0.000048236536,0.00023375628,0.000005906441,0.000045231034,0.0012628387],"genre_scores_gemma":[0.99539423,0.0000023049806,0.003983526,0.00055574486,0.000017201186,0.000008946905,0.0000071456784,0.000004043429,0.000026867096],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99936426,0.00015559209,0.00012781048,0.00015482813,0.00012374987,0.00007375652],"domain_scores_gemma":[0.99924016,0.00041336386,0.00007721278,0.00012294276,0.00011623754,0.00003008239],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040477017,0.00005705395,0.000093103044,0.000020266982,0.000094778254,0.000046375095,0.0003274239,0.00001711699,0.000005855837],"category_scores_gemma":[0.0002066327,0.000038352922,0.000035044734,0.0004280876,0.00003857182,0.0002553969,0.00007358987,0.000019822446,0.0000018462254],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021228305,0.000010132413,0.000063230844,0.000029640285,0.0000141180835,9.7933565e-8,0.0021445209,0.00078537804,0.000502289,0.9956636,0.00070989475,0.00005587154],"study_design_scores_gemma":[0.00035733692,0.00019547448,0.00015547541,0.000034913093,0.000006510399,2.5638712e-7,0.0016178562,0.9604846,0.010639839,0.026088847,0.00033623466,0.00008261915],"about_ca_topic_score_codex":0.000001892306,"about_ca_topic_score_gemma":0.0000015827824,"teacher_disagreement_score":0.9952997,"about_ca_system_score_codex":0.000026895457,"about_ca_system_score_gemma":0.000037824102,"threshold_uncertainty_score":0.15639868},"labels":[],"label_agreement":null},{"id":"W3010039054","doi":"10.21307/connections-2019.009","title":"Hairball Buster: A Graph Triage Method for Viewing and Comparing Graphs","year":2020,"lang":"en","type":"article","venue":"Connections","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Adjacency list; Computer science; Graph Layout; Centrality; Graph; Visualization; Graph drawing; Theoretical computer science; Node (physics); Data visualization; Representation (politics); Adjacency matrix; Data mining; Algorithm; Combinatorics; Mathematics","score_opus":0.10229824680252501,"score_gpt":0.34784641454521015,"score_spread":0.24554816774268512,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3010039054","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00072707905,0.00010232074,0.9953834,0.0028816473,0.00015697972,0.00014320428,0.000008268652,0.00018016627,0.00041696095],"genre_scores_gemma":[0.7113536,0.00008300783,0.2821165,0.0060083615,0.00013008724,0.000053356518,0.00003535226,0.000019537061,0.00020020675],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99934554,0.000044018536,0.00016586452,0.00025693592,0.00006468359,0.0001229312],"domain_scores_gemma":[0.9994736,0.00014065515,0.000052335436,0.00016433031,0.000055356668,0.000113748014],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018029532,0.000075706324,0.00014439307,0.000085961416,0.00022865502,0.00020390944,0.00022358393,0.000024305298,0.000005980295],"category_scores_gemma":[0.0001683952,0.000075833654,0.00006316728,0.0005175211,0.000017367976,0.00027479586,0.00010870032,0.00005494837,0.0000049868254],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000822171,0.000054788223,0.0015154575,0.00008610688,0.000080754464,0.000002543253,0.0029137188,0.0006541929,0.0006184742,0.9687852,0.012679768,0.012600749],"study_design_scores_gemma":[0.00057565107,0.00005493626,0.00016525893,0.00001287624,0.000025620928,0.0000064594306,0.00012020553,0.92799026,0.00016448312,0.004973987,0.06578492,0.00012533677],"about_ca_topic_score_codex":0.000010027996,"about_ca_topic_score_gemma":0.000012320315,"teacher_disagreement_score":0.9638112,"about_ca_system_score_codex":0.0000054298766,"about_ca_system_score_gemma":0.000016604941,"threshold_uncertainty_score":0.30924067},"labels":[],"label_agreement":null},{"id":"W3010621335","doi":"10.3390/mti4010007","title":"Data-Driven Activities Involving Electronic Health Records: An Activity and Task Analysis Framework for Interactive Visualization Tools","year":2020,"lang":"en","type":"article","venue":"Multimodal Technologies and Interaction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Visualization; Context (archaeology); Task (project management); Data science; Data visualization; Digital library; Data mining; Engineering","score_opus":0.07283877948924461,"score_gpt":0.3811776126390576,"score_spread":0.308338833149813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3010621335","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.078622915,0.00011253988,0.9169973,0.003146216,0.000095425174,0.00027753128,0.00014249676,0.0005987462,0.0000068081404],"genre_scores_gemma":[0.9635324,0.0011570955,0.03443433,0.00046869466,0.000040822313,0.00002563579,0.00032326666,0.000012391157,0.0000053906756],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99852365,0.00008960973,0.0002550515,0.00072424044,0.00013154716,0.000275872],"domain_scores_gemma":[0.99874175,0.00028446558,0.00032068996,0.0005035842,0.00007350815,0.00007602225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002026071,0.00018657003,0.0003249903,0.0002753713,0.0002548747,0.0006064221,0.00054806925,0.00013397474,0.000004240627],"category_scores_gemma":[0.00074016576,0.00017918574,0.000046012028,0.00071385416,0.00006375782,0.004463084,0.0006129263,0.00030035523,9.0095864e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015296668,0.0002077747,0.0015939506,0.000117542775,0.00046980043,0.0000010860633,0.0026247925,0.0005534155,0.002466339,0.06884453,0.00041717457,0.9225506],"study_design_scores_gemma":[0.00018491033,0.0005170704,0.0007571409,0.00003461151,0.000052721956,0.0000020389878,0.0037037365,0.9885977,0.0011749305,0.0016148802,0.0031613866,0.00019889859],"about_ca_topic_score_codex":0.00014293942,"about_ca_topic_score_gemma":0.00028327404,"teacher_disagreement_score":0.98804426,"about_ca_system_score_codex":0.000107875894,"about_ca_system_score_gemma":0.000052301937,"threshold_uncertainty_score":0.7306982},"labels":[],"label_agreement":null},{"id":"W3011668859","doi":"10.1080/19466315.2020.1736142","title":"Clinical Trial Drug Safety Assessment With Interactive Visual Analytics","year":2020,"lang":"en","type":"article","venue":"Statistics in Biopharmaceutical Research","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Eli Lilly (Canada)","funders":"","keywords":"Visual analytics; Leverage (statistics); Analytics; Computer science; Patient safety; Drug reaction; Clinical trial; Data science; Medicine; Visualization; Data mining; Artificial intelligence; Health care; Drug","score_opus":0.2941365035090849,"score_gpt":0.6015167684857263,"score_spread":0.30738026497664145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3011668859","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020277125,0.000018049253,0.98946506,0.0048201317,0.00025916393,0.0005961239,0.00017239076,0.00006864165,0.0025727325],"genre_scores_gemma":[0.8377612,0.0004552169,0.15849696,0.0024076882,0.00040209916,0.000025689691,0.00012521559,0.00003360233,0.00029230645],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9947157,0.0013710185,0.00085786596,0.00077796145,0.001607489,0.0006699851],"domain_scores_gemma":[0.9948776,0.0033585685,0.000105436055,0.00037559742,0.0005630747,0.00071976276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037689055,0.00019288299,0.00038892045,0.00024254047,0.00016217867,0.0004085783,0.0011668912,0.00008420849,0.00021297195],"category_scores_gemma":[0.0023046206,0.00016019878,0.000053596163,0.0018856252,0.0004921825,0.00030880296,0.0009100354,0.0016643142,0.00016554902],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.016606696,0.0024433204,0.0070706103,0.00014788397,0.00020710663,0.0010793216,0.000892853,0.00025314884,0.0000760648,0.8608636,0.022563007,0.08779637],"study_design_scores_gemma":[0.01730996,0.0012122792,0.0013814582,0.000034401768,0.000016281614,0.0000021339947,0.00021093426,0.95297015,0.000097458884,0.0018827906,0.024629518,0.00025266554],"about_ca_topic_score_codex":0.00001534333,"about_ca_topic_score_gemma":0.000019593743,"teacher_disagreement_score":0.95271695,"about_ca_system_score_codex":0.00018545425,"about_ca_system_score_gemma":0.00080122624,"threshold_uncertainty_score":0.723071},"labels":[],"label_agreement":null},{"id":"W3012021395","doi":"10.1075/idj.25.1.04kos","title":"Belief at first sight","year":2020,"lang":"en","type":"article","venue":"Information Design Journal","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of Calgary","funders":"Alberta Innovates; European Commission; University of Calgary","keywords":"Objectivity (philosophy); Computer science; Representation (politics); Visualization; Credibility; Epistemology; Information visualization; Context (archaeology); Interpretation (philosophy); Data science; Human–computer interaction; Sociology; Artificial intelligence","score_opus":0.041552588459466924,"score_gpt":0.2487625530847851,"score_spread":0.20720996462531815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3012021395","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00004831778,0.000017332171,0.9904936,0.0071298634,0.00014656519,0.000047190813,0.0000024736053,0.000075307435,0.002039371],"genre_scores_gemma":[0.50218046,0.0006256661,0.39701262,0.097633414,0.0011839452,0.000011121571,0.00010855291,0.0000310227,0.0012131955],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99912834,0.00003590163,0.0003385796,0.000055044842,0.00031183753,0.00013032042],"domain_scores_gemma":[0.9992979,0.00003625388,0.00019995963,0.000118855874,0.00013519185,0.00021182421],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002415209,0.0000712148,0.00007416218,0.00008110714,0.00028125785,0.00060350104,0.0005421123,0.000029154404,0.00024985656],"category_scores_gemma":[0.00012615121,0.000060549653,0.000039430513,0.00031284452,0.0000122893625,0.003830703,0.000117309915,0.00010495491,0.0013352534],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002823531,0.00003392783,0.00034088845,0.00003663855,0.00004536148,0.0000277355,0.013196278,0.028571617,0.00012807087,0.039536178,0.8785859,0.03946922],"study_design_scores_gemma":[0.0003012985,0.00006468255,0.00007789351,0.000008010112,0.0000028492193,0.00009047887,0.000031006344,0.5069254,0.0006355541,0.00025098372,0.4915202,0.00009166923],"about_ca_topic_score_codex":2.41219e-7,"about_ca_topic_score_gemma":1.4553434e-7,"teacher_disagreement_score":0.59348094,"about_ca_system_score_codex":0.000043466123,"about_ca_system_score_gemma":0.000068255904,"threshold_uncertainty_score":0.99944234},"labels":[],"label_agreement":null},{"id":"W3012808763","doi":"10.21105/joss.01882","title":"splot - visual analytics for spatial statistics","year":2020,"lang":"en","type":"article","venue":"The Journal of Open Source Software","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Economic and Social Research Council","keywords":"Visual analytics; Analytics; Computer science; Interactive visual analysis; Cultural analytics; Summary statistics; Data science; Statistics; Visualization; Artificial intelligence; Semantic analytics; Mathematics; World Wide Web; The Internet","score_opus":0.0549351589260266,"score_gpt":0.3474003838398196,"score_spread":0.292465224913793,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3012808763","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004936041,0.000038414993,0.99589914,0.003156758,0.00013228515,0.00016333154,0.00006094858,0.000028046483,0.000027470982],"genre_scores_gemma":[0.32504493,0.0001409133,0.6528667,0.018994221,0.0013587908,0.0000035666342,0.00006208989,0.000094666626,0.001434106],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987911,0.000109127366,0.00041468194,0.00011974291,0.00038596598,0.00017937428],"domain_scores_gemma":[0.9982769,0.00038319733,0.00050505676,0.00023523028,0.00040886627,0.00019074169],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071815774,0.00011738892,0.00025953716,0.00004763172,0.00018821673,0.00054749585,0.0027235583,0.000031800508,0.000047653626],"category_scores_gemma":[0.0008406016,0.00007990174,0.00007363849,0.00031544236,0.00005056669,0.00052503654,0.0006575262,0.00016612436,0.000022083737],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00064058055,0.0004865484,0.00450274,0.00020432487,0.00065464387,0.00007803178,0.01351095,0.028538289,0.00027339763,0.028682934,0.67309606,0.24933147],"study_design_scores_gemma":[0.0021249927,0.0014484341,0.00053754303,0.00006739767,0.00024634434,0.00008461232,0.0007029461,0.69541466,0.00059411826,0.0031904539,0.2952032,0.00038528745],"about_ca_topic_score_codex":0.00001324674,"about_ca_topic_score_gemma":0.0000056085923,"teacher_disagreement_score":0.6668764,"about_ca_system_score_codex":0.000022074533,"about_ca_system_score_gemma":0.00020343362,"threshold_uncertainty_score":0.5279515},"labels":[],"label_agreement":null},{"id":"W3013414970","doi":"10.1002/pst.2012","title":"A critical review of graphics for subgroup analyses in clinical trials","year":2020,"lang":"en","type":"review","venue":"Pharmaceutical Statistics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Medical Research Council; Horizon 2020 Framework Programme; Medical Research Council Canada; European Commission; Marie Curie; National Institute for Health and Care Research","keywords":"Subgroup analysis; Computer science; Population; Plot (graphics); Identification (biology); Clinical trial; Visualization; Econometrics; Statistics; Data mining; Medicine; Mathematics; Pathology","score_opus":0.7492670943859359,"score_gpt":0.6880764956332216,"score_spread":0.061190598752714265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013414970","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[4.3158727e-10,0.5135837,0.4835107,0.00023352512,0.00022770396,0.0005912197,0.001804848,0.000023764405,0.000024536506],"genre_scores_gemma":[2.9956394e-7,0.9256588,0.07136103,0.0021388817,0.00017783798,0.00007160734,0.000552147,0.00003103326,0.000008332101],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99021083,0.003136919,0.0049136826,0.0007481274,0.00057659746,0.00041383598],"domain_scores_gemma":[0.97537965,0.022202892,0.0009630944,0.0005654152,0.00040815468,0.0004808181],"candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0071037165,0.00042823498,0.0051021725,0.0002268911,0.000042018255,0.00011400147,0.0013859103,0.00024736582,0.00009396841],"category_scores_gemma":[0.058151968,0.00033960954,0.00108374,0.0015143204,0.00025886277,0.00015021705,0.00036978262,0.00068647583,0.000032354976],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000035770377,0.00015622907,7.96024e-7,0.103437595,0.00011212765,0.000025480733,0.000003279105,6.3772056e-8,2.852286e-8,0.30667555,0.011489925,0.5780954],"study_design_scores_gemma":[0.00033911146,0.000092380586,4.7006824e-7,0.024679396,0.0022161875,0.000007002977,7.603175e-7,0.034158994,5.71772e-7,0.0030858647,0.9351,0.0003192241],"about_ca_topic_score_codex":0.000002438209,"about_ca_topic_score_gemma":0.0000012769984,"teacher_disagreement_score":0.9236101,"about_ca_system_score_codex":0.00004635685,"about_ca_system_score_gemma":0.0006357933,"threshold_uncertainty_score":0.9999056},"labels":[],"label_agreement":null},{"id":"W3015404063","doi":"10.1177/0049124120914943","title":"Clustered Iconography: A Resurrected Method for Representing Multidimensional Data","year":2020,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Iconography; Computer science; Presentation (obstetrics); Data science; Data mining; Information retrieval; History; Archaeology","score_opus":0.6367181529069946,"score_gpt":0.6249219023411513,"score_spread":0.011796250565843325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3015404063","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00023137352,0.00020126255,0.98632205,0.011848016,0.00012911388,0.00049066066,0.00008477137,0.00024323497,0.00044952147],"genre_scores_gemma":[0.0022750753,0.00004265511,0.99525154,0.0017964379,0.00025846553,0.000043749515,0.00022774166,0.000013711651,0.00009061486],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.98989314,0.0069725006,0.0004831241,0.0013642574,0.0005862136,0.0007007418],"domain_scores_gemma":[0.9876876,0.009837075,0.00012162229,0.0013655981,0.00061563135,0.00037250615],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.018057846,0.00016495664,0.00038640457,0.00015315197,0.00052510476,0.00021764888,0.0030075568,0.00021204921,0.000060538518],"category_scores_gemma":[0.020270584,0.00012855881,0.00014762889,0.001437656,0.00027843053,0.00038629002,0.0043074153,0.0006933763,0.000029478266],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024631494,0.00038904708,0.0012358732,0.00017156408,0.00029742677,0.000036026802,0.0032213018,0.0001298546,0.040636647,0.35364455,0.07466406,0.5253273],"study_design_scores_gemma":[0.0005248138,0.00017493904,0.00035275795,0.00001108688,0.000008307138,0.0000022375707,0.00034024692,0.90927166,0.0010210808,0.02217655,0.06593434,0.00018197796],"about_ca_topic_score_codex":0.000023030243,"about_ca_topic_score_gemma":8.182879e-7,"teacher_disagreement_score":0.9091418,"about_ca_system_score_codex":0.000024320052,"about_ca_system_score_gemma":0.00014550849,"threshold_uncertainty_score":0.9879821},"labels":[],"label_agreement":null},{"id":"W3016163547","doi":"10.1145/3313831.3376348","title":"Dear Pictograph: Investigating the Role of Personalization and Immersion for Consuming and Enjoying Visualizations","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Personalization; Visualization; Human–computer interaction; Computer science; Immersion (mathematics); Craft; Data visualization; Multimedia; World Wide Web; Visual arts; Artificial intelligence; Art","score_opus":0.04835025408702979,"score_gpt":0.3180772006866632,"score_spread":0.26972694659963337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3016163547","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0052755093,0.0006565693,0.9923769,0.00093763863,0.00006019749,0.0003272973,0.00003033549,0.00006289122,0.00027261887],"genre_scores_gemma":[0.92783177,0.00039613957,0.07051439,0.000930828,0.000044709563,0.000022460945,0.0002051395,0.000018875617,0.000035708556],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99899995,0.00006739483,0.00028754454,0.00036194833,0.00017104358,0.000112085996],"domain_scores_gemma":[0.99909186,0.00020243158,0.00024896665,0.00021987267,0.00015642661,0.00008041345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025661782,0.00013825174,0.00018264192,0.000108414766,0.00024185794,0.00029168898,0.00031700957,0.00008122417,0.0000046235227],"category_scores_gemma":[0.0002134705,0.0001115312,0.00004648703,0.00028273845,0.000123773,0.0001803475,0.00084322784,0.00009984546,3.2099413e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021222324,0.000023947376,0.019668406,0.0006076803,0.000084727006,2.1723676e-7,0.0077688806,0.00017840462,0.0040855026,0.95861113,0.00051606406,0.0084529035],"study_design_scores_gemma":[0.00014866296,0.000020812737,0.0003976677,0.00014677989,0.000046742094,0.0000018115674,0.0016170692,0.9796602,0.0015941316,0.01457616,0.0016392706,0.00015066974],"about_ca_topic_score_codex":0.000044114342,"about_ca_topic_score_gemma":0.0000058893097,"teacher_disagreement_score":0.9794818,"about_ca_system_score_codex":0.0000071605427,"about_ca_system_score_gemma":0.00007796814,"threshold_uncertainty_score":0.454811},"labels":[],"label_agreement":null},{"id":"W3023921534","doi":"","title":"Toward User-adaptive Visualizations.","year":2020,"lang":"en","type":"article","venue":"International Conference on Pattern Recognition Applications and Methods","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Human–computer interaction","score_opus":0.19853679229376098,"score_gpt":0.4307730672553638,"score_spread":0.23223627496160282,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3023921534","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006249671,0.00002008858,0.9805599,0.009246728,0.000106539694,0.00024730052,0.000114848655,0.00016854689,0.009473593],"genre_scores_gemma":[0.40888754,0.0008256653,0.56718796,0.021037541,0.00035816865,0.0004911425,0.0007474153,0.000034124365,0.00043044222],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987118,0.00014495643,0.000299368,0.0004780168,0.00023598238,0.00012984042],"domain_scores_gemma":[0.9989647,0.00010368207,0.00015439093,0.00020510258,0.00038822836,0.0001838412],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021328192,0.00015046677,0.00014411996,0.00013214661,0.000109506684,0.00032838064,0.0005501333,0.000060124166,0.000402863],"category_scores_gemma":[0.00007229247,0.00015093424,0.000047306443,0.00032824255,0.000051723815,0.0003882177,0.00017015163,0.00012739419,0.00024997638],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000045735237,0.00006377568,0.00005278092,0.000008257464,0.000026412981,0.0000011007367,0.00024376453,0.000004832133,0.00049759826,0.37031743,0.0005106693,0.6282688],"study_design_scores_gemma":[0.0010068687,0.00025486576,0.00056585716,0.00008507638,0.00003698479,0.000020960098,0.0006194221,0.7447311,0.006139261,0.04620684,0.19963546,0.0006972689],"about_ca_topic_score_codex":0.0000069424186,"about_ca_topic_score_gemma":0.0000013278521,"teacher_disagreement_score":0.7447263,"about_ca_system_score_codex":0.000022415736,"about_ca_system_score_gemma":0.00004951901,"threshold_uncertainty_score":0.615492},"labels":[],"label_agreement":null},{"id":"W3028946697","doi":"10.3390/informatics7020017","title":"Visual Analytics for Dimension Reduction and Cluster Analysis of High Dimensional Electronic Health Records","year":2020,"lang":"en","type":"article","venue":"Informatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Dimensionality reduction; Computer science; Visual analytics; Cluster analysis; Dimension (graph theory); Data science; Analytics; Data mining; Reduction (mathematics); Cluster (spacecraft); Data analysis; Visualization; Machine learning","score_opus":0.019140036288045705,"score_gpt":0.3036517722546214,"score_spread":0.2845117359665757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3028946697","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.053615484,0.000033388686,0.94338113,0.0026171706,0.00008362906,0.00016462232,0.000034394176,0.000048237976,0.000021971568],"genre_scores_gemma":[0.94855803,0.00010211796,0.046786133,0.004149923,0.00004054603,0.0000032335809,0.0003123597,0.0000075390767,0.000040138624],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987554,0.0000291902,0.0006170387,0.00012952296,0.00025792557,0.00021094177],"domain_scores_gemma":[0.99908215,0.00006150416,0.00037260406,0.00019185116,0.00016148703,0.0001304331],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033458308,0.000105725805,0.00031345134,0.0002490939,0.00008765536,0.000067348374,0.00018786297,0.000044029228,0.000005924053],"category_scores_gemma":[0.00007049131,0.00009625704,0.00007957584,0.0011607242,0.00003252249,0.00049874914,0.00014574187,0.0000736235,0.0000030128851],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029631553,0.0006117793,0.0025045562,0.0015499403,0.004045448,0.0000012276513,0.027187355,0.23739639,0.00037801775,0.4918387,0.06692119,0.16726908],"study_design_scores_gemma":[0.00034017186,0.00032410916,0.00025731337,0.000010277254,0.00013568191,0.0000019670154,0.00011472479,0.9961472,0.00016244083,0.00037236142,0.0020322397,0.000101516256],"about_ca_topic_score_codex":0.000015645224,"about_ca_topic_score_gemma":0.000007699892,"teacher_disagreement_score":0.89659494,"about_ca_system_score_codex":0.00004330125,"about_ca_system_score_gemma":0.00014036938,"threshold_uncertainty_score":0.3925248},"labels":[],"label_agreement":null},{"id":"W3030234902","doi":"10.1145/3334480.3383072","title":"An Unquantified Uncertainty Visualization Design Space During the Opioid Crisis","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Visualization; Computer science; Harm reduction; Space (punctuation); Harm; Uncertainty reduction theory; Risk analysis (engineering); Data science; Computer security; Data mining; Medicine; Psychology; Public health","score_opus":0.06151189530797489,"score_gpt":0.33987795299153434,"score_spread":0.27836605768355943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3030234902","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005284245,0.000036285393,0.99475807,0.0028301605,0.0004976574,0.0003841985,0.000020525089,0.0006312765,0.00031342453],"genre_scores_gemma":[0.93856376,0.0003076344,0.054877613,0.004393817,0.00038607605,0.00004520477,0.00044648186,0.00006123658,0.0009181543],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974939,0.00039559937,0.00040988956,0.0009055001,0.0005205128,0.00027455812],"domain_scores_gemma":[0.9976856,0.00008064085,0.00026198968,0.001577284,0.00021511348,0.00017938715],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00049610785,0.00030949977,0.00028596146,0.00013183022,0.00028915223,0.0014868069,0.0025730962,0.00017201026,0.00008731218],"category_scores_gemma":[0.000104766754,0.0002273665,0.000105669336,0.0006524961,0.000043760916,0.00041808616,0.0014900517,0.0003039141,0.00008816969],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021391916,0.00018819366,0.00015192847,0.00028636368,0.00012693433,0.00002378848,0.0041438225,0.19719459,0.001356677,0.7602487,0.035219774,0.0010377984],"study_design_scores_gemma":[0.00014462486,0.00003278213,0.00019603448,0.000030118785,0.00002512181,0.0000021894064,0.0002708461,0.9842124,0.0038617363,0.007528725,0.0033486118,0.00034680523],"about_ca_topic_score_codex":0.0001632935,"about_ca_topic_score_gemma":0.000021707523,"teacher_disagreement_score":0.93988043,"about_ca_system_score_codex":0.00007278722,"about_ca_system_score_gemma":0.00023886876,"threshold_uncertainty_score":0.99954975},"labels":[],"label_agreement":null},{"id":"W3030796420","doi":"10.1145/3334480.3383150","title":"Tree Illustrator: Interactive Construction of Tree Visualizations","year":2020,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Tree (set theory); Visualization; Set (abstract data type); Tree structure; Human–computer interaction; Theoretical computer science; Programming language; Artificial intelligence; Data structure; Mathematics","score_opus":0.03192976569319514,"score_gpt":0.30533488780266704,"score_spread":0.2734051221094719,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3030796420","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006190654,0.0000046358477,0.977124,0.0016000554,0.00009487967,0.000049473176,0.00000963544,0.0001172462,0.020381022],"genre_scores_gemma":[0.94697493,0.000015082703,0.05111991,0.0015589471,0.00005479985,0.0000018744721,0.000031816573,0.0000066202983,0.0002360096],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993472,0.000033022283,0.00021582948,0.00017895331,0.00014686538,0.00007813276],"domain_scores_gemma":[0.9994935,0.00003283861,0.00009963385,0.00016866828,0.00012157359,0.000083787876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000038248374,0.00006778755,0.00010782104,0.00006041562,0.0000351841,0.00006135611,0.0003164257,0.000026464959,0.00016827893],"category_scores_gemma":[0.00007651382,0.000061978666,0.00003953492,0.00057055964,0.00005066143,0.0005183122,0.00010263688,0.000041113817,0.000041162162],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000032634423,0.000049442795,0.0006363456,0.000011333644,0.000023623157,0.0000012468189,0.0007660406,0.000028556577,0.0011602342,0.97064644,0.007178864,0.01949458],"study_design_scores_gemma":[0.0005313422,0.00017690353,0.0005084052,0.000016658065,0.000018942414,0.0000074958007,0.0013786827,0.9494486,0.027104624,0.0017511118,0.018836657,0.00022060078],"about_ca_topic_score_codex":0.000004330953,"about_ca_topic_score_gemma":0.0000127981775,"teacher_disagreement_score":0.9688954,"about_ca_system_score_codex":0.000007802215,"about_ca_system_score_gemma":0.000051495812,"threshold_uncertainty_score":0.25274166},"labels":[],"label_agreement":null},{"id":"W3032037053","doi":"10.1145/3334480.3383101","title":"Interactive Parallel Coordinates for Parametric Design Space Exploration","year":2020,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Parametric statistics; Computer science; Usability; Visualization; Design space exploration; Parallel coordinates; Space (punctuation); Parametric design; Human–computer interaction; Data visualization; Interactive visualization; Space exploration; Computational science; Distributed computing; Data mining; Embedded system; Aerospace engineering; Engineering; Operating system","score_opus":0.11656396098085701,"score_gpt":0.33175348723114356,"score_spread":0.21518952625028653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3032037053","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000018989525,0.000011574229,0.98931265,0.009777676,0.00006173648,0.00020226443,0.0000024515898,0.00014596671,0.0004666675],"genre_scores_gemma":[0.42114395,0.000021029662,0.5745413,0.0035058649,0.000051620977,0.000033091925,0.000027444734,0.000008059019,0.0006676672],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994268,0.00003693628,0.00011817984,0.0002161327,0.00009673838,0.000105207975],"domain_scores_gemma":[0.9994151,0.00021255198,0.000058057518,0.0001320156,0.000103806655,0.00007849785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000099804405,0.00006975598,0.00008800766,0.00006566181,0.00005036668,0.00021211545,0.0003253387,0.000020760308,0.000019553288],"category_scores_gemma":[0.00034075434,0.00006020587,0.000031516334,0.0006242632,0.000009358727,0.0010428571,0.000077244586,0.00003238404,0.000089929614],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041781033,0.0001071658,0.0000762602,0.000024320969,0.00004073442,0.000003054235,0.001805869,0.01773866,0.00022419792,0.7921499,0.17484426,0.012943787],"study_design_scores_gemma":[0.00024221874,0.00014208985,0.000009336331,0.0000027852393,0.0000039598826,3.5060154e-7,0.00015792363,0.97828996,0.002781171,0.0044041425,0.013875273,0.00009075923],"about_ca_topic_score_codex":0.000002768215,"about_ca_topic_score_gemma":5.370668e-7,"teacher_disagreement_score":0.9605513,"about_ca_system_score_codex":0.000012060401,"about_ca_system_score_gemma":0.00002743622,"threshold_uncertainty_score":0.24551243},"labels":[],"label_agreement":null},{"id":"W3032952342","doi":"10.1139/cjfas-2019-0424","title":"Improving the communication and accessibility of stock assessment using interactive visualization tools","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Computer science; Data science; Variety (cybernetics); Visualization; Stock (firearms); Data visualization; Disparate system; Interactive visualization; World Wide Web; Data mining; Geography; Artificial intelligence","score_opus":0.08496774250320374,"score_gpt":0.34836145353752784,"score_spread":0.2633937110343241,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3032952342","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5030061,0.00027529,0.49204388,0.004351995,0.00007676507,0.00007739522,0.0000034609989,0.0000028647664,0.00016222821],"genre_scores_gemma":[0.98960143,0.000026955819,0.009893299,0.0004617535,0.000012072921,2.192438e-7,5.505598e-7,0.0000012828154,0.0000024491508],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99933,0.00009852499,0.00025275524,0.00009146079,0.00014941744,0.000077846635],"domain_scores_gemma":[0.99919367,0.00015025004,0.00034250994,0.00009547843,0.000084257634,0.00013381477],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063333113,0.000047080346,0.00010398396,0.000059368787,0.00028458683,0.0006478832,0.00046524953,0.000013418204,0.000009075581],"category_scores_gemma":[0.0004372046,0.00003155341,0.000015576037,0.00036474678,0.0003350568,0.0014247408,0.000066656976,0.000058346952,4.130774e-8],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017012828,0.00005780477,0.4236111,0.00019400184,0.00010245098,0.00001132844,0.057306692,0.0003788628,0.0027244089,0.08426235,0.0012467565,0.43008724],"study_design_scores_gemma":[0.00013082697,0.00017004691,0.021244088,0.00006359575,0.000015238876,0.00001277886,0.0043704254,0.97221124,0.00018776956,0.0011699647,0.00035347635,0.000070547416],"about_ca_topic_score_codex":0.0011922481,"about_ca_topic_score_gemma":0.0008452508,"teacher_disagreement_score":0.9718324,"about_ca_system_score_codex":0.000021345404,"about_ca_system_score_gemma":0.0005900185,"threshold_uncertainty_score":0.62475526},"labels":[],"label_agreement":null},{"id":"W3033258914","doi":"10.4000/communiquer.5337","title":"Visualisation de données et design émotionnel peuvent-ils se conjuguer?","year":2020,"lang":"fr","type":"article","venue":"Communiquer Revue de communication sociale et publique","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science","score_opus":0.22447238360587712,"score_gpt":0.3823092997521902,"score_spread":0.15783691614631307,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3033258914","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005497305,0.002066349,0.6385654,0.35479915,0.00017385051,0.00050848915,0.000070142385,0.00038628426,0.002880616],"genre_scores_gemma":[0.69851756,0.019309146,0.16353114,0.11321787,0.00039061063,0.00023355955,0.0015763276,0.00016060586,0.003063213],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.98337114,0.013847649,0.0010782891,0.00052909914,0.00039876357,0.0007750894],"domain_scores_gemma":[0.99326354,0.0013947022,0.0009008474,0.0025517296,0.0012739988,0.0006151683],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.007688595,0.00047225287,0.00059763674,0.0002124266,0.00088557357,0.0021302388,0.004357747,0.00058591855,0.00021059683],"category_scores_gemma":[0.002937894,0.0006243985,0.00027388247,0.0015071495,0.00049931335,0.0037442837,0.00220804,0.001649571,0.00011699642],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002082169,0.0005237898,0.00056947715,0.00025131667,0.00009980594,0.000008427321,0.060170677,0.0017205402,0.00033704386,0.89797133,0.03170848,0.0066182637],"study_design_scores_gemma":[0.0013040758,0.0002505553,0.0018292315,0.0009864568,0.000121331796,0.00007255833,0.0033110802,0.49254498,0.0010329501,0.0450676,0.45242807,0.0010511009],"about_ca_topic_score_codex":0.0011405607,"about_ca_topic_score_gemma":0.0010850624,"teacher_disagreement_score":0.8529038,"about_ca_system_score_codex":0.00070053065,"about_ca_system_score_gemma":0.0028637536,"threshold_uncertainty_score":0.99962074},"labels":[],"label_agreement":null},{"id":"W3033904340","doi":"10.20380/gi2020.36","title":"Exploring the Design of Patient-Generated Data Visualizations","year":2020,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Simon Fraser University; University of Victoria; University of Calgary","funders":"","keywords":"Computer science; Data visualization; Visualization; Human–computer interaction; Artificial intelligence","score_opus":0.14914763148161572,"score_gpt":0.29790807080227005,"score_spread":0.14876043932065433,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3033904340","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00093165727,0.0002443569,0.9875367,0.008666844,0.00027010648,0.00037285444,0.00017705902,0.00024044374,0.0015599561],"genre_scores_gemma":[0.5435806,0.0022037392,0.44727015,0.0007299368,0.000053521708,0.000113334056,0.0049674204,0.000082714265,0.0009986159],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9924507,0.005218419,0.0006718166,0.00086552877,0.0005556228,0.00023790519],"domain_scores_gemma":[0.9912741,0.0011215066,0.0006542131,0.00501891,0.0017852215,0.00014605004],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0031710372,0.00026430356,0.00031355486,0.00015537081,0.0003327212,0.0006767025,0.005860047,0.00009341341,0.00002993892],"category_scores_gemma":[0.002451209,0.000232761,0.00008944926,0.0010923435,0.00015981756,0.0005907779,0.007253441,0.00036459143,0.000025561929],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000074726345,0.00084009103,0.00023272634,0.00024183503,0.00026520586,0.000007750824,0.028014528,0.0077102724,0.0027816705,0.8677838,0.013211691,0.07890295],"study_design_scores_gemma":[0.00016037314,4.846367e-7,0.000113380345,0.00047731158,0.000040476236,0.0000021993014,0.0001131614,0.96174216,0.022737337,0.0023922264,0.011942401,0.00027849476],"about_ca_topic_score_codex":0.00023330873,"about_ca_topic_score_gemma":0.00008788469,"teacher_disagreement_score":0.9540319,"about_ca_system_score_codex":0.000037686907,"about_ca_system_score_gemma":0.00044712922,"threshold_uncertainty_score":0.99951875},"labels":[],"label_agreement":null},{"id":"W3036080139","doi":"","title":"Visualizing Unquantifiable Uncertainty in Drug Checking Test Results","year":2019,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Visualization; Space (punctuation); Test (biology); Harm; Harm reduction; Data science; Risk analysis (engineering); Data mining; Medicine","score_opus":0.024684410770236042,"score_gpt":0.27974663824026386,"score_spread":0.2550622274700278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3036080139","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014010673,0.000673403,0.8625584,0.012583469,0.000868618,0.0008305085,0.00033646816,0.00061998,0.10751847],"genre_scores_gemma":[0.9147632,0.0007025669,0.053932153,0.00041363147,0.00003827053,0.000031165593,0.0017425113,0.00006766713,0.028308827],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9933388,0.00307603,0.0010028834,0.0013817123,0.00065611245,0.00054445025],"domain_scores_gemma":[0.9913582,0.0024091348,0.0008107641,0.003729263,0.001508915,0.00018369657],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00927467,0.00041530936,0.00052146666,0.0004791187,0.0002346423,0.0014265592,0.0035260636,0.00026531878,0.00003877805],"category_scores_gemma":[0.0038340262,0.00045738544,0.00017849321,0.0011736148,0.00013152859,0.0004759098,0.0038899097,0.00079914206,0.00019488973],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023186418,0.002491938,0.009874011,0.00089868583,0.00011937813,0.00004702178,0.0353915,0.020967582,0.0020819367,0.87399817,0.0198933,0.03421329],"study_design_scores_gemma":[0.0009210336,3.929782e-7,0.0013016877,0.003436232,0.00001718417,0.000004825171,0.00016200557,0.93972254,0.010231261,0.0037827485,0.039708927,0.0007111761],"about_ca_topic_score_codex":0.0023244005,"about_ca_topic_score_gemma":0.0022804157,"teacher_disagreement_score":0.91875494,"about_ca_system_score_codex":0.00022970022,"about_ca_system_score_gemma":0.00057561597,"threshold_uncertainty_score":0.9997878},"labels":[],"label_agreement":null},{"id":"W3041241202","doi":"10.1007/978-3-030-50020-7_10","title":"A Visualization Tool for the CIRMMT Distinguished Lecture Series","year":2020,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Interdisciplinary Research in Music Media and Technology; McGill University","funders":"","keywords":"Computer science; Visualization; Metadata; Encyclopedia; Data visualization; Information retrieval; Series (stratigraphy); Task (project management); Data science; World Wide Web; Computer graphics (images); Multimedia; Human–computer interaction; Library science; Artificial intelligence","score_opus":0.02332694641875024,"score_gpt":0.2871689519317753,"score_spread":0.26384200551302506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3041241202","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000013632975,0.00026629632,0.99317193,0.0036731346,0.0014485348,0.0006204895,0.000033144657,0.00022100906,0.00056407985],"genre_scores_gemma":[0.12304485,0.00037279294,0.82910794,0.038160913,0.0054327725,0.00012330047,0.00042594917,0.0002658536,0.0030656578],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969497,0.000032201526,0.0005166556,0.0012369892,0.00081233867,0.00045216017],"domain_scores_gemma":[0.99736375,0.0006596608,0.0003299985,0.0011186579,0.0004127779,0.000115151204],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0006198057,0.0004600429,0.00042352703,0.00028772742,0.0005350556,0.0013502022,0.0032797847,0.00021628398,0.000020807827],"category_scores_gemma":[0.0007838529,0.00033984144,0.00015379323,0.00090286165,0.00047835254,0.000602318,0.0010425611,0.00038778753,0.00001981834],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016832755,0.000030776053,0.000044404464,0.00014516705,0.000039782975,0.000028196408,0.0014524512,0.026954321,0.000079834026,0.6015402,0.000917471,0.3687505],"study_design_scores_gemma":[0.00021085644,0.00014202914,0.000025954338,0.00013979593,0.00002096487,0.000023497236,2.7631356e-7,0.8498424,0.00045373262,0.105844975,0.04280404,0.00049145706],"about_ca_topic_score_codex":0.000005042822,"about_ca_topic_score_gemma":0.000041812375,"teacher_disagreement_score":0.8228881,"about_ca_system_score_codex":0.00013087253,"about_ca_system_score_gemma":0.00049825927,"threshold_uncertainty_score":0.99990535},"labels":[],"label_agreement":null},{"id":"W3042318688","doi":"10.1111/cgf.13968","title":"Ocupado: Visualizing Location‐Based Counts Over Time Across Buildings","year":2020,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Human–computer interaction; Task (project management); Set (abstract data type); Space (punctuation); Visualization; Resource (disambiguation); Stakeholder; Data science; Artificial intelligence; Systems engineering","score_opus":0.023524893852769273,"score_gpt":0.3046954082164624,"score_spread":0.2811705143636931,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3042318688","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004955211,0.000041261923,0.99654794,0.0019484623,0.00028210127,0.00007344489,0.000016346596,0.00030199467,0.0002929592],"genre_scores_gemma":[0.81798303,0.00003826176,0.07200929,0.10851853,0.0006609311,0.000010147933,0.0002625525,0.000082544124,0.00043470005],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882823,0.000028216915,0.00021170176,0.00035223257,0.00029566928,0.00028397143],"domain_scores_gemma":[0.99924123,0.000040979412,0.00009021089,0.00035141438,0.0001382994,0.00013787755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013539799,0.00013987366,0.00014407301,0.00007704173,0.00015692278,0.00036588396,0.0008160634,0.00006278234,0.00003661895],"category_scores_gemma":[0.000019454184,0.00014256898,0.00007478841,0.0010520832,0.000053780153,0.00036467332,0.00035114976,0.00010942513,0.000434376],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000051615352,0.000100299934,0.0033176027,0.000072601026,0.000048011334,0.000016290234,0.0005543079,0.0003847901,0.000098474775,0.673526,0.3087439,0.013132583],"study_design_scores_gemma":[0.00020937613,0.000037608756,0.00024603787,0.000020183359,0.0000034826026,0.0000011175258,0.0000026836306,0.8224728,0.00012473985,0.00058231596,0.17613919,0.0001604537],"about_ca_topic_score_codex":0.0000027174822,"about_ca_topic_score_gemma":6.7084295e-7,"teacher_disagreement_score":0.9245386,"about_ca_system_score_codex":0.000014532419,"about_ca_system_score_gemma":0.00005554682,"threshold_uncertainty_score":0.5813794},"labels":[],"label_agreement":null},{"id":"W3043051650","doi":"10.1002/jrsm.1435","title":"Creating effective interrupted time series graphs: Review and recommendations","year":2020,"lang":"en","type":"review","venue":"Research Synthesis Methods","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ottawa Hospital; University of Ottawa","funders":"National Health and Medical Research Council; Canadian Institutes of Health Research; Monash University; Medical Research Council; Australian Government","keywords":"Computer science; Standardization; Visualization; Data mining; Data visualization; Graph; Software; Data extraction; Graph drawing; Information retrieval; Time series; Data science; Machine learning; Theoretical computer science; MEDLINE","score_opus":0.21463601494254203,"score_gpt":0.5644807030011398,"score_spread":0.3498446880585978,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3043051650","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[1.0386599e-9,0.84763044,0.14726824,0.0015509251,0.0000476415,0.001016664,0.000064016946,0.00013523508,0.0022868186],"genre_scores_gemma":[6.824384e-9,0.7557792,0.24307118,0.00011116613,0.00003686975,0.0003948928,0.000045226698,0.00003245829,0.0005289702],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.98167133,0.015790965,0.0007344178,0.0008985909,0.00045711748,0.00044755565],"domain_scores_gemma":[0.98407024,0.014040993,0.0003133519,0.0009383739,0.00032465887,0.00031235305],"candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0112712,0.00038209558,0.0021045625,0.0006317071,0.0003969291,0.00055457826,0.0015576129,0.00017085373,0.00024415032],"category_scores_gemma":[0.021603579,0.00030281127,0.00031745556,0.0030745235,0.0001927933,0.00057424494,0.001554927,0.0007796806,0.00021501006],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.7186802e-7,0.000019425575,7.758309e-8,0.018561421,0.00017842659,0.000006048081,0.000056765322,9.998492e-9,0.0000010313793,0.0070668426,0.006205333,0.96790415],"study_design_scores_gemma":[0.000020673493,0.000050333285,2.3534113e-7,0.035293896,0.00036908544,0.000032297878,0.00001422589,0.00073687994,0.00001637691,0.0006256921,0.96257174,0.00026854614],"about_ca_topic_score_codex":0.000007849588,"about_ca_topic_score_gemma":7.220058e-7,"teacher_disagreement_score":0.9676356,"about_ca_system_score_codex":0.00012696537,"about_ca_system_score_gemma":0.00029238584,"threshold_uncertainty_score":0.9999424},"labels":[],"label_agreement":null},{"id":"W3043524377","doi":"10.52842/conf.acadia.2017.414","title":"A Design Gallery System: Prototype and Evaluation","year":2017,"lang":"en","type":"article","venue":"ACADIA quarterly","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Parametric statistics; Human–computer interaction; Parametric design; Work (physics); Multimedia; Software engineering; Engineering","score_opus":0.0575638127015725,"score_gpt":0.33078271456287583,"score_spread":0.2732189018613033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3043524377","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00581976,0.00008871086,0.98967445,0.00066357746,0.00024636928,0.00073962146,0.000002106785,0.00012722603,0.002638158],"genre_scores_gemma":[0.992532,0.000004820937,0.0071420968,0.00009664346,0.000055276465,0.00005646993,0.0000034123443,0.000005303733,0.00010393713],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99915975,0.00009815007,0.00013525573,0.00022719914,0.0002521559,0.0001274868],"domain_scores_gemma":[0.99904054,0.000025921672,0.00012729203,0.00062604545,0.000105036,0.00007517596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00075694086,0.00007392219,0.000088173714,0.000056306693,0.00028409204,0.00078975514,0.0005856502,0.000046842633,0.000008224765],"category_scores_gemma":[0.0000421071,0.000066608336,0.000014827203,0.0000515614,0.000032868134,0.0009440757,0.00003804903,0.000049601982,0.000097104836],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025895632,0.00008970769,0.0024763222,0.00016689373,0.00007866294,0.000029126426,0.0064208093,0.00004712517,0.0009095107,0.20670196,0.008440812,0.77461314],"study_design_scores_gemma":[0.0005288807,0.00034070585,0.013374625,0.00007062296,0.000021246158,0.000015939706,0.0001112264,0.9810099,0.00009853673,0.0025221051,0.0017265531,0.00017965565],"about_ca_topic_score_codex":0.000018829216,"about_ca_topic_score_gemma":0.0000045118036,"teacher_disagreement_score":0.9867123,"about_ca_system_score_codex":0.000021357082,"about_ca_system_score_gemma":0.000069516595,"threshold_uncertainty_score":0.7615627},"labels":[],"label_agreement":null},{"id":"W3045012226","doi":"10.1186/s41044-020-00047-z","title":"From ancient times to modern: realizing the power of data visualization in healthcare and medicine","year":2020,"lang":"en","type":"article","venue":"Big Data Analytics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Computer science; Visualization; Image (mathematics); Process (computing); Value (mathematics); Perception; Power (physics); Data science; Data visualization; Estimation; Data type; Artificial intelligence; Information retrieval; Psychology; Machine learning; Engineering","score_opus":0.24439315596303332,"score_gpt":0.39956894304922946,"score_spread":0.15517578708619614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3045012226","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008366976,0.00055464637,0.9612,0.035677604,0.00009052094,0.00014157647,0.0013567244,0.000034350694,0.00010787286],"genre_scores_gemma":[0.9741164,0.0003585666,0.0070607914,0.013616893,0.00020405086,8.781683e-7,0.004606409,0.000014129444,0.000021925085],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99832296,0.00009016977,0.0004187658,0.00059829344,0.00040994067,0.00015988815],"domain_scores_gemma":[0.99731976,0.000108376735,0.00014233298,0.0021757998,0.00009184624,0.00016186731],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005578001,0.00011146177,0.00022993657,0.00010326693,0.00005735447,0.00008780342,0.0026844523,0.000037250185,0.000008854772],"category_scores_gemma":[0.0005489126,0.00008180785,0.000008277175,0.001103597,0.00006136398,0.0005568795,0.0028372123,0.00007413158,0.0000056041863],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007081095,0.00032418728,0.016486423,0.0003197258,0.00022273057,0.00006271498,0.026406502,0.001557243,0.0016408082,0.3146627,0.50721616,0.13102998],"study_design_scores_gemma":[0.00021090594,0.000052417265,0.0012128844,0.000065537744,0.000021017899,7.620411e-7,0.00038007443,0.9720606,0.000031438012,0.0008002092,0.02506471,0.000099449084],"about_ca_topic_score_codex":0.000814063,"about_ca_topic_score_gemma":0.00034299237,"teacher_disagreement_score":0.97327965,"about_ca_system_score_codex":0.0000138027735,"about_ca_system_score_gemma":0.00009487124,"threshold_uncertainty_score":0.4988425},"labels":[],"label_agreement":null},{"id":"W3048699628","doi":"10.11575/prism/38068","title":"Health Visualizations at Home: Who Sees What Where","year":2018,"lang":"en","type":"article","venue":"Open MIND","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; Alberta Innovates - Technology Futures","keywords":"Computer science","score_opus":0.052746069441923484,"score_gpt":0.3894156355820954,"score_spread":0.3366695661401719,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3048699628","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013544013,0.0009629281,0.93760365,0.02083559,0.001404015,0.00075741345,0.00007947429,0.00004153603,0.024771372],"genre_scores_gemma":[0.33629712,0.005933564,0.29318294,0.027210005,0.0015163221,0.000051665622,0.0010881948,0.0001568441,0.33456334],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99894863,0.000072165996,0.00021624666,0.00034731234,0.00019817069,0.00021744422],"domain_scores_gemma":[0.9990518,0.000022492444,0.000113287606,0.0005483014,0.00011503477,0.00014905981],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00027950772,0.0000955963,0.00015599489,0.000067406625,0.00036249188,0.0018612519,0.0010225407,0.00003327221,0.0017875625],"category_scores_gemma":[0.000017944109,0.000088930945,0.000023758254,0.00053305493,0.00006621253,0.0021422934,0.0009978586,0.00003500739,0.002239938],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008521279,0.00029240845,0.0023309737,0.000027271764,0.00005140564,0.000012080245,0.011467791,0.00003277772,0.00010456931,0.04704936,0.34660968,0.5920132],"study_design_scores_gemma":[0.00027131502,0.000116883566,0.00045013617,0.000112184454,0.0000035327573,0.000010583268,0.0002542085,0.04190075,0.0006745318,0.00021921728,0.9558036,0.00018308243],"about_ca_topic_score_codex":0.00003210527,"about_ca_topic_score_gemma":0.00075921963,"teacher_disagreement_score":0.64442074,"about_ca_system_score_codex":0.00005544297,"about_ca_system_score_gemma":0.00016454485,"threshold_uncertainty_score":0.9991749},"labels":[],"label_agreement":null},{"id":"W3055273286","doi":"10.1109/tvcg.2020.3030387","title":"VizCommender: Computing Text-Based Similarity in Visualization Repositories for Content-Based Recommendations","year":2020,"lang":"en","type":"preprint","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Visualization; Relevance (law); Information retrieval; Similarity (geometry); Visual analytics; Latent Dirichlet allocation; Similarity measure; Analytics; Tag cloud; Topic model; Data science; Measure (data warehouse); Recommender system; Information visualization; World Wide Web; Data mining; Artificial intelligence; Image (mathematics)","score_opus":0.07907896541989255,"score_gpt":0.3382526641997582,"score_spread":0.2591736987798656,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3055273286","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0003936408,0.000041409305,0.99308264,0.0021615745,0.0021976866,0.0011534315,0.0002847581,0.0006715679,0.000013297237],"genre_scores_gemma":[0.9364959,0.00021530823,0.044850096,0.015702067,0.00027926275,0.00020979143,0.0020814189,0.0001351215,0.000031042782],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99583805,0.00049865706,0.0012779982,0.0013858617,0.0005541849,0.0004452668],"domain_scores_gemma":[0.9970871,0.00058337743,0.00063828117,0.000787308,0.0006304353,0.00027346867],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0005964802,0.0006514424,0.00072077947,0.0011378754,0.0006601138,0.0011197898,0.00083091896,0.0005042232,0.000008504866],"category_scores_gemma":[0.000039723916,0.0007523995,0.00031086535,0.0015765831,0.00012951028,0.00043961307,0.000052630374,0.0006309933,0.0000026913954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014203203,0.0022010044,0.0006716482,0.0013160404,0.00023929052,0.000012478044,0.0018455228,0.06308799,0.000043449985,0.9162491,0.0030250014,0.011166457],"study_design_scores_gemma":[0.0018696644,0.00031806715,0.00014921649,0.00047432104,0.00008377913,0.0000023107887,0.0000706971,0.9904952,0.002092771,0.0013321788,0.0023788302,0.00073297205],"about_ca_topic_score_codex":0.000057354548,"about_ca_topic_score_gemma":0.00010718031,"teacher_disagreement_score":0.94823253,"about_ca_system_score_codex":0.00014853291,"about_ca_system_score_gemma":0.00038208123,"threshold_uncertainty_score":0.99991715},"labels":[],"label_agreement":null},{"id":"W305579182","doi":"10.1007/978-3-319-07467-2_33","title":"A Data Driven Approach for Smart Lighting","year":2014,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Computer science; Smart lighting; Energy consumption; Energy (signal processing); Control (management); Architectural engineering; Artificial intelligence; Engineering","score_opus":0.054030452318602554,"score_gpt":0.30119107271691153,"score_spread":0.247160620398309,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W305579182","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[7.3068674e-7,0.00007946673,0.9946568,0.00042288075,0.0007511791,0.00036599228,0.00006325872,0.00015341492,0.0035062933],"genre_scores_gemma":[0.004310078,0.000017821521,0.9914824,0.002322718,0.0006346961,0.00000730484,0.00032692446,0.00003578132,0.0008623218],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99631864,0.000026763913,0.0004923916,0.0018980296,0.0007243808,0.0005397694],"domain_scores_gemma":[0.9958901,0.0003890281,0.00031193448,0.0030204663,0.00022766335,0.00016084594],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0012836058,0.0003970148,0.0004685343,0.0005441521,0.00027958074,0.0009248033,0.00827171,0.00022139783,0.0000062393133],"category_scores_gemma":[0.00023757362,0.0003571078,0.0000862536,0.00046790866,0.0003355153,0.0006375825,0.003646878,0.00036979953,0.000021417905],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003854337,0.000055424778,0.000039579747,0.0001791367,0.000029070121,0.000012469357,0.00040577934,0.04106333,0.000031393367,0.25383273,0.0014803291,0.7028669],"study_design_scores_gemma":[0.00018497997,0.00006058272,0.0000040897235,0.00012343854,0.000009894039,0.000015712785,7.773521e-8,0.9500154,0.000052131112,0.018885186,0.030221006,0.00042746324],"about_ca_topic_score_codex":0.0000049836863,"about_ca_topic_score_gemma":0.000022649094,"teacher_disagreement_score":0.9089521,"about_ca_system_score_codex":0.00009492193,"about_ca_system_score_gemma":0.00038440005,"threshold_uncertainty_score":0.99988806},"labels":[],"label_agreement":null},{"id":"W3076096311","doi":"10.1186/s12911-020-01194-y","title":"Home blood pressure data visualization for the management of hypertension: designing for patient and physician information needs","year":2020,"lang":"en","type":"article","venue":"BMC Medical Informatics and Decision Making","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sinai Health System; Lunenfeld-Tanenbaum Research Institute; University of Toronto","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; Agency for Healthcare Research and Quality","keywords":"Blood pressure; Workflow; Medicine; Thematic analysis; Health informatics; Data visualization; Focus group; Visualization; Qualitative research; Nursing; Computer science; Data mining; Internal medicine; Public health; Database","score_opus":0.0791037999413446,"score_gpt":0.32619982513837725,"score_spread":0.24709602519703266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3076096311","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00091229094,0.00023267049,0.9981784,0.00009467119,0.000080089536,0.0004027437,0.000036107962,0.000024597952,0.000038413404],"genre_scores_gemma":[0.15731445,0.00039212027,0.83669823,0.005384727,0.000050991675,0.000020092548,0.00013044583,0.000007270581,0.0000017025354],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99873513,0.000012759019,0.00056173786,0.00008403711,0.0004924856,0.00011383078],"domain_scores_gemma":[0.99846417,0.00072788453,0.000271513,0.00030946874,0.00013597938,0.00009099344],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005330727,0.000090091184,0.00015405848,0.000069796755,0.00016463049,0.00023767872,0.000511161,0.00004749203,0.00000199767],"category_scores_gemma":[0.00022706919,0.000060302576,0.000024663987,0.00028121893,0.000033722223,0.0010356656,0.00073454104,0.000038655147,6.853032e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040891533,0.000028903409,0.00002986066,0.0011050388,0.00009136208,2.812334e-7,0.0026892812,0.0011642318,0.0000017137038,0.0865851,0.0031138815,0.90514946],"study_design_scores_gemma":[0.00075762486,0.000091058195,0.000025861935,0.00026083723,0.00011244517,0.0000029719727,0.0019048975,0.98567027,0.000013359043,0.0009554554,0.010124334,0.0000808857],"about_ca_topic_score_codex":3.1548626e-7,"about_ca_topic_score_gemma":2.49042e-7,"teacher_disagreement_score":0.984506,"about_ca_system_score_codex":0.0000016514218,"about_ca_system_score_gemma":0.00003794845,"threshold_uncertainty_score":0.24590677},"labels":[],"label_agreement":null},{"id":"W3080485811","doi":"10.1109/tvcg.2020.3018724","title":"ChartSeer: Interactive Steering Exploratory Visual Analysis With Machine Intelligence","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Visualization; Baseline (sea); Intelligence analysis; Data science; Human–computer interaction; Data visualization; Exploratory data analysis; Session (web analytics); Asynchronous communication; Artificial intelligence; Machine learning; Data mining; World Wide Web","score_opus":0.022829860738458642,"score_gpt":0.2795975151436216,"score_spread":0.2567676544051629,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3080485811","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015790723,0.000027847353,0.9974671,0.00020529231,0.00016513625,0.00015007485,0.000021023621,0.00035919354,0.000025271906],"genre_scores_gemma":[0.9931601,0.00021286587,0.0019112884,0.004581638,0.000044019453,0.000014055625,0.000033829587,0.00002292666,0.000019236879],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982956,0.00012598769,0.0003595979,0.00061228254,0.0003923559,0.00021417254],"domain_scores_gemma":[0.99902785,0.00008020569,0.00014012783,0.00027958184,0.00020027687,0.0002719366],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012516217,0.00027124098,0.00030633443,0.0005964015,0.0002576227,0.00039057384,0.00037078993,0.00007113541,0.000033059056],"category_scores_gemma":[0.0000030979004,0.00024918796,0.000098675206,0.003231069,0.00008236815,0.00086627644,0.000014650769,0.00021767034,0.000015986245],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000218001,0.0012534489,0.00086252537,0.0001869686,0.0024461718,0.000061779654,0.01875948,0.063831955,0.0000724835,0.8579225,0.00029539235,0.05408927],"study_design_scores_gemma":[0.0002614345,0.00051243615,0.00008918187,0.000026509342,0.00014174316,0.0000051915067,0.00013857314,0.9954355,0.0021700345,0.000049155777,0.00086369325,0.0003065864],"about_ca_topic_score_codex":0.000009271408,"about_ca_topic_score_gemma":0.00002669266,"teacher_disagreement_score":0.9955558,"about_ca_system_score_codex":0.000020332585,"about_ca_system_score_gemma":0.000040520234,"threshold_uncertainty_score":0.99999607},"labels":[],"label_agreement":null},{"id":"W3080867337","doi":"10.1109/vis47514.2020.00048","title":"Why Shouldn’t All Charts Be Scatter Plots? Beyond Precision-Driven Visualizations","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Science Foundation","keywords":"Visualization; Scatter plot; Plot (graphics); Argument (complex analysis); Chart; Variable (mathematics); Computer science; Information visualization; Visual analytics; Perception; Formative assessment; Pie chart; Data visualization; Artificial intelligence; Epistemology; Mathematics; Statistics; Machine learning; Philosophy","score_opus":0.07807545814621687,"score_gpt":0.3546371624030114,"score_spread":0.27656170425679455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3080867337","genre_codex":"methods","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006314196,0.00004905922,0.9447549,0.045765433,0.0009260586,0.00043668842,0.00017814987,0.00074286404,0.0070837107],"genre_scores_gemma":[0.07258482,0.0011430575,0.2574479,0.64083624,0.0018848991,0.00029361164,0.009092756,0.00037676247,0.016339973],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99659055,0.00015066608,0.0006823893,0.0013176191,0.000854563,0.00040418483],"domain_scores_gemma":[0.99724555,0.000104247825,0.00029066406,0.0016777425,0.0002914505,0.0003903704],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00020225333,0.00045527614,0.00048417717,0.00030977535,0.0001568309,0.0012498284,0.0028806482,0.0003093932,0.0009197768],"category_scores_gemma":[0.00012744092,0.00042851426,0.00022688835,0.00056910387,0.00007243469,0.0006226702,0.0050700833,0.0004441557,0.0004424762],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021202827,0.00017774432,0.00018375559,0.00008287726,0.00012417145,0.000017202368,0.0011690498,0.0015857408,0.00009075659,0.1356834,0.8597655,0.0011176683],"study_design_scores_gemma":[0.00021129927,0.000040192142,0.00011477832,0.00007666578,0.000054659988,0.0000044256803,0.000027205657,0.57461107,0.00034060192,0.008801356,0.41511825,0.00059947517],"about_ca_topic_score_codex":0.000044103122,"about_ca_topic_score_gemma":0.000040816623,"teacher_disagreement_score":0.687307,"about_ca_system_score_codex":0.00006951262,"about_ca_system_score_gemma":0.00022973769,"threshold_uncertainty_score":0.9999935},"labels":[],"label_agreement":null},{"id":"W3081955760","doi":"10.1109/vis47514.2020.00033","title":"Encodable: Configurable Grammar for Visualization Components","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Air Canada","funders":"","keywords":"Grammar; Visualization; Computer science; Parsing; Component (thermodynamics); Rendering (computer graphics); Programming language; Natural language processing; Artificial intelligence; Linguistics","score_opus":0.0755000314713328,"score_gpt":0.33698256161195356,"score_spread":0.26148253014062073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3081955760","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000023201077,0.00003576089,0.9911114,0.0016288962,0.0008560487,0.00054963306,0.00011597505,0.0005144441,0.0051646433],"genre_scores_gemma":[0.3566047,0.0007635595,0.5592494,0.028308967,0.0013952819,0.0005528587,0.027011495,0.00026734397,0.025846407],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981896,0.00005913921,0.00043192346,0.0007172128,0.00034263666,0.0002594788],"domain_scores_gemma":[0.99854445,0.00007426267,0.00024731067,0.0006794949,0.00028308926,0.00017138725],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022320657,0.00025079102,0.0003408523,0.00012244795,0.000121051344,0.0007121588,0.0014605252,0.00017908309,0.000078003286],"category_scores_gemma":[0.00013290581,0.00024582958,0.00012262921,0.0003124767,0.000026257863,0.00027323834,0.0010133305,0.00015209401,0.0000990479],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004491689,0.00008544395,0.000044345346,0.00027175577,0.00005439712,0.0000025742893,0.00014718095,0.0007125172,0.00039055472,0.918555,0.07807841,0.0016533314],"study_design_scores_gemma":[0.0002952202,0.00003379389,0.00002504925,0.000046948324,0.000019523915,9.240382e-7,0.000011525595,0.83210945,0.0014654335,0.025966914,0.1397321,0.00029313104],"about_ca_topic_score_codex":0.00005112493,"about_ca_topic_score_gemma":0.000005469127,"teacher_disagreement_score":0.8925881,"about_ca_system_score_codex":0.000045689765,"about_ca_system_score_gemma":0.00018790796,"threshold_uncertainty_score":0.9999994},"labels":[],"label_agreement":null},{"id":"W3081999666","doi":"10.1155/2020/9082370","title":"Visual Analytic Method for Metro Anomaly Detection and Diffusion","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Beijing Municipal Science and Technology Commission; National Natural Science Foundation of China","keywords":"Computer science; Urban rail transit; GRASP; Beijing; Scheduling (production processes); Real-time computing; Transport engineering; Simulation; Engineering; Operations management; China; Geography","score_opus":0.01668869332409839,"score_gpt":0.3225803894152184,"score_spread":0.30589169609112,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3081999666","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10503443,0.000063271706,0.8941127,0.00057726505,0.000109488916,0.00007574914,0.0000050498784,0.000018214929,0.000003842371],"genre_scores_gemma":[0.7808082,0.000053311895,0.21869385,0.00035538967,0.000068117406,0.0000011431933,0.000008254153,0.0000060749016,0.0000056585245],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991566,0.000027174552,0.00038438902,0.00014773759,0.00019557736,0.00008850223],"domain_scores_gemma":[0.9992021,0.000074331256,0.0003411515,0.000056556753,0.0002100707,0.00011582828],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019833518,0.000080602054,0.00017965652,0.00012140262,0.000059257578,0.000051745148,0.00013460749,0.00003083285,0.0000026681896],"category_scores_gemma":[0.00007087159,0.00007162744,0.00008085838,0.00036454952,0.000009250395,0.00086053624,0.000003915747,0.000071642775,4.5402408e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065314915,0.0002577709,0.0041012242,0.00032569972,0.00019592718,0.000040922798,0.005861781,0.039502244,0.3439527,0.011747521,0.000115575705,0.5932455],"study_design_scores_gemma":[0.00330145,0.0018116677,0.06954083,0.0000515212,0.00019906585,0.000013910784,0.00070434355,0.8890664,0.027261313,0.0022247543,0.0055398727,0.00028484763],"about_ca_topic_score_codex":0.0000013874527,"about_ca_topic_score_gemma":0.000015141029,"teacher_disagreement_score":0.8495642,"about_ca_system_score_codex":0.000015805792,"about_ca_system_score_gemma":0.000027402128,"threshold_uncertainty_score":0.2920882},"labels":[],"label_agreement":null},{"id":"W3082046364","doi":"10.1109/beliv51497.2020.00016","title":"Data-First Visualization Design Studies","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Transferability; Process (computing); Data science; Visualization; Design process; Data visualization; Adaptation (eye); Data mining; Engineering; Machine learning; Work in process; Programming language","score_opus":0.3454013949793777,"score_gpt":0.43208527589239093,"score_spread":0.08668388091301321,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3082046364","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000011814911,0.00039753984,0.9935646,0.003739216,0.00069627445,0.00022421895,0.00008382082,0.000586356,0.0007067609],"genre_scores_gemma":[0.022885052,0.007374973,0.94580084,0.0134582035,0.0009778497,0.00005726792,0.006056242,0.000099934725,0.003289662],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99797195,0.0001217541,0.0003878909,0.0009583648,0.00039140932,0.00016861765],"domain_scores_gemma":[0.9973771,0.00012439354,0.00020796526,0.001976092,0.00021142894,0.000103032515],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.00043480346,0.00023526791,0.00032953193,0.00011168616,0.0001175838,0.00057271303,0.003614245,0.00010690113,0.000032444328],"category_scores_gemma":[0.00045860172,0.00020755561,0.00004121732,0.00040999384,0.00004031151,0.0005527295,0.010911404,0.00016192222,0.0002223075],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000020997688,0.00007361737,0.000035944373,0.00029646672,0.0002409644,0.000018173898,0.0008768435,0.0043748263,0.000006396214,0.42529446,0.5667008,0.0020793776],"study_design_scores_gemma":[0.00008742426,0.000019412495,0.000010613151,0.00006251073,0.000031775304,0.0000011187846,0.00005763129,0.9228712,0.000104488434,0.01068045,0.06581166,0.00026175383],"about_ca_topic_score_codex":0.000008974319,"about_ca_topic_score_gemma":0.000017822957,"teacher_disagreement_score":0.9184964,"about_ca_system_score_codex":0.000041534047,"about_ca_system_score_gemma":0.00018475422,"threshold_uncertainty_score":0.99708813},"labels":[],"label_agreement":null},{"id":"W3083453358","doi":"10.1109/beliv51497.2020.00008","title":"Distributed Synchronous Visualization Design: Challenges and Strategies","year":2020,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Cumming School of Medicine, University of Calgary; European Commission; University of Calgary","keywords":"Visualization; Dependency (UML); Data visualization; Drone; Teamwork; Space (punctuation); Representation (politics); Process (computing); Physical space","score_opus":0.06761388283812458,"score_gpt":0.30335104243185035,"score_spread":0.23573715959372576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3083453358","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006283493,0.0004693255,0.9952809,0.002754758,0.000022694594,0.000056090717,0.000003570614,0.00024417788,0.0011056332],"genre_scores_gemma":[0.9763971,0.0014857918,0.020587735,0.0013904319,0.000047678124,0.000003174537,0.0000466314,0.000007642858,0.00003379509],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994262,0.000043957578,0.0001087244,0.00021431854,0.000108956454,0.00009788206],"domain_scores_gemma":[0.9996751,0.00003023954,0.00003303567,0.00012301921,0.00004359953,0.000094982715],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000070662696,0.00007294764,0.00008257156,0.000022518678,0.00004768405,0.00024588575,0.00022136753,0.00002641735,0.000021006166],"category_scores_gemma":[0.00003569307,0.00006369839,0.000010553556,0.00016989255,0.000021631506,0.0006123202,0.000114133465,0.00002408978,0.00002274094],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000013043417,0.00001847063,0.00001044262,0.000022731436,0.000007808976,0.00000375082,0.000849241,0.0002973168,0.00009256481,0.98550963,0.0013083695,0.011878352],"study_design_scores_gemma":[0.00018257035,0.00011973342,0.00036168564,0.000006326999,0.0000049230302,0.0000032684409,0.0005791244,0.9881844,0.0005288126,0.0028494908,0.007037771,0.00014188245],"about_ca_topic_score_codex":0.0000016833985,"about_ca_topic_score_gemma":0.0000017233424,"teacher_disagreement_score":0.9878871,"about_ca_system_score_codex":0.000005837681,"about_ca_system_score_gemma":0.000038308648,"threshold_uncertainty_score":0.2597545},"labels":[],"label_agreement":null},{"id":"W3083632304","doi":"10.1109/vis47514.2020.00023","title":"Designing for Ambiguity: Visual Analytics in Avalanche Forecasting","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Simon Fraser University","funders":"Simon Fraser University","keywords":"Sensemaking; Ambiguity; Visual analytics; Data science; Computer science; Variety (cybernetics); Visualization; Analytics; Negotiation; Domain (mathematical analysis); Knowledge management; Management science; Artificial intelligence; Engineering; Political science","score_opus":0.15439836916242197,"score_gpt":0.36035894492487963,"score_spread":0.20596057576245766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3083632304","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00022557015,0.000026720989,0.99619424,0.0014736217,0.0003257522,0.0003310628,0.000015277945,0.00021655203,0.0011911999],"genre_scores_gemma":[0.25616547,0.00003596799,0.7394935,0.0026645123,0.0003374468,0.000054065404,0.0002825343,0.000047323607,0.0009192007],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99803203,0.000061396524,0.00055572955,0.00072938134,0.00028325676,0.00033821596],"domain_scores_gemma":[0.99886304,0.0001814766,0.00024322337,0.00044332887,0.0001371844,0.00013175997],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006034977,0.0002505829,0.00042571445,0.000252841,0.00006343949,0.0005737027,0.0011710925,0.00017927658,0.000010500843],"category_scores_gemma":[0.0004888349,0.0002538065,0.0001447016,0.0005126416,0.000013740544,0.00020796056,0.00179911,0.0003393632,0.000012490543],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008897659,0.0013893682,0.02654809,0.005480039,0.00086080504,0.0004263883,0.00754276,0.13443527,0.0017346645,0.4320344,0.14672683,0.24273239],"study_design_scores_gemma":[0.0002639648,0.000042883625,0.00007090557,0.0001122104,0.000018285158,0.0000016814107,0.000047018046,0.98550636,0.00075312634,0.011199806,0.0016830665,0.00030071376],"about_ca_topic_score_codex":0.00006540646,"about_ca_topic_score_gemma":0.00006791371,"teacher_disagreement_score":0.85107106,"about_ca_system_score_codex":0.00015523405,"about_ca_system_score_gemma":0.00025245594,"threshold_uncertainty_score":0.9999914},"labels":[],"label_agreement":null},{"id":"W3084592132","doi":"10.1109/ccece47787.2020.9255824","title":"Geo-Spatial Data Visualization and Critical Metrics Predictions for Canadian Elections","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Visualization; Geospatial analysis; Computer science; Data science; Traverse; Process (computing); Interpretation (philosophy); Data visualization; Information visualization; Creative visualization; Data mining; World Wide Web; Information retrieval; Geography; Cartography","score_opus":0.10508089089740569,"score_gpt":0.38574071601820303,"score_spread":0.28065982512079735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3084592132","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000032824903,0.00006628641,0.98875576,0.0067013516,0.0008733286,0.00034283067,0.0022162441,0.00024238112,0.0007985409],"genre_scores_gemma":[0.6145916,0.0011321093,0.32928807,0.011932548,0.002221534,0.0002406669,0.03877622,0.00013734282,0.0016799212],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983032,0.000051977397,0.0003170383,0.0008272662,0.00023681083,0.00026372282],"domain_scores_gemma":[0.9979844,0.00019222201,0.000066581626,0.0009672802,0.000327682,0.00046179976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023846372,0.00017371692,0.00019855991,0.00046517546,0.000382412,0.00090365624,0.0012324464,0.00019748318,0.00003725973],"category_scores_gemma":[0.0018357511,0.00018784526,0.000039096805,0.000703619,0.00005010618,0.00046640186,0.0016289966,0.00021072033,0.000009630667],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012076422,0.0000491914,0.00016160047,0.00011543278,0.00005416313,0.000002175854,0.00012579198,0.00018787441,0.0000032082894,0.89675057,0.09986637,0.00268242],"study_design_scores_gemma":[0.000092543625,0.00003485628,0.00015745522,0.000013809411,0.0000632989,0.0000036865472,0.000017681592,0.903198,0.000010145211,0.0059632612,0.09026195,0.00018332012],"about_ca_topic_score_codex":0.024540924,"about_ca_topic_score_gemma":0.06963478,"teacher_disagreement_score":0.90301013,"about_ca_system_score_codex":0.000086028274,"about_ca_system_score_gemma":0.0010182789,"threshold_uncertainty_score":0.98195475},"labels":[],"label_agreement":null},{"id":"W3084885766","doi":"10.1016/j.entcom.2020.100388","title":"Exploring alternatives with Unreal Engine’s Blueprints Visual Scripting System","year":2020,"lang":"en","type":"article","venue":"Entertainment Computing","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ontario Institute of Technology; Ubisoft (Canada)","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Blueprint; Computer science; Scripting language; Usability; Game development tool; Workflow; Human–computer interaction; Swap (finance); USable; Game design; Software engineering; Video game development; Multimedia; World Wide Web; Game art design; Operating system; Engineering","score_opus":0.08036728376316715,"score_gpt":0.27613216955011816,"score_spread":0.195764885786951,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3084885766","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16434431,0.000010677904,0.8338597,0.0003973656,0.00024163169,0.000106519445,0.0000012168084,0.00042492553,0.00061365595],"genre_scores_gemma":[0.98158604,0.000003936219,0.017462203,0.0006848564,0.00021934345,0.0000042349166,0.000008313528,0.000017692319,0.000013400262],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983143,0.0000832931,0.00032480693,0.0005025992,0.00043850907,0.00033645012],"domain_scores_gemma":[0.9993005,0.00005992505,0.00016284968,0.00022566272,0.000055132736,0.00019594604],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021994955,0.00019779372,0.00020500271,0.00008167558,0.0001828635,0.0003279354,0.00066910044,0.000016072945,0.000004661382],"category_scores_gemma":[0.000036098747,0.00017581868,0.000048222304,0.00036541704,0.000020810405,0.0006205312,0.00057609595,0.00013379627,0.000051785206],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012303381,0.00081632065,0.0865134,0.0015194094,0.0009896592,0.0011586638,0.093321085,0.14489399,0.0052405884,0.2908699,0.00071319146,0.37384075],"study_design_scores_gemma":[0.00046665128,0.000114707764,0.0008531969,0.0002617194,0.000007659428,0.000010857853,0.0015592987,0.993671,0.002328067,0.0000032590222,0.00050734886,0.00021624767],"about_ca_topic_score_codex":0.000012482292,"about_ca_topic_score_gemma":6.211695e-7,"teacher_disagreement_score":0.848777,"about_ca_system_score_codex":0.00008902819,"about_ca_system_score_gemma":0.000024770734,"threshold_uncertainty_score":0.71696776},"labels":[],"label_agreement":null},{"id":"W3085436467","doi":"10.1109/tvcg.2020.3023336","title":"Touch and Beyond: Comparing Physical and Virtual Reality Visualizations","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Virtual reality; Annotation; Visualization; Data visualization; Augmented reality; Immersion (mathematics); Simple (philosophy); Virtual world","score_opus":0.03806530169637595,"score_gpt":0.30494559580093256,"score_spread":0.2668802941045566,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3085436467","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017938275,0.000024078503,0.9808317,0.00048224727,0.00015917733,0.00016874578,0.000023323626,0.00030910314,0.000063390355],"genre_scores_gemma":[0.9940504,0.00032840244,0.00067414495,0.004794969,0.00007978379,0.000008258425,0.000027693064,0.00002039824,0.000015982612],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99839497,0.00014461517,0.00032528324,0.00061396166,0.0003103364,0.00021083625],"domain_scores_gemma":[0.99908507,0.00011182673,0.00009997994,0.0002421957,0.00012108487,0.00033986027],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00011486968,0.0002521123,0.00030071364,0.00021885578,0.0004602502,0.0004868229,0.00022670897,0.00008810363,0.0000045089296],"category_scores_gemma":[0.000007249952,0.00026040143,0.000054122833,0.0009056838,0.00017059769,0.0006355432,0.000028347411,0.00017819187,0.0000041760914],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011726566,0.00020474412,0.00025162936,0.00004666121,0.00004672847,0.0000026524106,0.0035599205,0.0007100013,0.000043498156,0.988185,0.0003147811,0.0066226455],"study_design_scores_gemma":[0.00061947305,0.0003129443,0.0005046535,0.000019036328,0.000036993737,0.00001200095,0.000099535784,0.9959511,0.00046581708,0.0007246452,0.0009645783,0.00028922042],"about_ca_topic_score_codex":0.000010443911,"about_ca_topic_score_gemma":0.000012945528,"teacher_disagreement_score":0.9952411,"about_ca_system_score_codex":0.00001072373,"about_ca_system_score_gemma":0.000028878494,"threshold_uncertainty_score":0.9999848},"labels":[],"label_agreement":null},{"id":"W3087574828","doi":"","title":"The Visual Cortex as a Spatial Cortex Recruited by Sight and Sound: Implications for ‘Accessible InfoVis’","year":2014,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario College of Art and Design; University of Toronto","funders":"","keywords":"Sight; Computer science; Visual cortex; Sound (geography); Perception; Human–computer interaction; Psychology; Neuroscience; Acoustics; Physics; Optics","score_opus":0.011988721675469103,"score_gpt":0.3126282466869433,"score_spread":0.3006395250114742,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3087574828","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0073331213,0.0005361513,0.98852444,0.0028701033,0.00013978338,0.00018216223,0.000007709645,0.00005283047,0.00035370144],"genre_scores_gemma":[0.9947662,0.0020588483,0.0004227172,0.00088033045,0.00021367348,0.000022563325,0.00004334671,0.0000188527,0.0015734909],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99804246,0.00008821858,0.00033495977,0.00025875313,0.00019744218,0.0010781863],"domain_scores_gemma":[0.9988843,0.0002462726,0.00026194687,0.00029016365,0.00018447595,0.00013281003],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012208135,0.00013886594,0.00014159107,0.00008201558,0.00090409967,0.00084269594,0.00079146615,0.000057711823,0.0000047800327],"category_scores_gemma":[0.00020434428,0.000101255806,0.00006280352,0.0002935736,0.00007057873,0.0004690369,0.0001179207,0.0004469249,0.000012844507],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015816302,0.000057029894,0.0009772835,0.0000035260043,0.000069032096,1.14654235e-7,0.000093409675,0.0000034159889,0.00087296107,0.8349344,0.00209849,0.1608745],"study_design_scores_gemma":[0.0014597104,0.0009393534,0.00282349,0.000013086186,0.000052379324,0.00025345685,0.00025355126,0.12835939,0.0001281579,0.69824606,0.16709684,0.00037453815],"about_ca_topic_score_codex":0.000041584237,"about_ca_topic_score_gemma":0.0003976187,"teacher_disagreement_score":0.9881017,"about_ca_system_score_codex":0.00014264398,"about_ca_system_score_gemma":0.0007261617,"threshold_uncertainty_score":0.81261367},"labels":[],"label_agreement":null},{"id":"W3088990937","doi":"10.2196/17892","title":"Visual Analytic Tools and Techniques in Population Health and Health Services Research: Scoping Review","year":2020,"lang":"en","type":"article","venue":"Journal of Medical Internet Research","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Centre for Disease Control; University of British Columbia; University of Calgary; Impact; McMaster University; University of Toronto; Université de Sherbrooke; Ontario Neurotrauma Foundation; University of Waterloo; Canadian Institute for Health Information; Toronto Rehabilitation Institute; University Health Network","funders":"Canadian Institutes of Health Research; University of Toronto; Toronto Rehabilitation Institute","keywords":"Visual analytics; Data science; Computer science; Analytics; Population health; Health care; Systematic review; Presentation (obstetrics); Population; Visualization; MEDLINE; Medicine; Data mining","score_opus":0.3214844140167463,"score_gpt":0.5885567520420297,"score_spread":0.2670723380252834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3088990937","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025489766,0.13370323,0.08230451,0.75637937,0.00013070875,0.001727672,0.0000049171426,0.00007898569,0.00018081567],"genre_scores_gemma":[0.65312153,0.2977072,0.004149564,0.04448612,0.00043190422,0.000008704489,0.000022686218,0.000021294045,0.00005096649],"study_design_codex":"design_other","study_design_gemma":"systematic_review","domain_scores_codex":[0.9947232,0.0013101279,0.0008538623,0.00025197575,0.002500131,0.00036070705],"domain_scores_gemma":[0.998031,0.0003689369,0.0002203192,0.00013269165,0.0003277521,0.00091929885],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.020385735,0.00007472133,0.00040084217,0.00047950933,0.00007327113,0.000358922,0.00082595745,0.00006201811,0.000038721333],"category_scores_gemma":[0.001216405,0.000057956135,0.00002740715,0.0011137022,0.00010956206,0.0005919057,0.0007004563,0.0009872684,0.0000033548204],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006292108,0.00034312104,0.022742184,0.03273695,0.00005269058,0.00030899624,0.007832228,0.0000010923181,0.000016352615,0.02157729,0.048690364,0.8656358],"study_design_scores_gemma":[0.002200326,0.009552122,0.013129815,0.5582723,0.000008779985,0.0005464725,0.0027083496,0.38842294,0.00019991896,0.0030694427,0.021372264,0.00051724643],"about_ca_topic_score_codex":0.00042043737,"about_ca_topic_score_gemma":0.0002135284,"teacher_disagreement_score":0.86511856,"about_ca_system_score_codex":0.00011651167,"about_ca_system_score_gemma":0.0008464515,"threshold_uncertainty_score":0.70653296},"labels":[],"label_agreement":null},{"id":"W3089673451","doi":"10.1145/3399715.3399830","title":"Understanding and Supporting Academic Literature Review Workflows with LitSense","year":2020,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Workflow; Computer science; Formative assessment; Field (mathematics); Visualization; Systematic review; Data science; Space (punctuation); Work (physics); Knowledge management; Psychology; Engineering; Mathematics education; MEDLINE","score_opus":0.11345026526644782,"score_gpt":0.3306372387838199,"score_spread":0.2171869735173721,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3089673451","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000829696,0.004980925,0.97216576,0.020687914,0.000017735018,0.00009240227,0.0000020643322,0.00014249058,0.0018277566],"genre_scores_gemma":[0.53632027,0.10075153,0.10154473,0.2588682,0.00033730164,0.000007744204,0.000100739475,0.000050443177,0.0020190675],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931276,0.000026239997,0.00016019958,0.00022971156,0.0001419831,0.00012910865],"domain_scores_gemma":[0.99960786,0.000027747468,0.00006535264,0.00013343173,0.000028031414,0.00013755828],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015569793,0.00007869819,0.0001164131,0.000024234085,0.00005528771,0.00017166122,0.00020699085,0.00003077536,0.000017901275],"category_scores_gemma":[0.00007119821,0.000054897264,0.000014386573,0.0006563433,0.000016127939,0.00045047086,0.00012212057,0.00014750192,0.000008422591],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000075475273,0.0000150921105,0.0036515405,0.002100514,0.00003895415,0.00019602293,0.0034910657,0.000022550033,0.00012323429,0.89045185,0.08753445,0.0123672085],"study_design_scores_gemma":[0.001403301,0.00040133268,0.00028826343,0.017859561,0.000116541705,0.00040353462,0.0007165202,0.8103042,0.0003529128,0.0051482497,0.1615783,0.0014272874],"about_ca_topic_score_codex":2.4968165e-7,"about_ca_topic_score_gemma":6.96663e-7,"teacher_disagreement_score":0.88530356,"about_ca_system_score_codex":0.000011358692,"about_ca_system_score_gemma":0.00002295225,"threshold_uncertainty_score":0.22386454},"labels":[],"label_agreement":null},{"id":"W3093958547","doi":"10.1109/mcg.2020.3017064","title":"Challenges in Evaluating Interactive Visual Machine Learning Systems","year":2020,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Human–computer interaction; Usability; Artificial intelligence; Machine learning; Multimedia","score_opus":0.09900912250097373,"score_gpt":0.3588387416213695,"score_spread":0.25982961912039576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3093958547","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0029850872,0.00071234565,0.9943066,0.0013702994,0.000074277385,0.00022687457,0.0000042373813,0.00012250606,0.00019775012],"genre_scores_gemma":[0.9948521,0.0010866375,0.0031611912,0.00060517894,0.00019438431,0.00006442156,0.000018590788,0.000010171114,0.000007275873],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99898183,0.00009070716,0.00023495262,0.0004005267,0.00015768617,0.00013431987],"domain_scores_gemma":[0.99943805,0.000109019544,0.000100841025,0.00016565448,0.00008016142,0.00010626888],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022276155,0.00011026667,0.00014869838,0.00012140954,0.00011989687,0.00021661236,0.00033273496,0.000037828122,9.715883e-7],"category_scores_gemma":[0.000008784597,0.00011003451,0.000028289905,0.00046062114,0.000027741662,0.00023779401,0.0001659366,0.00020040476,0.000012150662],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000038395056,0.00015610288,0.001421719,0.00011374688,0.00003862219,0.000004753044,0.0022227764,0.004664305,0.00029952163,0.83520114,0.0001285583,0.15574493],"study_design_scores_gemma":[0.00019045951,0.00008436667,0.0005639763,0.000022830709,0.0000042281645,0.000004687571,0.000049840146,0.9887367,0.000022990447,0.00056520855,0.009632185,0.00012256051],"about_ca_topic_score_codex":0.000013763251,"about_ca_topic_score_gemma":0.000008211649,"teacher_disagreement_score":0.99186707,"about_ca_system_score_codex":0.000008637624,"about_ca_system_score_gemma":0.000018881536,"threshold_uncertainty_score":0.44870773},"labels":[],"label_agreement":null},{"id":"W3094173950","doi":"10.1109/tvcg.2020.3032984","title":"Understanding Missing Links in Bipartite Networks With MissBiN","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Computer science; Bipartite graph; Variety (cybernetics); Link analysis; Task (project management); Visualization; Data mining; Intelligence analysis; Machine learning; Link (geometry); Informatics; Artificial intelligence; Information retrieval; Data science; Theoretical computer science","score_opus":0.07947087621210688,"score_gpt":0.2855767233914348,"score_spread":0.20610584717932792,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3094173950","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005230772,0.000024395438,0.99810416,0.0008046766,0.00014963771,0.00012903585,0.0000031072084,0.00021252868,0.00004939478],"genre_scores_gemma":[0.9904238,0.0001991269,0.0025187016,0.0067677884,0.000046730212,0.0000045651414,0.000010716995,0.00002031042,0.000008287094],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99872035,0.00010520204,0.00029017782,0.0004233763,0.0002435123,0.00021738869],"domain_scores_gemma":[0.99939793,0.00006915676,0.000082518745,0.00019406935,0.000055440894,0.00020090149],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013689043,0.00018545934,0.00018680921,0.00028411328,0.00021827803,0.0003694925,0.00023562158,0.00013160675,0.000009903292],"category_scores_gemma":[0.000002053414,0.00017637988,0.000041790423,0.0016793883,0.00006615406,0.00045353264,0.000005988656,0.00028712477,0.0000030900865],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005012074,0.00027098178,0.00058264105,0.00007100915,0.0000609551,0.000031024214,0.003138773,0.058220915,0.00002148292,0.9325837,0.00048935023,0.0044790627],"study_design_scores_gemma":[0.0006524342,0.00020382777,0.00006661694,0.00008220165,0.000012236176,0.0000071597983,0.00005697075,0.99754316,0.00029464357,0.00022838048,0.000626849,0.00022551659],"about_ca_topic_score_codex":0.0000057762168,"about_ca_topic_score_gemma":0.000026562599,"teacher_disagreement_score":0.99558544,"about_ca_system_score_codex":0.000029747634,"about_ca_system_score_gemma":0.000045638637,"threshold_uncertainty_score":0.7192563},"labels":[],"label_agreement":null},{"id":"W3094467965","doi":"10.1145/3382507.3418884","title":"Eye-Tracking to Predict User Cognitive Abilities and Performance for User-Adaptive Narrative Visualizations","year":2020,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Eye tracking; Leverage (statistics); Human–computer interaction; Narrative; Cognition; Visualization; User interface; Comprehension; User modeling; Task (project management); Cognitive load; Multimedia; Artificial intelligence","score_opus":0.045146640731431056,"score_gpt":0.334546095878952,"score_spread":0.28939945514752097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3094467965","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.050881352,0.000011719624,0.94602996,0.0018413309,0.000057310852,0.0004399759,0.00006026295,0.00016584518,0.00051226665],"genre_scores_gemma":[0.974316,0.000015919908,0.019419657,0.005002786,0.00007182176,0.000049291542,0.000040138537,0.000013048351,0.0010713118],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989909,0.000037385507,0.00021289992,0.00038853183,0.00017732945,0.00019293942],"domain_scores_gemma":[0.9990987,0.00016131657,0.000057428166,0.00012603035,0.0003739297,0.0001825905],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000117609256,0.00013451968,0.00015457078,0.000068739006,0.0002471486,0.0002613871,0.0002666511,0.00003522522,0.000035186073],"category_scores_gemma":[0.0003016223,0.00012204659,0.00003074128,0.0004533659,0.00005982448,0.0010493107,0.00020528662,0.000051092662,0.000016277158],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018794036,0.00026612944,0.039379444,0.00027856062,0.00023614243,0.0000038323356,0.19971965,0.001680025,0.0003595239,0.7188294,0.026272925,0.012786412],"study_design_scores_gemma":[0.00068813626,0.0010266607,0.0067431773,0.00008685525,0.000025794792,0.0000012858968,0.013263368,0.9644886,0.0030808803,0.00027928106,0.009942064,0.0003738638],"about_ca_topic_score_codex":0.0000061941,"about_ca_topic_score_gemma":0.00001317045,"teacher_disagreement_score":0.9628086,"about_ca_system_score_codex":0.000015943244,"about_ca_system_score_gemma":0.000064178756,"threshold_uncertainty_score":0.49769157},"labels":[],"label_agreement":null},{"id":"W3094824040","doi":"10.1123/ijspp.2020-0813","title":"Show Me the Data, Jerry! Data Visualization and Transparency","year":2020,"lang":"en","type":"article","venue":"International Journal of Sports Physiology and Performance","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Sport Centre Pacific","funders":"","keywords":"Transparency (behavior); Visualization; Computer science; Artificial intelligence; Computer security","score_opus":0.05947802969525306,"score_gpt":0.3276387437665449,"score_spread":0.26816071407129183,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3094824040","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7505598,0.0009122508,0.23445559,0.012415802,0.0011674763,0.000098604614,0.00014941978,0.00003339773,0.00020767695],"genre_scores_gemma":[0.9937638,0.0032524527,0.0006441235,0.0019060028,0.00027021614,1.6957613e-7,0.00014624193,0.0000029489536,0.000014024117],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99921167,0.000021430782,0.00027420727,0.00018842025,0.00023476842,0.00006949191],"domain_scores_gemma":[0.99927175,0.000030569645,0.00022845609,0.00028528037,0.00012817745,0.000055758548],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027776326,0.00006907333,0.00010942475,0.000039646333,0.000067675806,0.00007234861,0.0017086228,0.000026465272,0.000028665578],"category_scores_gemma":[0.00003422931,0.000046237667,0.000011003435,0.00008935119,0.00007736623,0.0012529475,0.0004579479,0.000104419996,0.0000016039875],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009084663,0.000515139,0.24785186,0.0003504059,0.0011605972,0.00024620225,0.014277309,0.0020232804,0.008487349,0.17166564,0.05074559,0.5017682],"study_design_scores_gemma":[0.00041469352,0.000111078465,0.108874165,0.000050473227,0.00002553252,0.0001608614,0.00006592321,0.8667844,0.00017962621,0.0006544305,0.02256146,0.000117377946],"about_ca_topic_score_codex":0.0000011990937,"about_ca_topic_score_gemma":6.420762e-7,"teacher_disagreement_score":0.8647611,"about_ca_system_score_codex":0.0000031269044,"about_ca_system_score_gemma":0.000046370656,"threshold_uncertainty_score":0.31750748},"labels":[],"label_agreement":null},{"id":"W3095283945","doi":"10.1145/3427323","title":"Flex-ER","year":2020,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Horizon 2020 Framework Programme","keywords":"FLEX; Computer science; Human–computer interaction; JSON; Visualization; Flexibility (engineering); Debugging; Field (mathematics); Software engineering; Multimedia; World Wide Web; Operating system; Artificial intelligence","score_opus":0.08918782119899336,"score_gpt":0.3476504447671012,"score_spread":0.25846262356810784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3095283945","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6005072,0.000030022165,0.26651677,0.09279153,0.0051538255,0.001108967,0.000017237788,0.001526995,0.032347437],"genre_scores_gemma":[0.982251,0.000003355903,0.011162793,0.005890709,0.0004272659,0.0000040786663,0.0000027384485,0.00001324034,0.00024484185],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99893117,0.000008556987,0.00028054306,0.00032899983,0.00031243433,0.0001383168],"domain_scores_gemma":[0.9990436,0.00003325892,0.00027124916,0.0003876021,0.00019594526,0.00006834355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011147153,0.00013081578,0.00014706234,0.00007964572,0.00012316422,0.0002653699,0.002823529,0.00003930623,0.000031448613],"category_scores_gemma":[0.000158606,0.00009766769,0.00010899097,0.00037106356,0.000029064864,0.0008594259,0.0012963094,0.00018381161,0.0000819932],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058365007,0.0004477516,0.001674312,0.0002592828,0.00014616302,0.0000019406418,0.0064243865,0.00043724276,0.058531642,0.450473,0.43943295,0.042112954],"study_design_scores_gemma":[0.0012328926,0.0010290317,0.0052127554,0.00045082424,0.000054227025,0.000030496816,0.0002532894,0.58775264,0.26115102,0.019282194,0.12278238,0.0007682358],"about_ca_topic_score_codex":0.000003505883,"about_ca_topic_score_gemma":2.669762e-7,"teacher_disagreement_score":0.5873154,"about_ca_system_score_codex":0.000031891825,"about_ca_system_score_gemma":0.000009719228,"threshold_uncertainty_score":0.52468663},"labels":[],"label_agreement":null},{"id":"W3095896639","doi":"10.1145/3385959.3418458","title":"Exploring the Need and Design for Situated Video Analytics","year":2020,"lang":"en","type":"article","venue":"Symposium on Spatial User Interaction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Situated; Computer science; Session (web analytics); Analytics; Visual analytics; Human–computer interaction; Situated learning; Process (computing); Multimedia; Visualization; Data science; Artificial intelligence; World Wide Web; Psychology","score_opus":0.14209942615113713,"score_gpt":0.31576964201443425,"score_spread":0.17367021586329712,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3095896639","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0048846523,0.000002279877,0.9830121,0.0110711055,0.000517546,0.00024985013,0.0000055054943,0.00010937472,0.0001476289],"genre_scores_gemma":[0.99305695,0.000041009374,0.003090061,0.003430298,0.00023250192,0.000034037985,0.000019047959,0.000013508448,0.000082607476],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991574,0.000071944174,0.00020043434,0.00027299693,0.00016581913,0.00013139739],"domain_scores_gemma":[0.99928194,0.00022564313,0.00009728475,0.00021525937,0.00009658713,0.00008327241],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001533027,0.00011260741,0.00010898754,0.0000650113,0.00014509376,0.00034377733,0.00028565194,0.000023206754,0.0000064341675],"category_scores_gemma":[0.00011913487,0.00008537643,0.000043188928,0.0002587057,0.000016345597,0.00079662516,0.00008880288,0.00009870061,0.000029710121],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026757703,0.0009093603,0.0016203042,0.00039733792,0.00092946534,0.000041673706,0.043709736,0.21051024,0.20083302,0.19938536,0.08588689,0.2531008],"study_design_scores_gemma":[0.0003144817,0.00029860882,0.00014572969,0.000020123953,0.000023846258,0.000002098192,0.00014641436,0.9517748,0.019237405,0.00010145922,0.027808286,0.00012677845],"about_ca_topic_score_codex":0.000044886452,"about_ca_topic_score_gemma":0.000011497523,"teacher_disagreement_score":0.9881723,"about_ca_system_score_codex":0.00002795635,"about_ca_system_score_gemma":0.000021200194,"threshold_uncertainty_score":0.348155},"labels":[],"label_agreement":null},{"id":"W3096382101","doi":"10.1145/3380867.3426423","title":"Virtual Reality for Understanding Multidimensional Spatiotemporal Phenomena in Neuroscience","year":2020,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Virtual reality; Computer science; Human–computer interaction; Data science; Neuroscience; Psychology","score_opus":0.17682095079373472,"score_gpt":0.3419262248733012,"score_spread":0.1651052740795665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3096382101","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000275627,0.0000016367236,0.99242955,0.006313703,0.00008199335,0.000107377346,0.000010258147,0.000074685595,0.0007051583],"genre_scores_gemma":[0.97506475,0.0000022164263,0.018169578,0.006586943,0.00004876358,0.0000027933038,0.000015442263,0.000004219672,0.000105265],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991367,0.000028196206,0.00018018,0.00031362954,0.00018842203,0.00015288025],"domain_scores_gemma":[0.9996271,0.000059506885,0.000044757107,0.00013993969,0.000023515717,0.000105188104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020632261,0.000066423454,0.00008729149,0.000049308943,0.0000711243,0.0000825936,0.00033012105,0.000018343093,0.000008808422],"category_scores_gemma":[0.00013966412,0.000060926748,0.000024201812,0.00044791732,0.00003359979,0.00044996655,0.00016038092,0.00004263841,0.0000059227027],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004568437,0.000029264853,0.0003585587,0.000004507342,6.5446807e-7,0.0000017707697,0.0002827753,0.0015843782,0.00034750524,0.9948678,0.0017597147,0.0007584875],"study_design_scores_gemma":[0.0003321558,0.00007510276,0.00033997462,0.000003156551,6.452342e-7,3.639637e-7,0.00010411141,0.9912903,0.00012936172,0.002797572,0.0048412755,0.000085979846],"about_ca_topic_score_codex":0.000015319856,"about_ca_topic_score_gemma":0.000018660196,"teacher_disagreement_score":0.99207026,"about_ca_system_score_codex":0.000043093147,"about_ca_system_score_gemma":0.000064887216,"threshold_uncertainty_score":0.24845207},"labels":[],"label_agreement":null},{"id":"W3096388188","doi":"10.1145/3385959.3422703","title":"BUDI: Building Urban Designs Interactively Can Spatial-Based Collaboration be Seamless?","year":2020,"lang":"en","type":"article","venue":"Symposium on Spatial User Interaction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Visualization; Server; Human–computer interaction; Space (punctuation); Virtual reality; Quality (philosophy); Data visualization; Multimedia; World Wide Web; Artificial intelligence; Operating system","score_opus":0.045163000580332804,"score_gpt":0.32100099096311435,"score_spread":0.27583799038278156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3096388188","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012126826,0.0000027033077,0.960598,0.024315268,0.0014284173,0.00035083474,0.00007132938,0.00034173488,0.0007648759],"genre_scores_gemma":[0.98649997,0.000006514484,0.0034819762,0.009181095,0.00046110962,0.000028926363,0.00019328164,0.000035744397,0.00011137854],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99767244,0.00025807787,0.0004915199,0.0007202628,0.0005579304,0.00029976977],"domain_scores_gemma":[0.9983456,0.00017529521,0.0003961342,0.00044271068,0.0003850209,0.00025525072],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00017166448,0.00030595026,0.00027321177,0.0002480554,0.00022486594,0.000810555,0.0006259718,0.00010836577,0.00010425041],"category_scores_gemma":[0.00019478447,0.00031552222,0.000103450264,0.000755572,0.00003210472,0.0012809249,0.00013896242,0.00030430773,0.0001029846],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019308577,0.0020086805,0.00703266,0.00031606204,0.0004604719,0.0001288826,0.020664183,0.07857535,0.69532096,0.06836211,0.092001215,0.03319857],"study_design_scores_gemma":[0.00084727525,0.00070529804,0.00031738012,0.000102456484,0.00003493591,0.0000025970583,0.00022147266,0.7193624,0.21627513,0.000045232475,0.061628677,0.00045720307],"about_ca_topic_score_codex":0.0007615966,"about_ca_topic_score_gemma":0.0005231481,"teacher_disagreement_score":0.97437316,"about_ca_system_score_codex":0.00029934285,"about_ca_system_score_gemma":0.00023470288,"threshold_uncertainty_score":0.99992967},"labels":[],"label_agreement":null},{"id":"W3096943329","doi":"10.1145/3410404.3414254","title":"Echo: Analyzing Gameplay Sessions by Reconstructing Them From Recorded Data","year":2020,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Session (web analytics); Workflow; Echo (communications protocol); Human–computer interaction; Representation (politics); Analytics; Bridge (graph theory); Video game; Multimedia; Process (computing); Game design; Data science; World Wide Web","score_opus":0.12655107132163232,"score_gpt":0.32495579159385635,"score_spread":0.19840472027222403,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3096943329","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018228855,0.00002617372,0.9876448,0.0032094978,0.00016420097,0.000040708135,0.00021057627,0.00029286294,0.0065883235],"genre_scores_gemma":[0.3552112,0.00017468075,0.6288097,0.012288973,0.0003197122,0.00000210852,0.0020385776,0.00003097362,0.0011240939],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99884176,0.000057182162,0.0002522862,0.00053283916,0.00015447178,0.00016145184],"domain_scores_gemma":[0.9986589,0.00013795002,0.00010341111,0.0008936635,0.00003610152,0.00016995672],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014453966,0.000101250516,0.00014198541,0.000024556044,0.00012437189,0.00034597694,0.0018200264,0.000037454985,0.0007608278],"category_scores_gemma":[0.00027378756,0.0000863954,0.000025308667,0.0005188743,0.000019714402,0.0009800367,0.0010447343,0.00011613055,0.00022202736],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000046805358,0.00007609224,0.024238802,0.000013640763,0.000117298616,0.000014569812,0.0011860866,0.000033909073,0.005594561,0.016744846,0.7183424,0.23363309],"study_design_scores_gemma":[0.00018920976,0.000008695652,0.000026904005,0.000019596975,0.000011699936,0.0000022505383,0.00032676093,0.9330909,0.0017377464,0.00060642365,0.06378802,0.00019175738],"about_ca_topic_score_codex":0.00007729708,"about_ca_topic_score_gemma":0.000010352172,"teacher_disagreement_score":0.933057,"about_ca_system_score_codex":0.000008768578,"about_ca_system_score_gemma":0.000051403134,"threshold_uncertainty_score":0.83305305},"labels":[],"label_agreement":null},{"id":"W3097765668","doi":"10.1007/978-3-030-63329-5_7","title":"COMET-OCEP: A Software Process for Research and Development","year":2020,"lang":"en","type":"book-chapter","venue":"Advances in intelligent systems and computing","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Comet; Computer science; Process (computing); Software; Software engineering; Identification (biology); Software development process; Software development; Systems engineering; Engineering; Programming language; Astronomy","score_opus":0.1420115449040842,"score_gpt":0.4064047274596541,"score_spread":0.2643931825555699,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3097765668","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000025671472,0.013344017,0.98058933,0.00006251633,0.00044900746,0.0006228968,0.000011614851,0.000083107436,0.0048118443],"genre_scores_gemma":[0.50858873,0.029569533,0.30689895,0.002144585,0.0041504144,0.0005077747,0.0009587172,0.0007087268,0.14647257],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979594,0.000027192084,0.00061820017,0.00069772184,0.00040008896,0.00029743265],"domain_scores_gemma":[0.99873257,0.00040095157,0.00022686731,0.00022215562,0.00028651784,0.0001309311],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006783242,0.0002450319,0.0004275149,0.00027555268,0.00024568586,0.0003219397,0.0005246373,0.00011421077,0.0000019170816],"category_scores_gemma":[0.00007805389,0.00023232421,0.000024681567,0.0001381583,0.00009141255,0.00024780456,0.00049134233,0.0002767177,0.00000883305],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009255754,0.000027358687,0.00045445285,0.0025443498,0.000040994197,0.000017681834,0.0020167201,0.0008558295,5.524333e-7,0.8243555,0.00022374224,0.16945356],"study_design_scores_gemma":[0.0002601186,0.00019736866,0.0000075793246,0.0028391676,0.000006002095,0.000025900268,0.0005438461,0.15229927,0.00004469021,0.022126913,0.8210707,0.0005784919],"about_ca_topic_score_codex":0.000003579674,"about_ca_topic_score_gemma":0.000009132486,"teacher_disagreement_score":0.8208469,"about_ca_system_score_codex":0.000064991546,"about_ca_system_score_gemma":0.000115907016,"threshold_uncertainty_score":0.9473906},"labels":[],"label_agreement":null},{"id":"W3100095370","doi":"10.1101/325290","title":"A systematic method for surveying data visualizations and a resulting genomic epidemiology visualization typology: GEViT","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Centre for Disease Control; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; University of British Columbia; Canada Research Chairs; Michael Smith Health Research BC; Fred Hutchinson Cancer Research Center","keywords":"Visualization; Computer science; Geovisualization; Information visualization; Data science; Data visualization; Visual analytics; Space (punctuation); Information retrieval; Human–computer interaction; World Wide Web; Data mining","score_opus":0.09622435877506268,"score_gpt":0.3724224916355451,"score_spread":0.2761981328604824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3100095370","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023700232,0.0011433652,0.9924574,0.000278233,0.0009524591,0.0014951315,0.00078473374,0.00051561825,0.0000030368008],"genre_scores_gemma":[0.19315822,0.0007310731,0.8026963,0.0018292847,0.00082847546,0.00044172088,0.00006945006,0.00023017278,0.000015327254],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9935305,0.001931383,0.001559376,0.0020692786,0.00025033014,0.000659125],"domain_scores_gemma":[0.99173933,0.0018985384,0.0015767185,0.0035696034,0.00094165007,0.00027418198],"candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.010138268,0.0005510498,0.001241445,0.0005427051,0.00046989514,0.0005313877,0.0025353543,0.0005670379,0.0000057905518],"category_scores_gemma":[0.011414288,0.0005734004,0.00010378801,0.00081599253,0.00015672618,0.00057370024,0.0036923485,0.00029786435,0.000022744714],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000662014,0.0006569897,0.018145453,0.068376504,0.0024886888,0.000033491993,0.00038512252,0.0010996495,0.05684131,0.8409766,0.010910021,0.000019991698],"study_design_scores_gemma":[0.00047471156,0.00005832649,0.0032549656,0.0023037323,0.00029429255,1.3975118e-7,0.000007733841,0.99058646,0.0009771177,0.00009622916,0.0011710272,0.00077525555],"about_ca_topic_score_codex":0.000057467583,"about_ca_topic_score_gemma":0.000010164883,"teacher_disagreement_score":0.9894868,"about_ca_system_score_codex":0.00016331987,"about_ca_system_score_gemma":0.00057530514,"threshold_uncertainty_score":0.99967176},"labels":[],"label_agreement":null},{"id":"W3105843598","doi":"10.3390/a13110290","title":"Similarity-Driven Edge Bundling: Data-Oriented Clutter Reduction in Graphs Layouts","year":2020,"lang":"en","type":"article","venue":"Algorithms","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Visualization; Similarity (geometry); Clutter; Graph; Enhanced Data Rates for GSM Evolution; Theoretical computer science; Graph drawing; Representation (politics); Data mining; Artificial intelligence; Image (mathematics)","score_opus":0.07093788200561514,"score_gpt":0.3178110354048003,"score_spread":0.2468731533991852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3105843598","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0024716756,0.000059023492,0.9868753,0.008984138,0.00069323083,0.00016328305,0.0000832518,0.00026239766,0.00040772048],"genre_scores_gemma":[0.7299728,0.00025709896,0.2522082,0.0134515,0.0011144788,0.00001697141,0.002521398,0.00006591063,0.0003916869],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985809,0.00006848272,0.00027784455,0.0005690965,0.00027260496,0.00023110176],"domain_scores_gemma":[0.9989745,0.000021601554,0.000077266996,0.0007170007,0.000067045476,0.00014260561],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001881668,0.00012555634,0.00016371872,0.000117443415,0.000073891075,0.00014579228,0.0011193786,0.00006228427,0.000021925704],"category_scores_gemma":[0.00008008388,0.0001267739,0.000032794065,0.0010514908,0.000033534736,0.00094463315,0.00064885407,0.00018078237,0.000095751646],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008252987,0.0026827985,0.025593758,0.00033400892,0.00044967575,0.0009569275,0.029484129,0.008067404,0.003644679,0.29155678,0.32625628,0.31089106],"study_design_scores_gemma":[0.0004049226,0.00004476861,0.00039616582,0.000013199803,0.000008367309,0.000009287545,0.00008946194,0.93738776,0.00021720916,0.00048326282,0.06076342,0.00018218237],"about_ca_topic_score_codex":0.00003600259,"about_ca_topic_score_gemma":0.000012222118,"teacher_disagreement_score":0.92932034,"about_ca_system_score_codex":0.000020536763,"about_ca_system_score_gemma":0.000054962464,"threshold_uncertainty_score":0.51696897},"labels":[],"label_agreement":null},{"id":"W3107694910","doi":"","title":"Visual Data Mining of Astronomic Data With Virtual Reality Spaces: Understanding the Underlying Structure of Large Data Sets","year":2005,"lang":"en","type":"article","venue":"NPARC","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Virtual reality; Visualization; Data mining; Data visualization; Artificial intelligence","score_opus":0.163836255851018,"score_gpt":0.38160508181693487,"score_spread":0.21776882596591687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3107694910","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01640764,0.000016900798,0.9790345,0.00080643094,0.000060895738,0.00009619444,0.003250987,0.00003174276,0.00029473074],"genre_scores_gemma":[0.95633084,0.000009933016,0.04006326,0.00011880518,0.000044183034,1.3622451e-7,0.0034058148,0.000010354582,0.000016702137],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982903,0.000110666915,0.00033713118,0.00061280513,0.00040790465,0.00024117288],"domain_scores_gemma":[0.99476236,0.00017008894,0.00031946806,0.004649218,0.00003739793,0.000061473416],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0008403492,0.00013510697,0.00021631889,0.00006858919,0.00014068423,0.00016018056,0.006021958,0.000041433916,0.000056188677],"category_scores_gemma":[0.000101613354,0.00009606394,0.000011345906,0.00034338463,0.0001324922,0.0019064234,0.004859854,0.00012210978,0.0000015368388],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019400526,0.00094532414,0.013003409,0.00038676534,0.0012277545,0.000016287893,0.0098015675,0.009484575,0.015512686,0.7230091,0.12703069,0.09938783],"study_design_scores_gemma":[0.00043788488,0.00006328331,0.00027713348,0.000063122025,0.000042674546,0.000005377812,0.0025583277,0.9937659,0.00017773267,0.0003738994,0.0021047643,0.00012992839],"about_ca_topic_score_codex":0.00001959219,"about_ca_topic_score_gemma":0.000535174,"teacher_disagreement_score":0.9842813,"about_ca_system_score_codex":0.00003927997,"about_ca_system_score_gemma":0.00022486465,"threshold_uncertainty_score":0.9993559},"labels":[],"label_agreement":null},{"id":"W3108978124","doi":"","title":"Recommendations for approaching the introduction section of manuscripts and grant applications.","year":2020,"lang":"en","type":"article","venue":"PubMed","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Section (typography); Medical education; Dental hygiene; Special section; Dental research; Key (lock); Public relations; Engineering ethics; Political science; Medicine; Psychology; Dentistry; Computer science; Engineering; Engineering physics","score_opus":0.08102256620141925,"score_gpt":0.2634145718653921,"score_spread":0.18239200566397284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3108978124","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000108180495,0.000025578998,0.9534744,0.045603145,0.000116844116,0.000492923,0.000008299696,0.00003853971,0.00013205995],"genre_scores_gemma":[0.95524645,0.000106061016,0.03659334,0.0034212114,0.0013145043,0.0028617557,0.00016659868,0.000013028056,0.0002770639],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99958813,0.000024496674,0.000118615724,0.00014363689,0.000058070782,0.00006703077],"domain_scores_gemma":[0.99969363,0.000026849038,0.000068193076,0.00013501983,0.000042329357,0.00003397773],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023294508,0.00003478114,0.000047615347,0.000027300966,0.00010986355,0.000066026856,0.00016148131,0.000012668501,8.008386e-7],"category_scores_gemma":[0.0000585936,0.00002687717,0.000016443157,0.00023252805,0.00001867444,0.00021124023,0.000051263232,0.00003471929,3.7642602e-7],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000046289288,0.00003842547,0.00012480996,0.00005252876,0.000019404659,1.7880957e-8,0.00059459615,0.00007938084,0.00007717437,0.30989814,0.032038163,0.6570727],"study_design_scores_gemma":[0.00025873815,0.000016850772,0.0038793134,0.0000013040981,0.000020290427,0.0000029852422,0.00015737051,0.12891084,0.00075411325,0.0034712248,0.8624407,0.00008623895],"about_ca_topic_score_codex":0.0000029996518,"about_ca_topic_score_gemma":0.0000011334307,"teacher_disagreement_score":0.95513827,"about_ca_system_score_codex":0.000006588602,"about_ca_system_score_gemma":0.0000049215896,"threshold_uncertainty_score":0.109601915},"labels":[],"label_agreement":null},{"id":"W3112172908","doi":"10.1109/smc42975.2020.9282852","title":"Enhancing Parallel Coordinates Visualization Using Genetic Algorithm with Smart Mutation","year":2020,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Parallel coordinates; Visualization; Intersection (aeronautics); Computer science; Metric (unit); Algorithm; Face (sociological concept); Mutation; Similarity (geometry); Genetic algorithm; Operator (biology); Data visualization; Data mining; Artificial intelligence; Machine learning; Image (mathematics)","score_opus":0.025668619400220083,"score_gpt":0.2885592408431707,"score_spread":0.2628906214429506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112172908","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018710429,0.00002053033,0.9972249,0.0003532318,0.00004180406,0.000093233895,0.0000016502725,0.00020013767,0.00019342203],"genre_scores_gemma":[0.16523667,0.000009162967,0.8321224,0.0023927512,0.000060202972,0.0000028103507,0.000043475196,0.0000152353405,0.000117298696],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991049,0.000040565028,0.00019789048,0.00028279793,0.00022475189,0.00014908284],"domain_scores_gemma":[0.99951196,0.000020515381,0.00008543166,0.00015136779,0.00012494909,0.000105756546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006708689,0.00010436879,0.0001071165,0.000058807902,0.00010198547,0.00024087893,0.0002478923,0.000028213704,0.00003869991],"category_scores_gemma":[0.000027139498,0.000089120476,0.00001925941,0.00066297286,0.000019065992,0.0005341737,0.000082649065,0.000035268473,0.00003674855],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052922536,0.00065376854,0.010821307,0.00047555802,0.00040216022,0.00045338363,0.015820988,0.2694063,0.017813852,0.44355366,0.005202413,0.2353437],"study_design_scores_gemma":[0.0002525151,0.000081401355,0.00019840291,0.000012979636,0.000010474202,0.00001238132,0.0000998008,0.9936725,0.0047410196,0.00017108393,0.00060169294,0.0001457333],"about_ca_topic_score_codex":0.00002862983,"about_ca_topic_score_gemma":0.000006102703,"teacher_disagreement_score":0.72426623,"about_ca_system_score_codex":0.000018877716,"about_ca_system_score_gemma":0.000061798666,"threshold_uncertainty_score":0.36342275},"labels":[],"label_agreement":null},{"id":"W3112777692","doi":"10.15353/acmla.n165.1903","title":"Mapbox.js: an engaging open-source web mapping tool for teaching data visualization theory","year":2020,"lang":"en","type":"article","venue":"Bulletin - Association of Canadian Map Libraries and Archives (ACMLA)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; World Wide Web; Open source; Context (archaeology); Visualization; Data science; Programming language; Software; Data mining","score_opus":0.03713109872656909,"score_gpt":0.26515416227149924,"score_spread":0.22802306354493015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112777692","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00071279967,0.0001381818,0.95020694,0.042476013,0.00015550299,0.0005051682,0.00078585214,0.00014822811,0.004871302],"genre_scores_gemma":[0.4590738,0.00058507617,0.4484424,0.061299585,0.0016278634,0.00008198684,0.010571743,0.00023957854,0.018077957],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980764,0.00044208497,0.0004097624,0.00052323024,0.00020855518,0.00033996443],"domain_scores_gemma":[0.9981026,0.0006879775,0.00036269065,0.00048030698,0.00003145525,0.0003349881],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0008204867,0.00016840588,0.00026477405,0.0003117374,0.0006875198,0.0013362694,0.0017528676,0.00006551124,0.000071853654],"category_scores_gemma":[0.00096153305,0.00018610284,0.000040395305,0.00029665686,0.00006461514,0.0012917713,0.00084203767,0.00015617191,0.000005068874],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019483168,0.000031095133,0.003025516,0.00009543133,0.00007297133,0.0000016690176,0.0077430387,0.00006990913,0.00017206876,0.89888585,0.063472256,0.026410699],"study_design_scores_gemma":[0.0004667926,0.000050745562,0.00046255454,0.00005199347,0.000016006556,5.444919e-7,0.0013648269,0.1981242,0.00005248412,0.004038968,0.7951516,0.00021931883],"about_ca_topic_score_codex":0.0004029328,"about_ca_topic_score_gemma":0.0002922226,"teacher_disagreement_score":0.8948469,"about_ca_system_score_codex":0.00002007706,"about_ca_system_score_gemma":0.0003346411,"threshold_uncertainty_score":0.9997004},"labels":[],"label_agreement":null},{"id":"W3114060458","doi":"10.1109/access.2020.3046623","title":"Designing and Evaluating Multimodal Interactions for Facilitating Visual Analysis With Dashboards","year":2020,"lang":"en","type":"article","venue":"IEEE Access","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Human–computer interaction; Visualization; Multimodal interaction; Artificial intelligence","score_opus":0.11400968387934197,"score_gpt":0.4402061388394984,"score_spread":0.3261964549601564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3114060458","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.072992295,0.000007263417,0.9263308,0.0003466086,0.00004470811,0.00012559516,0.000013837337,0.00008467589,0.0000542292],"genre_scores_gemma":[0.84101826,0.0000010829297,0.15814862,0.0007182883,0.000048057813,0.000017945442,0.000018931005,0.000006008706,0.000022821101],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907297,0.00005420249,0.00019106793,0.00033943186,0.00019577047,0.00014653595],"domain_scores_gemma":[0.99919707,0.00029934506,0.00010844293,0.00013279203,0.00016031494,0.00010205567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022354853,0.000096602234,0.00016004236,0.000120456534,0.00019332858,0.0006200002,0.00038737222,0.000017157126,0.000009323192],"category_scores_gemma":[0.00021718211,0.000083973304,0.000044734803,0.00093195966,0.000023313138,0.0012049977,0.000117277224,0.00006401853,0.000002522703],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002569486,0.00041907676,0.11048986,0.00060851296,0.003841919,0.000032029977,0.038444553,0.32174376,0.04040834,0.007845866,0.0033907408,0.47251838],"study_design_scores_gemma":[0.00031466337,0.000101947764,0.0006030964,0.000010834407,0.000121470606,8.3927097e-7,0.00026768842,0.9960339,0.0022395242,0.000048972226,0.00013643075,0.00012065551],"about_ca_topic_score_codex":0.00003073112,"about_ca_topic_score_gemma":0.000023438608,"teacher_disagreement_score":0.76818216,"about_ca_system_score_codex":0.000013553181,"about_ca_system_score_gemma":0.000041657422,"threshold_uncertainty_score":0.5978676},"labels":[],"label_agreement":null},{"id":"W3118145990","doi":"10.1145/3252370","title":"Session details: Analytics and Questionnaires","year":2015,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Session (web analytics); Computer science; Analytics; Data science; World Wide Web","score_opus":0.05353773838769994,"score_gpt":0.328329962757111,"score_spread":0.2747922243694111,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3118145990","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016066743,0.00006491357,0.99203825,0.0010058915,0.0000976474,0.000019893176,5.200635e-7,0.00012337549,0.0050428472],"genre_scores_gemma":[0.9377801,0.000045030403,0.057699863,0.0013744641,0.000041489806,8.208384e-7,0.000006584327,0.000004218155,0.0030474588],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995557,0.000022886366,0.00008628383,0.00012657019,0.00013589405,0.0000726796],"domain_scores_gemma":[0.9995698,0.000015457836,0.000023590994,0.00018689044,0.00007835223,0.00012595851],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016505986,0.00004521428,0.000052021023,0.000052807005,0.000033436063,0.00016329181,0.00017999571,0.000019803192,0.000006569882],"category_scores_gemma":[0.000103693244,0.000034544293,0.000008528463,0.00019820014,0.000019843194,0.00041240038,0.00014251923,0.00002376174,0.000038693706],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012251211,0.000048384423,0.0113097,0.000007920821,0.000008144852,0.000007709427,0.00036476846,0.0001263719,0.000032292384,0.90308946,0.05324763,0.031756394],"study_design_scores_gemma":[0.00023388375,0.000039776227,0.0017578249,0.000016150778,0.0000052364603,0.000011191551,0.00010171685,0.9531466,0.00032279774,0.012098711,0.03214395,0.00012216557],"about_ca_topic_score_codex":0.000014499635,"about_ca_topic_score_gemma":0.000012700506,"teacher_disagreement_score":0.9530202,"about_ca_system_score_codex":0.000009830801,"about_ca_system_score_gemma":0.00004357655,"threshold_uncertainty_score":0.15746267},"labels":[],"label_agreement":null},{"id":"W3118700037","doi":"10.3390/mti5010002","title":"Forming Cognitive Maps of Ontologies Using Interactive Visualizations","year":2021,"lang":"en","type":"article","venue":"Multimodal Technologies and Interaction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Ontology; Computer science; Visualization; Human–computer interaction; Process ontology; Ontology-based data integration; Upper ontology; Set (abstract data type); Cognition; Interactive visualization; Data science; Domain knowledge; Artificial intelligence","score_opus":0.04643971259994645,"score_gpt":0.3590202224822334,"score_spread":0.31258050988228697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3118700037","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08993613,0.0001656947,0.9082475,0.0002700837,0.00022589254,0.00009040193,0.000030448517,0.00037273768,0.0006611198],"genre_scores_gemma":[0.9743086,0.00022866642,0.025311215,0.000048397436,0.0000074312916,0.0000048187107,0.00004128608,0.0000052715054,0.0000443104],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992365,0.000032875603,0.0002403393,0.00025942945,0.00010120427,0.00012964265],"domain_scores_gemma":[0.9991682,0.00014290193,0.00017895683,0.00019245442,0.0003004142,0.000017033064],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006283343,0.00010475437,0.00016326453,0.00018701763,0.00010847325,0.00010878844,0.00018411463,0.000089355155,0.000009197152],"category_scores_gemma":[0.00070695404,0.00009841048,0.000042619013,0.00040645731,0.00008659477,0.0010645532,0.00042181194,0.00012911565,0.0000022967245],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051191455,0.00055232976,0.0065009594,0.00014006605,0.00023391798,0.00004426211,0.0025696189,0.00045780404,0.04105471,0.17366964,0.00040821786,0.77431726],"study_design_scores_gemma":[0.0004382499,0.00011397941,0.0005600309,0.00028102467,0.000029720124,0.0000864274,0.027266325,0.7213133,0.24314997,0.0045999805,0.0019224256,0.00023854419],"about_ca_topic_score_codex":0.00004964786,"about_ca_topic_score_gemma":0.000024386649,"teacher_disagreement_score":0.8843725,"about_ca_system_score_codex":0.00004072214,"about_ca_system_score_gemma":0.00003337151,"threshold_uncertainty_score":0.4013063},"labels":[],"label_agreement":null},{"id":"W3119225923","doi":"10.3808/jeil.202000047","title":"Visual Analytics in Environmental Decision-Making: A Comparison of Overlay Charts versus Simulation Decomposition","year":2020,"lang":"en","type":"article","venue":"Journal of Environmental Informatics Letters","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Strategic Research Council; Liikesivistysrahasto; Foundation for Economic Education","keywords":"Overlay; Decomposition; Analytics; Visual analytics; Computer science; Data science; Data mining; Visualization; Chemistry","score_opus":0.02374950670658754,"score_gpt":0.328404769367264,"score_spread":0.30465526266067644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3119225923","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.56186616,0.00002220935,0.43763664,0.0002385592,0.00012609035,0.0000648412,0.000016460228,0.0000053611525,0.000023702003],"genre_scores_gemma":[0.9812336,0.000029330942,0.017336404,0.0013299709,0.00004338491,3.0158617e-7,0.000018817473,0.000007730647,4.627072e-7],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977195,0.00004219247,0.0012882865,0.000092971786,0.00069279363,0.00016423098],"domain_scores_gemma":[0.9984636,0.00022468957,0.0010304775,0.00015223853,0.00000712292,0.000121881596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020940311,0.00015136259,0.00032158458,0.00023282085,0.000044737048,0.00007588337,0.0004422722,0.000053353575,0.000057345904],"category_scores_gemma":[0.00004720302,0.00014867401,0.00012255546,0.00020787619,0.000065054315,0.0013320632,0.00018340762,0.00019865569,0.00002351512],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003432353,0.0006932984,0.019682633,0.000047613215,0.00011286679,0.000029188384,0.0089887455,0.9348606,0.012708074,0.00017040169,0.0008867894,0.021476585],"study_design_scores_gemma":[0.0013522237,0.00040014365,0.007922259,0.000065435954,0.000027584661,0.0000071829954,0.0007838726,0.98760897,0.0010313727,0.000016073687,0.0006299122,0.00015496423],"about_ca_topic_score_codex":2.5738436e-7,"about_ca_topic_score_gemma":2.5961805e-7,"teacher_disagreement_score":0.42030025,"about_ca_system_score_codex":0.0001884485,"about_ca_system_score_gemma":0.000015757374,"threshold_uncertainty_score":0.60627496},"labels":[],"label_agreement":null},{"id":"W3123199427","doi":"","title":"Une nouvelle approche pour l'exploration de données spatio-temporelles","year":2018,"lang":"fr","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Visualization; Data visualization; Human–computer interaction; Data exploration; Robot; Artificial intelligence","score_opus":0.03525803483202017,"score_gpt":0.2618103870784014,"score_spread":0.2265523522463812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123199427","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0024266704,0.00065849413,0.8615164,0.07744445,0.0003978037,0.0002334926,0.00012576004,0.00024011754,0.056956805],"genre_scores_gemma":[0.27730864,0.0020125485,0.44269574,0.0016617111,0.00039586148,0.000060839408,0.0019593304,0.00010587833,0.27379945],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9937116,0.0037076145,0.0006474969,0.0008124466,0.00054176396,0.00057906285],"domain_scores_gemma":[0.9928647,0.0010549926,0.0005192625,0.0018221476,0.0034039535,0.00033489996],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0043550287,0.00034245048,0.0003005872,0.00021144914,0.0008293252,0.0011404958,0.0016929281,0.00024015544,0.0012663685],"category_scores_gemma":[0.0021252623,0.00038402993,0.00015277725,0.0016374964,0.0006716065,0.0012115922,0.0007462723,0.0002871483,0.0009608772],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008091177,0.0009654046,0.000715687,0.00011916135,0.00006293053,0.00000768039,0.03833952,0.000060732935,0.0012958782,0.7506348,0.12281112,0.08497902],"study_design_scores_gemma":[0.0004988524,0.000001953765,0.00039984353,0.0009088583,0.000036767153,0.000019585976,0.00074340496,0.45136273,0.02949974,0.010753246,0.5053496,0.00042546348],"about_ca_topic_score_codex":0.002126718,"about_ca_topic_score_gemma":0.005421046,"teacher_disagreement_score":0.7398815,"about_ca_system_score_codex":0.00014556487,"about_ca_system_score_gemma":0.00076988025,"threshold_uncertainty_score":0.9998964},"labels":[],"label_agreement":null},{"id":"W3124018482","doi":"10.1109/mcg.2020.3025425","title":"Using Artificial Intelligence to Visualize the Impacts of Climate Change","year":2021,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":90,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ubisoft (Canada); Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Climate change; Visualization; Computer science; Process (computing); Scale (ratio); Data science; Storm; Extreme weather; Artificial intelligence; Meteorology; Geography","score_opus":0.11222185399916906,"score_gpt":0.3776904701303416,"score_spread":0.26546861613117256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124018482","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0033583485,0.00009202305,0.99520314,0.00097302056,0.000101569065,0.00018073368,0.000026028352,0.00003221457,0.000032944343],"genre_scores_gemma":[0.92641574,0.0010926578,0.06762949,0.004365574,0.00040414245,0.00005783495,0.000018387078,0.0000138230125,0.000002327727],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99917334,0.000036508278,0.00023859864,0.00025261403,0.00014388826,0.00015502205],"domain_scores_gemma":[0.99910736,0.000068168585,0.00008390338,0.00046460127,0.00018225248,0.000093700786],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017552747,0.00008597655,0.000111806294,0.00009006533,0.00020069217,0.00019230461,0.00039375332,0.000029693923,0.000002256611],"category_scores_gemma":[0.0000046848004,0.00007061363,0.00004362848,0.0010216438,0.00005939003,0.00013756778,0.0002575575,0.000059488462,0.0000064378014],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.9321682e-7,0.000053422187,0.000086510336,0.000013714113,0.000006872061,7.562454e-7,0.00018365115,0.00007547129,0.0002448371,0.9544795,0.000031820353,0.04482304],"study_design_scores_gemma":[0.000033421602,0.00003987983,0.00066601177,0.000047123413,0.000020857913,0.000021604774,0.00005801361,0.924538,0.005547881,0.060549796,0.008272374,0.0002050157],"about_ca_topic_score_codex":0.000015325993,"about_ca_topic_score_gemma":0.000019253644,"teacher_disagreement_score":0.9275736,"about_ca_system_score_codex":0.0000050284907,"about_ca_system_score_gemma":0.000030322377,"threshold_uncertainty_score":0.287954},"labels":[],"label_agreement":null},{"id":"W3125717632","doi":"10.2139/ssrn.389301","title":"Learning in Cobweb Experiments","year":2003,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bank of Canada; Government of Canada","funders":"","keywords":"Business; Economics","score_opus":0.01416271036516763,"score_gpt":0.296141904699024,"score_spread":0.2819791943338564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125717632","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03364794,0.0010727126,0.95804334,0.00033125037,0.00021545043,0.000047996902,1.2948117e-7,0.00006135468,0.006579838],"genre_scores_gemma":[0.99557805,0.0008398828,0.0008509921,0.00016411392,0.000023560748,9.070101e-7,9.779242e-7,0.0000063703214,0.002535166],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983831,0.00012501796,0.00017159444,0.0001334832,0.00017947023,0.0010073344],"domain_scores_gemma":[0.99971634,0.000014394195,0.00007007101,0.000118777265,0.000028775088,0.000051656556],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010784392,0.00007048181,0.00008152255,0.00012376401,0.000101734906,0.00012347227,0.00036121678,0.00002638107,0.000020193134],"category_scores_gemma":[0.00008407118,0.000066208515,0.00003137125,0.00033221956,0.000010182853,0.0003597856,0.00003361973,0.0007447616,0.000045891637],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.742179e-7,0.00004236874,0.0031151182,6.041924e-7,0.000010689405,0.0000046098953,0.00021190914,0.00019070569,0.00014438131,0.9900325,0.000063006,0.00618312],"study_design_scores_gemma":[0.0049673943,0.0011671105,0.0011662932,0.00008306648,0.000017009226,0.0016103034,0.007694598,0.08455306,0.004456087,0.74155754,0.15159261,0.0011349374],"about_ca_topic_score_codex":0.0000050630656,"about_ca_topic_score_gemma":0.00003842685,"teacher_disagreement_score":0.9619301,"about_ca_system_score_codex":0.00029500833,"about_ca_system_score_gemma":0.0008984513,"threshold_uncertainty_score":0.323566},"labels":[],"label_agreement":null},{"id":"W312871047","doi":"","title":"Geovisualization of Retail Structural Change in Canada","year":2006,"lang":"en","type":"article","venue":"Canadian Journal of Regional Science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Geovisualization; Geospatial analysis; Cartography; Geography; Decision support system; Data science; Computer science; Geographic information system; Visualization; Data mining; Information visualization","score_opus":0.03401211362639474,"score_gpt":0.26994480958259537,"score_spread":0.23593269595620064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W312871047","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97258097,0.0005944843,0.020562341,0.0044079805,0.0008907193,0.0001141957,0.000021399303,0.000005168762,0.00082271936],"genre_scores_gemma":[0.99844414,0.0000063192183,0.0010404321,0.0004208943,0.00005329975,2.1757715e-7,0.0000023695277,0.0000020021366,0.000030309597],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99880725,0.000023390776,0.00031404893,0.00011762318,0.00050399837,0.00023366987],"domain_scores_gemma":[0.9989679,0.000019991598,0.0002566296,0.00013735866,0.0003562956,0.00026181227],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003603384,0.00005936515,0.00011389606,0.00042864901,0.00008649604,0.00006781115,0.00093053665,0.000015638547,0.000023455426],"category_scores_gemma":[0.0000652831,0.000053233533,0.00002278912,0.0014164221,0.0001761576,0.000882673,0.00002337604,0.00006315762,5.033069e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000032246674,0.000011118638,0.4531859,0.000018823617,0.000004831071,0.00021997534,0.0006781243,0.0029605625,0.0004349812,0.5262308,0.0052181683,0.011033531],"study_design_scores_gemma":[0.0004098983,0.00006308985,0.8416654,0.0001309128,0.0000047269928,0.0002423255,0.00015914893,0.13646436,0.00075838773,0.003975171,0.015874662,0.00025193757],"about_ca_topic_score_codex":0.9370161,"about_ca_topic_score_gemma":0.9900582,"teacher_disagreement_score":0.5222556,"about_ca_system_score_codex":0.00052331854,"about_ca_system_score_gemma":0.01079019,"threshold_uncertainty_score":0.99481773},"labels":[],"label_agreement":null},{"id":"W3128783651","doi":"10.1109/vis47514.2020.00040","title":"Gaze-Driven Links for Magazine Style Narrative Visualizations","year":2020,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Narrative; Gaze; Human–computer interaction; Modalities; Visualization; Reading (process); Style (visual arts); Eye tracking; Comprehension; Information visualization; Reading comprehension; Multimedia; World Wide Web; Artificial intelligence; Linguistics","score_opus":0.04445791319056748,"score_gpt":0.33154300156632455,"score_spread":0.2870850883757571,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3128783651","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006411387,0.0000088635015,0.98573077,0.009372114,0.00007606403,0.00017033453,0.000028316972,0.00025412784,0.0042952895],"genre_scores_gemma":[0.5094951,0.000057987527,0.4208553,0.055620786,0.0005563512,0.000072320065,0.0007532366,0.000054198772,0.012534734],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992464,0.000025111276,0.00018354875,0.0002679897,0.00013393501,0.00014297933],"domain_scores_gemma":[0.9994345,0.000049231574,0.000055943132,0.00020120552,0.000120808974,0.00013834887],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004579886,0.00008956668,0.00011357351,0.000042651725,0.00012365081,0.00017504557,0.00047223354,0.000054432086,0.00013133102],"category_scores_gemma":[0.000104170125,0.00008015156,0.000049198512,0.00049621786,0.000021373431,0.00039366225,0.0001474261,0.000062744824,0.00013596211],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003705617,0.0000799239,0.00014640599,0.00002577091,0.000030056413,0.0000020069326,0.006465656,0.0007521588,0.0010687176,0.72711664,0.26264513,0.0016637935],"study_design_scores_gemma":[0.00028966618,0.00009478915,0.000031493397,0.0000045004563,0.000005161318,5.6026323e-7,0.0001966437,0.84291327,0.00065146445,0.00036325556,0.15533447,0.000114743365],"about_ca_topic_score_codex":8.350522e-7,"about_ca_topic_score_gemma":0.0000064760457,"teacher_disagreement_score":0.8421611,"about_ca_system_score_codex":0.0000072011367,"about_ca_system_score_gemma":0.000052306154,"threshold_uncertainty_score":0.3268486},"labels":[],"label_agreement":null},{"id":"W3132074301","doi":"10.5220/0010195201470154","title":"SIMDGiraffe: Visualizing SIMD Functions","year":2021,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Computer science; SIMD; Computer graphics (images); Parallel computing","score_opus":0.029746285306288405,"score_gpt":0.3148482718368173,"score_spread":0.2851019865305289,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3132074301","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00024690913,0.00004018902,0.94029284,0.00095987454,0.0002630325,0.000017525948,0.0000023599657,0.00024915524,0.05792814],"genre_scores_gemma":[0.7661398,0.00008346627,0.07769486,0.017615061,0.0002961919,0.0000075890825,0.00017906017,0.00002704752,0.13795689],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99931365,0.000033746735,0.00012581664,0.00022857617,0.00016185116,0.00013635332],"domain_scores_gemma":[0.9993504,0.00004026471,0.000024271547,0.00039649374,0.00011426566,0.000074247255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000086293185,0.000061618346,0.00007018958,0.00004802051,0.00011086439,0.00027059735,0.00026316306,0.000024611922,0.00035110698],"category_scores_gemma":[0.00007241185,0.00005786608,0.000041155352,0.00063856976,0.00001217041,0.0004023467,0.00022322267,0.000043667114,0.00052638183],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.9206345e-7,0.00011088009,0.00037646887,0.000007712654,0.000018691246,0.000022120756,0.00012768667,0.00016166874,0.0012564891,0.86920416,0.11356745,0.01514635],"study_design_scores_gemma":[0.00020772121,0.00002297371,0.00024726492,0.000009164641,0.000007686624,0.000022268874,0.00020621195,0.33540365,0.0055402503,0.0014186923,0.6567127,0.00020143247],"about_ca_topic_score_codex":0.000004559186,"about_ca_topic_score_gemma":0.000016511172,"teacher_disagreement_score":0.8677855,"about_ca_system_score_codex":0.00001232107,"about_ca_system_score_gemma":0.00007594139,"threshold_uncertainty_score":0.6765749},"labels":[],"label_agreement":null},{"id":"W3133353820","doi":"10.3390/informatics8010012","title":"Visual Analytics for Electronic Health Records: A Review","year":2021,"lang":"en","type":"review","venue":"Informatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Visual analytics; Analytics; Computer science; Data science; Cultural analytics; Interactive visual analysis; Software analytics; Resource (disambiguation); Visualization; Health care; Semantic analytics; World Wide Web; Artificial intelligence; Software","score_opus":0.07350255607996942,"score_gpt":0.43282109152423814,"score_spread":0.3593185354442687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3133353820","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[4.3714501e-10,0.57353145,0.42524967,0.0001191825,0.000161795,0.0005914401,0.000057590518,0.00007384523,0.00021505015],"genre_scores_gemma":[5.729105e-9,0.97309273,0.019147549,0.0053244974,0.000092526934,0.00007506471,0.0016306002,0.0000291305,0.00060787227],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9964494,0.00012771708,0.0021139893,0.0002526521,0.00041157717,0.0006446529],"domain_scores_gemma":[0.996811,0.00022688738,0.0014923109,0.00099998,0.00027232818,0.00019753467],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0012394375,0.00041932103,0.0022072427,0.00025364573,0.00013938939,0.00036820336,0.0014065391,0.0001603605,0.000024758532],"category_scores_gemma":[0.0003529759,0.00035580326,0.00066781236,0.0015040125,0.000022452228,0.00055020873,0.00037885937,0.00035244453,0.00013175806],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.0759575e-8,0.00002635567,2.6103507e-8,0.07675257,0.00008349926,5.8627467e-7,0.0000432648,0.0000013655927,7.90403e-11,0.026066083,0.073817335,0.82320887],"study_design_scores_gemma":[0.00007938175,0.00009924612,4.7997584e-9,0.04301562,0.00023323421,0.000041339914,0.000013006869,0.02888686,2.0768269e-8,0.00008489713,0.92720944,0.0003369224],"about_ca_topic_score_codex":0.0000020197365,"about_ca_topic_score_gemma":0.0000054757384,"teacher_disagreement_score":0.8533921,"about_ca_system_score_codex":0.0003333321,"about_ca_system_score_gemma":0.0036401309,"threshold_uncertainty_score":0.9998894},"labels":[],"label_agreement":null},{"id":"W3133718336","doi":"10.22148/001c.21374","title":"Images of the arXiv: Reconfiguring large scientific image datasets","year":2021,"lang":"en","type":"article","venue":"Journal of Cultural Analytics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Metadata; Data science; Set (abstract data type); Representation (politics); Point (geometry); Range (aeronautics); Information retrieval; Scientific literature; World Wide Web","score_opus":0.03356266331921172,"score_gpt":0.30702755598187076,"score_spread":0.27346489266265905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3133718336","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24447094,0.0035221,0.7189158,0.019631064,0.0067996653,0.00024477096,0.0015121697,0.00008245497,0.004821013],"genre_scores_gemma":[0.9797845,0.00021610371,0.015552901,0.000560828,0.00020761722,1.8472569e-7,0.00007253112,0.0000092075825,0.003596146],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99856144,0.00008671716,0.0005453725,0.00015605937,0.0004765443,0.00017385701],"domain_scores_gemma":[0.9978196,0.000041800093,0.0005880053,0.0005028255,0.0009596376,0.000088122804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006087896,0.00009609632,0.00021768227,0.000075884665,0.00017550802,0.0005388761,0.0010725018,0.000029704326,0.00006437677],"category_scores_gemma":[0.00043738078,0.000055890654,0.00020438104,0.0008827537,0.00010570852,0.0010730452,0.00033124053,0.00017623327,0.000010177845],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017606653,0.0011085906,0.005141062,0.00031482117,0.0006325783,0.00052524055,0.0026436707,0.0015080909,0.16795164,0.08605418,0.7267988,0.007303729],"study_design_scores_gemma":[0.0018006876,0.00010845954,0.006403073,0.0006405114,0.00035944488,0.0010273075,0.002267494,0.1157267,0.5734975,0.0045009814,0.29304987,0.0006179816],"about_ca_topic_score_codex":0.0000011810553,"about_ca_topic_score_gemma":0.0000063909265,"teacher_disagreement_score":0.73531353,"about_ca_system_score_codex":0.00002706541,"about_ca_system_score_gemma":0.00018024468,"threshold_uncertainty_score":0.51963943},"labels":[],"label_agreement":null},{"id":"W3134596229","doi":"10.1145/3406522.3446041","title":"Visualizing Searcher Gaze Patterns","year":2021,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; CLARITY; Eye tracking; Gaze; Visualization; Information retrieval; Sample (material); Tracking (education); Information visualization; Tag cloud; Data visualization; Human–computer interaction; Artificial intelligence","score_opus":0.051855873923640106,"score_gpt":0.3498405323967137,"score_spread":0.2979846584730736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3134596229","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014943276,0.000022758903,0.9813276,0.0009969648,0.000092436196,0.000013845044,0.000002024287,0.000121666795,0.0159284],"genre_scores_gemma":[0.87935424,0.00012663315,0.06067274,0.012763098,0.00014828642,0.0000033847093,0.00007169165,0.0000187135,0.0468412],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999361,0.000042346473,0.00009328112,0.00018959245,0.00017817548,0.00013561224],"domain_scores_gemma":[0.9994851,0.00002391543,0.000014853204,0.00032391533,0.00008411001,0.00006812473],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011045585,0.000047472233,0.00005596455,0.000032185773,0.000042947286,0.00025003662,0.00029674434,0.000018597602,0.0006154076],"category_scores_gemma":[0.000035601144,0.000043013366,0.00002784044,0.0002976402,0.000006902442,0.00027399915,0.0002784715,0.000041702726,0.00024194116],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.394743e-7,0.00009502528,0.0068361736,0.000018245491,0.000016657908,0.000087152526,0.00034270383,0.000016083568,0.0011914434,0.9548968,0.013827282,0.022672163],"study_design_scores_gemma":[0.00057747593,0.0000380529,0.007423101,0.00006023405,0.000008275883,0.000055987734,0.0005300584,0.6153712,0.057029407,0.00374403,0.31463212,0.00053003384],"about_ca_topic_score_codex":0.000009287448,"about_ca_topic_score_gemma":0.0000135308455,"teacher_disagreement_score":0.9511528,"about_ca_system_score_codex":0.000010044109,"about_ca_system_score_gemma":0.00005473449,"threshold_uncertainty_score":0.6738282},"labels":[],"label_agreement":null},{"id":"W3135406022","doi":"10.1111/itor.12952","title":"Multiple criteria analysis of the popularity and growth of research and practice of visual analytics, and a forecast of the future trajectory","year":2021,"lang":"en","type":"article","venue":"International Transactions in Operational Research","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Popularity; Data science; Multidisciplinary approach; Computer science; Citation impact; Citation; Field (mathematics); Bibliometrics; Salience (neuroscience); Visualization; Analytics; Sensemaking; Knowledge management; Social science; Data mining; Political science; World Wide Web; Sociology; Artificial intelligence","score_opus":0.10707882986677902,"score_gpt":0.46264859685971654,"score_spread":0.3555697669929375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3135406022","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8543402,0.00067835185,0.12555951,0.016651997,0.00038094353,0.0005017121,0.0007855002,0.000007085498,0.0010946874],"genre_scores_gemma":[0.9962019,0.0003360447,0.0031940246,0.000031349566,0.000019167648,0.0000056631634,0.000016203423,0.0000034573277,0.00019221289],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974029,0.00068260526,0.00040929075,0.00023609369,0.0011593094,0.00010981849],"domain_scores_gemma":[0.99542016,0.0014183712,0.0000919334,0.00024227865,0.0027906336,0.000036641388],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022580235,0.00006163961,0.00017396235,0.00059013837,0.00014134482,0.00007280935,0.00043214724,0.000056950023,0.000050053324],"category_scores_gemma":[0.0014989874,0.000045510755,0.00006061133,0.0023557309,0.0005812017,0.00040080977,0.00017013687,0.00028275952,6.954828e-8],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036680832,0.0032481302,0.33227056,0.00044608978,0.002075729,0.000009142283,0.0075498275,0.0047621555,0.04023319,0.6033801,0.00022710576,0.0054311813],"study_design_scores_gemma":[0.00076631195,0.00011936199,0.37758258,0.0001296738,0.000084696694,0.000027260912,0.002407295,0.5958134,0.02003087,0.0024493295,0.0004910644,0.00009817745],"about_ca_topic_score_codex":0.00044762783,"about_ca_topic_score_gemma":0.0012407602,"teacher_disagreement_score":0.60093075,"about_ca_system_score_codex":0.000039666626,"about_ca_system_score_gemma":0.0003005672,"threshold_uncertainty_score":0.21414618},"labels":[],"label_agreement":null},{"id":"W3136024525","doi":"10.1201/9781003129660-5","title":"Twitter's Big Data Analysis Using RStudio","year":2021,"lang":"en","type":"book-chapter","venue":"Big Data Analytics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Big data; Computer science; Data science; Data mining","score_opus":0.3737511867560969,"score_gpt":0.366638216157477,"score_spread":0.007112970598619928,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3136024525","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000019887398,0.0010331721,0.9647673,0.00033494315,0.001413157,0.0001344675,0.0083129415,0.00015356601,0.02384848],"genre_scores_gemma":[0.0015090215,0.008211606,0.085407786,0.00509631,0.006606058,0.0000021219132,0.25614768,0.000315912,0.6367035],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99410516,0.00007804331,0.0011420257,0.0027530652,0.0013672365,0.00055448036],"domain_scores_gemma":[0.9798038,0.00014685844,0.0008060256,0.018477302,0.00042667417,0.0003393456],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.00094458845,0.0007166579,0.0013077026,0.0012153159,0.00027181313,0.0014112982,0.012462746,0.00039478365,0.00016348847],"category_scores_gemma":[0.0002668509,0.00073024735,0.00029323236,0.0016979071,0.00016931289,0.00091852486,0.018252764,0.0005207842,0.00018506807],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011721591,0.000485244,0.000872407,0.00044554198,0.028357849,0.0023168959,0.0002626425,0.002083619,0.000031779786,0.2905815,0.5498111,0.12473969],"study_design_scores_gemma":[0.00014231143,0.000010395367,0.000014584941,0.000092687245,0.0037680604,0.000016161968,0.000015946913,0.47742048,0.0000025679178,0.0004881899,0.5174093,0.00061926636],"about_ca_topic_score_codex":0.00009456738,"about_ca_topic_score_gemma":0.00047700715,"teacher_disagreement_score":0.8793595,"about_ca_system_score_codex":0.00013397707,"about_ca_system_score_gemma":0.00087282795,"threshold_uncertainty_score":0.9996253},"labels":[],"label_agreement":null},{"id":"W3138656273","doi":"10.1523/eneuro.0085-21.2021","title":"The Planning Horizon for Movement Sequences","year":2021,"lang":"en","type":"article","venue":"eNeuro","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":57,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Government of Canada; James S. McDonnell Foundation","keywords":"Horizon; Movement (music); Geology; Computer science; Geography; Mathematics; Geometry; Art; Aesthetics","score_opus":0.040357867461527204,"score_gpt":0.32455417464699843,"score_spread":0.28419630718547123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3138656273","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002056871,0.00019045114,0.99095297,0.0040185726,0.00058798696,0.000049936578,0.000005143983,0.00006023843,0.0020778102],"genre_scores_gemma":[0.8494132,0.00063251285,0.07780017,0.036611523,0.0011713884,0.000098403696,0.00012916108,0.000048657417,0.034094993],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99960023,0.000020314095,0.00006997805,0.00012054712,0.000098259174,0.000090661815],"domain_scores_gemma":[0.9996072,0.00010884437,0.000024104103,0.00019888558,0.00003956783,0.000021402107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009748045,0.000032683914,0.000031022642,0.000008964766,0.00015113692,0.00021464506,0.00028452178,0.0000073267215,0.000002745028],"category_scores_gemma":[0.00008710266,0.000023190085,0.000019857851,0.000117126634,0.00000963898,0.00009249528,0.00008920944,0.000020894608,0.0000057238017],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000014256067,0.000026009699,0.00034189312,0.000008678339,0.000012895765,0.000030187817,0.00024348863,0.00082348345,0.0028883112,0.92131674,0.036486406,0.037820473],"study_design_scores_gemma":[0.00014445615,0.00007953581,0.00027501484,0.000010623255,0.0000034318716,0.0000034279333,0.00009392679,0.13342501,0.030540928,0.013887776,0.82143766,0.000098214296],"about_ca_topic_score_codex":8.03081e-7,"about_ca_topic_score_gemma":0.0000018791953,"teacher_disagreement_score":0.9131528,"about_ca_system_score_codex":0.000004722571,"about_ca_system_score_gemma":0.000035912617,"threshold_uncertainty_score":0.20698273},"labels":[],"label_agreement":null},{"id":"W3138778257","doi":"10.1145/3258195","title":"Session details: Adaptation","year":2010,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Session (web analytics); Computer science; Adaptation (eye); Psychology; World Wide Web; Neuroscience","score_opus":0.032333807425537285,"score_gpt":0.309951722515684,"score_spread":0.2776179150901467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3138778257","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0025773817,0.0000012431284,0.98475236,0.0004369319,0.00023137088,0.000017229804,3.0581543e-7,0.00012175796,0.011861423],"genre_scores_gemma":[0.8484809,0.0000026921498,0.1481199,0.00081542437,0.00003594923,9.141631e-7,0.00000772716,0.000002282725,0.0025342703],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996802,0.000008266819,0.00006344953,0.00009582489,0.00009514916,0.00005707289],"domain_scores_gemma":[0.9996864,0.000012790041,0.000019683248,0.00020492004,0.0000382855,0.000037920676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008841258,0.000029333023,0.000026661623,0.00003351196,0.00004078893,0.00010556415,0.00024362489,0.000019544615,0.00013739937],"category_scores_gemma":[0.000030487896,0.000022744507,0.00001119305,0.0001506472,0.0000073458423,0.00041555255,0.00005801814,0.000042862983,0.00020679015],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.9511702e-7,0.000021397023,0.00025614753,0.000001370829,0.0000011858646,8.8136625e-7,0.00012408063,0.000022836073,0.003533693,0.9223046,0.0042411312,0.0694925],"study_design_scores_gemma":[0.00007313398,0.000007521863,0.000607949,0.0000015050854,8.829162e-7,0.000002261244,0.0000285474,0.93948144,0.002921655,0.0026699344,0.054148015,0.0000571491],"about_ca_topic_score_codex":0.0000061887363,"about_ca_topic_score_gemma":0.000037311846,"teacher_disagreement_score":0.9394586,"about_ca_system_score_codex":0.0000017840688,"about_ca_system_score_gemma":0.000020427051,"threshold_uncertainty_score":0.2657938},"labels":[],"label_agreement":null},{"id":"W3139661953","doi":"10.1109/infvis.2004.59","title":"Rethinking Visualization: A High-Level Taxonomy","year":2005,"lang":"en","type":"article","venue":"IEEE Symposium on Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":135,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Taxonomy (biology); Computer science; Visualization; Data visualization; Data science; Information retrieval; Artificial intelligence; Biology; Ecology","score_opus":0.039182389349250814,"score_gpt":0.28813754878078035,"score_spread":0.24895515943152954,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3139661953","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009911634,0.0000065681684,0.98710895,0.001278722,0.00096489344,0.0005082225,0.000040074105,0.00077562773,0.008325773],"genre_scores_gemma":[0.9524053,0.00014350307,0.025546504,0.017804256,0.0007821811,0.0001855712,0.0017431689,0.000053373078,0.0013361986],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970818,0.00014769858,0.0010487325,0.00038297565,0.00094450184,0.00039425414],"domain_scores_gemma":[0.99775493,0.00008019312,0.0006307753,0.0007455028,0.00060234976,0.00018625367],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006198592,0.0003363907,0.00026587397,0.00076721905,0.0004454296,0.0010783924,0.000861862,0.00020168809,0.00012003127],"category_scores_gemma":[0.00011024281,0.00034766283,0.000092601134,0.0015137916,0.00004867371,0.008275699,0.0001231335,0.00014808217,0.0013836647],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013138344,0.00013186198,0.00009574517,0.0000473972,0.000025954087,7.6643636e-7,0.0026615935,0.022295633,0.00023880796,0.9444325,0.020426985,0.009629621],"study_design_scores_gemma":[0.0010097278,0.0001426369,0.00015413995,0.00008230516,0.000017054568,0.000010882448,0.00006002922,0.70643634,0.0111302985,0.001084733,0.27933186,0.00054001075],"about_ca_topic_score_codex":0.000015921632,"about_ca_topic_score_gemma":0.000008299443,"teacher_disagreement_score":0.96156245,"about_ca_system_score_codex":0.0002515945,"about_ca_system_score_gemma":0.00016450362,"threshold_uncertainty_score":0.9999586},"labels":[],"label_agreement":null},{"id":"W3141264084","doi":"10.31219/osf.io/yfbwm","title":"multiverse: Multiplexing Alternative Data Analyses in R Notebooks","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Debugging; Flexibility (engineering); Workflow; Syntax; Pruning; Data science; Artificial intelligence; Programming language; Database","score_opus":0.3374359525430985,"score_gpt":0.46250238955830403,"score_spread":0.12506643701520553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3141264084","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008804122,0.0000982145,0.99434054,0.0001727651,0.0004464076,0.00013921323,0.00015549068,0.00012257593,0.0036443598],"genre_scores_gemma":[0.6125816,0.0002312924,0.3807733,0.0011367219,0.00015120493,0.0000101029655,0.003512588,0.000025770774,0.0015773827],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99770904,0.00015480825,0.0003945274,0.001143092,0.0003735694,0.00022496853],"domain_scores_gemma":[0.99697316,0.00012169162,0.00019338966,0.0024768193,0.00015182179,0.000083145205],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0002950778,0.00023299402,0.00034911156,0.00031667753,0.00004526319,0.0007027791,0.0038191534,0.00012232532,0.00008142363],"category_scores_gemma":[0.0002838731,0.0002249311,0.00007010813,0.00033844868,0.000040754592,0.0006882428,0.013305299,0.00039257083,0.000026475596],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003969008,0.0036008353,0.012935503,0.0012546515,0.002779268,0.004636639,0.04133033,0.50109315,0.005650099,0.19456375,0.019618824,0.21249723],"study_design_scores_gemma":[0.00028650233,0.0000035568867,0.00037548871,0.0001339629,0.000010756261,0.0000013964033,0.00036217546,0.996069,0.0010409249,0.00028726322,0.0011564881,0.00027244975],"about_ca_topic_score_codex":0.0017003978,"about_ca_topic_score_gemma":0.0010861711,"teacher_disagreement_score":0.6135673,"about_ca_system_score_codex":0.000073968265,"about_ca_system_score_gemma":0.00024607184,"threshold_uncertainty_score":0.9946749},"labels":[],"label_agreement":null},{"id":"W3142243502","doi":"10.1109/tvcg.2014.2318411","title":"Guest Editors' Introduction: Special Section on the IEEE Pacific Visualization Symposium","year":2014,"lang":"en","type":"editorial","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Special section; Visualization; Computer science; Section (typography); Focus (optics); Data visualization; Asia pacific; Library science; Data science; History; Engineering; Artificial intelligence; Engineering physics","score_opus":0.010490412630535371,"score_gpt":0.2591751765636441,"score_spread":0.2486847639331087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3142243502","genre_codex":"methods","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"editorial","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000004188067,0.0000057543657,0.51609117,0.00035932046,0.48273608,0.00029640316,0.00006796885,0.0003250814,0.00011403089],"genre_scores_gemma":[0.0012129975,0.0011058232,0.000097569704,0.00097424694,0.9947197,0.00007536952,0.0006472684,0.00012054287,0.0010465235],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9941845,0.0008153863,0.0010145986,0.0015695583,0.0018913319,0.0005246399],"domain_scores_gemma":[0.9959202,0.0008241729,0.0006457858,0.001365693,0.0009781893,0.00026599108],"candidate_categories":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0009795567,0.00086436205,0.0006525158,0.0011559342,0.0013916123,0.001678859,0.0010900854,0.0010987604,0.000067858455],"category_scores_gemma":[0.000051483952,0.0007517253,0.00030605195,0.0021685716,0.00027038384,0.0007713561,0.000021934624,0.0011913594,0.00010238457],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029890509,0.0003248068,8.408269e-7,0.00007973347,0.0001010578,0.0000021264839,0.00035386445,0.00069075153,0.0000046045725,0.15650879,0.84147584,0.0004277039],"study_design_scores_gemma":[0.00045726824,0.00051865523,0.0000013240167,0.00012010137,0.000092554765,0.0000068622926,0.000022252432,0.30177918,0.00036969766,0.00018209225,0.69586575,0.00058425165],"about_ca_topic_score_codex":0.000015452528,"about_ca_topic_score_gemma":0.00003008354,"teacher_disagreement_score":0.5159936,"about_ca_system_score_codex":0.0001708755,"about_ca_system_score_gemma":0.000223062,"threshold_uncertainty_score":0.99990845},"labels":[],"label_agreement":null},{"id":"W3143356065","doi":"10.1145/3448016.3457330","title":"DataPrep.EDA: Task-Centric Exploratory Data Analysis for Statistical Modeling in Python","year":2021,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Mitacs; National Science Foundation","keywords":"Python (programming language); Granularity; Exploratory data analysis; Statistical model; Data modeling; Data structure; Data exploration","score_opus":0.17463812581533672,"score_gpt":0.3712001494054153,"score_spread":0.19656202359007857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3143356065","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000192776,0.00007584539,0.99863523,0.00022669818,0.00007541838,0.000059867707,0.0004576077,0.00006595114,0.00021061575],"genre_scores_gemma":[0.39452866,0.00014888441,0.5925078,0.0013792807,0.00006572354,0.000012210476,0.010836561,0.000017176642,0.00050373987],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99850357,0.00007662835,0.00032258546,0.0006524502,0.00022980706,0.00021497776],"domain_scores_gemma":[0.99808097,0.00013138693,0.000040712544,0.0015354645,0.000117990414,0.00009346615],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042904227,0.00008988411,0.00019844275,0.00021808548,0.000056741912,0.00027260403,0.0010711089,0.0000329995,0.000053901498],"category_scores_gemma":[0.00031083627,0.00008728346,0.00003248264,0.0018154363,0.000012578432,0.00095285015,0.0009793284,0.00005745006,0.000017579428],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012977257,0.00085256866,0.005066239,0.00010474752,0.00050062395,0.00019710787,0.0005738265,0.110922374,0.00017556707,0.8259358,0.033855356,0.0218028],"study_design_scores_gemma":[0.0002318072,0.000005489509,0.000043721182,0.0000041220346,0.00006153609,0.0000010506028,0.00012867354,0.9946547,0.000051961037,0.0010651583,0.0036347858,0.00011695632],"about_ca_topic_score_codex":0.000029527326,"about_ca_topic_score_gemma":0.00023579097,"teacher_disagreement_score":0.8837324,"about_ca_system_score_codex":0.000027751788,"about_ca_system_score_gemma":0.00019720804,"threshold_uncertainty_score":0.3559316},"labels":[],"label_agreement":null},{"id":"W3146488696","doi":"10.1109/visual.2002.1183781","title":"GeneVis: visualization tools for genetic regulatory network dynamics","year":2003,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Visualization; Computer science; Focus (optics); Process (computing); Data visualization; Genetic network; Information visualization; Human–computer interaction; Data science; Artificial intelligence; Biology; Genetics; Gene","score_opus":0.025519121446096905,"score_gpt":0.2929731793355913,"score_spread":0.2674540578894944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3146488696","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000505984,0.000086371605,0.99576026,0.000076389246,0.0002939393,0.00018839542,0.0000046019354,0.0001650813,0.0029189494],"genre_scores_gemma":[0.15220957,0.00013869972,0.8349836,0.0050792727,0.00028011657,0.000050280305,0.0002523356,0.000050757597,0.0069553857],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990189,0.000054680928,0.00024348352,0.00027900288,0.00016647296,0.00023747687],"domain_scores_gemma":[0.9991938,0.000072668656,0.00007759072,0.000455207,0.00012228388,0.000078469355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025963128,0.0001039046,0.00011125028,0.00005070821,0.00012819655,0.0003541646,0.00037221785,0.00005381354,0.00003994725],"category_scores_gemma":[0.00012634274,0.00010025024,0.000052369225,0.00042976494,0.000017992768,0.000480805,0.000053347914,0.000023283961,0.000026633863],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.0574386e-7,0.000020394426,0.00040094627,0.0000089292735,0.0000081516855,4.256933e-7,0.000017051223,0.0034218132,0.000008584295,0.9770693,0.01018014,0.008863731],"study_design_scores_gemma":[0.0002089221,0.00003497605,0.00078639184,0.0000075784997,0.000008525339,0.0000038437,0.00001691765,0.9165465,0.00016504235,0.01108122,0.07096802,0.00017206071],"about_ca_topic_score_codex":0.0000010009614,"about_ca_topic_score_gemma":0.000010817134,"teacher_disagreement_score":0.9659881,"about_ca_system_score_codex":0.000044226654,"about_ca_system_score_gemma":0.00007450655,"threshold_uncertainty_score":0.4088086},"labels":[],"label_agreement":null},{"id":"W3148065246","doi":"10.1007/978-3-030-96731-4_9","title":"StreamTable: An Area Proportional Visualization for Tables with Flowing Streams","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"STREAMS; Rectangle; Row; Computer science; Visualization; Bounding overwatch; Minimum bounding box; Intersection (aeronautics); Geometry; Algorithm; Combinatorics; Mathematics; Artificial intelligence; Image (mathematics); Cartography; Database","score_opus":0.02470293285722995,"score_gpt":0.28553906090803816,"score_spread":0.2608361280508082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3148065246","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006304136,0.000059307426,0.9975302,0.00018330927,0.0005853721,0.00051500846,0.00009739079,0.00017723371,0.0007890876],"genre_scores_gemma":[0.07849707,0.00007703232,0.912905,0.0027780777,0.0010203016,0.000125639,0.0027565428,0.00017087115,0.0016695152],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99655706,0.000028072447,0.00046931495,0.0014014663,0.0010470545,0.0004970585],"domain_scores_gemma":[0.9980528,0.00018265398,0.0002446086,0.0009691327,0.00038143172,0.00016939342],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00066823844,0.0004184996,0.000391019,0.0006926681,0.00053804,0.00081050274,0.0020697296,0.00013591985,0.00013027772],"category_scores_gemma":[0.000067609726,0.0003718084,0.000070308466,0.0008594347,0.00026237592,0.0016499228,0.0006395507,0.00028701307,0.0000027642473],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019014056,0.00016859962,0.0002729558,0.00010217966,0.000031277952,0.000051028863,0.00064498803,0.29929608,0.00007026381,0.39767796,0.00009769541,0.30156797],"study_design_scores_gemma":[0.0003236132,0.00044098563,0.00001729722,0.00017080024,0.000016050592,0.000040480223,9.70491e-7,0.9640779,0.00038886588,0.025697535,0.0082814405,0.00054410007],"about_ca_topic_score_codex":0.000022097805,"about_ca_topic_score_gemma":0.00015183642,"teacher_disagreement_score":0.6647818,"about_ca_system_score_codex":0.00027419202,"about_ca_system_score_gemma":0.00094641896,"threshold_uncertainty_score":0.9998734},"labels":[],"label_agreement":null},{"id":"W3151148158","doi":"10.1109/infvis.2005.1532124","title":"Interactive visualization of genealogical graphs","year":2005,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Tree (set theory); Visualization; Graph drawing; Theoretical computer science; Dual (grammatical number); Family tree; Graph; Artificial intelligence; Combinatorics; Mathematics","score_opus":0.025993088358254018,"score_gpt":0.3339147585977246,"score_spread":0.3079216702394706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3151148158","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002374486,0.000009386926,0.9860159,0.00025629174,0.000041743813,0.000028782551,0.0000012614688,0.000068755464,0.011203358],"genre_scores_gemma":[0.9720324,0.000017106364,0.026692897,0.00082164066,0.000017547476,8.4219073e-7,0.000011834446,0.0000021819912,0.00040353267],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99951744,0.000024476522,0.00014832152,0.000119031814,0.00012432602,0.000066415516],"domain_scores_gemma":[0.999644,0.000023281134,0.000055696197,0.00016303375,0.000080474776,0.00003352386],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007536927,0.00004309546,0.00006524381,0.000078388344,0.000019964198,0.00003506331,0.00026836625,0.000019902849,0.00013301897],"category_scores_gemma":[0.000026668058,0.000034434404,0.000028024591,0.00031245156,0.000017610204,0.0004110996,0.00008849448,0.000018762288,0.000045417386],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.968037e-7,0.000074868396,0.00040651462,0.0000018722023,0.000005253865,2.919475e-7,0.0001622793,0.0000998897,0.00045146653,0.984761,0.0019739813,0.012061672],"study_design_scores_gemma":[0.0002707179,0.000079543286,0.0019163549,0.00000888613,0.000004903634,0.000004263018,0.000045433753,0.9348444,0.02777806,0.0058035697,0.029100886,0.00014303385],"about_ca_topic_score_codex":0.000004166292,"about_ca_topic_score_gemma":0.0000057773836,"teacher_disagreement_score":0.9789574,"about_ca_system_score_codex":0.000008422671,"about_ca_system_score_gemma":0.000012919238,"threshold_uncertainty_score":0.14564645},"labels":[],"label_agreement":null},{"id":"W3155007082","doi":"10.2196/15527","title":"Analysis of Mental Health Disease Trends Using BeGraph Software in Spanish Health Care Centers: Case Study","year":2021,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mental health; Health care; Medicine; Software; Disease; Data science; Medical emergency; Psychiatry; Computer science; Pathology","score_opus":0.032364414148971725,"score_gpt":0.3898849340744013,"score_spread":0.35752051992542955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3155007082","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6635444,0.0005972018,0.33196437,0.0020617673,0.0003840193,0.000530558,0.00068806903,0.00016820249,0.00006140083],"genre_scores_gemma":[0.97861105,0.00009107102,0.01509971,0.0052017625,0.000022381559,0.000007685427,0.00093946006,0.000009672323,0.000017231201],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99737114,0.00015762754,0.0010565637,0.00016942428,0.00094462064,0.0003005993],"domain_scores_gemma":[0.99835277,0.00003654498,0.00035159415,0.0005307441,0.00010663385,0.00062170904],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040373486,0.00013727818,0.00046510462,0.0006535906,0.00012539265,0.000099181474,0.00041161303,0.000040843042,0.000064732456],"category_scores_gemma":[0.00006800579,0.00012781918,0.00013408187,0.0034445706,0.000052589585,0.00045799883,0.0003630209,0.00015724842,0.0000012024173],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019249243,0.004186917,0.37206316,0.0013146184,0.00093463087,0.0022927774,0.36963207,0.0016349308,1.851784e-7,0.001371746,0.005167833,0.24138188],"study_design_scores_gemma":[0.0015031706,0.00020336066,0.009646434,0.0002408139,0.000091319685,0.00009736812,0.103539556,0.8834346,0.0000011459756,0.0000054740744,0.0009919034,0.00024486234],"about_ca_topic_score_codex":0.00030726104,"about_ca_topic_score_gemma":0.0014814214,"teacher_disagreement_score":0.88179964,"about_ca_system_score_codex":0.00017592288,"about_ca_system_score_gemma":0.0009820753,"threshold_uncertainty_score":0.5212315},"labels":[],"label_agreement":null},{"id":"W3156819776","doi":"10.5753/ihc.2020.14046","title":"Data-driven gameplay experience balancing","year":2020,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Process (computing); Human–computer interaction; Video game development; Game design; Game Developer; Game mechanics; Work (physics); Multimedia; Data science; Engineering","score_opus":0.0819859177550137,"score_gpt":0.3398350921871929,"score_spread":0.2578491744321792,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3156819776","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00062098936,0.00000862952,0.9921033,0.0022974883,0.000071722054,0.000025852734,0.000013484988,0.00020940343,0.0046491246],"genre_scores_gemma":[0.8747971,0.000017964167,0.1043055,0.020176204,0.00011596199,0.0000015440955,0.00009106879,0.0000067458964,0.0004879304],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99929404,0.000014417296,0.00011378187,0.00030542692,0.00016103272,0.000111320325],"domain_scores_gemma":[0.9992107,0.000018091017,0.000028153534,0.000604147,0.000022804415,0.0001161139],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000048077065,0.00005349482,0.00006687126,0.000015462803,0.000042106883,0.0001747245,0.0016587984,0.000013116914,0.00015042361],"category_scores_gemma":[0.00008006367,0.00004549768,0.000010696797,0.00029606294,0.000015256776,0.00083808065,0.0008490685,0.000036201927,0.00027722545],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000033942526,0.0000920429,0.005680194,0.000036625872,0.000029223882,0.000076016695,0.011956233,0.0010167414,0.0034313349,0.611173,0.34070355,0.025801662],"study_design_scores_gemma":[0.00005904459,0.000009838423,0.0000881972,0.0000022703582,9.089403e-7,0.0000014885768,0.00010798191,0.8702365,0.0003506104,0.000028320968,0.12904614,0.00006869279],"about_ca_topic_score_codex":0.0000042386687,"about_ca_topic_score_gemma":0.0000036181848,"teacher_disagreement_score":0.88779783,"about_ca_system_score_codex":0.0000043275745,"about_ca_system_score_gemma":0.000027172167,"threshold_uncertainty_score":0.3563265},"labels":[],"label_agreement":null},{"id":"W3161523625","doi":"10.5194/egusphere-egu21-11208","title":"The &amp;#8220;Scientific colour map&amp;#8221; Initiative: Version 7 and its new additions","year":2021,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Cyclase; Chemistry; Adenine nucleotide; Adenylate kinase; Nucleotide; Endocrinology; Internal medicine; Biology; Biochemistry; Enzyme; Medicine; Gene","score_opus":0.06875267785968273,"score_gpt":0.3250250627729677,"score_spread":0.25627238491328497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3161523625","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0043509286,0.00081475073,0.95374537,0.025589949,0.0018988282,0.0002074736,0.00022595987,0.00030488818,0.012861878],"genre_scores_gemma":[0.074741036,0.0009379142,0.068085104,0.009099806,0.00037098926,0.000015933909,0.0019852754,0.000035156772,0.84472877],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989435,0.000091012145,0.00016308493,0.00033282302,0.00027513632,0.00019443214],"domain_scores_gemma":[0.9988871,0.00021436226,0.000054941233,0.00044977746,0.00023897327,0.00015483628],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00022943974,0.00009108268,0.0000831042,0.00004638535,0.00074653974,0.0010935144,0.00042762517,0.00003789295,0.00071502564],"category_scores_gemma":[0.00024875326,0.00006853516,0.000036804733,0.0006889027,0.00006325237,0.0005549131,0.00043538972,0.00008308828,0.0009086162],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001131292,0.000036822064,0.00003085826,0.000005031754,0.000011853513,0.0000030771196,0.00035880244,0.000007981443,0.00044375533,0.2401946,0.757187,0.0017190853],"study_design_scores_gemma":[0.00019652642,0.00000948587,0.00023898209,0.00001404148,0.0000071206373,0.000009815322,0.00009880555,0.007441915,0.0006702846,0.002990201,0.9882163,0.00010654203],"about_ca_topic_score_codex":0.0000058051937,"about_ca_topic_score_gemma":0.00029457043,"teacher_disagreement_score":0.88566023,"about_ca_system_score_codex":0.000021457448,"about_ca_system_score_gemma":0.0002770887,"threshold_uncertainty_score":0.99994344},"labels":[],"label_agreement":null},{"id":"W3165673720","doi":"10.1109/tvcg.2021.3085327","title":"InfoColorizer: Interactive Recommendation of Color Palettes for Infographics","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":54,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Microsoft Research Asia","keywords":"Infographic; Computer science; Computer graphics (images); Data visualization; Visualization; Multimedia; World Wide Web; Information retrieval; Artificial intelligence; Data mining","score_opus":0.02309543016759274,"score_gpt":0.3051622337590534,"score_spread":0.28206680359146064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3165673720","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016714755,0.000013655721,0.9969121,0.00024393162,0.00063038594,0.0002656605,0.000077784294,0.00012525957,0.000059727525],"genre_scores_gemma":[0.9654909,0.0010403446,0.02285083,0.009780872,0.000107468535,0.00012530571,0.00042495158,0.00004426034,0.000135102],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987225,0.00011586408,0.0004551981,0.00036704855,0.00017392113,0.00016544903],"domain_scores_gemma":[0.9985216,0.00033853957,0.00021020655,0.0002758105,0.0005627065,0.000091108916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020439045,0.00017693137,0.0002384721,0.00043009623,0.00021799818,0.00019423477,0.0002142203,0.00011059509,0.0000146029315],"category_scores_gemma":[0.000015118282,0.00018913769,0.00013002251,0.0012511031,0.00007734285,0.00059652305,0.000009978139,0.00011790805,0.0000017101037],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003418672,0.00049608597,0.00010991449,0.00010346031,0.00013635031,0.0000011679781,0.00079142646,0.00038097933,0.00010275553,0.97442406,0.001055695,0.022363918],"study_design_scores_gemma":[0.00093069195,0.00034954454,0.00016330824,0.0000576423,0.000039993545,0.000007875882,0.00008640975,0.9687998,0.011537886,0.0014920263,0.016299503,0.0002353114],"about_ca_topic_score_codex":0.0000032259068,"about_ca_topic_score_gemma":0.000018884237,"teacher_disagreement_score":0.9740613,"about_ca_system_score_codex":0.000016278946,"about_ca_system_score_gemma":0.00007334891,"threshold_uncertainty_score":0.7712811},"labels":[],"label_agreement":null},{"id":"W3165874069","doi":"10.1145/3251536","title":"Session details: Off and around the screen","year":2012,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Session (web analytics); Computer science; Multimedia; World Wide Web","score_opus":0.039770743194499095,"score_gpt":0.31499033092533324,"score_spread":0.27521958773083416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3165874069","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0077091525,0.0002722583,0.97763026,0.001567336,0.00009940161,0.00004063486,0.0000010227991,0.000066970075,0.012612957],"genre_scores_gemma":[0.98648566,0.000066488465,0.007842679,0.0026393067,0.00009305581,7.900759e-7,0.0000035726232,0.0000027271735,0.0028657464],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996577,0.000024337605,0.000056923185,0.000068153495,0.00009410298,0.00009878696],"domain_scores_gemma":[0.9996741,0.0000323881,0.000018163148,0.0002074088,0.0000147582605,0.0000531936],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020101904,0.00003525128,0.000032707067,0.000016388944,0.00008536256,0.00013910212,0.00023103836,0.000012843991,0.000026638358],"category_scores_gemma":[0.000015325497,0.000018787765,0.000008754013,0.00011609739,0.000020820104,0.00055105775,0.00017993207,0.000025218867,0.00005830004],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.010597e-7,0.000045845944,0.022938352,0.000003627772,0.000008342481,4.2672272e-7,0.0004496919,0.0000033303584,0.00012508995,0.84717345,0.023993388,0.105257854],"study_design_scores_gemma":[0.00027329795,0.000029048551,0.03229133,0.000014815799,0.00001254893,0.000020177795,0.0004861502,0.4002663,0.0011762802,0.0023379966,0.5628632,0.00022890433],"about_ca_topic_score_codex":0.000009223312,"about_ca_topic_score_gemma":0.000004319385,"teacher_disagreement_score":0.97877645,"about_ca_system_score_codex":0.0000030278316,"about_ca_system_score_gemma":0.000007116707,"threshold_uncertainty_score":0.1341365},"labels":[],"label_agreement":null},{"id":"W3166607097","doi":"","title":"On augmenting the references section with a citation network visualization","year":2021,"lang":"en","type":"article","venue":"London School of Economics and Political Science Research Online (London School of Economics and Political Science)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Complement (music); Workflow; Section (typography); Citation; Set (abstract data type); Data science; Visualization; Reading (process); Graph; Graph drawing; Information retrieval; World Wide Web; Theoretical computer science; Data mining; Programming language; Database","score_opus":0.060705751806292035,"score_gpt":0.3737598153031471,"score_spread":0.31305406349685505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3166607097","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9852344,0.000094910865,0.0028932535,0.006575352,0.00025250873,0.00026698995,0.00006492423,0.000017713266,0.004599946],"genre_scores_gemma":[0.9946004,0.0008913134,0.0031149997,0.0009518248,0.00026756083,0.0000075741937,0.00001898403,0.000011638287,0.00013568602],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99555707,0.00022335374,0.00086309516,0.0010140097,0.0005385441,0.001803917],"domain_scores_gemma":[0.9950468,0.0010553388,0.00027673133,0.00068676815,0.001129131,0.0018052524],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0063782567,0.00023621041,0.000435117,0.00058798055,0.0009226631,0.0013415371,0.0012051428,0.0001086473,0.000058904126],"category_scores_gemma":[0.0029485212,0.00017717175,0.000069598056,0.0019943425,0.0035450934,0.0017790857,0.0008257922,0.0004395913,0.000011551962],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024393323,0.000107161446,0.003961719,0.000021885371,0.000011986579,0.0000011971243,0.000034058234,0.00079874037,0.00021001704,0.99393475,0.000058533733,0.00083558407],"study_design_scores_gemma":[0.0013809628,0.0012738109,0.05999859,0.00022150177,0.000034263747,0.00006100409,0.0013703025,0.5120085,0.006334074,0.41350237,0.0031957221,0.0006189393],"about_ca_topic_score_codex":0.000569214,"about_ca_topic_score_gemma":0.00036887027,"teacher_disagreement_score":0.58043236,"about_ca_system_score_codex":0.0004026423,"about_ca_system_score_gemma":0.0032568625,"threshold_uncertainty_score":0.9996952},"labels":[],"label_agreement":null},{"id":"W3170000029","doi":"10.1016/j.bdr.2021.100239","title":"ExplorerTree: A Focus+Context Exploration Approach for 2D Embeddings","year":2021,"lang":"en","type":"article","venue":"Big Data Research","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Computer science; Focus (optics); Artificial intelligence; Context (archaeology); Clutter; Convolutional neural network; Dimensionality reduction; Visualization; Machine learning; Pattern recognition (psychology); Data mining; Radar","score_opus":0.6266507062173049,"score_gpt":0.4639213162888603,"score_spread":0.1627293899284446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3170000029","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000040405648,0.00037177608,0.99494636,0.002537871,0.00014065449,0.0002606941,0.00029613273,0.00008196766,0.0013241606],"genre_scores_gemma":[0.44694418,0.0019042348,0.49769616,0.0020143597,0.0019680364,0.000712995,0.03346392,0.00013401471,0.015162098],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974739,0.00021885788,0.00024657685,0.0008325781,0.0007881587,0.0004399484],"domain_scores_gemma":[0.9965495,0.00022841872,0.000045630066,0.0023294217,0.0006927383,0.0001542891],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018776702,0.00010623651,0.00014931987,0.00021621537,0.00030094234,0.000937996,0.0024983787,0.000063667365,0.000019111167],"category_scores_gemma":[0.001216817,0.00010056906,0.000036905734,0.0013523189,0.000069605216,0.0020615035,0.0025145542,0.00017079504,0.00009444429],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016444934,0.00035056585,0.000038377813,0.0000862555,0.00003424666,0.000021035763,0.00095779315,0.000014137575,0.0008412002,0.1753126,0.2860791,0.53624827],"study_design_scores_gemma":[0.00049666286,0.000053220843,0.00000960238,0.000020603457,0.0000044467906,0.0000067548026,0.0011227553,0.6370202,0.0048256125,0.0029744138,0.35330534,0.00016039397],"about_ca_topic_score_codex":0.000040515042,"about_ca_topic_score_gemma":0.00008274393,"teacher_disagreement_score":0.63700604,"about_ca_system_score_codex":0.000040959796,"about_ca_system_score_gemma":0.00038924578,"threshold_uncertainty_score":0.9045117},"labels":[],"label_agreement":null},{"id":"W3170014045","doi":"10.3390/electronics10222862","title":"Random Forest Similarity Maps: A Scalable Visual Representation for Global and Local Interpretation","year":2021,"lang":"en","type":"article","venue":"Electronics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Random forest; Computer science; Scalability; Visual analytics; Visualization; Machine learning; Artificial intelligence; Similarity (geometry); Popularity; Representation (politics); GRASP; Data mining; Feature (linguistics); Human–computer interaction; Data science; Database; Image (mathematics)","score_opus":0.01255610545355446,"score_gpt":0.3170688413211087,"score_spread":0.30451273586755423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3170014045","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0031605763,0.0010286667,0.99454683,0.0006864699,0.00009387465,0.0001278607,0.000011849617,0.00006181541,0.00028203323],"genre_scores_gemma":[0.9731113,0.0005122558,0.024054924,0.0012667828,0.000078602076,0.000027210699,0.00049311575,0.000011800104,0.0004440441],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99909323,0.00005895888,0.00017495773,0.00030229974,0.00015191897,0.00021865225],"domain_scores_gemma":[0.99944943,0.000081724145,0.000058748534,0.00018743947,0.00016386778,0.00005880686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018891096,0.00008289968,0.0001245074,0.000024204852,0.00009990392,0.00024485198,0.00015310297,0.00004896596,0.000004127708],"category_scores_gemma":[0.00017406019,0.000086792956,0.00004464407,0.00034890743,0.000029543844,0.00040625298,0.00010550653,0.00005912571,0.0000036498393],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019210596,0.00029010786,0.0044522216,0.00009774857,0.00010811445,0.000014248478,0.0004328386,0.0039272015,0.00038004224,0.73226357,0.008861985,0.24897984],"study_design_scores_gemma":[0.0012546672,0.00009882358,0.0002904914,0.000011274608,0.000017998715,0.000017279006,0.00004857606,0.948373,0.002053878,0.030587707,0.017135838,0.00011044504],"about_ca_topic_score_codex":0.0000039127603,"about_ca_topic_score_gemma":0.00024666172,"teacher_disagreement_score":0.97049195,"about_ca_system_score_codex":0.000087962595,"about_ca_system_score_gemma":0.00020097056,"threshold_uncertainty_score":0.3539314},"labels":[],"label_agreement":null},{"id":"W3172765438","doi":"10.48550/arxiv.2012.13658","title":"Locally Persistent Exploration in Continuous Control Tasks with Sparse\\n Rewards","year":2020,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; McGill University; Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Reinforcement learning; Computer science; State space; Trajectory; State (computer science); Action (physics); Task (project management); Space (punctuation); Artificial intelligence; Algorithm; Mathematics; Engineering","score_opus":0.09598491008680228,"score_gpt":0.20741497558456104,"score_spread":0.11143006549775876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3172765438","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014952076,0.00006394666,0.97984976,0.0013846054,0.00043780715,0.00088110357,0.000098518256,0.00018211799,0.0021500823],"genre_scores_gemma":[0.9959486,0.00048591147,0.0006975385,0.0010601371,0.00010932163,0.0000024634019,0.00015540766,0.000042368676,0.0014982464],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9953649,0.0005291431,0.00068697275,0.0023617654,0.00036200136,0.0006951992],"domain_scores_gemma":[0.99644876,0.00011114802,0.0007509075,0.0015144524,0.000623366,0.0005513622],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00053258234,0.00071790157,0.0009856609,0.00051239505,0.00023940972,0.0005640834,0.0022923127,0.00040220353,0.00010811539],"category_scores_gemma":[0.00010766433,0.0008075252,0.00038161676,0.0021201016,0.0003519459,0.0014989371,0.0011965879,0.0009225446,0.00029552318],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005612385,0.0005399175,0.0069437413,0.00019131781,0.00041696962,0.0020735525,0.002192409,0.8483012,0.000033404445,0.13690326,0.0006349,0.0012080973],"study_design_scores_gemma":[0.0038872943,0.0006527713,0.0006294711,0.00042549497,0.00033199246,0.00001140747,0.0016490988,0.98638076,0.000029607047,0.0021843005,0.0028584576,0.00095933815],"about_ca_topic_score_codex":0.00027549014,"about_ca_topic_score_gemma":0.00037094855,"teacher_disagreement_score":0.98099655,"about_ca_system_score_codex":0.000504338,"about_ca_system_score_gemma":0.0009167252,"threshold_uncertainty_score":0.9994376},"labels":[],"label_agreement":null},{"id":"W3174686248","doi":"10.1609/aaai.v35i5.16575","title":"Inductive Graph Neural Networks for Spatiotemporal Kriging","year":2021,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":151,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Institut de Valorisation des Données","keywords":"Kriging; Adjacency matrix; Computer science; Graph; Adjacency list; Artificial neural network; Artificial intelligence; Scalability; Machine learning; Data mining; Algorithm; Theoretical computer science","score_opus":0.10448264763483878,"score_gpt":0.3354707719017566,"score_spread":0.23098812426691784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3174686248","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021459255,0.000024619645,0.96976036,0.004656594,0.0007923857,0.0003478597,0.0000116410265,0.00009340987,0.002853901],"genre_scores_gemma":[0.99299955,0.000020868592,0.0061336625,0.0005185938,0.00009436458,0.000015629957,0.000003889655,0.000009635177,0.00020380892],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985793,0.000015748752,0.00041374314,0.00042567268,0.00029568956,0.00026980077],"domain_scores_gemma":[0.99825525,0.00007723008,0.00030626892,0.00024941436,0.0010397655,0.00007208112],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029105286,0.00015973944,0.0002021315,0.00008866966,0.00020413796,0.00036219571,0.0011653297,0.000068255256,0.000028567407],"category_scores_gemma":[0.00036450516,0.00012872527,0.00012839875,0.00087553007,0.00014096244,0.0004992969,0.00030891437,0.00018407086,0.000006633879],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013554253,0.000081129736,0.00024619637,0.00001862767,0.000013418143,4.0148188e-7,0.00037864147,0.00046844207,0.0023568263,0.9525849,0.00034392325,0.04349394],"study_design_scores_gemma":[0.000025832273,0.00006813325,0.000051328818,0.00006859461,0.000010450025,0.0000025332695,0.00045455125,0.7264542,0.15275605,0.119737625,0.00021538333,0.00015529316],"about_ca_topic_score_codex":0.000013370393,"about_ca_topic_score_gemma":0.000011172982,"teacher_disagreement_score":0.9715403,"about_ca_system_score_codex":0.000018811526,"about_ca_system_score_gemma":0.00009339412,"threshold_uncertainty_score":0.52492636},"labels":[],"label_agreement":null},{"id":"W3182718252","doi":"10.1177/14738716211021591","title":"PrAVA: Preprocessing profiling approach for visual analytics","year":2021,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; University of Victoria","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Natural Sciences and Engineering Research Council of Canada; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Computer science; Preprocessor; Visual analytics; Visualization; Profiling (computer programming); Data pre-processing; Data visualization; Analytics; Data mining; Data science; Process (computing); Scope (computer science); Interactive visual analysis; Data analysis; Artificial intelligence; Programming language","score_opus":0.029905803181232624,"score_gpt":0.33192231753133683,"score_spread":0.3020165143501042,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3182718252","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000303672,0.000031106345,0.99569255,0.00008680502,0.00016441621,0.00028363444,0.000016500757,0.00029126252,0.0031300457],"genre_scores_gemma":[0.35899526,0.000076020624,0.62427396,0.004306623,0.00028953698,0.00014019314,0.011024305,0.00004225562,0.0008518661],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984525,0.000053773296,0.00060010864,0.0002577623,0.00040299178,0.00023286331],"domain_scores_gemma":[0.99809617,0.000046599627,0.00033483017,0.00032592262,0.0011122905,0.00008418147],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045602632,0.00014823975,0.00016581222,0.00022889792,0.00026519963,0.0009888798,0.0003090339,0.00009872529,0.000010330078],"category_scores_gemma":[0.00054433243,0.0001564853,0.00006713932,0.0012325817,0.000021448797,0.0048611746,0.00013718024,0.000059806345,0.000023226561],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012240859,0.0002857363,0.0011309382,0.00060111546,0.00006135647,0.0000010508932,0.0022376918,0.024697581,0.0006406814,0.941126,0.0028022951,0.026403299],"study_design_scores_gemma":[0.00043136918,0.000029370964,0.00006885726,0.000020057087,0.000016878315,0.000009046774,0.00036909705,0.97072375,0.0138935065,0.0006218469,0.013614718,0.00020147816],"about_ca_topic_score_codex":0.0000010738216,"about_ca_topic_score_gemma":4.5950182e-7,"teacher_disagreement_score":0.9460262,"about_ca_system_score_codex":0.00006112322,"about_ca_system_score_gemma":0.0002921072,"threshold_uncertainty_score":0.95357907},"labels":[],"label_agreement":null},{"id":"W3184356259","doi":"10.1155/2021/5545117","title":"SAVE-T: Safety Analysis Visualization and Evaluation Tool","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Young Scientists Fund; National Natural Science Foundation of China; York University; Natural Science Foundation for Young Scientists of Shanxi Province; New Jersey Turfgrass Association; New York University","keywords":"Visualization; Computer science; Crash; Visual analytics; Data visualization; Analytics; Data science; Transport engineering; Creative visualization; Data mining; Engineering","score_opus":0.01612948137569894,"score_gpt":0.3279742931784252,"score_spread":0.3118448118027263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3184356259","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13982235,0.0002452263,0.85946244,0.00020552544,0.00015252527,0.00004735244,0.000009876238,0.000012982995,0.000041698615],"genre_scores_gemma":[0.9679933,0.0005744045,0.030890929,0.00019030168,0.00004099062,0.0000010160769,0.0002618804,0.0000054979905,0.000041648767],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99862134,0.00008296237,0.00054473046,0.00015744672,0.0005118872,0.00008162365],"domain_scores_gemma":[0.9983509,0.000045879224,0.00039814695,0.00015178995,0.0009971254,0.000056128414],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051725906,0.0000770071,0.0001917624,0.00023857801,0.00006528314,0.00008384554,0.000116713716,0.000034617857,0.000044725228],"category_scores_gemma":[0.00008956979,0.000074643074,0.00009502782,0.0012916299,0.000012836097,0.0012758271,0.0000046432356,0.000058864705,9.5185214e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000092145514,0.0003331825,0.01486499,0.000084701336,0.000884866,0.00008853433,0.007722807,0.48428127,0.0083885575,0.28610572,0.00015690443,0.19699632],"study_design_scores_gemma":[0.0028714694,0.00016806256,0.5767153,0.00008769528,0.0016649048,0.00003395823,0.0009824167,0.3957989,0.005923482,0.006330889,0.009057132,0.0003658096],"about_ca_topic_score_codex":8.344554e-7,"about_ca_topic_score_gemma":0.000037571426,"teacher_disagreement_score":0.82857156,"about_ca_system_score_codex":0.000038812224,"about_ca_system_score_gemma":0.00014060225,"threshold_uncertainty_score":0.30438563},"labels":[],"label_agreement":null},{"id":"W3187365692","doi":"10.1109/tvcg.2021.3114844","title":"Perception! Immersion! Empowerment! Superpowers as Inspiration for Visualization","year":2021,"lang":"en","type":"preprint","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Agence Nationale de la Recherche; Alberta Innovates; Alberta Innovates - Technology Futures","keywords":"Perception; Set (abstract data type); Visualization; Empowerment; Intersection (aeronautics); Comics; Variety (cybernetics); Human–computer interaction; Computer science; Cognitive science; Psychology; Engineering; Artificial intelligence; Political science","score_opus":0.026707482856082675,"score_gpt":0.31678559775011966,"score_spread":0.290078114894037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3187365692","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009222598,0.00008056872,0.9860211,0.0001839455,0.0028758384,0.0009554872,0.00010920397,0.0004967209,0.000054525626],"genre_scores_gemma":[0.9747667,0.0033219766,0.008738759,0.009263164,0.00032676003,0.00029513732,0.002700667,0.00015077126,0.00043609986],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9962136,0.00030166065,0.00089868123,0.0014220132,0.00075009227,0.00041393258],"domain_scores_gemma":[0.99741596,0.00013679509,0.00038724722,0.00090885477,0.0008649344,0.00028622706],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0004242686,0.00063361775,0.0005559387,0.0010139665,0.0007501372,0.0016280933,0.00069209334,0.0005981484,0.0000909872],"category_scores_gemma":[0.000013360204,0.00071438466,0.00038078608,0.0011579046,0.00012725995,0.00095679157,0.00006147259,0.0004136941,0.000019258578],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007370613,0.0017219897,0.000105541876,0.0007781548,0.0004633697,0.000012216877,0.007833428,0.009194052,0.00019007758,0.9578568,0.0034452397,0.018325439],"study_design_scores_gemma":[0.0009948771,0.0004240503,0.00009589691,0.0002848065,0.00013158728,0.000016869142,0.00047196852,0.9915413,0.0009381507,0.0010145284,0.0032820215,0.0008039056],"about_ca_topic_score_codex":0.00004394709,"about_ca_topic_score_gemma":0.000024225843,"teacher_disagreement_score":0.9823473,"about_ca_system_score_codex":0.00013475667,"about_ca_system_score_gemma":0.00035303406,"threshold_uncertainty_score":0.99953073},"labels":[],"label_agreement":null},{"id":"W3188433186","doi":"10.20380/gi2021.29","title":"How Tall is that Bar Chart? Virtual Reality, Distance Compression and Visualizations","year":2021,"lang":"en","type":"article","venue":"Canada Human-Computer Communications Society","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Bar chart; Bar (unit); Virtual reality; Computer science; Computer graphics (images); Chart; Visualization; Data visualization; Pie chart; Compression (physics); Human–computer interaction; Artificial intelligence; Mathematics; Geology; Statistics; Materials science","score_opus":0.06056772600637307,"score_gpt":0.3139973107653009,"score_spread":0.25342958475892785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3188433186","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005102002,0.0007328539,0.9690922,0.028560745,0.00018940952,0.00012915631,0.0001311274,0.000141405,0.0005128897],"genre_scores_gemma":[0.8662705,0.0018638107,0.10499992,0.019399302,0.00016153508,0.00003484375,0.0017583119,0.000049185233,0.0054626213],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982335,0.00021380108,0.00030028875,0.00051290577,0.0004503408,0.00028917228],"domain_scores_gemma":[0.99638855,0.00015037703,0.00018477745,0.0027119685,0.0003511162,0.00021321747],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00017426205,0.00022176554,0.00025749093,0.000032647244,0.0013062945,0.00082045334,0.0018323588,0.00008527187,0.000024414918],"category_scores_gemma":[0.00001611029,0.00024112742,0.00010721566,0.00049432844,0.00022430303,0.00068230776,0.0022760632,0.00024064089,0.0000022253998],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.4784767e-7,0.00015172982,0.00061059406,0.00004304171,0.000092592585,0.0000058721685,0.0024860916,0.00008439182,0.00017942513,0.63251513,0.36077875,0.0030520528],"study_design_scores_gemma":[0.0003349184,0.000013516017,0.0011232346,0.00006965259,0.00002017325,0.000013358585,0.00049572776,0.42433357,0.0003167479,0.00070707814,0.5722246,0.00034737823],"about_ca_topic_score_codex":0.00456098,"about_ca_topic_score_gemma":0.037333086,"teacher_disagreement_score":0.86576027,"about_ca_system_score_codex":0.00017403167,"about_ca_system_score_gemma":0.0005321071,"threshold_uncertainty_score":0.99999386},"labels":[],"label_agreement":null},{"id":"W3188759586","doi":"10.1177/14738716211033246","title":"MuzLink: Connected beeswarm timelines for visual analysis of musical adaptations and artist relationships","year":2021,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Polytechnique Montréal","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Timeline; Computer science; Visualization; Musical; Set (abstract data type); Domain (mathematical analysis); Exploratory search; Human–computer interaction; Graph; Information visualization; World Wide Web; Data science; Artificial intelligence; Theoretical computer science; Visual arts","score_opus":0.03593310119932884,"score_gpt":0.3241047055257082,"score_spread":0.28817160432637934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3188759586","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015838446,0.000027467715,0.9830238,0.00033326278,0.00010276076,0.00017863013,0.00011363289,0.00011626446,0.00026572475],"genre_scores_gemma":[0.96591115,0.00005913098,0.026474722,0.0007097255,0.00003709356,0.000028025988,0.006639258,0.000008703039,0.00013221474],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985404,0.0001070929,0.00074183533,0.00018811529,0.00028888677,0.00013367168],"domain_scores_gemma":[0.99770606,0.0003161404,0.00037120027,0.0002463205,0.0012778183,0.00008245153],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038274284,0.00011610737,0.00023877367,0.00063658535,0.00023040564,0.00025575582,0.00014683501,0.00009227042,0.00003756662],"category_scores_gemma":[0.001216334,0.00012566811,0.000088436005,0.0028716254,0.00004482124,0.0020525104,0.000081370206,0.000054633492,0.000010592288],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010404374,0.00013788785,0.0027233409,0.00007009983,0.00030281136,4.3785437e-7,0.0030900326,0.010391589,0.0003757251,0.97331065,0.0013165859,0.008270436],"study_design_scores_gemma":[0.00037311166,0.00003754386,0.015474169,0.000014367894,0.00024160936,0.0000021215612,0.00040808882,0.97234565,0.0010219731,0.00066372415,0.009273789,0.00014385153],"about_ca_topic_score_codex":0.000009039605,"about_ca_topic_score_gemma":0.000042328662,"teacher_disagreement_score":0.97264695,"about_ca_system_score_codex":0.000024614566,"about_ca_system_score_gemma":0.00013198498,"threshold_uncertainty_score":0.5124597},"labels":[],"label_agreement":null},{"id":"W3189737287","doi":"10.1109/tvcg.2021.3114805","title":"Professional Differences: A Comparative Study of Visualization Task Performance and Spatial Ability Across Disciplines","year":2021,"lang":"en","type":"preprint","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada; University of Cincinnati; National Science Foundation","keywords":"Visualization; Computer science; Domain (mathematical analysis); Cognition; Correctness; Human–computer interaction; Data visualization; Task (project management); Geovisualization; Data science; Information visualization; Workflow; Cognitive psychology; Artificial intelligence; Psychology","score_opus":0.047345911926730634,"score_gpt":0.35904620156718975,"score_spread":0.3117002896404591,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3189737287","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4461593,0.000028628654,0.55251974,0.000011727761,0.0007000958,0.00043145547,0.000059369366,0.000087148386,0.000002512185],"genre_scores_gemma":[0.9986366,0.000509532,0.00038716843,0.00014421776,0.00005788767,0.00006839477,0.00014377893,0.00002177488,0.000030633983],"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99651027,0.0005109141,0.0009065155,0.0010816822,0.0007204911,0.00027013052],"domain_scores_gemma":[0.99781996,0.00016391878,0.0005110173,0.00067594793,0.00066146796,0.00016767587],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00038456288,0.00048348086,0.0007352581,0.00036476547,0.00056819554,0.0005713174,0.00051784224,0.00027916656,0.000008848478],"category_scores_gemma":[0.000006160785,0.00044854885,0.00010868883,0.00092193147,0.0002484446,0.0005202,0.00015406289,0.00042476927,6.83975e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007212017,0.051675044,0.10500093,0.00914499,0.003236773,0.000040244122,0.49996135,0.043089382,0.00022243481,0.1978118,0.0005146639,0.0885812],"study_design_scores_gemma":[0.00095244276,0.0005901423,0.026045788,0.00036322404,0.00007179221,0.0000050831995,0.00136769,0.9697049,0.0002726226,0.00016181136,0.000020846184,0.00044362593],"about_ca_topic_score_codex":0.00012182117,"about_ca_topic_score_gemma":0.00045007525,"teacher_disagreement_score":0.92661554,"about_ca_system_score_codex":0.000028761826,"about_ca_system_score_gemma":0.0001567558,"threshold_uncertainty_score":0.9997966},"labels":[],"label_agreement":null},{"id":"W3191341511","doi":"10.1109/cec45853.2021.9504983","title":"3D-RadViz: Three Dimensional Radial Visualization for Large-Scale Data Visualization","year":2021,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Visualization; Computer science; Python (programming language); Data visualization; Information visualization; Data mining; Computer graphics (images)","score_opus":0.04673339159117474,"score_gpt":0.34295499672535024,"score_spread":0.2962216051341755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3191341511","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00025195285,0.00008239122,0.99715453,0.00057874236,0.00061870913,0.00020181276,0.00023189891,0.0002554888,0.0006244564],"genre_scores_gemma":[0.097308725,0.00020908812,0.79803634,0.021496594,0.0019696283,0.00008296493,0.067826204,0.00020063564,0.012869842],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99796516,0.000076574266,0.00040082555,0.00076849514,0.0004645294,0.0003244134],"domain_scores_gemma":[0.9979429,0.00012104562,0.00012391029,0.0012520902,0.00042608744,0.00013395183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048450657,0.00017065824,0.0002022737,0.000114216564,0.00027243735,0.00040261316,0.0009866429,0.00009220796,0.0002610921],"category_scores_gemma":[0.00027785965,0.00016749537,0.00005588608,0.00084862864,0.000021659078,0.0014194401,0.0009223247,0.000048313846,0.000067796675],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008993496,0.00043914092,0.0010712155,0.00004212608,0.0000423806,0.000006908395,0.00016467238,0.0004650726,0.00048509586,0.92024475,0.072266445,0.004763207],"study_design_scores_gemma":[0.0007102016,0.000030501638,0.0002621202,0.000014288878,0.000020586294,0.000008197958,0.000023462895,0.8766045,0.0009897726,0.0019718362,0.119149834,0.00021472423],"about_ca_topic_score_codex":0.000007918714,"about_ca_topic_score_gemma":0.00028123788,"teacher_disagreement_score":0.9182729,"about_ca_system_score_codex":0.00003251776,"about_ca_system_score_gemma":0.00025642203,"threshold_uncertainty_score":0.6830263},"labels":[],"label_agreement":null},{"id":"W3191946594","doi":"10.1111/cgf.14389","title":"Design and Evaluation of Visualization Techniques to Facilitate Argument Exploration","year":2021,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Argument (complex analysis); Visualization; Computer science; Visibility; Data science; Information visualization; Human–computer interaction; Artificial intelligence","score_opus":0.11529510884497964,"score_gpt":0.3414102994331717,"score_spread":0.22611519058819207,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3191946594","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010221757,0.000093252675,0.99744785,0.00085890177,0.00013973033,0.0002977305,0.0000036741774,0.000095163356,0.000041498013],"genre_scores_gemma":[0.34913123,0.00041336459,0.6467646,0.0032452315,0.000059242622,0.000083223036,0.00020894644,0.000023043822,0.00007111639],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985347,0.00024851796,0.00028274473,0.00031656277,0.00048082974,0.00013668761],"domain_scores_gemma":[0.9986443,0.000047523707,0.00009382055,0.0003553654,0.0007874027,0.000071579314],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000915461,0.00010299261,0.00013067016,0.00023679277,0.00008125062,0.00015288036,0.000215824,0.00004424349,0.000003861294],"category_scores_gemma":[0.000038624643,0.00010752732,0.00003095054,0.00083274115,0.000024308445,0.0006164535,0.0002564495,0.000036297522,0.0000035976816],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000055865544,0.0001846251,0.0002997997,0.000050424012,0.000044998662,0.000002933034,0.0021393395,0.004932304,0.0018991623,0.7772389,0.0071216114,0.2060803],"study_design_scores_gemma":[0.00018426198,0.00012472777,0.00011927375,0.000041315983,0.000015692858,0.00000325135,0.000031787084,0.9482479,0.024206052,0.022610832,0.004287144,0.00012778273],"about_ca_topic_score_codex":0.0000029967603,"about_ca_topic_score_gemma":0.0000050617664,"teacher_disagreement_score":0.94331557,"about_ca_system_score_codex":0.000020373549,"about_ca_system_score_gemma":0.00008702236,"threshold_uncertainty_score":0.4384837},"labels":[],"label_agreement":null},{"id":"W3191993787","doi":"10.1186/s12911-021-01598-4","title":"Home blood pressure data visualization for the management of hypertension: using human factors and design principles","year":2021,"lang":"en","type":"article","venue":"BMC Medical Informatics and Decision Making","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute for Work & Health; Humber River Regional Hospital; University of Toronto","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; Agency for Healthcare Research and Quality","keywords":"Focus group; Blood pressure; Conceptualization; Data visualization; Medicine; Visualization; Computer science; Health informatics; Health care; Clinical decision support system; Multidisciplinary approach; Decision support system; Nursing; Data mining; Artificial intelligence; Public health; Internal medicine","score_opus":0.23920238105073569,"score_gpt":0.39136857023060706,"score_spread":0.15216618917987138,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3191993787","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011800768,0.0005629528,0.98735577,0.000009045025,0.00008099353,0.00014292968,0.00001183562,0.000015562615,0.000020127403],"genre_scores_gemma":[0.14325109,0.0005235152,0.8558987,0.00024194803,0.000022343045,0.0000018664997,0.000042439515,0.0000063790367,0.000011707146],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987003,0.000030042229,0.00047963372,0.0001478817,0.0005343723,0.00010776996],"domain_scores_gemma":[0.9982082,0.0008850835,0.00018492689,0.00053183996,0.00011904895,0.00007088905],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085058424,0.00008783481,0.00015881372,0.000055480876,0.00022382829,0.0002431784,0.00052093726,0.000053077933,0.000010297489],"category_scores_gemma":[0.00022448918,0.00005476924,0.000020208636,0.00021286467,0.000048866106,0.00039594236,0.0012699974,0.000041439762,1.8429252e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003634564,0.00034894756,0.0040399404,0.003256256,0.00070252246,0.000031545194,0.002237479,0.011625687,0.000052570223,0.6988007,0.001575175,0.27729285],"study_design_scores_gemma":[0.00041442172,0.000017475631,0.0004181012,0.0003894034,0.00013173227,0.000020499252,0.00045159995,0.9956564,0.000035258035,0.0012864104,0.00110389,0.00007481393],"about_ca_topic_score_codex":8.4967195e-7,"about_ca_topic_score_gemma":0.0000024997005,"teacher_disagreement_score":0.9840307,"about_ca_system_score_codex":0.0000020718303,"about_ca_system_score_gemma":0.00006644704,"threshold_uncertainty_score":0.23449749},"labels":[],"label_agreement":null},{"id":"W3195400065","doi":"10.3390/info12090344","title":"VERONICA: Visual Analytics for Identifying Feature Groups in Disease Classification","year":2021,"lang":"en","type":"article","venue":"Information","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Interpretability; Visual analytics; Computer science; Naive Bayes classifier; Random forest; Machine learning; Analytics; Predictive analytics; Support vector machine; Interactive visual analysis; Artificial intelligence; Visualization; Data mining; Decision tree; Data science","score_opus":0.04556151753470707,"score_gpt":0.3394224635250304,"score_spread":0.29386094599032336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3195400065","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0039864853,0.00003080595,0.9939037,0.0013951716,0.00019915086,0.000115811425,0.000019420122,0.00005968541,0.0002897597],"genre_scores_gemma":[0.9861799,0.00004958142,0.010847093,0.0012724126,0.000052722342,0.000021706459,0.0014022783,0.000004740205,0.00016960573],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99929035,0.000021472748,0.00025222337,0.000113512186,0.00019462469,0.00012781366],"domain_scores_gemma":[0.9993651,0.00003531358,0.00011328534,0.00023862679,0.00018453522,0.00006314162],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018806997,0.00006566092,0.00007487311,0.00014192905,0.000070811235,0.0004107751,0.00021407085,0.000042565167,0.000005326309],"category_scores_gemma":[0.00021221707,0.00006990483,0.000040653864,0.0005624918,0.000009536022,0.0029836723,0.00007723198,0.000060421615,0.00004069048],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026345122,0.00018701599,0.0045706904,0.00033347667,0.000026980666,0.000007683374,0.0024370812,0.0029416142,0.00027074214,0.916773,0.0119854305,0.060439944],"study_design_scores_gemma":[0.00036942342,0.000008719166,0.022983756,0.00002767106,0.0000075323433,0.0000012724265,0.0001967919,0.9460474,0.00014249636,0.0016626173,0.028452149,0.00010016658],"about_ca_topic_score_codex":0.0000012808695,"about_ca_topic_score_gemma":0.00001057428,"teacher_disagreement_score":0.9830566,"about_ca_system_score_codex":0.00007749528,"about_ca_system_score_gemma":0.00013846284,"threshold_uncertainty_score":0.3961114},"labels":[],"label_agreement":null},{"id":"W3196524514","doi":"10.1145/3439333","title":"A Taxonomy of Property Measures to Unify Active Learning and Human-centered Approaches to Data Labeling","year":2021,"lang":"en","type":"article","venue":"ACM Transactions on Interactive Intelligent Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft; Deutscher Akademischer Austauschdienst","keywords":"Computer science; Visual analytics; Machine learning; Summative assessment; Artificial intelligence; Process (computing); Set (abstract data type); Analytics; Taxonomy (biology); Property (philosophy); Formative assessment; Visualization; Data mining; Programming language","score_opus":0.34217404350818925,"score_gpt":0.35596952039399693,"score_spread":0.013795476885807678,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3196524514","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0022209964,0.00004684991,0.99535245,0.00062254025,0.00035142965,0.00055145635,0.00009585725,0.000069638474,0.0006888035],"genre_scores_gemma":[0.98713917,0.00003166838,0.010657089,0.0001350836,0.000034724726,0.00009837966,0.000056423538,0.000020226062,0.0018272154],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979402,0.00029434494,0.0004806241,0.0007367168,0.0003275241,0.00022060233],"domain_scores_gemma":[0.9979749,0.00022796179,0.0001591211,0.0011253605,0.0003315996,0.0001810733],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032503772,0.00020913835,0.0003287981,0.000309541,0.00020109279,0.00027103297,0.0010882585,0.000056882454,0.000038693408],"category_scores_gemma":[0.00027023046,0.00017242061,0.0000573728,0.0006193828,0.000031483185,0.0006450045,0.00020942528,0.00027541147,0.000043546086],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00066935975,0.005079166,0.0016654279,0.0009465971,0.0036381504,0.0000967446,0.03562581,0.0738167,0.052802984,0.019995743,0.0028392517,0.8028241],"study_design_scores_gemma":[0.00097199704,0.0011928104,0.00017695785,0.0026400853,0.00019262802,0.00012588683,0.03320968,0.18675174,0.3412478,0.0001445887,0.43200818,0.0013376675],"about_ca_topic_score_codex":0.00026214335,"about_ca_topic_score_gemma":0.00014219026,"teacher_disagreement_score":0.9849182,"about_ca_system_score_codex":0.00010980755,"about_ca_system_score_gemma":0.00008510941,"threshold_uncertainty_score":0.7031108},"labels":[],"label_agreement":null},{"id":"W3196599735","doi":"10.1200/cci.21.00050","title":"Interactive Data Visualization Tool for Patient-Centered Decision Making in Kidney Cancer","year":2021,"lang":"en","type":"article","venue":"JCO Clinical Cancer Informatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"William Osler Health System; University of Calgary","funders":"","keywords":"Usability; Visualization; Medicine; Interactive visualization; Kidney cancer; Computer science; Medical physics; Renal cell carcinoma; Oncology; Human–computer interaction; Data mining","score_opus":0.13312352953412057,"score_gpt":0.4882935578949105,"score_spread":0.3551700283607899,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3196599735","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0045393347,0.00009723453,0.9916491,0.00044832163,0.0019481531,0.00032307714,0.00069911184,0.00006345139,0.00023223061],"genre_scores_gemma":[0.5406091,0.0043391283,0.3669139,0.08222335,0.0009262157,0.00029831126,0.0042201304,0.00009299113,0.0003768367],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973258,0.00009101192,0.0015763737,0.00034056444,0.00038991123,0.00027634788],"domain_scores_gemma":[0.99723786,0.00064370135,0.00055536604,0.000998083,0.0004415268,0.00012346928],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069249317,0.00015879478,0.00032526226,0.000117812655,0.00008191176,0.00037762366,0.0010595168,0.000116248746,0.00009725796],"category_scores_gemma":[0.0029057579,0.00014962119,0.000083015555,0.0006877432,0.000033888944,0.0022704795,0.0011814891,0.0001835448,0.000016713497],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014801712,0.0005243627,0.031364594,0.00036933224,0.00008251096,0.0000089122095,0.0032683206,0.0017030935,0.0000054961233,0.011408006,0.083541416,0.86757594],"study_design_scores_gemma":[0.0012253795,0.000056357923,0.0010332268,0.00067742454,0.000022195136,0.0000016778773,0.00023406626,0.87775695,0.00007354668,0.000587385,0.11811075,0.00022105301],"about_ca_topic_score_codex":0.000015401436,"about_ca_topic_score_gemma":0.0001839894,"teacher_disagreement_score":0.87605387,"about_ca_system_score_codex":0.00013494879,"about_ca_system_score_gemma":0.0007279658,"threshold_uncertainty_score":0.61013746},"labels":[],"label_agreement":null},{"id":"W3196807941","doi":"","title":"Supporting Transportation Decision-Makers with Tool Design and Data Uncertainty Visualizations","year":2020,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Political science; Humanities; Business; Art","score_opus":0.027759899110632973,"score_gpt":0.3014589253698176,"score_spread":0.27369902625918463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3196807941","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0033564202,0.0001064775,0.9908661,0.0044359863,0.000025752473,0.00047529596,0.00011766599,0.0005917766,0.000024506739],"genre_scores_gemma":[0.325892,0.00011973813,0.6669801,0.006381916,0.000042882548,0.000046427267,0.00044286027,0.00003597824,0.00005811643],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978781,0.000101854166,0.0004859362,0.0007124433,0.0004154934,0.00040620376],"domain_scores_gemma":[0.998089,0.0002249627,0.00023843932,0.000988253,0.00013634659,0.00032295738],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006255609,0.00023533206,0.00024860707,0.00016616755,0.0002595667,0.00049758644,0.0011912038,0.00010001659,0.000027727898],"category_scores_gemma":[0.000395679,0.0002140779,0.00003455207,0.0010672595,0.000065636275,0.001389213,0.00021753533,0.00016475002,0.00000659913],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035240248,0.0005146949,0.040445905,0.00018707034,0.00025438683,0.00041210637,0.0051557724,0.28341636,0.0021955022,0.4065235,0.041132838,0.21940947],"study_design_scores_gemma":[0.00042786342,0.00013357763,0.0024843412,0.000038062706,0.000033442073,0.00001888974,0.00012140001,0.98984265,0.0002947449,0.0009890472,0.0053201835,0.00029582367],"about_ca_topic_score_codex":0.00039552274,"about_ca_topic_score_gemma":0.00043292204,"teacher_disagreement_score":0.70642626,"about_ca_system_score_codex":0.00005711449,"about_ca_system_score_gemma":0.00030335877,"threshold_uncertainty_score":0.87298435},"labels":[],"label_agreement":null},{"id":"W3197405043","doi":"10.1145/3447992","title":"Effect of Adaptive Guidance and Visualization Literacy on Gaze Attentive Behaviors and Sequential Patterns on Magazine-Style Narrative Visualizations","year":2021,"lang":"en","type":"article","venue":"ACM Transactions on Interactive Intelligent Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Visualization; Narrative; Computer science; Psychological intervention; Comprehension; Gaze; Eye tracking; Literacy; Reading comprehension; Human–computer interaction; Reading (process); Cognitive psychology; Multimedia; Psychology; Artificial intelligence; Linguistics; Pedagogy","score_opus":0.022376789157294998,"score_gpt":0.34636703602714675,"score_spread":0.32399024686985173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3197405043","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1086324,0.0000769786,0.8892074,0.00011140099,0.0008520137,0.0005546017,0.00026780216,0.00008410859,0.00021328893],"genre_scores_gemma":[0.9981835,0.00017916186,0.00032766597,0.0001619056,0.000042442698,0.00010297433,0.00010854415,0.00003355054,0.00086025515],"study_design_codex":"qualitative","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9969375,0.00087278284,0.00066107116,0.0007999565,0.00047961887,0.00024908604],"domain_scores_gemma":[0.9971982,0.0009676317,0.00038249933,0.00067663356,0.0006279379,0.00014710122],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003093456,0.00038321214,0.000462978,0.00045854127,0.00026979166,0.00032461353,0.0003650168,0.00011481514,0.00008759461],"category_scores_gemma":[0.00019564271,0.000353785,0.00013358287,0.0006472317,0.00009968051,0.0008255588,0.000053948905,0.00026658204,0.000039419127],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0061761294,0.017112892,0.014397568,0.0037869792,0.006690991,0.00080619,0.288854,0.06685968,0.062619604,0.27211848,0.002424079,0.2581534],"study_design_scores_gemma":[0.0028295454,0.010691054,0.0021385641,0.006415484,0.00045667798,0.00019138468,0.009549699,0.35374793,0.60919595,0.00028731857,0.0028671038,0.0016292711],"about_ca_topic_score_codex":0.000064591215,"about_ca_topic_score_gemma":0.000023879807,"teacher_disagreement_score":0.8895511,"about_ca_system_score_codex":0.00016564666,"about_ca_system_score_gemma":0.00005387342,"threshold_uncertainty_score":0.9998914},"labels":[],"label_agreement":null},{"id":"W3198380835","doi":"10.1145/3429448","title":"QuestionComb: A Gamification Approach for the Visual Explanation of Linguistic Phenomena through Interactive Labeling","year":2021,"lang":"en","type":"article","venue":"ACM Transactions on Interactive Intelligent Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Deutsche Forschungsgemeinschaft","keywords":"Computer science; Visual analytics; Process (computing); Workspace; Domain (mathematical analysis); Human–computer interaction; Artificial intelligence; Task (project management); Analytics; Interface (matter); Visualization; Machine learning; Natural language processing; Data science","score_opus":0.05629626048807195,"score_gpt":0.35444123625994944,"score_spread":0.2981449757718775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3198380835","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001591339,0.00020624118,0.99633664,0.00026309822,0.0015654003,0.00058474357,0.00007393597,0.00008663131,0.0007241609],"genre_scores_gemma":[0.9782199,0.00018259665,0.02022353,0.00016862733,0.00015354175,0.00029341536,0.00014638707,0.000023533288,0.00058843155],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980193,0.00023766678,0.0006819151,0.0005013326,0.00035836676,0.00020146335],"domain_scores_gemma":[0.9958279,0.0017292645,0.00042223398,0.00077393436,0.0011949278,0.000051739793],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036650163,0.00021210391,0.00028152505,0.00017654928,0.00025882915,0.00023775257,0.00073718815,0.000072314935,0.000028663231],"category_scores_gemma":[0.0006359764,0.00017465014,0.00017090193,0.00061129325,0.000053810047,0.0006227522,0.00002868691,0.00024426173,0.000021651998],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007838701,0.008684882,0.00010301534,0.001186454,0.0037453522,0.000015560161,0.10885042,0.35367358,0.013436731,0.3476585,0.0011593396,0.16070233],"study_design_scores_gemma":[0.00036243952,0.00022061552,0.000016755122,0.0002828121,0.00010729521,0.000025467813,0.010818188,0.9259931,0.05341919,0.0014509498,0.00704141,0.00026176588],"about_ca_topic_score_codex":0.00012432582,"about_ca_topic_score_gemma":0.000011107792,"teacher_disagreement_score":0.9780608,"about_ca_system_score_codex":0.0002329732,"about_ca_system_score_gemma":0.00012017718,"threshold_uncertainty_score":0.71220255},"labels":[],"label_agreement":null},{"id":"W3199328824","doi":"10.1109/tvcg.2021.3114211","title":"ChartStory: Automated Partitioning, Layout, and Captioning of Charts into Comic-Style Narratives","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Science Foundation of Sri Lanka; Natural Sciences and Engineering Research Council of Canada","keywords":"Comics; Storytelling; Computer science; Narrative; Operationalization; Visualization; Pipeline (software); Closed captioning; Data visualization; Human–computer interaction; Data science; World Wide Web; Artificial intelligence; Programming language","score_opus":0.01863847029110049,"score_gpt":0.28338133682486355,"score_spread":0.26474286653376305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3199328824","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033448424,0.00009710776,0.96552885,0.00015026277,0.00031404407,0.00008934267,0.000015863203,0.00032103734,0.00003507211],"genre_scores_gemma":[0.99504846,0.0003332859,0.0035542552,0.0008860944,0.00002775791,0.000009313,0.000043968983,0.000015382519,0.0000815007],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99870867,0.0001644447,0.00034486505,0.00039372288,0.00023697039,0.00015134209],"domain_scores_gemma":[0.9991415,0.000056031553,0.00014563349,0.00026503764,0.00027169925,0.00012007994],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016488333,0.00017187855,0.00022714828,0.00028280047,0.00038495776,0.00022976073,0.00013867325,0.00008730904,0.000022537706],"category_scores_gemma":[0.0000045706965,0.00018662246,0.000056589746,0.00073346676,0.00014057012,0.0004999447,0.000011646266,0.00010497215,0.0000033295025],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009232602,0.00040298115,0.00041330245,0.00013114377,0.000115430754,0.000009316934,0.013300324,0.0010561418,0.0004363662,0.98104954,0.000733271,0.0023429596],"study_design_scores_gemma":[0.0005092281,0.000117221854,0.0005565786,0.00010280392,0.000019058121,0.000023477616,0.00028572947,0.99221814,0.003807442,0.00069189165,0.0014539551,0.0002144544],"about_ca_topic_score_codex":0.000012753027,"about_ca_topic_score_gemma":0.00003285996,"teacher_disagreement_score":0.991162,"about_ca_system_score_codex":0.000014495814,"about_ca_system_score_gemma":0.00006246592,"threshold_uncertainty_score":0.7610243},"labels":[],"label_agreement":null},{"id":"W3199977262","doi":"10.1109/mcg.2021.3102711","title":"Powering Visualization With Deep Learning","year":2021,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Visualization; Computer science; Deep learning; Visual analytics; Leverage (statistics); Data visualization; Artificial intelligence; Human–computer interaction; Data science; Focus (optics); Information visualization; Creative visualization; Learning analytics","score_opus":0.012641765936252318,"score_gpt":0.2693196983516385,"score_spread":0.25667793241538617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3199977262","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012529737,0.00011929558,0.99788964,0.00017370035,0.00004820576,0.00007832169,0.0000016008181,0.00015451292,0.0002817363],"genre_scores_gemma":[0.9064024,0.0010078289,0.08939285,0.0022956918,0.00032692598,0.00008092101,0.00017043849,0.000035638288,0.00028730097],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992167,0.000030914394,0.00014267843,0.00033263557,0.00014607907,0.00013099206],"domain_scores_gemma":[0.9993261,0.000040327202,0.000064187654,0.00029794124,0.00018546222,0.000085984786],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000079749705,0.00009627364,0.000096369884,0.00009152166,0.00026868557,0.00035308438,0.00021614716,0.000034374778,0.000003984267],"category_scores_gemma":[0.0000024341925,0.00009212585,0.000024239589,0.00076484977,0.000039750757,0.0002324561,0.00010629918,0.00008899896,0.000008450107],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.7014098e-7,0.000051211482,0.0010208136,0.000015016052,0.000016780623,0.000004260901,0.00013189776,0.00086230616,0.000099763056,0.97510266,0.000100414225,0.022594485],"study_design_scores_gemma":[0.00021874711,0.000037527618,0.0013742961,0.000019010578,0.000011732875,0.000044517903,0.000023361868,0.9061202,0.00044767148,0.0030014638,0.088493824,0.00020768405],"about_ca_topic_score_codex":0.0000023084729,"about_ca_topic_score_gemma":0.000009178239,"teacher_disagreement_score":0.9721012,"about_ca_system_score_codex":0.0000058478313,"about_ca_system_score_gemma":0.00002906264,"threshold_uncertainty_score":0.3756783},"labels":[],"label_agreement":null},{"id":"W3200503446","doi":"","title":"Information Visualization for Systems People","year":2002,"lang":"en","type":"article","venue":"USENIX Annual Technical Conference","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visualization; Computer science; Information visualization; Information system; Human–computer interaction; Artificial intelligence; Engineering","score_opus":0.035236021026322104,"score_gpt":0.2951441122454369,"score_spread":0.2599080912191148,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3200503446","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00022593209,0.00002543004,0.99583817,0.00047893336,0.00020483136,0.00032352307,0.00009261506,0.0005012391,0.002309333],"genre_scores_gemma":[0.9925307,0.00005642239,0.0061018066,0.0004768598,0.000050596605,0.000057428133,0.00012419488,0.000007712938,0.0005942917],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988606,0.000037996655,0.00038354972,0.0001888593,0.0002982356,0.00023076768],"domain_scores_gemma":[0.9987361,0.0000898415,0.00014592889,0.00041568952,0.00050761487,0.0001048295],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021638238,0.00012801863,0.00016968558,0.00013693054,0.00012848445,0.00048778826,0.00069829024,0.00010872294,0.000044097465],"category_scores_gemma":[0.00032400846,0.000120120385,0.00005059685,0.0005295588,0.00003113162,0.0020548815,0.0001595439,0.00007387127,0.00017154143],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000018985393,0.000054536315,0.00006733854,0.000029805473,0.0000051581846,2.8929406e-7,0.00060661696,0.00005643463,0.00006521995,0.96741325,0.02601849,0.005680964],"study_design_scores_gemma":[0.0003191996,0.00012323927,0.00022415438,0.000024820854,0.000008349009,0.000010071667,0.0001571709,0.8058801,0.000121653764,0.0010734622,0.1918247,0.00023301499],"about_ca_topic_score_codex":0.000013810924,"about_ca_topic_score_gemma":0.000009127773,"teacher_disagreement_score":0.99230474,"about_ca_system_score_codex":0.000031357788,"about_ca_system_score_gemma":0.000030153851,"threshold_uncertainty_score":0.4898367},"labels":[],"label_agreement":null},{"id":"W3200908759","doi":"10.1007/978-3-030-86062-2_34","title":"The Science of Seeing Science: Examining the Visuality Hypothesis","year":2021,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Thomas University; University of New Brunswick","funders":"","keywords":"Discipline; Space (punctuation); Computer science; Imperfect; Visualization; Data science; Sociology; Social science; Artificial intelligence","score_opus":0.05070707667579359,"score_gpt":0.30571477226864757,"score_spread":0.25500769559285397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3200908759","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000584839,0.0004766636,0.99147886,0.000866561,0.0015992855,0.00025241156,0.0000057335105,0.000073988456,0.0046616355],"genre_scores_gemma":[0.8720224,0.00026695753,0.12451863,0.0019244358,0.00040906313,0.000008518656,0.0000025934646,0.000040861683,0.00080654694],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9929843,0.000085714506,0.0008005458,0.0017820781,0.0033805452,0.00096683827],"domain_scores_gemma":[0.99306184,0.0019030571,0.00061802147,0.0029838933,0.0012234208,0.00020977663],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science"],"consensus_categories":["sts"],"category_scores_codex":[0.009165372,0.0004283413,0.00046300242,0.0008658644,0.002542274,0.0028852182,0.012313569,0.00012624284,0.0000130376275],"category_scores_gemma":[0.0019641616,0.00026651827,0.00011570684,0.0050708707,0.011892967,0.0013449634,0.0050822124,0.0006487997,0.000012422736],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002491677,0.000038179456,0.000077450255,0.000036629488,0.000013033624,0.000023964105,0.0017058703,0.0072734426,0.0033377663,0.3408824,0.000025097026,0.6465837],"study_design_scores_gemma":[0.00020773362,0.00013464798,0.00092768634,0.0005903294,0.000021043581,0.0000736095,0.000011650951,0.8965236,0.03236393,0.065903686,0.0024299284,0.0008121342],"about_ca_topic_score_codex":0.000018894563,"about_ca_topic_score_gemma":0.000030045405,"teacher_disagreement_score":0.88925016,"about_ca_system_score_codex":0.00036370655,"about_ca_system_score_gemma":0.0042562364,"threshold_uncertainty_score":0.9999787},"labels":[],"label_agreement":null},{"id":"W3201716672","doi":"","title":"AIive: Interactive Visualization and Sonification of Neural Network in Virtual Reality","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Sonification; Visualization; Computer science; Human–computer interaction; Virtual reality; Representation (politics); Artificial neural network; Range (aeronautics); Hyperparameter; Artificial intelligence; Multimedia; Engineering","score_opus":0.07143467700214003,"score_gpt":0.2516807783162679,"score_spread":0.18024610131412788,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3201716672","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21490403,0.000026790822,0.78444767,0.000046066914,0.00019512871,0.000112510344,0.000011797679,0.000040794177,0.0002152411],"genre_scores_gemma":[0.9991107,0.00024952466,0.00024237204,0.00006548588,0.000028181668,3.3854658e-7,0.00016958232,0.00000681386,0.00012702546],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986255,0.00026712916,0.00025045683,0.0006317139,0.00007615625,0.000149027],"domain_scores_gemma":[0.9987789,0.00008672628,0.00033063898,0.0005357458,0.00020299536,0.00006504319],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025535154,0.00015161243,0.00025152156,0.00017765172,0.000048097485,0.00011016155,0.00051655236,0.00013961733,0.000010016612],"category_scores_gemma":[0.000066066954,0.00018897226,0.000058168782,0.0007914901,0.00007235855,0.00056566007,0.001077428,0.00021731191,0.0000015681532],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021910086,0.00013490379,0.008264543,0.0000661612,0.0000374834,0.000040493946,0.0010077886,0.48493233,0.000024069566,0.50431645,0.00012865891,0.0010251735],"study_design_scores_gemma":[0.0002352655,0.00002755157,0.0076495907,0.00010696721,0.000020957834,0.0000012002645,0.00034489267,0.9872988,0.000074379015,0.004024561,0.000047732876,0.00016814179],"about_ca_topic_score_codex":0.00016078554,"about_ca_topic_score_gemma":0.00016649076,"teacher_disagreement_score":0.7842066,"about_ca_system_score_codex":0.00008949999,"about_ca_system_score_gemma":0.00011544961,"threshold_uncertainty_score":0.7706065},"labels":[],"label_agreement":null},{"id":"W3202884280","doi":"10.1177/25152459211045334","title":"Doing Better Data Visualization","year":2021,"lang":"en","type":"article","venue":"Advances in Methods and Practices in Psychological Science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Visualization; Computer science; Data science; Data visualization; Focus (optics); Information visualization; Code (set theory); Creative visualization; World Wide Web; Human–computer interaction; Data mining","score_opus":0.13286475681795973,"score_gpt":0.6140051293640173,"score_spread":0.48114037254605757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3202884280","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0021454797,0.002040294,0.98453104,0.0013430492,0.00040859546,0.000052357118,0.0000016471548,0.000027749187,0.009449763],"genre_scores_gemma":[0.029980995,0.0057378616,0.9617992,0.0024170612,0.000029722407,0.0000032460694,0.0000070910787,0.0000025196587,0.000022283735],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974781,0.00067041797,0.00030668342,0.0009823209,0.0002963241,0.0002661535],"domain_scores_gemma":[0.9978304,0.0009298312,0.00025852423,0.00083954,0.00006697618,0.000074724216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0062137134,0.000092823204,0.00014863092,0.00014159287,0.00012016509,0.0004232375,0.0015630891,0.000047749552,0.00003308409],"category_scores_gemma":[0.004610827,0.00007492907,0.000009261178,0.0027418712,0.00027911333,0.006751124,0.0010410233,0.00018854346,0.0000038085943],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003367923,0.00012782951,0.009165596,0.0000087885355,7.161953e-7,0.000038109578,0.00013261577,0.000050777893,0.0012229629,0.1286301,0.00002428065,0.86059487],"study_design_scores_gemma":[0.00061064604,0.00010465916,0.023160033,0.000080634505,0.000006005343,0.00011538124,0.0003271052,0.31175092,0.0011891051,0.0988759,0.5633238,0.0004558236],"about_ca_topic_score_codex":0.000004971149,"about_ca_topic_score_gemma":0.000027247546,"teacher_disagreement_score":0.860139,"about_ca_system_score_codex":0.000017656726,"about_ca_system_score_gemma":0.00004105084,"threshold_uncertainty_score":0.5519924},"labels":[{"model":"gpt","categories":[],"domain":null,"study_design":"not_applicable","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"high"},{"model":"opus","categories":[],"domain":null,"study_design":"not_applicable","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"medium"}],"label_agreement":"agree"},{"id":"W3203187103","doi":"10.11575/prism/39323","title":"Visualizations as Data Input?","year":2021,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Data science","score_opus":0.037173164529702624,"score_gpt":0.30458400562598253,"score_spread":0.2674108410962799,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3203187103","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001375103,0.00067605625,0.9528838,0.010698797,0.0003956579,0.0002327244,0.00016407014,0.00047466665,0.033099126],"genre_scores_gemma":[0.35431245,0.004052886,0.57000566,0.0028682344,0.00012485145,0.00007828226,0.032611147,0.00015590395,0.035790596],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9927445,0.0040618065,0.00065765105,0.0014768121,0.00069662096,0.00036258565],"domain_scores_gemma":[0.98715043,0.00076633703,0.00052961777,0.008561703,0.0027237213,0.00026816153],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.004187566,0.00035312632,0.00039238267,0.0002628095,0.00041244263,0.002644519,0.007152251,0.00027714254,0.00021597317],"category_scores_gemma":[0.0032994375,0.00040347388,0.0001413941,0.0010737851,0.00015662448,0.0008209753,0.014007391,0.0005312179,0.00013675347],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.984103e-7,0.0007114517,0.0004063893,0.00013211681,0.000109100816,0.00001980918,0.00539425,0.00013313966,0.00023999557,0.9574529,0.00912972,0.026270157],"study_design_scores_gemma":[0.0004639566,3.375246e-7,0.00058166916,0.0017169488,0.000076273485,0.000029222692,0.00019425273,0.8456835,0.008873525,0.008103094,0.13337272,0.000904464],"about_ca_topic_score_codex":0.0006417356,"about_ca_topic_score_gemma":0.0009447216,"teacher_disagreement_score":0.94934976,"about_ca_system_score_codex":0.00007878058,"about_ca_system_score_gemma":0.0010367578,"threshold_uncertainty_score":0.9998417},"labels":[],"label_agreement":null},{"id":"W3203764532","doi":"10.1177/14738716211045354","title":"Which emphasis technique to use? Perception of emphasis techniques with varying distractors, backgrounds, and visualization types","year":2021,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund","keywords":"Emphasis (telecommunications); Computer science; Visualization; Perception; Predictability; Visual perception; Human–computer interaction; Data science; Artificial intelligence; Psychology","score_opus":0.01854502352333071,"score_gpt":0.30574905242116773,"score_spread":0.287204028897837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3203764532","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011395152,0.000008160513,0.9869213,0.00015899258,0.0000644663,0.00039012477,0.00003671029,0.0003154159,0.00070967857],"genre_scores_gemma":[0.93929386,0.00015748084,0.058356807,0.0006382779,0.000029770945,0.000052102878,0.0013805442,0.000021363152,0.00006976373],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99824864,0.000113781505,0.0006568835,0.0002832593,0.0005065105,0.00019094037],"domain_scores_gemma":[0.99765223,0.000062218685,0.00036459937,0.00040580495,0.0013996032,0.00011553333],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034669222,0.00020635582,0.00023365027,0.0004856006,0.00017549178,0.00068864255,0.00023705125,0.00013602451,0.000043486867],"category_scores_gemma":[0.00029464898,0.00020062616,0.0000327223,0.0022964324,0.000034262914,0.007601132,0.00015681991,0.00006338416,0.000014126004],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016083202,0.00090019987,0.049333047,0.0014318166,0.0002469658,0.0000077562045,0.02090087,0.0021266525,0.05333201,0.69877994,0.0039173868,0.1688625],"study_design_scores_gemma":[0.0024151194,0.0014318665,0.058756854,0.0017724528,0.00027183446,0.0003433686,0.0031136384,0.39789662,0.43363103,0.0016802521,0.095769204,0.00291777],"about_ca_topic_score_codex":0.00005396992,"about_ca_topic_score_gemma":0.000029285984,"teacher_disagreement_score":0.9285645,"about_ca_system_score_codex":0.00008798007,"about_ca_system_score_gemma":0.0001533376,"threshold_uncertainty_score":0.8181298},"labels":[],"label_agreement":null},{"id":"W3204132069","doi":"","title":"One Picture to Study One Thousand Words: Visualization for Qualitative Research in the Age of Digitalization","year":2021,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Visualization; Visual analytics; Sensemaking; Data science; Computer science; Interactive visualization; Qualitative research; Information visualization; TRACE (psycholinguistics); Data visualization; Cultural analytics; Process (computing); Focus (optics); Human–computer interaction; Interactive visual analysis; Open source; World Wide Web; Data mining; The Internet; Sociology","score_opus":0.10054992294607512,"score_gpt":0.45630560176273827,"score_spread":0.35575567881666315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3204132069","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037040193,0.00023276014,0.9608867,0.0011957284,0.00004536211,0.00041255905,0.000005731935,0.0000123285035,0.00016861378],"genre_scores_gemma":[0.9977942,0.00024045269,0.0013021152,0.0002695783,0.00008176293,0.00001859319,0.00004953016,0.000011784085,0.00023194858],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9966636,0.0011119628,0.00040955248,0.00025358537,0.00075595255,0.0008053804],"domain_scores_gemma":[0.9985914,0.00033982925,0.00012281834,0.00031453394,0.0005903546,0.00004102396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007097895,0.00008935221,0.00018218446,0.0002867942,0.00020001581,0.00032467977,0.00069272664,0.00004038736,0.0000037126101],"category_scores_gemma":[0.0005916963,0.00007485312,0.000047211168,0.0021355909,0.000028470882,0.00039676417,0.00011870816,0.00044799456,0.0000025521301],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003168099,0.001326356,0.0005349239,0.000019524019,0.00010227281,0.000005521571,0.054978818,0.00027523618,0.0003884946,0.93272346,0.00010553633,0.009508145],"study_design_scores_gemma":[0.0024587784,0.0025161426,0.0020417725,0.00015784608,0.00004762906,0.000035789293,0.16860214,0.006720885,0.0012515469,0.81406826,0.0017618391,0.00033736648],"about_ca_topic_score_codex":0.0000111819745,"about_ca_topic_score_gemma":0.0007090367,"teacher_disagreement_score":0.96075404,"about_ca_system_score_codex":0.00022164446,"about_ca_system_score_gemma":0.00092069537,"threshold_uncertainty_score":0.31308946},"labels":[],"label_agreement":null},{"id":"W3204150480","doi":"10.1109/tvcg.2021.3114841","title":"VizSnippets: Compressing Visualization Bundles Into Representative Previews for Browsing Visualization Collections","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visualization; Snippet; Computer science; Pipeline (software); Relevance (law); Information retrieval; World Wide Web; Data visualization; Key (lock); Human–computer interaction; Data mining","score_opus":0.039986493947683305,"score_gpt":0.3469616154669047,"score_spread":0.30697512151922135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3204150480","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000549515,0.00029340177,0.99664134,0.000112454574,0.0010785803,0.00066807907,0.00004830914,0.00050029403,0.00010804573],"genre_scores_gemma":[0.8565525,0.013122655,0.10342596,0.017211206,0.001038142,0.0008424528,0.0024598201,0.00049042766,0.0048568705],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9965752,0.00053110474,0.00090990216,0.0010505104,0.0005455432,0.0003877485],"domain_scores_gemma":[0.9973423,0.00037004423,0.00038414184,0.0006285885,0.0010435189,0.00023144571],"candidate_categories":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00042381368,0.0004271293,0.00048863166,0.0008010931,0.0017705325,0.0013061229,0.00038321575,0.00020844472,0.000027314996],"category_scores_gemma":[0.00005149814,0.00047035242,0.00022660555,0.0036412273,0.00015424636,0.0013376119,0.000028001288,0.00017248579,0.00000578972],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031894913,0.000911297,0.000073573094,0.0003171236,0.00018502552,0.000006121331,0.0032258644,0.0031242012,0.0003679828,0.97860134,0.0037743286,0.009381234],"study_design_scores_gemma":[0.0011199176,0.00023468031,0.000046837617,0.00028032975,0.00010568745,0.000038305236,0.00021767401,0.9667923,0.013226804,0.0028798548,0.014528369,0.000529268],"about_ca_topic_score_codex":0.000032467866,"about_ca_topic_score_gemma":0.00010833732,"teacher_disagreement_score":0.9757215,"about_ca_system_score_codex":0.000090812944,"about_ca_system_score_gemma":0.00021128495,"threshold_uncertainty_score":0.9997748},"labels":[],"label_agreement":null},{"id":"W3205560381","doi":"10.2196/27534","title":"Interactive Visualization Applications in Population Health and Health Services Research: Systematic Scoping Review","year":2021,"lang":"en","type":"article","venue":"Journal of Medical Internet Research","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University; BC Centre for Disease Control; University of British Columbia; Simon Fraser University; University of Waterloo; Toronto Rehabilitation Institute; Toronto Metropolitan University; University Health Network; Université de Sherbrooke; University of Toronto; University of Calgary; McMaster University; Ontario Neurotrauma Foundation; Alberta Health Services","funders":"Canadian Institutes of Health Research; University of Toronto; Toronto Rehabilitation Institute","keywords":"Visualization; Computer science; Data science; Population; Population health; World Wide Web; Medicine; Environmental health; Data mining","score_opus":0.21903100961472333,"score_gpt":0.5882186175579803,"score_spread":0.369187607943257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3205560381","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0033880195,0.22349451,0.69320107,0.076441966,0.0003207519,0.0029119821,0.0000036722508,0.000045253226,0.00019280794],"genre_scores_gemma":[0.6900377,0.2919269,0.0033652144,0.013542308,0.00040037968,0.00010969467,0.0001607183,0.00004007989,0.00041701074],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.992286,0.0030946247,0.0012140103,0.0002535622,0.0028289356,0.00032285947],"domain_scores_gemma":[0.99676156,0.00080650207,0.00044323492,0.00029594224,0.0011827673,0.0005100094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.022015324,0.00007634218,0.00047526113,0.00064342533,0.0001111964,0.00031751936,0.00086465635,0.000059757687,0.00004841777],"category_scores_gemma":[0.0014197687,0.00006027478,0.000040424937,0.0017979942,0.00005984823,0.00055906206,0.00052148686,0.0007305628,0.000008624789],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024425335,0.0015271148,0.009238455,0.6719414,0.00014650056,0.0002815584,0.019010521,0.000012070098,0.00001045014,0.25016427,0.014612281,0.033030946],"study_design_scores_gemma":[0.000493683,0.00038768447,0.0009568764,0.917829,0.0000040241566,0.00027930032,0.0035855933,0.073722094,0.000034360306,0.0018390021,0.0007572279,0.000111201436],"about_ca_topic_score_codex":0.00035026282,"about_ca_topic_score_gemma":0.0006395515,"teacher_disagreement_score":0.68983585,"about_ca_system_score_codex":0.00032403326,"about_ca_system_score_gemma":0.0014918705,"threshold_uncertainty_score":0.7630116},"labels":[],"label_agreement":null},{"id":"W3207577578","doi":"10.5281/zenodo.56702","title":"KymographBuilder: Release 1.2.4","year":2016,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science","score_opus":0.032593766134907484,"score_gpt":0.26103002358907257,"score_spread":0.22843625745416507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3207577578","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013522551,0.000036153157,0.94164765,0.003830947,0.00012222455,0.00017038046,0.00010407066,0.0018305859,0.05090576],"genre_scores_gemma":[0.9866532,0.00034592635,0.00502594,0.0012838453,0.00020425422,3.3342985e-8,0.0005195058,0.0012047909,0.0047624838],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986134,0.00018767145,0.00019075575,0.00039028906,0.00032761856,0.00029026193],"domain_scores_gemma":[0.9986309,0.00002358944,0.000075233846,0.0007032186,0.00036647235,0.00020063327],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004163293,0.00010179348,0.00009040401,0.00024127758,0.0009108858,0.000848669,0.0018554666,0.000037316742,0.003909239],"category_scores_gemma":[0.00044306685,0.0000806274,0.000048786304,0.0007663156,0.000106923006,0.000645616,0.0012991454,0.000078187964,0.009798998],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000074520995,0.000103550046,0.000007715413,0.0000132205105,0.000020852596,0.000013231575,0.00026877937,0.0000050000017,0.0028448906,0.23588848,0.33962575,0.42120108],"study_design_scores_gemma":[0.0003522351,0.00007303641,0.00017072269,0.000021929472,0.0000036394533,0.00004313417,0.000021262442,0.0012867444,0.00061280985,0.0011127397,0.9961648,0.00013696786],"about_ca_topic_score_codex":0.0000025529614,"about_ca_topic_score_gemma":7.286884e-8,"teacher_disagreement_score":0.98530096,"about_ca_system_score_codex":0.000051705487,"about_ca_system_score_gemma":0.0000032761004,"threshold_uncertainty_score":0.99700135},"labels":[],"label_agreement":null},{"id":"W3209423045","doi":"10.23977/acss.2021.050117","title":"Research on Information Visualization Based on User Experience (UX)","year":2021,"lang":"en","type":"article","venue":"Advances in Computer Signals and Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Visualization; Information visualization; Computer science; Human–computer interaction; User experience design; Data visualization; Product (mathematics); Multimedia; Simplicity; Information retrieval; World Wide Web; Artificial intelligence","score_opus":0.056821566422420186,"score_gpt":0.3970957295358454,"score_spread":0.3402741631134252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3209423045","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0026855534,0.00032105081,0.9949093,0.0001332286,0.0005874905,0.0001437532,0.0000047974545,0.0000521278,0.0011627323],"genre_scores_gemma":[0.9943766,0.00026303116,0.0036057218,0.0014787954,0.00011098221,0.000030987965,0.00004430829,0.000006756228,0.00008280991],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981385,0.00034372637,0.00036397195,0.00032775002,0.0006006453,0.00022544044],"domain_scores_gemma":[0.99883515,0.00031864975,0.00009110304,0.0003989625,0.00028182098,0.00007432542],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006667284,0.00011462541,0.00016705197,0.00031555144,0.00013881744,0.0006695651,0.00034311396,0.000051973864,0.000008257191],"category_scores_gemma":[0.00004636052,0.00010291917,0.000021362039,0.0009891215,0.000037790564,0.0017118275,0.00012835942,0.00011107668,0.00003019108],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016669592,0.00022033714,0.0019239617,0.00019304575,0.000005835287,0.00003935472,0.0017667168,0.42096147,0.000048468773,0.5237757,0.0017335755,0.049314853],"study_design_scores_gemma":[0.0002956465,0.00014199085,0.00026551014,0.00027502657,4.998023e-7,0.0000036494373,0.00016453944,0.9485936,0.0003584468,0.00023009483,0.04954582,0.00012516738],"about_ca_topic_score_codex":0.000008412879,"about_ca_topic_score_gemma":0.0000042848765,"teacher_disagreement_score":0.99169105,"about_ca_system_score_codex":0.000040716637,"about_ca_system_score_gemma":0.000058181737,"threshold_uncertainty_score":0.6456632},"labels":[],"label_agreement":null},{"id":"W3209638721","doi":"10.1109/iv53921.2021.00016","title":"ContourDiff: Revealing Differential Trends in Spatiotemporal Data","year":2021,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Visualization; Computer science; Contour line; Differential (mechanical device); Domain (mathematical analysis); Data visualization; Data mining; Overlay; Field (mathematics); Noise (video); Change detection; Pattern recognition (psychology); Artificial intelligence; Cartography; Geography; Mathematics","score_opus":0.0806578132950636,"score_gpt":0.35600997497508513,"score_spread":0.2753521616800215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3209638721","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0029967048,0.00003027809,0.9889823,0.001903346,0.00022620443,0.000015573207,0.000032637334,0.00007598611,0.0057369717],"genre_scores_gemma":[0.9654232,0.000021093574,0.02389218,0.0008914478,0.00009628372,7.1428593e-7,0.0015798083,0.0000062526397,0.008089005],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991305,0.000052186017,0.00019526972,0.00032768573,0.00016348824,0.00013087981],"domain_scores_gemma":[0.99895906,0.000019606006,0.000036692843,0.0008997697,0.00003481329,0.000050082348],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012132511,0.00006390104,0.0001093533,0.00009826847,0.000029592344,0.00020597296,0.00078425586,0.000027940616,0.00040515035],"category_scores_gemma":[0.000039877217,0.000059130383,0.000018622195,0.0005144782,0.000010056096,0.00051153166,0.00072871934,0.00005587891,0.00002134464],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004671548,0.0005306735,0.013468675,0.000027268328,0.000043648968,0.00028805915,0.00051936915,0.00007558318,0.0013797553,0.53405225,0.12077266,0.32883736],"study_design_scores_gemma":[0.00057734846,0.000009473808,0.009086532,0.000017586599,0.0000048033644,0.0000068906047,0.000041955995,0.9654824,0.0013684627,0.00048254087,0.022738116,0.00018389357],"about_ca_topic_score_codex":0.00007444042,"about_ca_topic_score_gemma":0.00048703485,"teacher_disagreement_score":0.96540684,"about_ca_system_score_codex":0.000011672235,"about_ca_system_score_gemma":0.000044055745,"threshold_uncertainty_score":0.44361123},"labels":[],"label_agreement":null},{"id":"W3210385438","doi":"10.1007/s12650-021-00809-4","title":"Neural network training fingerprint: visual analytics of the training process in classification neural networks","year":2021,"lang":"en","type":"article","venue":"Journal of Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Artificial neural network; Computer science; Process (computing); Artificial intelligence; Visualization; Fingerprint (computing); Machine learning; Training (meteorology); Visual analytics; Analytics; Time delay neural network; Pattern recognition (psychology); Data mining","score_opus":0.06650849845540834,"score_gpt":0.35174880660640456,"score_spread":0.2852403081509962,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3210385438","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16066656,0.0002057793,0.8375586,0.00056030136,0.0007891826,0.00008811963,0.000001265958,0.000021027607,0.000109167464],"genre_scores_gemma":[0.998105,0.0000663499,0.0010651845,0.0004352932,0.000277994,0.0000010620028,0.00001278547,0.00001450811,0.000021830008],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99759424,0.00031609522,0.0010534567,0.00021096137,0.0005594835,0.00026574242],"domain_scores_gemma":[0.99774724,0.00013610064,0.0011438082,0.00025220108,0.00063951965,0.00008114372],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00083022565,0.0001452289,0.00033742053,0.00018520877,0.000112503294,0.0001767317,0.00062409404,0.0000935636,0.000010904699],"category_scores_gemma":[0.00047656914,0.000119112454,0.00014008959,0.0024641564,0.000053529242,0.0007556077,0.00011184908,0.00026735483,2.9142356e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015138242,0.00016008227,0.015249942,0.000039551807,0.000035458776,0.000018252558,0.0046593123,0.9372532,0.00034143712,0.020258553,0.00015692542,0.021812165],"study_design_scores_gemma":[0.00040373745,0.00006434406,0.014115022,0.00016545679,0.000028124132,0.00006070697,0.0009574923,0.9831375,0.00025186018,0.0005665511,0.00013121808,0.000118010365],"about_ca_topic_score_codex":0.0000012313619,"about_ca_topic_score_gemma":0.000015806902,"teacher_disagreement_score":0.83743846,"about_ca_system_score_codex":0.000053368774,"about_ca_system_score_gemma":0.00031915886,"threshold_uncertainty_score":0.48572648},"labels":[],"label_agreement":null},{"id":"W3212883308","doi":"","title":"Presenting Temporal vs. Spatial Information in a Meaningful Way","year":2016,"lang":"en","type":"article","venue":"URSCA Proceedings","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Visualization; Range (aeronautics); Distribution (mathematics); Spatial analysis; Feature (linguistics); Space (punctuation); Geovisualization; Cartography; Geography; Data science; Information visualization; Data mining; Remote sensing; Mathematics; Engineering","score_opus":0.01378324652448589,"score_gpt":0.25151519083548757,"score_spread":0.23773194431100167,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3212883308","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11317179,0.000008237708,0.86109835,0.006386908,0.00038322882,0.00031976638,0.000008060474,0.0005071845,0.018116493],"genre_scores_gemma":[0.9962397,0.000005051757,0.0030189103,0.00031059913,0.00006146389,0.0000067660685,0.0000050848894,0.0000046898735,0.0003477239],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990731,0.000004947205,0.00026715355,0.00016766928,0.00026891596,0.00021821471],"domain_scores_gemma":[0.99954957,0.00001634129,0.00013583705,0.000101388316,0.00013556296,0.00006130557],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002811734,0.000089627996,0.00009717161,0.0002039779,0.000052820607,0.00029279696,0.0004734666,0.000043586173,0.000023041743],"category_scores_gemma":[0.00021614823,0.00006561136,0.000024862364,0.00037665362,0.0000219272,0.003333287,0.0002175444,0.00005226597,0.00011972475],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044584078,0.0001734858,0.31295034,0.00018866289,0.000028824583,0.000007765844,0.015211818,0.0000103876755,0.0021381152,0.40601367,0.052952155,0.21028018],"study_design_scores_gemma":[0.0037407014,0.00022997818,0.04064392,0.0005314666,0.000015426729,0.000035111185,0.0005076082,0.6072291,0.01402565,0.011706851,0.32027927,0.0010548804],"about_ca_topic_score_codex":0.00006334966,"about_ca_topic_score_gemma":0.000012118422,"teacher_disagreement_score":0.8830679,"about_ca_system_score_codex":0.00003963994,"about_ca_system_score_gemma":0.000029677698,"threshold_uncertainty_score":0.2823448},"labels":[],"label_agreement":null},{"id":"W3213701454","doi":"10.1007/s42489-021-00087-y","title":"Designing Virtual Spaces for Immersive Visual Analytics","year":2021,"lang":"en","type":"article","venue":"KN - Journal of Cartography and Geographic Information","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Marine Environmental Observation Prediction and Response Network","keywords":"Geospatial analysis; Visualization; Virtual reality; Computer science; Human–computer interaction; Geovisualization; Visual analytics; Heuristics; Analytics; Data visualization; Data science; Scientific visualization; Interactive visual analysis; Information visualization; Artificial intelligence; Geography; Cartography","score_opus":0.009995356729039865,"score_gpt":0.2568105039688456,"score_spread":0.24681514723980572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3213701454","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014564779,0.00036797317,0.98410577,0.00037916546,0.0002895525,0.00006773806,0.000012874748,0.000011041022,0.00020110336],"genre_scores_gemma":[0.975416,0.00089830416,0.022583826,0.0009168907,0.000103036495,0.0000022761742,0.000061297855,0.000005111957,0.000013237829],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882656,0.00004903143,0.00052340276,0.000089233305,0.00033138838,0.00018036488],"domain_scores_gemma":[0.99819624,0.00011035473,0.00048607902,0.00012393342,0.0009608024,0.0001225726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055579375,0.00011682915,0.00020208735,0.0008061146,0.0001970602,0.000476137,0.00021181579,0.00006654668,0.000004819751],"category_scores_gemma":[0.00010360507,0.000105276624,0.00023491535,0.0011152828,0.00006535815,0.002893209,0.000057530393,0.00011864954,0.0000010307338],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026096392,0.00047313192,0.048096232,0.0005146514,0.0020174321,0.00007317776,0.018841939,0.0056567444,0.0034395924,0.70792735,0.011995895,0.2007029],"study_design_scores_gemma":[0.015424931,0.006750581,0.03378731,0.001083746,0.001493976,0.0017550733,0.045863263,0.4572026,0.0506221,0.035203043,0.34790003,0.0029133416],"about_ca_topic_score_codex":0.0000021100784,"about_ca_topic_score_gemma":0.0000022307297,"teacher_disagreement_score":0.9615219,"about_ca_system_score_codex":0.0000059786707,"about_ca_system_score_gemma":0.00009975885,"threshold_uncertainty_score":0.45914},"labels":[],"label_agreement":null},{"id":"W3214288572","doi":"10.1080/13546783.2021.1999327","title":"Investigating lay evaluations of models","year":2021,"lang":"en","type":"article","venue":"Thinking & Reasoning","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Overfitting; Distrust; Computer science; Cognitive psychology; Mean squared prediction error; Mean squared error; Machine learning; Psychology; Function (biology); Econometrics; Artificial intelligence; Statistics; Mathematics; Artificial neural network","score_opus":0.053562441379743815,"score_gpt":0.3362210250929328,"score_spread":0.28265858371318897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3214288572","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014886472,0.00016712751,0.9766073,0.0003148612,0.00010136299,0.000030147989,0.0000024525968,0.00012503698,0.0077652005],"genre_scores_gemma":[0.61713916,0.000012962422,0.3819917,0.0005237221,0.00003092568,0.0000016471007,0.000025251513,0.000007608964,0.00026698367],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998968,0.00009257466,0.00021790291,0.00020475713,0.00038124734,0.00013553751],"domain_scores_gemma":[0.9990898,0.0000958396,0.00013157984,0.00039147746,0.00023808956,0.000053209442],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005838064,0.00006899513,0.00011806227,0.000057578225,0.00016233997,0.00016103104,0.00040763966,0.000031037536,0.000017595881],"category_scores_gemma":[0.0004834864,0.00007195575,0.000040382216,0.0005848592,0.000026994807,0.00053178787,0.00026399866,0.00008764171,0.000008141436],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.9922814e-8,0.000018335599,0.00079690694,0.000013395321,0.000013450996,0.0000031785426,0.0033308757,0.01600434,0.0011405089,0.97294545,0.00018702955,0.0055464413],"study_design_scores_gemma":[0.000105083906,0.0000064903975,0.00030727597,0.0002127919,0.000010850274,0.000008649389,0.00012268306,0.9072813,0.0042455182,0.08744026,0.0001731363,0.000086005246],"about_ca_topic_score_codex":0.000017914625,"about_ca_topic_score_gemma":0.0000047493377,"teacher_disagreement_score":0.8912769,"about_ca_system_score_codex":0.000018892613,"about_ca_system_score_gemma":0.00017865896,"threshold_uncertainty_score":0.29342705},"labels":[],"label_agreement":null},{"id":"W3215623317","doi":"","title":"Exploring a Multi-focus Visual Comparison of Dynamic Graphs","year":2020,"lang":"en","type":"article","venue":"IEEE Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Focus (optics); Computer science; Artificial intelligence","score_opus":0.15850956903143798,"score_gpt":0.380665560077692,"score_spread":0.222155991046254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3215623317","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.044379015,0.0000541646,0.9545166,0.00017987809,0.00041517965,0.00012584192,0.000007565008,0.00026531817,0.000056431007],"genre_scores_gemma":[0.9933848,0.0000667284,0.006245448,0.00017870017,0.00003389804,0.000009789471,0.000048073758,0.000019350131,0.000013251458],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99845606,0.000092421236,0.0005037185,0.00036846442,0.00038374748,0.00019559484],"domain_scores_gemma":[0.99913335,0.000051509218,0.00025592808,0.00024678765,0.00017130216,0.00014115075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012618881,0.0001570556,0.00026261993,0.00019115333,0.00008534124,0.00010722256,0.00050752034,0.000049093655,0.0000122540405],"category_scores_gemma":[0.000121106204,0.00016435988,0.0000739784,0.0014982279,0.00004035888,0.0009819777,0.00010894098,0.00007214029,0.00004747237],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023002597,0.0037921416,0.017009499,0.0007857335,0.00038080488,0.00002416171,0.042788956,0.0149452975,0.12042375,0.6010464,0.0039367513,0.1946365],"study_design_scores_gemma":[0.0007551595,0.0002105341,0.0005712184,0.000025531132,0.0000147661285,3.9673884e-7,0.00019145788,0.9723259,0.025099333,0.00007053999,0.00054795557,0.00018716259],"about_ca_topic_score_codex":0.000013431237,"about_ca_topic_score_gemma":0.000014941442,"teacher_disagreement_score":0.95738065,"about_ca_system_score_codex":0.000024555766,"about_ca_system_score_gemma":0.000044728222,"threshold_uncertainty_score":0.67024016},"labels":[],"label_agreement":null},{"id":"W3217087610","doi":"10.1109/vis49827.2021.9623320","title":"TimeElide: Visual Analysis of Non-Contiguous Time Series Slices","year":2021,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Abstraction; Encoding (memory); Time series; Visualization; Code (set theory); Series (stratigraphy); Underpinning; Sequence (biology); Data mining; Programming language; Artificial intelligence; Machine learning; Set (abstract data type)","score_opus":0.009449962752475916,"score_gpt":0.293123849476112,"score_spread":0.2836738867236361,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3217087610","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015698614,0.000058874753,0.9643572,0.0006655908,0.00008381133,0.000037041955,0.000019052508,0.00012122343,0.018958623],"genre_scores_gemma":[0.7495829,0.00013793804,0.14416037,0.0033895383,0.000086515516,0.000004797309,0.0004984095,0.000022348,0.102117196],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991327,0.000035011493,0.00024135126,0.00024244707,0.00022522463,0.00012325369],"domain_scores_gemma":[0.9992099,0.000035402718,0.00008376668,0.00039578186,0.00021621771,0.000058922928],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00012773536,0.00007968193,0.00025189065,0.0002091111,0.000041014653,0.0001476899,0.00037522442,0.000031252668,0.00091519346],"category_scores_gemma":[0.000041559713,0.0000713191,0.00011670258,0.0022603779,0.00002967729,0.0004952636,0.00022045027,0.000028523176,0.0001486696],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037059825,0.0028537577,0.043096848,0.00025119114,0.013295992,0.00045958924,0.0060222396,0.00861447,0.11281922,0.54376286,0.17848079,0.09030598],"study_design_scores_gemma":[0.00014277351,0.000043713422,0.005578117,0.0000074444133,0.00024505844,0.000003720469,0.00008709401,0.94341666,0.03839222,0.00011320258,0.011793275,0.00017671502],"about_ca_topic_score_codex":0.000027081205,"about_ca_topic_score_gemma":0.000032271695,"teacher_disagreement_score":0.9348022,"about_ca_system_score_codex":0.000006700457,"about_ca_system_score_gemma":0.00007217344,"threshold_uncertainty_score":0.9999981},"labels":[],"label_agreement":null},{"id":"W326479723","doi":"","title":"AUTOMATIC MOTIVIC ANALYSIS INCLUDING MELODIC SIMILARITY FOR DIFFERENT CONTOUR CARDINALITIES: APPLICATION TO SCHUMANN'S OF FOREIGN LANDS AND PEOPLE","year":2005,"lang":"en","type":"article","venue":"The Journal of the Abraham Lincoln Association","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"","keywords":"Motif (music); Computer science; Artificial intelligence; Melody; Gestalt psychology; Theoretical computer science; Mathematics; Topology (electrical circuits); Algorithm; Natural language processing; Combinatorics; Epistemology; Physics; Art; Visual arts","score_opus":0.01727889065036053,"score_gpt":0.2965798602547251,"score_spread":0.27930096960436457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W326479723","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5083286,0.000052821957,0.48840687,0.0028131984,0.00005894287,0.00024762715,0.00002010052,0.000013448426,0.000058385463],"genre_scores_gemma":[0.9975341,0.000029610166,0.0018388135,0.0003277811,0.00012793088,0.000006013664,0.0000044010953,0.000005385172,0.00012596713],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99853444,0.00023455636,0.0005136488,0.0000969359,0.00048152902,0.00013891212],"domain_scores_gemma":[0.99747056,0.00060798944,0.0011848278,0.0002922905,0.00038905645,0.000055300512],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023669023,0.00009671379,0.000341752,0.00017876693,0.00024766327,0.00010190851,0.00065188226,0.000050948656,0.0000035140208],"category_scores_gemma":[0.0005663903,0.00005871916,0.00018468534,0.000642618,0.000014004311,0.00031271446,0.00018148412,0.00010267025,7.434028e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001555569,0.0009207557,0.7302691,0.00038963847,0.0057940045,4.4067679e-7,0.04114278,0.0886909,0.0025602893,0.07575501,0.010589927,0.043731645],"study_design_scores_gemma":[0.00064541004,0.00011758914,0.201744,0.000047126647,0.00089190877,0.0000024344997,0.00050998904,0.7882525,0.0010141884,0.0060974164,0.00056291505,0.000114536066],"about_ca_topic_score_codex":0.000028870105,"about_ca_topic_score_gemma":0.00030103687,"teacher_disagreement_score":0.6995616,"about_ca_system_score_codex":0.00031084399,"about_ca_system_score_gemma":0.000053337182,"threshold_uncertainty_score":0.23944978},"labels":[],"label_agreement":null},{"id":"W33342907","doi":"10.4103/0028-3886.304095","title":"Visualization in the Context of Model Driven Engineering.","year":2005,"lang":"en","type":"article","venue":"Neurology India","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Visualization; Human–computer interaction; Software engineering; Program comprehension; Software visualization; Personalization; Domain (mathematical analysis); Context (archaeology); User interface; Information visualization; Software; Software system; World Wide Web; Component-based software engineering; Programming language; Artificial intelligence","score_opus":0.01697283398101546,"score_gpt":0.2767189156234078,"score_spread":0.2597460816423923,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W33342907","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22494829,0.000030338357,0.76972246,0.004114109,0.00013490023,0.00015537206,0.000008468511,0.00007763656,0.0008084458],"genre_scores_gemma":[0.99316317,0.000010715876,0.00080215425,0.005981299,0.000017654942,0.0000028053307,0.000007243923,0.0000031997051,0.000011749992],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995108,0.000043846037,0.00014238837,0.00011236909,0.00009538767,0.000095180214],"domain_scores_gemma":[0.99965334,0.00005150263,0.000047550446,0.000211351,0.000021765514,0.000014519473],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000116967036,0.00004794572,0.00007084366,0.00010117977,0.000014605022,0.00001560012,0.00046251647,0.00004298629,0.000003930716],"category_scores_gemma":[0.000039209717,0.00003869749,0.000016222797,0.00024951473,0.000019357865,0.00014877385,0.000052555497,0.00007315777,0.00001146822],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004899841,0.00014867319,0.007583852,0.000008352297,0.0000060726065,0.000008853484,0.0044570924,0.10499882,0.0004996325,0.8758102,0.0029446254,0.0035289288],"study_design_scores_gemma":[0.00014513338,0.000036213743,0.0039055191,0.0000011354047,0.000001409272,0.00000436377,0.0000057947454,0.99204266,0.0001899046,0.00010905798,0.0035247032,0.000034112385],"about_ca_topic_score_codex":0.00000242687,"about_ca_topic_score_gemma":0.000011493209,"teacher_disagreement_score":0.88704383,"about_ca_system_score_codex":0.0000033366475,"about_ca_system_score_gemma":0.000020546246,"threshold_uncertainty_score":0.15780377},"labels":[],"label_agreement":null},{"id":"W34378897","doi":"10.18388/pb.2021_374","title":"Modellbildung und Visualisierung: Das Sowinet.de-Wahlmodell","year":2002,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Visualization; Context (archaeology); Representation (politics); Information retrieval; Data visualization; Information visualization; Human–computer interaction; Data mining; Geography; Politics","score_opus":0.03062978587028624,"score_gpt":0.28761749551339344,"score_spread":0.2569877096431072,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W34378897","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006042968,0.00023278603,0.9742629,0.00014910322,0.00019672325,0.0001451425,0.000012314432,0.0003696024,0.018588483],"genre_scores_gemma":[0.98039514,0.00014819927,0.017433181,0.0013544697,0.000076575394,0.0000148496965,0.00008853573,0.000013121709,0.00047591748],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984476,0.00006335886,0.0005568894,0.00017961363,0.0003692512,0.00038326022],"domain_scores_gemma":[0.9988455,0.00004082714,0.00023281702,0.0005175393,0.00020924491,0.00015403575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003982399,0.00018596169,0.00017899016,0.0002835771,0.00026255715,0.0008483004,0.0006992203,0.000105762316,0.00007846073],"category_scores_gemma":[0.00011901742,0.00018564366,0.00007341346,0.00071058446,0.000070404945,0.006929169,0.00018931879,0.000116188356,0.00052019156],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011013783,0.00021251202,0.0008780243,0.0005437132,0.0001326811,0.000011392582,0.039866712,0.08442763,0.00014625072,0.6821912,0.025178436,0.16640042],"study_design_scores_gemma":[0.0002616387,0.000039495197,0.0001611711,0.000052846994,0.000011838203,0.000020195677,0.000119403936,0.96933573,0.00021865722,0.0058546294,0.023688624,0.00023577575],"about_ca_topic_score_codex":0.000037544192,"about_ca_topic_score_gemma":0.000002455619,"teacher_disagreement_score":0.9743522,"about_ca_system_score_codex":0.0002024923,"about_ca_system_score_gemma":0.000053541873,"threshold_uncertainty_score":0.818018},"labels":[],"label_agreement":null},{"id":"W346574303","doi":"10.3102/10769986030004353","title":"No Humble Pie: The Origins and Usage of a Statistical Chart","year":2005,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Chart; Pie chart; Appeal; Brother; Plot (graphics); History; Mathematics; Law; Statistics; Political science","score_opus":0.042396656169007806,"score_gpt":0.37864577538451666,"score_spread":0.3362491192155089,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W346574303","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13843012,0.00050465704,0.85199267,0.007001874,0.00070926297,0.00014114258,0.0008370791,0.0000070902424,0.00037609335],"genre_scores_gemma":[0.6892441,0.0003219557,0.30819717,0.00047707531,0.00037501715,0.0000016492262,0.00003802744,0.000007319032,0.0013377296],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99920636,0.00003201464,0.0003304651,0.00008136932,0.0002594373,0.00009036337],"domain_scores_gemma":[0.9990416,0.00022589814,0.00022370114,0.000089277906,0.0003179106,0.000101607104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002124589,0.000067736524,0.00012487943,0.00005284706,0.000085842694,0.00009665866,0.0001992416,0.000019710484,0.00016884135],"category_scores_gemma":[0.0000923306,0.000045457713,0.000015602165,0.000098474084,0.000118335454,0.0002447669,0.000052996325,0.00009534305,0.000006868682],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000089839505,0.0004928145,0.011624444,0.00002136917,0.00001598067,0.0000037347786,0.00043841504,0.000009272621,0.0002240103,0.92597675,0.03355467,0.027629577],"study_design_scores_gemma":[0.0021740538,0.0018284871,0.39823803,0.00017215364,0.0004148942,0.00081412966,0.00045164503,0.043152686,0.00041874597,0.051540874,0.5000622,0.0007320956],"about_ca_topic_score_codex":0.000022249322,"about_ca_topic_score_gemma":0.0000123139625,"teacher_disagreement_score":0.87443584,"about_ca_system_score_codex":0.000023262399,"about_ca_system_score_gemma":0.00019703055,"threshold_uncertainty_score":0.18537118},"labels":[],"label_agreement":null},{"id":"W349314819","doi":"10.1177/0145482x1410800403","title":"Straight from the Source: Perceptions of Students with Visual Impairments about Graphic Use","year":2014,"lang":"en","type":"article","venue":"Journal of Visual Impairment & Blindness","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":57,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Graphics; Likert scale; Inclusion (mineral); Perception; Computer science; Quality (philosophy); Psychology; Multimedia; Computer graphics; Statistical graphics; Braille; Mathematics education; Social psychology; Computer graphics (images); Developmental psychology","score_opus":0.015136783566053016,"score_gpt":0.3270337027028151,"score_spread":0.3118969191367621,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W349314819","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.715679,0.000024505063,0.28359398,0.0002139289,0.00028077982,0.00015125787,0.000016448363,0.00002547181,0.000014659426],"genre_scores_gemma":[0.9967017,0.00007442315,0.0020011785,0.00075321837,0.00026577804,0.0000035629298,0.000021048767,0.000024484762,0.00015457234],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99629754,0.00037783582,0.000984008,0.00030323837,0.0016710061,0.0003663869],"domain_scores_gemma":[0.99725807,0.0002735489,0.001081226,0.00048910506,0.0006016372,0.00029640176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011589755,0.00029095376,0.0004894181,0.0003220165,0.0002504186,0.00068374485,0.0017629818,0.00009049905,0.000100994024],"category_scores_gemma":[0.000094196046,0.00017713741,0.00024140328,0.00085460494,0.00018070679,0.0014132325,0.00034493936,0.00032698657,0.0000145238555],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000490191,0.029199462,0.93050176,0.000086537984,0.0013820996,0.0000804144,0.010236613,0.0018480776,0.0029680198,0.0019871767,0.008930277,0.012289346],"study_design_scores_gemma":[0.009249967,0.01890646,0.9017204,0.0008391796,0.00054195034,0.0002174704,0.0033580274,0.05603065,0.0010538918,0.00038511006,0.006800431,0.00089648186],"about_ca_topic_score_codex":0.000041402105,"about_ca_topic_score_gemma":0.000023286795,"teacher_disagreement_score":0.28159282,"about_ca_system_score_codex":0.00006739463,"about_ca_system_score_gemma":0.00018564954,"threshold_uncertainty_score":0.72234535},"labels":[],"label_agreement":null},{"id":"W37637453","doi":"10.1097/as9.0000000000000020","title":"Understanding and predicting the affordances of visual logics","year":2012,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario College of Art and Design","funders":"","keywords":"Notation; Affordance; Computer science; Context (archaeology); Cognitive dimensions of notations; Existentialism; Programming language; Cognitive science; Human–computer interaction; Theoretical computer science; Natural language processing; Linguistics; Epistemology; Cognition; Psychology","score_opus":0.13473316993336307,"score_gpt":0.333161032686443,"score_spread":0.19842786275307991,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W37637453","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006273621,0.00006994503,0.9884029,0.00021450223,0.00008312299,0.000022605862,6.020825e-7,0.000028446033,0.0049042637],"genre_scores_gemma":[0.9951503,0.000030034269,0.0045197457,0.00018094016,0.00002726508,2.5234382e-7,6.261451e-7,0.0000011705833,0.00008965757],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996629,0.000016752309,0.000079417136,0.00005279403,0.000097985125,0.000090161826],"domain_scores_gemma":[0.9997626,0.000071697665,0.000041550386,0.00008495231,0.000011118131,0.000028101626],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026628026,0.000030923897,0.000040711122,0.000019686939,0.00007130885,0.000047956873,0.00015086771,0.000010888725,0.000007526901],"category_scores_gemma":[0.000027647706,0.000017833538,0.000009075181,0.00013880362,0.0000415335,0.0003494497,0.00012259845,0.000021746377,0.0000012310509],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.0219409e-7,0.000014802539,0.03159599,0.0000055105693,0.0000042210336,5.2214215e-8,0.0005748604,0.000008751069,0.0000374696,0.96671987,0.0003391896,0.0006990715],"study_design_scores_gemma":[0.00025320865,0.00008394567,0.008292364,0.000029610213,0.00001616752,0.000012568869,0.0058602523,0.9630134,0.0025789393,0.016037786,0.0036425572,0.00017916871],"about_ca_topic_score_codex":0.000003291063,"about_ca_topic_score_gemma":0.0000022361417,"teacher_disagreement_score":0.9888767,"about_ca_system_score_codex":0.000006361944,"about_ca_system_score_gemma":0.000006993533,"threshold_uncertainty_score":0.07272305},"labels":[],"label_agreement":null},{"id":"W37642680","doi":"","title":"The Bridge project: A visualisation exercise on Free Associationand internet query and search procedures","year":2007,"lang":"en","type":"article","venue":"Sabanci University","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Zoom; The Internet; Visualization; Bridge (graph theory); Process (computing); Computer graphics; Virtual reality; Association (psychology); World Wide Web; Information retrieval; Human–computer interaction; Computer graphics (images); Multimedia; Artificial intelligence; Psychology","score_opus":0.025775258446333906,"score_gpt":0.28609583260755944,"score_spread":0.26032057416122556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W37642680","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.51396215,0.00014980839,0.4706518,0.0023579346,0.00036977412,0.00073010416,0.00007626687,0.00034490388,0.011357214],"genre_scores_gemma":[0.99554545,0.00011240528,0.00050694327,0.00018471669,0.000033133674,2.1091218e-7,0.000017853788,0.000003918804,0.0035953952],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99929696,0.000041915493,0.000077041404,0.00018702964,0.00024427497,0.00015275482],"domain_scores_gemma":[0.9994538,0.00012519801,0.00005431564,0.00021496828,0.000105341074,0.00004638067],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000524444,0.00006343972,0.000059738166,0.00009854571,0.0002454224,0.0001256865,0.0004290866,0.00003713118,0.00000197162],"category_scores_gemma":[0.0001238552,0.000053784777,0.000021253296,0.0003283667,0.00005391152,0.0003334565,0.00023372668,0.000075295764,0.000007988558],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014412892,0.0002430036,0.03827562,0.00005774742,0.00005431591,0.000046026562,0.009412092,0.000013560618,0.000091263646,0.82025534,0.09442311,0.036983818],"study_design_scores_gemma":[0.0027244147,0.00035198737,0.8008459,0.00023009142,0.000048455033,0.000013286031,0.003221635,0.057207763,0.0024700086,0.0034467515,0.12871002,0.000729694],"about_ca_topic_score_codex":0.00016711222,"about_ca_topic_score_gemma":0.00047926448,"teacher_disagreement_score":0.8168086,"about_ca_system_score_codex":0.00009794126,"about_ca_system_score_gemma":0.00010858319,"threshold_uncertainty_score":0.21932796},"labels":[],"label_agreement":null},{"id":"W39042619","doi":"10.1371/journal.pgph.0003496","title":"Innovations in visualization","year":2013,"lang":"en","type":"article","venue":"Graphics Interface","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Visualization; Focus (optics); Information visualization; Data science; Human–computer interaction; World Wide Web; Everyday life; Data visualization; Internet privacy; Multimedia; Artificial intelligence; Epistemology","score_opus":0.028241508507078187,"score_gpt":0.3221411870749466,"score_spread":0.2938996785678684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W39042619","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01753798,0.000023008954,0.9792432,0.0009773233,0.00015002044,0.0001027478,0.0000014592617,0.000110902896,0.0018533247],"genre_scores_gemma":[0.99560106,0.000024342136,0.0030650736,0.0009855782,0.000010908265,0.000012259374,0.000013446558,0.0000059241233,0.0002814241],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992673,0.000033351185,0.00022917661,0.00019030014,0.00014238797,0.00013750677],"domain_scores_gemma":[0.9994123,0.000027283693,0.000057001263,0.0003084925,0.00016003818,0.00003488646],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014362778,0.00007325575,0.00007304793,0.00035846076,0.000043118514,0.00021340587,0.0004774126,0.000042183518,0.00007508752],"category_scores_gemma":[0.000072710165,0.00007278469,0.000017368171,0.0019204797,0.000028752429,0.00077183184,0.00013998241,0.000084886924,0.00020308491],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.860449e-7,0.000046557565,0.0025800006,0.000004556828,0.0000033382696,4.4517463e-7,0.00026677814,0.00011200533,0.00031774497,0.9896103,0.005415968,0.0016420915],"study_design_scores_gemma":[0.0003127063,0.000042944615,0.00967356,0.00004372297,0.0000019772963,0.0000037026982,0.000111730646,0.8966186,0.0026560987,0.07336146,0.016905718,0.00026778434],"about_ca_topic_score_codex":0.00006512654,"about_ca_topic_score_gemma":0.000036859215,"teacher_disagreement_score":0.97806305,"about_ca_system_score_codex":0.000017059816,"about_ca_system_score_gemma":0.00002237221,"threshold_uncertainty_score":0.29680738},"labels":[],"label_agreement":null},{"id":"W39104023","doi":"10.1007/978-90-481-8816-1_2","title":"A History of Visualization in Psychology and Science","year":2010,"lang":"en","type":"book-chapter","venue":"Models and modeling in science education","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Visualization; Psychological science; Perception; Object (grammar); Phenomenon; Psychology; Epistemology; Visual thinking; Cognitive science; Cognitive psychology; Computer science; Social psychology; Artificial intelligence; Philosophy; Mathematics education","score_opus":0.10364040082354083,"score_gpt":0.3774717854210719,"score_spread":0.2738313845975311,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W39104023","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007145281,0.0026815422,0.921646,0.00024108289,0.0013948756,0.00028551207,0.0000026912696,0.000030710275,0.06657228],"genre_scores_gemma":[0.9468995,0.005464364,0.03531187,0.0008747099,0.000069068345,0.000013845416,0.000016584658,0.000026781549,0.011323288],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99826944,0.000009673482,0.0003935979,0.00071185647,0.00041784436,0.00019761732],"domain_scores_gemma":[0.99895954,0.000014289657,0.0001781863,0.00042843,0.00032082517,0.00009874554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001340562,0.00013937325,0.00019476168,0.0014976019,0.00007512908,0.000092937786,0.0006685547,0.00012382542,0.0000036302768],"category_scores_gemma":[0.0000686313,0.00014609454,0.000013403249,0.00037449104,0.0009127631,0.0013987492,0.0002346274,0.0001865457,6.949097e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000017232366,0.000056631583,0.000027955544,0.000029130693,5.0906044e-7,2.750225e-7,0.0023353675,0.0020931005,0.001868887,0.9535592,0.000020309353,0.040006865],"study_design_scores_gemma":[0.00008194935,0.000017181768,0.000019455392,0.00011046188,0.0000022031936,0.0000038992985,0.000015909403,0.8774204,0.000017683817,0.12120764,0.00096965034,0.00013354994],"about_ca_topic_score_codex":0.000080987375,"about_ca_topic_score_gemma":0.00006562234,"teacher_disagreement_score":0.9397542,"about_ca_system_score_codex":0.00016708327,"about_ca_system_score_gemma":0.003354031,"threshold_uncertainty_score":0.59575623},"labels":[],"label_agreement":null},{"id":"W40033625","doi":"10.1007/978-3-642-25243-3_32","title":"Situational Assessment of Intrusion Alerts: A Multi Attack Scenario Evaluation","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Intrusion detection system; Situation awareness; Network security; Visualization; Computer security; Focus (optics); Attack patterns; Process (computing); Situation analysis; Intelligence analysis; Network monitoring; Data science; Data mining","score_opus":0.0793679378694384,"score_gpt":0.35839041375308917,"score_spread":0.27902247588365076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W40033625","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000055890763,0.00008453669,0.9955934,0.0001972883,0.0008675138,0.0003821416,0.000011304435,0.000054003165,0.0027538822],"genre_scores_gemma":[0.18717667,0.00007263768,0.81099254,0.0010538829,0.00021446636,0.000009704279,0.000099833596,0.00002797115,0.0003523168],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99625355,0.00006613704,0.00064157386,0.0010092403,0.0017174908,0.00031198838],"domain_scores_gemma":[0.99725616,0.00018816326,0.00051810866,0.0010532908,0.0008674313,0.00011685447],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0017201892,0.0003327341,0.00038934575,0.00079124677,0.00015121614,0.00022954018,0.0021149158,0.00021062828,0.00017572402],"category_scores_gemma":[0.00014527046,0.00030435194,0.00009927306,0.00056567305,0.00040310773,0.0006840046,0.0011058169,0.00035660193,0.000024340197],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003671099,0.00018305778,0.0006581189,0.00006293814,0.000026252113,0.000011507704,0.0011033068,0.06438694,0.0001496541,0.07956393,0.00011390237,0.8537367],"study_design_scores_gemma":[0.00034437334,0.00009363956,0.0011277257,0.00028363182,0.000015906302,0.0000122942865,1.2816672e-7,0.97151405,0.0002592352,0.025337134,0.0006874569,0.000324439],"about_ca_topic_score_codex":0.000019804029,"about_ca_topic_score_gemma":0.00008542893,"teacher_disagreement_score":0.9071271,"about_ca_system_score_codex":0.00033309517,"about_ca_system_score_gemma":0.0013827343,"threshold_uncertainty_score":0.9999409},"labels":[],"label_agreement":null},{"id":"W4070980","doi":"10.4018/978-1-59140-051-6.ch003","title":"Cooperative Learning and Virtual Reality-Based Visualization for Data Mining","year":2003,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; University of Ottawa","funders":"","keywords":"Knowledge extraction; Visualization; Computer science; Data mining; Process (computing); Data pre-processing; Data visualization; Domain knowledge; Domain (mathematical analysis); Preprocessor; Data science; Artificial intelligence","score_opus":0.061239118324241365,"score_gpt":0.3420987791353524,"score_spread":0.280859660811111,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4070980","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000021499775,0.00006661028,0.7816868,0.00009869479,0.0001685782,0.0002549822,0.00040158004,0.00012954234,0.21719107],"genre_scores_gemma":[0.03623424,0.00013271748,0.19845426,0.028111627,0.0014233256,0.00010853324,0.011792749,0.0005324711,0.7232101],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982495,0.00006379378,0.00034110696,0.0008025798,0.0003115788,0.00023144683],"domain_scores_gemma":[0.9985603,0.00010829912,0.00028020766,0.00067288836,0.00024395785,0.00013432396],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00036559132,0.000314226,0.00034425207,0.0000810633,0.0002466207,0.0004521388,0.0007106604,0.00022032025,0.0000069691655],"category_scores_gemma":[0.00017965522,0.00032749353,0.000049787042,0.000046816556,0.0000888298,0.000217795,0.0004037631,0.0001222362,0.000009234946],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000071570357,0.0000069179614,0.000006239815,0.00002799261,0.00003709566,0.0000050939707,0.00004683299,0.00009896905,0.0000033795382,0.9818099,0.011214501,0.006735893],"study_design_scores_gemma":[0.00067254907,0.0002438066,0.000001063101,0.00019114169,0.0000734195,0.000009609051,0.000025222836,0.4929223,0.00002859734,0.011351576,0.49394932,0.0005313997],"about_ca_topic_score_codex":0.000008832106,"about_ca_topic_score_gemma":0.00003494441,"teacher_disagreement_score":0.9704583,"about_ca_system_score_codex":0.00007285705,"about_ca_system_score_gemma":0.00026899495,"threshold_uncertainty_score":0.9999177},"labels":[],"label_agreement":null},{"id":"W41345981","doi":"","title":"Synthetic tree models from iterated discrete graphs","year":2012,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Iterated function; Computer science; Tree (set theory); K-ary tree; Graph; Tree structure; Algorithm; Point distribution model; Theoretical computer science; Matching (statistics); Mathematics; Artificial intelligence; Combinatorics; Binary tree; Statistics","score_opus":0.03243633970731092,"score_gpt":0.27938122171014346,"score_spread":0.24694488200283254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W41345981","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0025631587,0.00006581419,0.9794904,0.0002877964,0.00016472863,0.000033484022,0.000014067022,0.00017672303,0.017203819],"genre_scores_gemma":[0.9801676,0.000013511629,0.017710824,0.00078920374,0.000028517741,0.0000018942778,0.0000424857,0.0000056230583,0.0012403397],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931633,0.00003490031,0.0001297888,0.00016891578,0.00015428811,0.00019576107],"domain_scores_gemma":[0.99935293,0.000032306772,0.00003119629,0.00042830646,0.000029323395,0.00012590631],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009263698,0.0000808267,0.00008435049,0.00006166541,0.00004905704,0.00016840972,0.0004436419,0.000027342516,0.00013863122],"category_scores_gemma":[0.000010952428,0.00006173902,0.000037106267,0.00029648747,0.000017807286,0.0012069689,0.00013484828,0.000035481426,0.00018952508],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.149204e-7,0.000053414005,0.00051856437,0.0000015602883,0.000014882736,9.732537e-7,0.0004579411,0.00010076339,0.000202736,0.9898724,0.003664855,0.0051111057],"study_design_scores_gemma":[0.000120751494,0.000008450075,0.00035363736,0.000008207723,0.0000075517432,0.0000012340187,0.000023669638,0.97093266,0.0011156749,0.023135636,0.004148451,0.00014409193],"about_ca_topic_score_codex":0.00004609676,"about_ca_topic_score_gemma":0.000007784396,"teacher_disagreement_score":0.97760445,"about_ca_system_score_codex":0.000006942929,"about_ca_system_score_gemma":0.000009704346,"threshold_uncertainty_score":0.25176442},"labels":[],"label_agreement":null},{"id":"W4200124991","doi":"10.32920/ifmj.v1i2.1497","title":"Nonlinearity, Multilinearity, Simultaneity","year":2021,"lang":"en","type":"article","venue":"Interactive Film and Media Journal","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Simultaneity; Narrative; Context (archaeology); Reading (process); Computer science; Avatar; Hypertext; World Wide Web; Human–computer interaction; Art; Linguistics; Literature; Physics; Philosophy; History","score_opus":0.02387774213487731,"score_gpt":0.3264934194258245,"score_spread":0.3026156772909472,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200124991","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.084164776,0.00047430815,0.9047994,0.004111531,0.003106877,0.00007145553,0.00007391589,0.00008845392,0.0031092688],"genre_scores_gemma":[0.95864487,0.0006433273,0.03689933,0.0022715568,0.00065233256,0.0000010266026,0.000041811316,0.000011139719,0.00083460496],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99906415,0.00009834206,0.00021939627,0.00020702895,0.00024027721,0.0001708114],"domain_scores_gemma":[0.99871,0.00033164234,0.00010268373,0.0001784516,0.00044780917,0.00022940831],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002110571,0.00009913858,0.00014703635,0.00007547149,0.00013776546,0.00047826933,0.0002860819,0.0000455256,0.00015920085],"category_scores_gemma":[0.0010753954,0.00008596439,0.000057003053,0.00019451819,0.000041729316,0.00078162807,0.00032507718,0.00037407232,0.000031527856],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013526413,0.0030615604,0.029381271,0.00011612245,0.0006386463,0.006672196,0.023869125,0.0005527008,0.010276155,0.052862506,0.041547798,0.83088666],"study_design_scores_gemma":[0.0016177878,0.00008478964,0.0079396935,0.00013289934,0.0000320342,0.0024087632,0.0009812717,0.8529945,0.01129346,0.0055107498,0.11661351,0.00039054395],"about_ca_topic_score_codex":0.000004450841,"about_ca_topic_score_gemma":0.000034645134,"teacher_disagreement_score":0.87448007,"about_ca_system_score_codex":0.00002347863,"about_ca_system_score_gemma":0.00016081907,"threshold_uncertainty_score":0.4611962},"labels":[],"label_agreement":null},{"id":"W4200292339","doi":"10.3390/info13010008","title":"Interfaces for Searching and Triaging Large Document Sets: An Ontology-Supported Visual Analytics Approach","year":2021,"lang":"en","type":"article","venue":"Information","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Ontology; Visual analytics; Triage; Workflow; Analytics; Interface (matter); Information retrieval; Set (abstract data type); Domain (mathematical analysis); Data science; World Wide Web; Visualization; Data mining; Database","score_opus":0.030077955309139034,"score_gpt":0.35096850397299817,"score_spread":0.32089054866385913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200292339","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018821554,0.000014598839,0.9800132,0.00029276262,0.00008290292,0.00012581663,0.000019863284,0.00007327499,0.0005560331],"genre_scores_gemma":[0.92246634,0.000020304831,0.074896105,0.0013751069,0.000026859005,0.0000120347495,0.0011145537,0.000004798479,0.00008388073],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99919045,0.000047692913,0.0002916261,0.00013101785,0.0001633057,0.00017593519],"domain_scores_gemma":[0.99944824,0.000039073228,0.000112586036,0.0001807081,0.00014821655,0.00007116981],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053178624,0.00007723446,0.00011064581,0.00012883355,0.00013833598,0.0006141651,0.00018562832,0.000038463877,0.0000075653675],"category_scores_gemma":[0.00010153988,0.00007404977,0.000022043727,0.00022924837,0.000014004849,0.0035078088,0.00015240393,0.00006247315,0.0000059187228],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006645893,0.0004722379,0.0033581802,0.0006133282,0.00022017732,0.0000070698693,0.030161679,0.0034048154,0.00031932833,0.5377458,0.0045416993,0.41908923],"study_design_scores_gemma":[0.00060374005,0.000060212802,0.00029272688,0.000010356244,0.000009944326,0.000012433379,0.0011962374,0.9866141,0.0006817097,0.0008258576,0.009593745,0.000098949895],"about_ca_topic_score_codex":0.000005521509,"about_ca_topic_score_gemma":0.000010392138,"teacher_disagreement_score":0.98320925,"about_ca_system_score_codex":0.000027415397,"about_ca_system_score_gemma":0.00007462047,"threshold_uncertainty_score":0.5922408},"labels":[],"label_agreement":null},{"id":"W4200375399","doi":"10.1177/15291006211051956","title":"The Science of Visual Data Communication: What Works","year":2021,"lang":"en","type":"review","venue":"Gothic.net","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":341,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Science North","funders":"National Science Foundation","keywords":"Data science; Computer science; Psychology; Human–computer interaction","score_opus":0.15205838952428227,"score_gpt":0.4405513242665917,"score_spread":0.2884929347423094,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200375399","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[2.6391094e-8,0.9611599,0.03743498,0.00036766767,0.00044156707,0.000160042,0.000022485452,0.00004053812,0.00037279943],"genre_scores_gemma":[0.0000025954519,0.9948707,0.003955587,0.00017066752,0.000059575093,0.0000074562868,0.0006464131,0.000013498971,0.00027345965],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9972785,0.00039602313,0.0006713747,0.0006321238,0.0007365439,0.0002854395],"domain_scores_gemma":[0.9923294,0.00065132615,0.00056271296,0.006053768,0.00030198408,0.00010078527],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.002624803,0.00022214586,0.00067664724,0.00013294489,0.00049309415,0.003705853,0.013289639,0.00014045177,0.000028543112],"category_scores_gemma":[0.0005006973,0.00015276395,0.00011440976,0.0024359466,0.0006992741,0.0028632618,0.006908386,0.00043047377,0.00006393823],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.00635965e-7,0.000030780677,7.648034e-8,0.00035897744,0.000024061366,0.0000015166381,0.000055215653,0.0000022359313,4.346435e-8,0.042710043,0.0059184465,0.9508985],"study_design_scores_gemma":[0.00003667113,0.0000096057975,1.6444946e-7,0.011703951,0.000061617575,0.000013960972,0.00008380972,0.015058656,0.0000010584461,0.00011488951,0.9727475,0.00016812616],"about_ca_topic_score_codex":0.000007983049,"about_ca_topic_score_gemma":0.00001242163,"teacher_disagreement_score":0.96682906,"about_ca_system_score_codex":0.000046594363,"about_ca_system_score_gemma":0.0015068941,"threshold_uncertainty_score":0.9973284},"labels":[],"label_agreement":null},{"id":"W4200507709","doi":"10.4300/jgme-d-21-00944.1","title":"Making Your Educational Data Visual","year":2021,"lang":"en","type":"article","venue":"Journal of Graduate Medical Education","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal College of Physicians and Surgeons of Canada; University of Saskatchewan","funders":"","keywords":"Computer science; Visualization; Data visualization; Data science; Process (computing); Information retrieval; Information visualization; Data mining","score_opus":0.1878149046086034,"score_gpt":0.471404300084105,"score_spread":0.2835893954755016,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200507709","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015390631,0.0010928181,0.7924386,0.18154584,0.007617997,0.000059538772,0.00000842135,0.00002956563,0.00181656],"genre_scores_gemma":[0.8903693,0.00079261354,0.08610515,0.016313082,0.0040305224,0.0000021820845,0.00044734785,0.000022367565,0.0019174225],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978983,0.0001258964,0.0005210056,0.00020096004,0.0011194197,0.0001344529],"domain_scores_gemma":[0.9980769,0.000103284634,0.00035941572,0.00045281087,0.0007518922,0.000255668],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009645027,0.00008041241,0.000150828,0.00014662324,0.00007946022,0.00020555634,0.0012748747,0.000050018363,0.00035438352],"category_scores_gemma":[0.0037988585,0.000070001835,0.000050363116,0.00055253605,0.000037651134,0.00092778465,0.00032044848,0.00024372207,0.000036697296],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000067295255,0.002420166,0.0023496265,0.000059277965,0.00009284614,0.0000618341,0.0008565393,0.000013544705,0.00011419496,0.13555823,0.4528568,0.4056102],"study_design_scores_gemma":[0.0017711374,0.000249537,0.032223355,0.0014617242,0.00018600235,0.005565781,0.002276909,0.35214508,0.00072737725,0.05772691,0.5448192,0.0008469793],"about_ca_topic_score_codex":0.00000343744,"about_ca_topic_score_gemma":0.0000042373813,"teacher_disagreement_score":0.87497866,"about_ca_system_score_codex":0.000054584667,"about_ca_system_score_gemma":0.0075075226,"threshold_uncertainty_score":0.998119},"labels":[],"label_agreement":null},{"id":"W4200534583","doi":"10.1109/iemcon53756.2021.9623112","title":"BUDI: Building Urban Designs Interactively A Spatial-Based Visualization and Collaboration Platform for Urban Planning","year":2021,"lang":"en","type":"article","venue":"2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Visualization; Computer science; Human–computer interaction; Server; Data visualization; Multimedia; World Wide Web; Artificial intelligence","score_opus":0.020951281482503227,"score_gpt":0.312957527599409,"score_spread":0.29200624611690573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200534583","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016073264,0.0009856794,0.9805494,0.0011588492,0.00009478859,0.00062470825,0.000116764146,0.0002119137,0.00018465836],"genre_scores_gemma":[0.9792682,0.0011751803,0.017519793,0.000638252,0.000022339338,0.00029659402,0.0009999616,0.000014358981,0.0000653281],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983966,0.00007858149,0.00063237624,0.00033873005,0.00020292218,0.00035083457],"domain_scores_gemma":[0.996934,0.00021338215,0.0005264326,0.0006856399,0.0015379246,0.000102631624],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00046606778,0.00024542017,0.00029152888,0.0004885674,0.0005480382,0.00079868676,0.0005935551,0.00025545608,0.000016228338],"category_scores_gemma":[0.00033542054,0.0002736459,0.000040515904,0.0009893405,0.00014612879,0.0031847986,0.00025183716,0.00028801995,0.000004759976],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004070665,0.00012156627,0.00039635916,0.000099263016,0.000069984344,7.062543e-7,0.0047073774,0.00054688845,0.0027908753,0.9107396,0.0023338026,0.07815287],"study_design_scores_gemma":[0.0013767584,0.00048085148,0.00006728986,0.00016806567,0.00004040871,0.000013961205,0.0053769248,0.7622038,0.050190404,0.005150597,0.17443824,0.00049269875],"about_ca_topic_score_codex":0.000011338378,"about_ca_topic_score_gemma":0.00005096256,"teacher_disagreement_score":0.9631949,"about_ca_system_score_codex":0.000132313,"about_ca_system_score_gemma":0.0007237973,"threshold_uncertainty_score":0.99997157},"labels":[],"label_agreement":null},{"id":"W4205109443","doi":"10.24251/hicss.2022.210","title":"A Visual Decision-Support System using Fingerprint Matrices applied to Cyclical Spatio-Temporal Data from Motorsports","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Fingerprint (computing); Computer science; Artificial intelligence; Decision support system; Pattern recognition (psychology); Fingerprint recognition; Computer vision; Data mining","score_opus":0.07085640057220845,"score_gpt":0.3408336671005795,"score_spread":0.26997726652837106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205109443","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13466685,0.000026330294,0.005651342,0.004252879,0.008176754,0.0021500995,0.004516842,0.00047688486,0.84008205],"genre_scores_gemma":[0.9935031,0.000008608621,0.00518935,0.00027781294,0.00039944382,0.00011903175,0.000042170777,0.00003826833,0.00042221465],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.98599905,0.0000891757,0.002424799,0.002584757,0.008007949,0.00089428114],"domain_scores_gemma":[0.9907513,0.00028643114,0.0036242628,0.00080953055,0.0041284636,0.0003999991],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0055510756,0.0008162774,0.0010790983,0.0013363288,0.0019549092,0.0018662254,0.023475762,0.0002011004,0.00016911721],"category_scores_gemma":[0.0001573567,0.0005850811,0.00039159536,0.003502805,0.001030517,0.0032514734,0.009331024,0.0006642312,0.00006409938],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019718178,0.00025506556,0.0055519543,0.00013373063,0.00010967948,0.000003238617,0.0015850216,0.0008864967,0.0005044614,0.9869762,0.00314265,0.0006543308],"study_design_scores_gemma":[0.0013120482,0.0011633799,0.0025453581,0.004337924,0.00012208396,0.00028682733,0.8689003,0.11298303,0.0009480738,0.0018671458,0.0040172758,0.0015165474],"about_ca_topic_score_codex":0.0007771013,"about_ca_topic_score_gemma":0.000024039258,"teacher_disagreement_score":0.98510903,"about_ca_system_score_codex":0.0010185312,"about_ca_system_score_gemma":0.0011112434,"threshold_uncertainty_score":0.9996601},"labels":[],"label_agreement":null},{"id":"W4205252725","doi":"10.1109/cog52621.2021.9619021","title":"StABLE: Analyzing Player Movement Similarity Using Text Mining","year":2021,"lang":"en","type":"article","venue":"2021 IEEE Conference on Games (CoG)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Similarity (geometry); String (physics); Sequence (biology); Data mining; Sequential Pattern Mining; Information retrieval; Data science; Artificial intelligence; Mathematics","score_opus":0.08269248880411519,"score_gpt":0.32742615374054207,"score_spread":0.2447336649364269,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205252725","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.030605217,0.00020027111,0.95832855,0.0011282053,0.00086586364,0.00015896256,0.000060327893,0.00012187583,0.008530743],"genre_scores_gemma":[0.95271724,0.00024537396,0.037695985,0.004366171,0.00022358797,0.000011438653,0.00007631019,0.000033093358,0.0046308166],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977986,0.00014920629,0.00039816592,0.0007218518,0.0004900785,0.00044209746],"domain_scores_gemma":[0.99829674,0.00009707508,0.00017321503,0.00085620006,0.00039042038,0.0001863275],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00030427446,0.0002478253,0.00032012956,0.00015683957,0.00019554583,0.00084737263,0.00067483104,0.00009196791,0.00089001044],"category_scores_gemma":[0.00014086551,0.0002546134,0.000092341266,0.00089619186,0.000048676164,0.0005484655,0.0003191895,0.0002045924,0.00008008804],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046654684,0.0019063832,0.01337576,0.00034348076,0.0010332917,0.0013394182,0.0061592837,0.026868362,0.11879878,0.54319775,0.032415763,0.25451505],"study_design_scores_gemma":[0.00044103552,0.000054491604,0.00056392554,0.00024095837,0.00005374869,0.0000066173334,0.0005097309,0.96731365,0.02220818,0.001125739,0.0070347856,0.00044713772],"about_ca_topic_score_codex":0.00003101007,"about_ca_topic_score_gemma":0.00005899717,"teacher_disagreement_score":0.9404453,"about_ca_system_score_codex":0.000069549176,"about_ca_system_score_gemma":0.0005051123,"threshold_uncertainty_score":0.9999906},"labels":[],"label_agreement":null},{"id":"W4205405110","doi":"10.17760/d20335152","title":"In pennies we trust : but should we?","year":2019,"lang":"en","type":"dissertation","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Storytelling; Viewpoints; Value (mathematics); Public relations; Law and economics; Political science; Computer science; Sociology; Narrative; Art","score_opus":0.044376194530250615,"score_gpt":0.34533477461021156,"score_spread":0.30095858007996096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205405110","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00905092,0.0025580707,0.27991375,0.015845027,0.012395108,0.001363848,0.00012936429,0.0009925037,0.6777514],"genre_scores_gemma":[0.03030441,0.001328883,0.0034808796,0.0015326742,0.00010115999,0.000012261389,0.0009780646,0.00003274174,0.96222895],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99886096,0.000026269208,0.00027224547,0.0003716248,0.00029951215,0.00016937427],"domain_scores_gemma":[0.99925566,0.000034431912,0.00010583223,0.00049256923,0.00006457123,0.000046930672],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010880334,0.00017635014,0.00023000331,0.0002882376,0.00003068549,0.00025628915,0.0009278738,0.00017173553,0.0004288973],"category_scores_gemma":[0.00002682162,0.00015493529,0.000060267284,0.0003944089,0.000008088781,0.00051606,0.000082758976,0.0001724314,0.00074971974],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001057143,0.00016874472,0.00046172302,0.00045164747,0.000034834193,0.000029645453,0.0035372942,0.000059940598,0.00018708031,0.8583901,0.120064095,0.016604349],"study_design_scores_gemma":[0.0011229935,0.00013630868,0.0021233028,0.00067251537,0.000043631375,0.000007821714,0.007829685,0.35937428,0.0041313944,0.0107729705,0.6119928,0.0017923393],"about_ca_topic_score_codex":0.0000842996,"about_ca_topic_score_gemma":0.00042168793,"teacher_disagreement_score":0.8476171,"about_ca_system_score_codex":0.000028248602,"about_ca_system_score_gemma":0.000139573,"threshold_uncertainty_score":0.96363807},"labels":[],"label_agreement":null},{"id":"W4205606434","doi":"10.1007/978-3-030-90439-5_8","title":"Putting Table Cartograms into Practice","year":2021,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Table (database); Artificial intelligence; Data mining","score_opus":0.020523478250309386,"score_gpt":0.29755575248280897,"score_spread":0.2770322742324996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205606434","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000018675497,0.0005551137,0.98793036,0.002298465,0.0014917376,0.00016018873,0.0000036077754,0.00017082263,0.007387862],"genre_scores_gemma":[0.0041959505,0.0001333011,0.98692137,0.006492489,0.00049718784,0.000003969772,0.000035916935,0.00003627426,0.0016835429],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99612033,0.000056310986,0.0005316473,0.0015380783,0.0011670908,0.0005865373],"domain_scores_gemma":[0.9966361,0.0005593076,0.00036240075,0.0015728478,0.00066140865,0.0002079648],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0011598925,0.00042390102,0.0004502084,0.00052638236,0.00034301248,0.0017672327,0.0030194,0.00024592187,0.00003865708],"category_scores_gemma":[0.0006329166,0.0004166928,0.00010123201,0.0013564661,0.00037310325,0.0015105408,0.002226176,0.0006769798,0.0000678691],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.970563e-7,0.00004101619,0.000016611511,0.000042329568,0.000015555177,0.00022969143,0.00074808084,0.0088934265,0.000052217416,0.12189919,0.00019888616,0.867862],"study_design_scores_gemma":[0.00018565377,0.00008101078,0.0000036614165,0.00039625732,0.00001723053,0.00014056607,0.000001021593,0.7992148,0.00071311556,0.067691445,0.13092032,0.0006349256],"about_ca_topic_score_codex":0.00006920709,"about_ca_topic_score_gemma":0.00008439494,"teacher_disagreement_score":0.8672271,"about_ca_system_score_codex":0.00025496876,"about_ca_system_score_gemma":0.0010153985,"threshold_uncertainty_score":0.9998285},"labels":[],"label_agreement":null},{"id":"W4206573774","doi":"10.46692/9781847425737.008","title":"Social alarms (PRS) in North America","year":2022,"lang":"en","type":"other","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Data science; Psychology; History","score_opus":0.01975662781977449,"score_gpt":0.29973511428537575,"score_spread":0.27997848646560125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206573774","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[5.0403537e-7,0.000030811538,0.0993781,0.0003964841,0.00012179843,0.000060102437,0.000030762167,0.00022893585,0.8997525],"genre_scores_gemma":[0.000046659818,0.00006808137,0.0027734449,0.002629472,0.00010676087,0.0000068700724,0.00028088168,0.00006937169,0.99401844],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992744,0.000034887984,0.000107144384,0.00024288267,0.00021320881,0.00012748706],"domain_scores_gemma":[0.9996342,0.0000064816936,0.0000759438,0.0002501916,0.0000056498675,0.000027523916],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000034743152,0.000094962204,0.00013971003,0.00021642131,0.000031484073,0.00006372609,0.0007672854,0.000038754875,0.01956408],"category_scores_gemma":[0.000005943253,0.00009008135,0.00003515326,0.0006932718,0.000018352655,0.000050067945,0.00038305504,0.000103801554,0.00029731216],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.07670196e-7,0.000030311243,0.00033410752,0.000004801454,0.000006053283,0.000008976238,0.00011195715,0.0000031701293,4.2741622e-8,0.014268792,0.97823846,0.0069931955],"study_design_scores_gemma":[0.00007620844,0.0000071159725,0.0000910554,0.000001463596,0.0000015272367,2.9032887e-7,0.00002696867,0.0044609737,9.39045e-8,0.000029802377,0.99518245,0.00012204326],"about_ca_topic_score_codex":0.00015465505,"about_ca_topic_score_gemma":0.0009338387,"teacher_disagreement_score":0.09660465,"about_ca_system_score_codex":0.000027800212,"about_ca_system_score_gemma":0.0000489308,"threshold_uncertainty_score":0.9813322},"labels":[],"label_agreement":null},{"id":"W4206748168","doi":"10.1080/10447318.2021.2016237","title":"Echoing the Gameplay: Analyzing Gameplay Sessions across Genres by Reconstructing Them from Recorded Data","year":2022,"lang":"en","type":"article","venue":"International Journal of Human-Computer Interaction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Human–computer interaction; Psychology","score_opus":0.0840276115429998,"score_gpt":0.3949873294278338,"score_spread":0.310959717884834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206748168","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25970882,0.00009463554,0.7288312,0.0022065304,0.008491017,0.00008129759,0.00028964962,0.00006834088,0.00022857309],"genre_scores_gemma":[0.9804512,0.0000545937,0.016196664,0.0012886155,0.0014302705,0.0000035781425,0.00038718397,0.000022120696,0.00016576282],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972494,0.00032932145,0.0009173889,0.00041337177,0.0008677003,0.0002227822],"domain_scores_gemma":[0.9970077,0.0005074851,0.0013345975,0.0006722183,0.000397299,0.00008067128],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0011103512,0.00018147437,0.00023548091,0.00019941494,0.0006793868,0.0011773504,0.00457519,0.00003602274,0.0004799472],"category_scores_gemma":[0.000112752685,0.00014697472,0.00015010514,0.00027585754,0.000046179128,0.0025109318,0.00226871,0.00073740055,0.000018650973],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017308106,0.0008238333,0.014508521,0.000011992832,0.0021387727,0.00033905485,0.0108928075,0.012450415,0.015228733,0.004994127,0.28575808,0.6526806],"study_design_scores_gemma":[0.0014779209,0.00020127454,0.0008707346,0.00026589882,0.00006974365,0.0019670262,0.0044860886,0.8268303,0.00259057,0.002423676,0.15828483,0.0005318895],"about_ca_topic_score_codex":0.00013578872,"about_ca_topic_score_gemma":0.000024691662,"teacher_disagreement_score":0.81437993,"about_ca_system_score_codex":0.00024665895,"about_ca_system_score_gemma":0.00008355416,"threshold_uncertainty_score":0.9998595},"labels":[],"label_agreement":null},{"id":"W4206796990","doi":"10.1007/978-3-030-92300-6_39","title":"Contextualization of Design Qualities in Interactive Story-Based Visualization Applied to Engineering","year":2021,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Visualization; Novelty; Contextualization; Information visualization; Engineering design process; Human–computer interaction; Context (archaeology); Terminology; Data science; Field (mathematics); Usability; Artificial intelligence; Interpretation (philosophy); Engineering","score_opus":0.028742911557229398,"score_gpt":0.289626012274527,"score_spread":0.2608831007172976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206796990","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000029427933,0.0000677551,0.9986102,0.00014135291,0.00047571317,0.00035670746,0.000008438217,0.00007281272,0.00023757789],"genre_scores_gemma":[0.47114077,0.00002072699,0.52576846,0.0025177537,0.00015259892,0.000025169275,0.000101757614,0.00006366164,0.0002090918],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974523,0.00007971897,0.0005862066,0.0008647241,0.0007057938,0.00031124646],"domain_scores_gemma":[0.99789804,0.00067231955,0.00029093595,0.00066645973,0.00037183333,0.00010041343],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009824197,0.00033266773,0.0004989385,0.0015152781,0.00006199565,0.00027528682,0.0012334309,0.00016909225,0.00001736333],"category_scores_gemma":[0.00035825613,0.000359432,0.000058128495,0.0012856984,0.0001277424,0.00041068532,0.00043655434,0.00028014876,0.0000067208925],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009059732,0.00004198328,0.000014946497,0.00007922286,0.000007750542,0.000011988265,0.0025036337,0.788147,0.0006127396,0.18014956,0.000017941848,0.028404184],"study_design_scores_gemma":[0.0002803545,0.00008626761,0.000032348657,0.00068623904,0.0000046762366,0.0000021862513,0.0000032834025,0.98483545,0.010273677,0.0028898737,0.0005025226,0.00040310796],"about_ca_topic_score_codex":0.000012327428,"about_ca_topic_score_gemma":0.000045478664,"teacher_disagreement_score":0.47284174,"about_ca_system_score_codex":0.0003240511,"about_ca_system_score_gemma":0.00059560634,"threshold_uncertainty_score":0.99988574},"labels":[],"label_agreement":null},{"id":"W4206873235","doi":"10.1007/978-3-030-68766-3","title":"Graph drawing and network visualization 28th international symposium, GD 2020, Vancouver, BC, Canada, September 16–18, 2020 : revised selected papers","year":2021,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Library science; History; Computer science","score_opus":0.007839695639777768,"score_gpt":0.23227419334424856,"score_spread":0.2244344977044708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206873235","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005984356,0.0013463551,0.9340686,0.007493946,0.002458185,0.0005962878,0.000111451365,0.00046006002,0.047480732],"genre_scores_gemma":[0.8401938,0.011228094,0.08516023,0.0036330926,0.00044997426,0.00013968695,0.012876305,0.00023148839,0.04608734],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99375564,0.0028910623,0.0007867888,0.0012341628,0.00087991526,0.00045242958],"domain_scores_gemma":[0.99356127,0.00062363764,0.000715442,0.0017055426,0.0030855325,0.00030855136],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0022365719,0.00044277933,0.00049066835,0.00011743081,0.0004832122,0.0015848993,0.0019334493,0.00025234194,0.0003827972],"category_scores_gemma":[0.00085291656,0.00050828647,0.00014836219,0.0014550026,0.00011521033,0.0004569314,0.002506207,0.0005209568,0.0000057841194],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030882857,0.0011810284,0.026361117,0.0010533493,0.0013060862,0.00014567176,0.010313477,0.01042611,0.0027711752,0.10598627,0.78796995,0.05245487],"study_design_scores_gemma":[0.0015049214,0.0000015474758,0.006185633,0.004421272,0.00019258755,0.0000325594,0.00030162948,0.6603433,0.004713816,0.0012417878,0.3191791,0.0018818603],"about_ca_topic_score_codex":0.02185397,"about_ca_topic_score_gemma":0.34940198,"teacher_disagreement_score":0.8489084,"about_ca_system_score_codex":0.00034446473,"about_ca_system_score_gemma":0.0012394188,"threshold_uncertainty_score":0.99973685},"labels":[],"label_agreement":null},{"id":"W4207058220","doi":"10.32920/16834417.v1","title":"Design And Implementation Of A Geospatial Dashboard For Crime Analysis And Prediction","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Crime analysis; Dashboard; Geospatial analysis; Visualization; Data science; Computer science; Geovisualization; Function (biology); Computer security; Criminology; Data mining; Geography; Cartography; Information visualization; Sociology","score_opus":0.03657848968340807,"score_gpt":0.3507200112355052,"score_spread":0.3141415215520972,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4207058220","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006001511,0.000040458945,0.99337256,0.00011798948,0.00007251972,0.0002706747,0.00007224855,0.000034634504,0.000017418448],"genre_scores_gemma":[0.42611602,0.00025600917,0.5723289,0.00020342901,0.00003547867,0.00004232885,0.0009285773,0.000007261443,0.00008197706],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991018,0.000055334353,0.00026890196,0.00035606287,0.0001400712,0.00007780407],"domain_scores_gemma":[0.9993068,0.000055861918,0.00016112423,0.00026198328,0.00017179716,0.00004241578],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027731596,0.00009362101,0.00021836757,0.0002096453,0.000039554565,0.00023204884,0.000149639,0.00006273774,0.000024035058],"category_scores_gemma":[0.000017164366,0.000091190166,0.000055621833,0.00024675817,0.00001760911,0.00018050362,0.00044372212,0.00004013308,8.419771e-8],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013232365,0.0009277533,0.12180338,0.0048495675,0.017146058,0.000014550074,0.032593228,0.047834378,0.008153068,0.18094246,0.018311517,0.5672917],"study_design_scores_gemma":[0.00026422925,0.000054987428,0.011370177,0.000011828072,0.00047416604,6.0377744e-7,0.00016023559,0.983629,0.003278431,0.0005893332,0.000069742455,0.000097252734],"about_ca_topic_score_codex":0.00018786364,"about_ca_topic_score_gemma":0.000089181325,"teacher_disagreement_score":0.93579465,"about_ca_system_score_codex":0.000011267719,"about_ca_system_score_gemma":0.00008896274,"threshold_uncertainty_score":0.3718627},"labels":[],"label_agreement":null},{"id":"W4207081362","doi":"10.32920/16834417","title":"Design And Implementation Of A Geospatial Dashboard For Crime Analysis And Prediction","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Crime analysis; Dashboard; Geospatial analysis; Visualization; Data science; Computer science; Geovisualization; Computer security; Criminology; Geography; Data mining; Cartography; Information visualization; Sociology","score_opus":0.03657848968340807,"score_gpt":0.3507200112355052,"score_spread":0.3141415215520972,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4207081362","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006001511,0.000040458945,0.99337256,0.00011798948,0.00007251972,0.0002706747,0.00007224855,0.000034634504,0.000017418448],"genre_scores_gemma":[0.42611602,0.00025600917,0.5723289,0.00020342901,0.00003547867,0.00004232885,0.0009285773,0.000007261443,0.00008197706],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991018,0.000055334353,0.00026890196,0.00035606287,0.0001400712,0.00007780407],"domain_scores_gemma":[0.9993068,0.000055861918,0.00016112423,0.00026198328,0.00017179716,0.00004241578],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027731596,0.00009362101,0.00021836757,0.0002096453,0.000039554565,0.00023204884,0.000149639,0.00006273774,0.000024035058],"category_scores_gemma":[0.000017164366,0.000091190166,0.000055621833,0.00024675817,0.00001760911,0.00018050362,0.00044372212,0.00004013308,8.419771e-8],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013232365,0.0009277533,0.12180338,0.0048495675,0.017146058,0.000014550074,0.032593228,0.047834378,0.008153068,0.18094246,0.018311517,0.5672917],"study_design_scores_gemma":[0.00026422925,0.000054987428,0.011370177,0.000011828072,0.00047416604,6.0377744e-7,0.00016023559,0.983629,0.003278431,0.0005893332,0.000069742455,0.000097252734],"about_ca_topic_score_codex":0.00018786364,"about_ca_topic_score_gemma":0.000089181325,"teacher_disagreement_score":0.93579465,"about_ca_system_score_codex":0.000011267719,"about_ca_system_score_gemma":0.00008896274,"threshold_uncertainty_score":0.3718627},"labels":[],"label_agreement":null},{"id":"W4210453740","doi":"10.1111/cgf.14443","title":"A Survey of Tasks and Visualizations in Multiverse Analysis Reports","year":2022,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Data science; Terminology; Variety (cybernetics); Visualization; Archetype; Data mining; Artificial intelligence","score_opus":0.02673716764399995,"score_gpt":0.3004707295011269,"score_spread":0.27373356185712694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210453740","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.030887395,0.00007242157,0.9685368,0.00011355082,0.00016110759,0.00009525186,0.00006335368,0.000041553936,0.000028563907],"genre_scores_gemma":[0.9963434,0.000022656412,0.0029800034,0.00039693055,0.0000035384835,0.0000058733895,0.00022127172,0.0000053360686,0.000021029828],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99860215,0.00022476696,0.00038212378,0.00034957548,0.00027457,0.00016683129],"domain_scores_gemma":[0.9990401,0.00009963723,0.00020343412,0.000471416,0.00012538012,0.0000599963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007356058,0.00009349319,0.00022909843,0.0009800913,0.0001516024,0.00006140849,0.00036584216,0.000025005173,0.000012564762],"category_scores_gemma":[0.000034379216,0.00010412363,0.00007045608,0.004970769,0.000056454126,0.00021329141,0.0009034983,0.00009944065,3.035305e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000024507922,0.00022266859,0.8611952,0.000009058416,0.00014213112,0.00004478708,0.0005835601,0.0062904884,0.0000038700937,0.12884063,0.0013611411,0.0013040055],"study_design_scores_gemma":[0.00013973685,0.000041206426,0.24335238,0.0000025763743,0.000020277648,0.000005900676,0.000028394661,0.75462675,0.0000048945312,0.0006156625,0.0010669987,0.00009521738],"about_ca_topic_score_codex":0.00047700902,"about_ca_topic_score_gemma":0.00081575965,"teacher_disagreement_score":0.9655568,"about_ca_system_score_codex":0.00001651811,"about_ca_system_score_gemma":0.000049396585,"threshold_uncertainty_score":0.42460385},"labels":[],"label_agreement":null},{"id":"W4210558560","doi":"10.33137/js.v4i0.37904","title":"A Diagrammatic Notation for Visualizing Epistemic Entities and Relations","year":2021,"lang":"en","type":"article","venue":"Scientonomy Journal for the Science of Science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"University of British Columbia; University of Victoria; University of Toronto","funders":"Jackman Humanities Institute, University of Toronto; University of Toronto","keywords":"Diagrammatic reasoning; Notation; Ontology; Construct (python library); Computer science; Epistemology; Visualization; Linguistics; Programming language; Artificial intelligence; Philosophy","score_opus":0.038155878849550566,"score_gpt":0.346975675495373,"score_spread":0.30881979664582243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210558560","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022534482,0.00024293149,0.9718188,0.0035510366,0.0012583366,0.00026399508,0.000007652552,0.000017069397,0.00030567736],"genre_scores_gemma":[0.9154911,0.000070967326,0.0831238,0.00017974428,0.000053924112,0.000019026138,0.0000015001382,0.0000047545473,0.0010551852],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978204,0.000025477424,0.00041329185,0.0004186128,0.0008903147,0.0004319508],"domain_scores_gemma":[0.9969641,0.00045690237,0.00035134176,0.0003887773,0.001638972,0.00019988298],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":["sts"],"category_scores_codex":[0.006498425,0.000094092895,0.00013261223,0.0005005654,0.0036842155,0.0019632871,0.0019220549,0.000016759892,0.0000066060447],"category_scores_gemma":[0.002269056,0.000067882516,0.000076876466,0.0035727406,0.003714929,0.0036469204,0.00035740665,0.0000752654,0.0000020448542],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002114824,0.00003463333,0.00013977513,0.000025823114,0.000005495516,4.822771e-7,0.0023008727,0.00086569274,0.03778577,0.9470896,0.00026287214,0.011486877],"study_design_scores_gemma":[0.0004975778,0.00011657519,0.00087893417,0.00008333077,0.00003066707,0.00015108948,0.0035513276,0.8204587,0.05463844,0.11545606,0.0039242352,0.00021302448],"about_ca_topic_score_codex":0.0000030949561,"about_ca_topic_score_gemma":0.000003839723,"teacher_disagreement_score":0.8929566,"about_ca_system_score_codex":0.00011305802,"about_ca_system_score_gemma":0.0019397511,"threshold_uncertainty_score":0.9990728},"labels":[],"label_agreement":null},{"id":"W4210632432","doi":"10.1109/mcg.2021.3132730","title":"Perception, Visual Inference, and Exploratory Visualization","year":2022,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Visualization; Inference; Perception; Exploratory research; Editorial board; Data science; Computer graphics (images); Human–computer interaction; Artificial intelligence; Library science; Psychology","score_opus":0.022105866479836474,"score_gpt":0.30082895201853604,"score_spread":0.27872308553869957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210632432","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010347186,0.00006944636,0.9888378,0.0002283436,0.00010523288,0.0001888819,0.000018724731,0.00014651452,0.00005786922],"genre_scores_gemma":[0.9919775,0.00040240548,0.0046215774,0.0024092167,0.00015449956,0.00024905233,0.00011552257,0.000013971901,0.000056234003],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989926,0.000071435636,0.00020466051,0.0003817638,0.00021591168,0.0001335961],"domain_scores_gemma":[0.999391,0.00005254573,0.00008349473,0.00027112206,0.0000952978,0.00010649128],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019866804,0.00011327944,0.00010810385,0.0002305172,0.0007139072,0.00025759137,0.00031663448,0.000028604962,0.000014175428],"category_scores_gemma":[0.000002127147,0.00012418604,0.000025472978,0.000715488,0.00007891833,0.00031909402,0.00038007856,0.00011056538,0.000006258245],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.230352e-7,0.000117980904,0.0015057533,0.000012865237,0.000010641133,6.8148495e-7,0.0004524718,0.00014078396,0.00010652737,0.9725752,0.0019851017,0.023091258],"study_design_scores_gemma":[0.00026578023,0.00010218566,0.0033892258,0.00000444101,0.000011631563,0.000015510477,0.00014698962,0.8611666,0.000015280199,0.013061005,0.12155501,0.0002663406],"about_ca_topic_score_codex":0.0000053210892,"about_ca_topic_score_gemma":0.0000024962906,"teacher_disagreement_score":0.9842162,"about_ca_system_score_codex":0.000013365563,"about_ca_system_score_gemma":0.000038080852,"threshold_uncertainty_score":0.5490869},"labels":[],"label_agreement":null},{"id":"W4212958358","doi":"10.1145/2468356.2479540","title":"Interacting with microseismic visualizations","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Microseism; Visualization; Human–computer interaction; Data science; Data visualization; Information visualization; Perception; Artificial intelligence; Geology","score_opus":0.012575032683854497,"score_gpt":0.27975156961227543,"score_spread":0.2671765369284209,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4212958358","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0029938743,0.000003177703,0.9853648,0.0008319575,0.00006326137,0.00006071415,4.6037917e-7,0.00016622861,0.01051553],"genre_scores_gemma":[0.9018053,0.000004134639,0.08687744,0.0035507227,0.000024416948,0.000009033428,0.00001705482,0.000008612361,0.007703306],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995461,0.000013646351,0.00010066763,0.00014266765,0.00008790555,0.000109005065],"domain_scores_gemma":[0.9995502,0.000035911038,0.000037895574,0.00022912642,0.000096301395,0.000050546107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003596671,0.000055242726,0.000049347324,0.00006078857,0.000071941686,0.0004036501,0.00031479303,0.000012123168,0.00030764888],"category_scores_gemma":[0.00002218739,0.00003984181,0.000011803088,0.00032429336,0.000014086094,0.0009231194,0.00009682614,0.000031446736,0.0006059318],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.724972e-7,0.0001685761,0.004697579,0.000015245639,0.000033684348,0.000004470483,0.0010347049,0.00038938344,0.003203285,0.8738944,0.096432194,0.020125696],"study_design_scores_gemma":[0.00020391095,0.00004242629,0.0009019759,0.000025193518,0.0000034940983,0.000020223466,0.00020905193,0.9565707,0.0030509871,0.0008104635,0.037963502,0.00019809068],"about_ca_topic_score_codex":0.000057689555,"about_ca_topic_score_gemma":0.0000071859736,"teacher_disagreement_score":0.9561813,"about_ca_system_score_codex":0.000008745691,"about_ca_system_score_gemma":0.000022111746,"threshold_uncertainty_score":0.77882296},"labels":[],"label_agreement":null},{"id":"W4213341543","doi":"10.1109/tcss.2022.3146049","title":"Data Analytics and Visualization of Adaptive Collaboration Simulations","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Computational Social Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nipissing University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Visualization; Visual analytics; Computer science; Analytics; Data visualization; Data science; Complex system; Complex adaptive system; Open source; Scale (ratio); Human–computer interaction; Distributed computing; Data mining; Artificial intelligence; Software","score_opus":0.07174199904608834,"score_gpt":0.3437723361903213,"score_spread":0.27203033714423297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4213341543","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012341412,0.00002542148,0.995814,0.00023538245,0.0004424614,0.00023213546,0.0018503395,0.000074707255,0.00009136237],"genre_scores_gemma":[0.99715185,0.0000036448564,0.0021600504,0.000098073746,0.00004137385,0.000013574753,0.00041606877,0.00001059486,0.00010473793],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99830145,0.00024998834,0.00039641676,0.00031788854,0.00062792766,0.00010635483],"domain_scores_gemma":[0.9989634,0.0002023729,0.00024552736,0.00024450073,0.00029679015,0.000047408812],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028813153,0.00010542984,0.00017426551,0.00024666934,0.00081750954,0.00013090935,0.00043035913,0.000036927642,0.000025644109],"category_scores_gemma":[0.000008600635,0.0001260017,0.00002982217,0.0012854313,0.000051151404,0.00053151307,0.000022234215,0.00009260029,0.0000026133225],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009006749,0.00015134997,0.000018408908,0.000011874835,0.000049980332,6.0272674e-7,0.00063023175,0.8999362,0.000025499347,0.097670294,0.0006135112,0.0008830604],"study_design_scores_gemma":[0.0003225668,0.000090822694,0.00011900588,0.0000058217715,0.000027356627,0.0000035200094,0.00055261835,0.99639374,0.000018521072,0.000925423,0.001419888,0.000120705714],"about_ca_topic_score_codex":0.000047601254,"about_ca_topic_score_gemma":0.000022774624,"teacher_disagreement_score":0.99591774,"about_ca_system_score_codex":0.000102861304,"about_ca_system_score_gemma":0.00018674458,"threshold_uncertainty_score":0.62877053},"labels":[],"label_agreement":null},{"id":"W4214636912","doi":"10.1007/978-3-030-90625-2_29","title":"Interactive Visualization for Design Dialog","year":2022,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Dialog box; Visualization; Computer science; Human–computer interaction; World Wide Web; Artificial intelligence","score_opus":0.06336771390423009,"score_gpt":0.3267184781754614,"score_spread":0.26335076427123133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4214636912","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[3.5057828e-9,0.00001557859,0.6770528,0.00011687075,0.00029054,0.00024483784,0.00003569605,0.00012553019,0.32211813],"genre_scores_gemma":[0.000052125757,0.00010932178,0.058361735,0.0017567979,0.00013806853,0.000044965338,0.0007287641,0.000048447266,0.9387598],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989591,0.000026665548,0.00024978418,0.00040464045,0.00023429765,0.0001255057],"domain_scores_gemma":[0.998982,0.00024097497,0.00019931459,0.0003798898,0.00014469915,0.000053090233],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00019976635,0.00018295091,0.00019662749,0.00019937422,0.00012171007,0.00016902752,0.0006642425,0.00008193391,0.0020379468],"category_scores_gemma":[0.00005606401,0.00018122219,0.000102692095,0.000056163168,0.00001713368,0.00038851815,0.00032192245,0.0000928624,0.000109338784],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000399007,0.000014104022,1.3392264e-7,0.000009024512,0.00002941506,0.0000018534033,0.00007046811,0.00007245747,0.0000033848387,0.9414277,0.05360657,0.00476091],"study_design_scores_gemma":[0.0001591318,0.00009761378,1.9754115e-7,0.000014332907,0.000019445108,0.0000022807642,0.000003565534,0.17832218,0.00006382624,0.11464974,0.70643705,0.0002305999],"about_ca_topic_score_codex":0.0000023663913,"about_ca_topic_score_gemma":0.0000020733044,"teacher_disagreement_score":0.82677794,"about_ca_system_score_codex":0.00009453246,"about_ca_system_score_gemma":0.000136519,"threshold_uncertainty_score":0.9988743},"labels":[],"label_agreement":null},{"id":"W4221058222","doi":"10.1177/14780771221082247","title":"D-ART for collaboration in evaluating design alternatives","year":2022,"lang":"en","type":"article","venue":"International Journal of Architectural Computing","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Mitacs","keywords":"Workflow; Computer science; Analytics; Design science; Software engineering; Systems engineering; Design education; Human–computer interaction; Systems design; Knowledge management; Process management; Engineering management; Data science; Engineering; Database","score_opus":0.05878262652225007,"score_gpt":0.4108037275429185,"score_spread":0.3520211010206684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221058222","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06946589,0.00003887553,0.9267993,0.0023955805,0.001089753,0.000120447294,0.000006846501,0.000015610389,0.00006769835],"genre_scores_gemma":[0.8084493,0.0000016975331,0.19083591,0.00045163726,0.00019221219,0.0000027816857,0.000009322502,0.000005830247,0.000051277206],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982447,0.0002658854,0.00052339473,0.00014565019,0.0006879083,0.00013244979],"domain_scores_gemma":[0.99841803,0.00048021294,0.00052175374,0.00008449269,0.00045825334,0.000037280315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016061584,0.00008083508,0.00013338414,0.00044453552,0.00012724371,0.00020083907,0.0011751417,0.000009735399,0.000014521278],"category_scores_gemma":[0.0004238484,0.00007767737,0.00007035931,0.0003390078,0.000014592023,0.0003443419,0.00034159268,0.00017981963,0.0000012238561],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010427755,0.00007709921,0.00067068316,0.0000046770815,0.00006253725,0.00003445115,0.0035137455,0.881784,0.0018897691,0.013780167,0.0007228141,0.097355776],"study_design_scores_gemma":[0.0009487495,0.0003351187,0.00045282248,0.000031855536,0.0000036413562,0.00019467501,0.00023258351,0.9889204,0.0006683174,0.006039191,0.0020775453,0.000095111995],"about_ca_topic_score_codex":0.0000024652056,"about_ca_topic_score_gemma":0.0000021614346,"teacher_disagreement_score":0.73898345,"about_ca_system_score_codex":0.00017311203,"about_ca_system_score_gemma":0.00016921585,"threshold_uncertainty_score":0.3167591},"labels":[],"label_agreement":null},{"id":"W4221121500","doi":"10.3390/ijgi11040223","title":"Perspective Charts in a Multi-Foci Globe-Based Visualization of COVID-19 Data","year":2022,"lang":"en","type":"article","venue":"ISPRS International Journal of Geo-Information","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Visualization; Bar chart; Perspective (graphical); Computer science; Zoom; Geospatial analysis; Projection (relational algebra); Readability; Scale (ratio); Data visualization; Globe; Data science; Chart; Pie chart; Data mining; Artificial intelligence; Cartography; Geography; Statistics; Mathematics; Engineering","score_opus":0.05323685806349747,"score_gpt":0.3881288464438666,"score_spread":0.3348919883803691,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221121500","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014367354,0.0000393487,0.9934301,0.003574931,0.0008114708,0.00011946216,0.0003040362,0.000022034958,0.00026190747],"genre_scores_gemma":[0.9827976,0.000051356474,0.01131753,0.004886742,0.000071481176,0.0000053862154,0.0008327768,0.000006351722,0.00003076191],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99759436,0.00014031994,0.0008664509,0.0001176521,0.0011627268,0.00011850804],"domain_scores_gemma":[0.9973562,0.000082329876,0.0011612824,0.00031695972,0.0009887307,0.00009454712],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012558617,0.00010007788,0.00016679203,0.0009956012,0.00009605485,0.00018183907,0.0020927624,0.000032234446,0.00013529109],"category_scores_gemma":[0.0009806849,0.00010335675,0.000065835564,0.00060902425,0.000033187072,0.0049705417,0.0005491444,0.00015670383,0.000009829806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006373793,0.0018249628,0.015136001,0.00014471174,0.00037935306,0.00010305802,0.030956425,0.29564303,0.00026445184,0.5985609,0.037038565,0.019311132],"study_design_scores_gemma":[0.0025794948,0.00015723919,0.0014051326,0.00003306218,0.000011902602,0.00007403364,0.0022620996,0.9372463,0.00017077859,0.00096651906,0.054945838,0.00014756023],"about_ca_topic_score_codex":0.00017145938,"about_ca_topic_score_gemma":0.000020973524,"teacher_disagreement_score":0.9821125,"about_ca_system_score_codex":0.00067806453,"about_ca_system_score_gemma":0.00077200966,"threshold_uncertainty_score":0.42147663},"labels":[],"label_agreement":null},{"id":"W4223956787","doi":"10.1007/s11042-022-12307-2","title":"NCCollab: collaborative behavior tree authoring in game development","year":2022,"lang":"en","type":"article","venue":"Multimedia Tools and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Tree (set theory); Video game development; Human–computer interaction; Multimedia; Game design","score_opus":0.03535875926281279,"score_gpt":0.3085923465391242,"score_spread":0.2732335872763114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4223956787","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027663726,0.0006749963,0.9605,0.0026572256,0.0002788981,0.0030193646,0.00043228423,0.00041904955,0.0043544527],"genre_scores_gemma":[0.81918216,0.000094665695,0.16983156,0.0006910628,0.00009046509,0.007974283,0.0004577202,0.000024117944,0.0016539518],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99915683,0.00003434752,0.00020945728,0.00027587728,0.00017945797,0.00014403259],"domain_scores_gemma":[0.9995273,0.000062141036,0.00006123505,0.00022477467,0.000049524573,0.000075055854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016728173,0.00008096898,0.00009898515,0.00010831078,0.00024650324,0.00013787483,0.00034331964,0.000018489642,0.000037632206],"category_scores_gemma":[0.000017032673,0.00008699709,0.000011594468,0.00089859753,0.000024626623,0.00020716267,0.00033322748,0.0000924345,0.000018002685],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002472887,0.00043975704,0.0060895053,0.000009019213,0.000009993147,0.000007689653,0.004028403,0.00029209538,0.000642106,0.071215756,0.0009926512,0.91627055],"study_design_scores_gemma":[0.0008418251,0.00003512669,0.061766878,0.000007081514,0.000010051569,0.000005782795,0.0011113391,0.10192412,0.00093687064,0.00034082233,0.832657,0.00036310928],"about_ca_topic_score_codex":0.000005659725,"about_ca_topic_score_gemma":0.00003206175,"teacher_disagreement_score":0.91590744,"about_ca_system_score_codex":0.00006645424,"about_ca_system_score_gemma":0.00012931548,"threshold_uncertainty_score":0.35476384},"labels":[],"label_agreement":null},{"id":"W4224241337","doi":"10.1111/cgf.14527","title":"Infographics Wizard: Flexible Infographics Authoring and Design Exploration","year":2022,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Infographic; Computer science; Wizard; Representation (politics); Human–computer interaction; Multimedia; World Wide Web; Data mining","score_opus":0.05201679111776838,"score_gpt":0.2832203008529653,"score_spread":0.2312035097351969,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224241337","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00057404547,0.00022869589,0.99549395,0.001808225,0.0008990032,0.00028965523,0.000014479932,0.00056486746,0.00012705768],"genre_scores_gemma":[0.69960546,0.0017792896,0.27969685,0.017502215,0.0003588346,0.00028596332,0.0003644978,0.00013312532,0.00027376993],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99751467,0.00024312569,0.0004642928,0.00059657847,0.00068461854,0.0004967133],"domain_scores_gemma":[0.99848527,0.00015219394,0.00021254894,0.0007793488,0.00015938809,0.00021127239],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009502915,0.00027513277,0.00025465066,0.001118541,0.0011521652,0.0006543839,0.0011720512,0.000083427556,0.000008996849],"category_scores_gemma":[0.000022872162,0.00030828489,0.00012798536,0.003294019,0.00013390649,0.0016021006,0.0017791578,0.0004465308,0.000004985197],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007190688,0.000090746114,0.0038260578,0.000021188824,0.00004908929,0.000013282484,0.00073064223,0.004629685,0.000011959788,0.96962076,0.010365458,0.010633938],"study_design_scores_gemma":[0.0004715629,0.00034934262,0.0005719574,0.000016189846,0.000017835768,0.000039632512,0.00014511714,0.84830356,0.00006702354,0.057581756,0.09198829,0.00044775076],"about_ca_topic_score_codex":0.000009866699,"about_ca_topic_score_gemma":0.0000063236453,"teacher_disagreement_score":0.912039,"about_ca_system_score_codex":0.000026460166,"about_ca_system_score_gemma":0.00010054093,"threshold_uncertainty_score":0.99993694},"labels":[],"label_agreement":null},{"id":"W4225004662","doi":"10.1038/s41598-022-10887-5","title":"Automatic assessment of adverse drug reaction reports with interactive visual exploration","year":2022,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Peking University","keywords":"Computer science; Workflow; Visualization; Multinomial logistic regression; Task (project management); Causality (physics); Adverse drug reaction; Logistic regression; Data mining; Artificial intelligence; Machine learning; Medicine; Database; Drug","score_opus":0.017056003466965237,"score_gpt":0.3193992264424932,"score_spread":0.30234322297552796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225004662","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.60285825,0.00001075648,0.3827345,0.00037115975,0.009974161,0.00067305454,0.000004459107,0.00035969252,0.0030139543],"genre_scores_gemma":[0.99243367,5.825576e-7,0.005849717,0.000037012473,0.000015136183,0.000046550187,0.00017575527,0.000008567958,0.0014330181],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972077,0.00013596728,0.0006593742,0.0006794544,0.0011545247,0.00016295297],"domain_scores_gemma":[0.99749726,0.000030436519,0.0011819736,0.00094444904,0.0002718981,0.00007398816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018848956,0.00011282601,0.00017180934,0.00033805196,0.00042215543,0.00015174196,0.00020645704,0.00001376085,0.0001221381],"category_scores_gemma":[0.00006753251,0.000101844955,0.000057733472,0.00125315,0.00007972507,0.001742407,0.00031903887,0.00012263302,0.0000025914132],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011502154,0.014754011,0.108338706,0.0009444578,0.0011318816,0.029454116,0.071330756,0.14226846,0.20164867,0.056243595,0.26495385,0.10881649],"study_design_scores_gemma":[0.00027984756,0.00027269888,0.004883972,0.00008664846,0.000055429253,0.0017826208,0.003849282,0.9406935,0.012370861,0.006335569,0.028926626,0.00046291843],"about_ca_topic_score_codex":0.000028162904,"about_ca_topic_score_gemma":0.000013138165,"teacher_disagreement_score":0.7984251,"about_ca_system_score_codex":0.00017075309,"about_ca_system_score_gemma":0.00043401416,"threshold_uncertainty_score":0.41531166},"labels":[],"label_agreement":null},{"id":"W4225105538","doi":"10.2196/25249","title":"Data Visualization for Chronic Neurological and Mental Health Condition Self-management: Systematic Review of User Perspectives","year":2021,"lang":"en","type":"review","venue":"JMIR Mental Health","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Institute for Health and Care Research","keywords":"Visualization; Computer science; Thematic analysis; Mental health; Data science; Data visualization; World Wide Web; Psychology; Human–computer interaction; Qualitative research; Data mining; Psychiatry","score_opus":0.06127766974739823,"score_gpt":0.45326164042026873,"score_spread":0.3919839706728705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225105538","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[7.2804056e-8,0.97412556,0.015877377,0.00084313244,0.00017012778,0.0069491128,0.0019307302,0.00008891045,0.000014982492],"genre_scores_gemma":[0.0000013006791,0.98229754,0.0020614828,0.0016546426,0.000044875287,0.00024698896,0.013575145,0.000026959277,0.00009105317],"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","domain_scores_codex":[0.99603355,0.0008929456,0.0013853671,0.000909941,0.00044660643,0.00033157945],"domain_scores_gemma":[0.9971012,0.00009436956,0.0014836891,0.0010678406,0.00007279918,0.00018012217],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0012567654,0.00034013484,0.002083172,0.00017949463,0.0002608358,0.00011698021,0.00095970684,0.00007941505,0.000018957659],"category_scores_gemma":[0.00004034594,0.0002804341,0.00017035619,0.000618889,0.00004559363,0.00044218765,0.00083265983,0.00012232222,0.0000063979296],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.3338115e-7,0.00021398075,1.9234933e-7,0.9209425,0.00010651195,9.1542233e-7,0.00021760823,2.5509342e-8,5.191997e-9,0.044211365,0.016865797,0.017440485],"study_design_scores_gemma":[0.0002688271,0.00038679445,9.1287285e-7,0.44258007,0.00014639682,0.00004726129,0.00012605185,0.003218396,1.9181279e-8,0.000009437674,0.5530051,0.00021071173],"about_ca_topic_score_codex":0.0000036649133,"about_ca_topic_score_gemma":0.0000056286176,"teacher_disagreement_score":0.5361393,"about_ca_system_score_codex":0.0004524253,"about_ca_system_score_gemma":0.000594661,"threshold_uncertainty_score":0.9999648},"labels":[],"label_agreement":null},{"id":"W4225771412","doi":"10.1145/3512896","title":"Abstractions for Visualizing Preferences in Group Decisions","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Situational ethics; Set (abstract data type); Visualization; Preference; Group decision-making; Stakeholder; Task (project management); Preference elicitation; Human–computer interaction; Data science; Order (exchange); Knowledge management; Decision support system; Management science; Decision analysis; Artificial intelligence; Psychology; Engineering; Systems engineering","score_opus":0.11856622844736076,"score_gpt":0.3877788652634,"score_spread":0.26921263681603924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225771412","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88620996,0.00001736074,0.103065446,0.0031630958,0.0034440262,0.0010465067,0.000038056798,0.00025866381,0.0027568627],"genre_scores_gemma":[0.98625576,0.0000045556944,0.01296304,0.00041221522,0.00010610002,0.00009304328,0.000011243176,0.000011007949,0.00014303264],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99868846,0.00001898205,0.00040696363,0.0003558043,0.00035760278,0.00017221592],"domain_scores_gemma":[0.99882704,0.00025564662,0.0003656256,0.0003821011,0.00013631175,0.000033281387],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042330887,0.00012236327,0.00015344714,0.0003415836,0.0004642198,0.00021495401,0.0024218566,0.000028372373,0.000032488195],"category_scores_gemma":[0.0002081894,0.00010333693,0.00011657219,0.00046443264,0.000022536397,0.0008274674,0.0013702288,0.00025009015,0.0000049081946],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013995773,0.0025634558,0.004465522,0.00013825875,0.00012610348,0.0000013146959,0.00601335,0.0064126803,0.024974259,0.7932031,0.07839687,0.0835651],"study_design_scores_gemma":[0.0027789623,0.0022857965,0.035589363,0.0007018622,0.00006931041,0.00007761632,0.003157721,0.6170163,0.021279734,0.21688946,0.099048965,0.0011049202],"about_ca_topic_score_codex":0.000023820554,"about_ca_topic_score_gemma":0.00001158132,"teacher_disagreement_score":0.61060363,"about_ca_system_score_codex":0.00012777952,"about_ca_system_score_gemma":0.000016912612,"threshold_uncertainty_score":0.45004523},"labels":[],"label_agreement":null},{"id":"W4226018502","doi":"10.1145/3545995","title":"EDAssistant: Supporting Exploratory Data Analysis in Computational Notebooks with In Situ Code Search and Recommendation","year":2022,"lang":"en","type":"article","venue":"ACM Transactions on Interactive Intelligent Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Computer science; Context (archaeology); Code (set theory); Exploratory search; Data science; Visualization; Information retrieval; Human–computer interaction; World Wide Web; Data mining; Programming language","score_opus":0.08697835265267972,"score_gpt":0.3651222442131325,"score_spread":0.27814389156045277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4226018502","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016027667,0.000014099573,0.982518,0.00053497776,0.00017604562,0.0002642795,0.00024098303,0.00004255397,0.00018135153],"genre_scores_gemma":[0.99680495,0.000010697807,0.0024333615,0.00012589921,0.000008206877,0.000073580886,0.00042760881,0.000011662486,0.00010404158],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99770725,0.0004784999,0.00057065213,0.00063334854,0.0003970102,0.00021325672],"domain_scores_gemma":[0.9985015,0.0004668957,0.00016370574,0.0006969901,0.000100993224,0.00006995307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008953789,0.00015227908,0.0002611823,0.0011436391,0.00025317265,0.00021547993,0.00087528717,0.000027863907,0.00008652769],"category_scores_gemma":[0.000030317953,0.00015397223,0.000037050515,0.0014601361,0.00003501715,0.0008611544,0.00013114054,0.00040136118,0.000007740463],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025548352,0.0011613043,0.0065826317,0.00006896084,0.00067066506,0.00008564277,0.013932153,0.93628454,0.00020667109,0.0035503798,0.00008006488,0.037121523],"study_design_scores_gemma":[0.0003340055,0.00014137228,0.00074923097,0.00005458123,0.00004043035,0.00002144884,0.010991431,0.9858273,0.00048087735,0.000096425814,0.0010582457,0.00020462896],"about_ca_topic_score_codex":0.00038648926,"about_ca_topic_score_gemma":0.0016669268,"teacher_disagreement_score":0.98077726,"about_ca_system_score_codex":0.00033434434,"about_ca_system_score_gemma":0.000114492446,"threshold_uncertainty_score":0.6278806},"labels":[],"label_agreement":null},{"id":"W4229000427","doi":"10.2196/32456","title":"Exploring Human-Data Interaction in Clinical Decision-making Using Scenarios: Co-design Study","year":2022,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; Connected Health Cities","keywords":"Pulmonary disease; Work (physics); Health professionals; Health care; Decision support system; Space (punctuation); Knowledge management; Clinical decision making; Medicine; Computer science; Engineering; Data mining; Intensive care medicine","score_opus":0.5343941342951667,"score_gpt":0.5162282768176758,"score_spread":0.018165857477490888,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229000427","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8885637,0.0000039912184,0.11031956,0.00000843189,0.00053397275,0.0003742433,0.000011179181,0.00012885692,0.000056073644],"genre_scores_gemma":[0.99827766,0.0000015701194,0.0014467861,0.00008316196,0.00007446375,0.000022506436,0.000055095585,0.000019492185,0.00001926386],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99700177,0.00055615185,0.0007997679,0.0007264461,0.0006503178,0.0002655396],"domain_scores_gemma":[0.9979517,0.00040233176,0.00028225518,0.0012449861,0.00004148596,0.00007724048],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017676703,0.00017426391,0.00027082884,0.0005456828,0.0007249085,0.00042736618,0.0021279587,0.000029705961,0.00017709563],"category_scores_gemma":[0.00016781181,0.00017990195,0.00006109769,0.0007452554,0.000028947468,0.002070771,0.0020617477,0.00046188082,0.000013563844],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000085548374,0.008898658,0.8498785,0.000040147443,0.00020486266,0.00045627964,0.036910497,0.03367693,0.0005913725,0.0065949257,0.00706155,0.055600718],"study_design_scores_gemma":[0.002689326,0.0014945996,0.36587602,0.0002797309,0.000047327307,0.000016028891,0.025144551,0.5922601,0.00005464879,0.0013417575,0.009413141,0.001382759],"about_ca_topic_score_codex":0.000058206475,"about_ca_topic_score_gemma":0.000059846952,"teacher_disagreement_score":0.5585832,"about_ca_system_score_codex":0.00023052703,"about_ca_system_score_gemma":0.0000655185,"threshold_uncertainty_score":0.73361886},"labels":[],"label_agreement":null},{"id":"W4229044053","doi":"10.1016/j.jneb.2022.03.009","title":"Communicating Your Findings Through Graphical Abstracts","year":2022,"lang":"en","type":"editorial","venue":"Journal of Nutrition Education and Behavior","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Psychology","score_opus":0.036489289917221564,"score_gpt":0.3733758971878162,"score_spread":0.33688660727059466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229044053","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007135999,0.002350386,0.0042252983,0.0028528061,0.98252213,0.00034522635,0.00015195197,0.000063505,0.00035272643],"genre_scores_gemma":[0.03083782,0.021475947,0.104971334,0.0017226511,0.8363882,0.0002748134,0.002515232,0.00011420431,0.0016998537],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979153,0.00013500609,0.0007992844,0.00020887311,0.00079687685,0.00014464576],"domain_scores_gemma":[0.99770373,0.00024100144,0.00091726653,0.00036929784,0.00063608127,0.0001326032],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058993994,0.00017018142,0.00030711273,0.00034793085,0.00028284284,0.0004161821,0.0009822372,0.0002347424,0.00010044343],"category_scores_gemma":[0.0003316067,0.00016949918,0.00014260192,0.00040442077,0.000053229716,0.00087132,0.00020590401,0.0010393758,0.000003570443],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000029176394,0.0044933986,0.00005542309,0.00007667595,0.000010686719,0.000007530361,0.00047126555,4.1620933e-7,0.00003938946,0.0013352343,0.9902807,0.0032263927],"study_design_scores_gemma":[0.00047400704,0.00015794336,0.000550966,0.00020567185,0.00012248948,0.000099327845,0.000791056,0.00002042314,0.000026772075,0.0007222728,0.9966441,0.0001850175],"about_ca_topic_score_codex":0.000015609749,"about_ca_topic_score_gemma":0.000001916351,"teacher_disagreement_score":0.14613396,"about_ca_system_score_codex":0.00011539321,"about_ca_system_score_gemma":0.0006128182,"threshold_uncertainty_score":0.6911976},"labels":[],"label_agreement":null},{"id":"W4229068469","doi":"10.33137/ijidi.v6i1.37027","title":"Art of (Data) Storytelling","year":2022,"lang":"en","type":"article","venue":"The International Journal of Information Diversity & Inclusion (IJIDI)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Toronto","keywords":"Storytelling; Interactivity; Narrative; Computer science; Multimedia; Psychology; Art","score_opus":0.03255696766569053,"score_gpt":0.28255022407076275,"score_spread":0.24999325640507222,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229068469","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021413378,0.000071016024,0.96398586,0.009269577,0.0020724747,0.00009818309,0.00014857993,0.000030982097,0.0029099234],"genre_scores_gemma":[0.9892333,0.00014757266,0.006294686,0.0037997004,0.00010928868,3.343494e-7,0.00014304885,0.000002991404,0.0002690439],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975259,0.00007827428,0.00050441216,0.00006182212,0.0017539824,0.000075643155],"domain_scores_gemma":[0.99790627,0.00010095904,0.0009533609,0.00031395903,0.00068068085,0.000044758348],"candidate_categories":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0017714566,0.00006383008,0.000107068336,0.00032916354,0.0007728193,0.00009406572,0.005548835,0.000016350452,0.00028339727],"category_scores_gemma":[0.00011510519,0.000051335144,0.000078971745,0.00027155707,0.00003781903,0.0034243267,0.021192092,0.00019177982,0.00002971521],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047992865,0.00070447585,0.0045807385,0.000040105977,0.0007871899,0.000069257774,0.05833014,0.10012215,0.0006230309,0.24067616,0.47384447,0.119742334],"study_design_scores_gemma":[0.001121018,0.00014102337,0.00059825747,0.000037140326,0.000034456978,0.00017496796,0.0021647883,0.26915377,0.0006262462,0.0032632614,0.72252214,0.00016291249],"about_ca_topic_score_codex":0.000017586732,"about_ca_topic_score_gemma":0.0000021085575,"teacher_disagreement_score":0.9678199,"about_ca_system_score_codex":0.00015475551,"about_ca_system_score_gemma":0.0001460935,"threshold_uncertainty_score":0.9998316},"labels":[],"label_agreement":null},{"id":"W4229519808","doi":"10.1007/978-1-4614-6170-8_110119","title":"Graph Visualization","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Visualization; Graph drawing; Graph; Artificial intelligence; Theoretical computer science","score_opus":0.02523669671853584,"score_gpt":0.28467501968601533,"score_spread":0.2594383229674795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229519808","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[1.3025307e-8,0.000016378472,0.52841836,0.00006908695,0.0001341008,0.000032310963,0.0000025996999,0.00016393364,0.47116318],"genre_scores_gemma":[0.00011567147,0.00012520612,0.0039241742,0.0021474012,0.00011127766,8.9943575e-7,0.00018075005,0.00002388996,0.9933707],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990014,0.000010015382,0.00023725019,0.00034177874,0.00029550627,0.00011406694],"domain_scores_gemma":[0.99903256,0.000022874072,0.00014061807,0.00060983194,0.0001153532,0.000078738594],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00012140711,0.00017804283,0.0001808709,0.00021899429,0.000055523768,0.00020126738,0.00067820546,0.00014912701,0.0006042124],"category_scores_gemma":[0.000012731694,0.00016217506,0.00008486542,0.00006365334,0.000028048402,0.00014232939,0.00020138125,0.00007320284,0.0010585069],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.2731414e-7,0.000002849029,9.84288e-7,0.000008921214,0.000009994541,0.0000012895266,0.000009695227,0.0000037738243,8.635316e-7,0.9437662,0.05067822,0.005517116],"study_design_scores_gemma":[0.00006473551,0.000021129683,0.000001309438,0.000029174473,0.000009573345,0.000002530379,3.789403e-7,0.02938306,0.000017106096,0.087959476,0.8822871,0.00022445217],"about_ca_topic_score_codex":0.0000017784888,"about_ca_topic_score_gemma":0.0000048299094,"teacher_disagreement_score":0.8558067,"about_ca_system_score_codex":0.000015007351,"about_ca_system_score_gemma":0.000036060374,"threshold_uncertainty_score":0.99971926},"labels":[],"label_agreement":null},{"id":"W4229595495","doi":"10.1145/634133.634137","title":"Examining edge congestion","year":2001,"lang":"en","type":"article","venue":"CHI '01 extended abstracts on Human factors in computer systems - CHI '01","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Enhanced Data Rates for GSM Evolution; Computer network; Telecommunications","score_opus":0.09256347964122529,"score_gpt":0.32550352584731945,"score_spread":0.23294004620609415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229595495","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7466949,0.00017117934,0.23373632,0.00012435728,0.008384988,0.0009312366,0.00004680193,0.0011855925,0.008724616],"genre_scores_gemma":[0.9963984,0.000036396745,0.0013226356,0.00033636965,0.0010880625,0.000018187045,0.00021973933,0.00005986533,0.0005203666],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9953348,0.00027846915,0.0013763347,0.001307062,0.00085927505,0.0008440359],"domain_scores_gemma":[0.9970485,0.0002632773,0.000651072,0.0015270489,0.00011551432,0.0003945642],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0008084426,0.00067038956,0.00075677654,0.00080379256,0.0004020551,0.0012295215,0.001777289,0.00029559873,0.000054839053],"category_scores_gemma":[0.00006761125,0.0006327097,0.00015198541,0.00079451065,0.00011130706,0.0011213664,0.00042092358,0.0006445465,0.00016971446],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001732074,0.009811575,0.092571564,0.0015776454,0.0009939579,0.0034250994,0.01844443,0.14109021,0.002508258,0.5206953,0.061964545,0.1467442],"study_design_scores_gemma":[0.003124017,0.00090443186,0.76227796,0.0015294934,0.000040754585,0.00020904414,0.0003016411,0.19987214,0.00063176383,0.001015172,0.027866824,0.0022267906],"about_ca_topic_score_codex":0.00018418093,"about_ca_topic_score_gemma":0.00011453339,"teacher_disagreement_score":0.66970634,"about_ca_system_score_codex":0.00026902746,"about_ca_system_score_gemma":0.00009812082,"threshold_uncertainty_score":0.9998073},"labels":[],"label_agreement":null},{"id":"W4229874843","doi":"10.4018/978-1-4666-0152-9.ch008","title":"How People Approach Graphical Information","year":2012,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Graphics; Typography; Computer science; Graph; Presentation (obstetrics); Information retrieval; Human–computer interaction; World Wide Web; Data science; Computer graphics (images); Theoretical computer science; Advertising","score_opus":0.020070746592120995,"score_gpt":0.24365077787487438,"score_spread":0.2235800312827534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229874843","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[7.8856476e-7,0.000057153167,0.36891523,0.00011277076,0.00021209047,0.00011082134,0.000070082766,0.00015556667,0.6303655],"genre_scores_gemma":[0.41406772,0.00015129846,0.09863202,0.015170076,0.0027022872,0.00008875107,0.0015669256,0.00018198675,0.46743894],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99866235,0.000013817971,0.00026730122,0.00025086122,0.0005259558,0.00027971607],"domain_scores_gemma":[0.9987465,0.000010540472,0.00022866338,0.000674778,0.00013507543,0.00020445236],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012213041,0.0002786298,0.00027605853,0.00011416214,0.00009164891,0.00072085,0.00087855133,0.00030630484,0.0000080387645],"category_scores_gemma":[0.000015618823,0.00026079366,0.00015162239,0.000056375553,0.0000489336,0.0007977658,0.00038500928,0.000195008,0.00020773213],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000011447837,0.00000703297,0.0000116529045,0.000028067963,0.000023036513,9.0651713e-7,0.00007687734,0.0000011588494,1.8701898e-7,0.98288995,0.0056618913,0.011298104],"study_design_scores_gemma":[0.0003114727,0.000043364147,0.000071599694,0.000046007175,0.00005825967,0.00006160444,0.00001737711,0.008306722,0.000005010693,0.26380587,0.7265856,0.00068707124],"about_ca_topic_score_codex":0.00000894596,"about_ca_topic_score_gemma":0.000008984679,"teacher_disagreement_score":0.7209238,"about_ca_system_score_codex":0.00007231073,"about_ca_system_score_gemma":0.000100191755,"threshold_uncertainty_score":0.99998444},"labels":[],"label_agreement":null},{"id":"W4230323307","doi":"10.1057/ivs.2008.28","title":"Building and Applying a Human Cognition Model for Visual Analytics","year":2009,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":84,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"U.S. Department of Homeland Security","keywords":"Visual analytics; Computer science; Visualization; Cultural analytics; Analytics; Human–computer interaction; Data science; Visual reasoning; Cognition; Analytic reasoning; Perception; Interactive visual analysis; Artificial intelligence; Cognitive science; Semantic analytics; Reasoning system; Psychology","score_opus":0.03433443006959723,"score_gpt":0.3538639534782666,"score_spread":0.31952952340866936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230323307","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0021195267,0.0000069455878,0.99661,0.00012979095,0.00004499332,0.00039415318,0.000013190982,0.0002385152,0.000442871],"genre_scores_gemma":[0.95471334,0.0000162539,0.042315193,0.0022647725,0.00004287191,0.000030190244,0.0005688388,0.0000067839474,0.00004177435],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99890953,0.000019637318,0.00045996468,0.00016296712,0.00026450443,0.00018341251],"domain_scores_gemma":[0.99916273,0.000028114642,0.00024976893,0.0001512363,0.0003265843,0.00008154476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032507247,0.00013260116,0.00013138603,0.0003578828,0.0003263853,0.00061232666,0.00019061934,0.00007576989,0.0000025338463],"category_scores_gemma":[0.000108062944,0.00014323123,0.000037346508,0.00047830387,0.000018871002,0.0040909057,0.000048972935,0.000043504708,0.0000065748814],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004434308,0.000040703297,0.000030722276,0.000039900962,0.000008384947,9.5783776e-8,0.00076372223,0.008179309,0.00073322083,0.9572582,0.0005936311,0.032347657],"study_design_scores_gemma":[0.0005346438,0.00008288635,0.00014036015,0.000026525922,0.000018592818,0.0000026784496,0.000047464706,0.97687036,0.0007667353,0.019623403,0.0017056804,0.00018065637],"about_ca_topic_score_codex":0.0000011822525,"about_ca_topic_score_gemma":8.970683e-7,"teacher_disagreement_score":0.96869105,"about_ca_system_score_codex":0.00003646273,"about_ca_system_score_gemma":0.00003796439,"threshold_uncertainty_score":0.590468},"labels":[],"label_agreement":null},{"id":"W4230468999","doi":"10.1007/978-1-4939-7131-2_101442","title":"Visualization Framework","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Visualization; Computer science; Data mining","score_opus":0.032705557953703376,"score_gpt":0.31697576627561297,"score_spread":0.2842702083219096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230468999","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[3.3149604e-8,0.000021240476,0.5411051,0.00007348648,0.00024152099,0.00003683571,0.000004311979,0.00018326736,0.4583342],"genre_scores_gemma":[0.000034190223,0.00012053671,0.03227017,0.0025132496,0.00034741673,8.716688e-7,0.00011113064,0.000028204477,0.9645742],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989119,0.000007955588,0.00024132397,0.00038419594,0.0003250046,0.00012957351],"domain_scores_gemma":[0.9988158,0.000037291993,0.00014337142,0.0007444987,0.00017627167,0.00008280781],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00010385846,0.0001876933,0.00017121153,0.0001546867,0.00006806373,0.00026769316,0.00080119143,0.00027092246,0.005443447],"category_scores_gemma":[0.000038240833,0.00017238958,0.0000694073,0.00007478341,0.000049650305,0.00024367099,0.00031045362,0.00010768931,0.0040576383],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.0772028e-7,0.000004679591,8.022859e-7,0.0000065552335,0.000011917347,0.000002087475,0.000049216957,4.709268e-7,2.9783047e-7,0.90972394,0.088494025,0.001705818],"study_design_scores_gemma":[0.000026454454,0.000024890007,6.784296e-7,0.00006557463,0.000007367196,0.0000018925733,0.0000010822957,0.0138412025,0.00001763268,0.29460734,0.6912181,0.00018778797],"about_ca_topic_score_codex":8.4430917e-7,"about_ca_topic_score_gemma":0.0000021881697,"teacher_disagreement_score":0.6151166,"about_ca_system_score_codex":0.000026208565,"about_ca_system_score_gemma":0.00006137988,"threshold_uncertainty_score":0.9967178},"labels":[],"label_agreement":null},{"id":"W4230687468","doi":"10.1002/asi.20786","title":"Controlled user evaluations of information visualization interfaces for text retrieval: Literature review and meta‐analysis","year":2008,"lang":"en","type":"article","venue":"Journal of the American Society for Information Science and Technology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Usability; Information retrieval; Visualization; Set (abstract data type); Subject (documents); Information visualization; World Wide Web; Human–computer interaction; Data mining","score_opus":0.0268601805584366,"score_gpt":0.35510571258709367,"score_spread":0.3282455320286571,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230687468","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0057055443,0.0028978172,0.9776619,0.01279682,0.000057729634,0.0007703038,0.0000585499,0.000026494863,0.000024855659],"genre_scores_gemma":[0.8248379,0.04233352,0.11294946,0.019603917,0.000027233582,0.00007510359,0.000041547468,0.00000892943,0.00012233357],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986654,0.000022738404,0.0006892285,0.00007264423,0.000438036,0.00011197253],"domain_scores_gemma":[0.9944763,0.00012025869,0.001875088,0.00021711331,0.003273992,0.000037244383],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019097942,0.00008451296,0.0005377701,0.0005801506,0.00031290593,0.00013777245,0.0005944854,0.000038592767,0.0000011818126],"category_scores_gemma":[0.0013106012,0.00005092819,0.00032983493,0.005881215,0.0006882005,0.0046245363,0.00012772276,0.00007395601,2.2608836e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004646227,0.00037123906,0.0020171907,0.003845315,0.058027573,3.61074e-7,0.035545524,0.0020741392,0.003501061,0.75809723,0.07798576,0.058069967],"study_design_scores_gemma":[0.010124121,0.0027865036,0.002490868,0.00037691253,0.11468408,0.0004558529,0.008209162,0.6930928,0.013020674,0.008119374,0.14555955,0.0010800954],"about_ca_topic_score_codex":9.281668e-7,"about_ca_topic_score_gemma":3.2522573e-7,"teacher_disagreement_score":0.8647124,"about_ca_system_score_codex":0.000028884064,"about_ca_system_score_gemma":0.00021840424,"threshold_uncertainty_score":0.33526772},"labels":[],"label_agreement":null},{"id":"W4230836163","doi":"10.4018/978-1-4666-0285-4.ch005","title":"Calligraphic Video","year":2012,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Intuition; Leverage (statistics); Human–computer interaction; Gesture; Computer science; Computer graphics (images); Multimedia; Artificial intelligence; Cognitive science; Psychology","score_opus":0.027512692020581955,"score_gpt":0.2760794233389261,"score_spread":0.24856673131834414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230836163","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000001064959,0.00052538316,0.07515096,0.00008149912,0.000499925,0.0001055325,0.000088210174,0.00025992948,0.9232875],"genre_scores_gemma":[0.07122081,0.00016156182,0.013394359,0.011682373,0.0017242878,0.000017989385,0.00008207467,0.0001418555,0.9015747],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984647,0.000013936469,0.0003146315,0.00043383217,0.00044338166,0.00032952434],"domain_scores_gemma":[0.99851215,0.000017582512,0.00018370558,0.0009299529,0.000102805716,0.00025380068],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00012181536,0.00031622252,0.00029895533,0.00009016812,0.000082043436,0.00021921727,0.0011490657,0.0002746079,0.00005754042],"category_scores_gemma":[0.0000103504135,0.0003066118,0.00018655842,0.000038184186,0.00007039081,0.0001478234,0.0004315907,0.0001773817,0.0010088547],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.393301e-7,0.000006023551,0.000011519433,0.000012211428,0.000035905738,0.000017491511,0.0000177095,5.5173643e-7,0.000001553962,0.9770614,0.012130496,0.0107043125],"study_design_scores_gemma":[0.000116118834,0.000024083494,0.000016611904,0.000072271745,0.000037793456,0.000027756676,7.901168e-7,0.00043140666,0.000011812935,0.39905414,0.5998142,0.00039306388],"about_ca_topic_score_codex":0.000019560886,"about_ca_topic_score_gemma":0.00003273631,"teacher_disagreement_score":0.5876837,"about_ca_system_score_codex":0.00007829842,"about_ca_system_score_gemma":0.00012788497,"threshold_uncertainty_score":0.9999386},"labels":[],"label_agreement":null},{"id":"W4231027105","doi":"10.32920/ryerson.14654745.v1","title":"Information-assisted volume rendering and visual evaluation through machine intelligence","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Visualization; Usability; Cluster analysis; Machine learning; USable; Data mining; Rendering (computer graphics); Artificial intelligence; Data visualization; Classifier (UML); Information visualization; Human–computer interaction; Raw data; Information retrieval","score_opus":0.05508364877892811,"score_gpt":0.35873324274523244,"score_spread":0.3036495939663043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231027105","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00051760254,0.00025154956,0.99351764,0.00064828305,0.0004566427,0.0001915647,0.000011463668,0.00016964362,0.0042355973],"genre_scores_gemma":[0.8818714,0.00059380376,0.113585375,0.0015978853,0.00006459607,0.00003403446,0.0017411936,0.000013028271,0.0004986966],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983134,0.000106990294,0.0004929148,0.00032982696,0.00059739134,0.00015946203],"domain_scores_gemma":[0.9987228,0.00003387396,0.0002356336,0.00048775238,0.00045006763,0.000069868474],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00054401945,0.00019773531,0.00021512443,0.00012910918,0.000105156025,0.0014484824,0.00051159813,0.00013843185,0.00019119577],"category_scores_gemma":[0.0002138828,0.00019405865,0.000054293134,0.00036201303,0.000033818524,0.0018877714,0.0020457273,0.00024000977,0.000036941143],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003673553,0.00013975496,0.0007559374,0.0004118432,0.00014258779,0.000005251782,0.0065215,0.00548566,0.000031574364,0.053663623,0.0035937817,0.9292448],"study_design_scores_gemma":[0.0000822604,0.000014711862,0.0011102022,0.000074616364,0.000024521098,0.000010415149,0.00034357523,0.99338233,0.00030308915,0.0014462358,0.0029697581,0.00023830566],"about_ca_topic_score_codex":0.00017681155,"about_ca_topic_score_gemma":0.000055713586,"teacher_disagreement_score":0.9878966,"about_ca_system_score_codex":0.00007678974,"about_ca_system_score_gemma":0.00031867434,"threshold_uncertainty_score":0.99958813},"labels":[],"label_agreement":null},{"id":"W4231149916","doi":"10.1007/978-1-4939-7131-2_101429","title":"Visual Analytics","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Visual analytics; Analytics; Computer science; Data science; Visualization; Artificial intelligence","score_opus":0.03717745313734462,"score_gpt":0.31008230704065126,"score_spread":0.27290485390330665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231149916","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[1.199144e-7,0.000015554255,0.4359651,0.00009582574,0.00017443785,0.000029903307,0.0000064618644,0.00013727079,0.5635753],"genre_scores_gemma":[0.00006076963,0.000073291434,0.008393021,0.0016100593,0.00027823864,3.3509926e-7,0.000071916395,0.000022063225,0.98949033],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988123,0.000005579707,0.0002650591,0.0004002697,0.00035505233,0.00016173293],"domain_scores_gemma":[0.9988893,0.000024205166,0.00013219909,0.0006588249,0.00017819235,0.00011724193],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000113131646,0.00021279334,0.0002192655,0.00019278233,0.000058188005,0.0002558368,0.00091215974,0.00017417583,0.0040628333],"category_scores_gemma":[0.000014030698,0.00018872197,0.00010448797,0.00006531331,0.000071770126,0.0002013932,0.00045285883,0.0001157779,0.0048518665],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.4091952e-7,0.000006984491,9.33401e-7,0.000005215813,0.00002592244,0.000007481294,0.00001579746,7.244536e-7,5.5060053e-7,0.853056,0.1443261,0.002554057],"study_design_scores_gemma":[0.00006237738,0.00005495836,0.0000011324918,0.000024971676,0.000018934603,0.000004791941,0.0000015661017,0.06764844,0.000022016757,0.036517147,0.89537704,0.00026664828],"about_ca_topic_score_codex":0.0000013932843,"about_ca_topic_score_gemma":0.000007971507,"teacher_disagreement_score":0.8165388,"about_ca_system_score_codex":0.000030347128,"about_ca_system_score_gemma":0.00009779617,"threshold_uncertainty_score":0.99684757},"labels":[],"label_agreement":null},{"id":"W4231719972","doi":"10.1002/asi.21095","title":"Developing a visual taxonomy: Children's views on aesthetics","year":2009,"lang":"en","type":"article","venue":"Journal of the American Society for Information Science and Technology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Taxonomy (biology); Visualization; Computer science; Balance (ability); Psychology; Artificial intelligence","score_opus":0.02674341990369629,"score_gpt":0.31685752108523924,"score_spread":0.29011410118154296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231719972","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11992877,0.000021248186,0.8411783,0.038289066,0.00014175648,0.00023543931,0.000003088344,0.00005052731,0.00015178153],"genre_scores_gemma":[0.8587319,0.00020609715,0.11852386,0.022486078,0.000032942175,0.000003816714,8.533681e-7,0.00000231101,0.0000121386165],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990828,0.0000068809177,0.00031948,0.000076450815,0.0003518455,0.00016252093],"domain_scores_gemma":[0.99843854,0.000020575193,0.00076821324,0.00018987268,0.0005410294,0.00004176688],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008019415,0.00007020043,0.00014407505,0.0002642505,0.00032611666,0.0001950055,0.0010399088,0.00002630573,1.768852e-7],"category_scores_gemma":[0.00020775007,0.000044894554,0.00009209995,0.0024704176,0.00054572127,0.0015334982,0.00012274878,0.000119163065,0.0000018938359],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000042506326,0.00002858295,0.0004847211,0.0000029360665,0.000013422623,9.131459e-8,0.00041949705,0.00003735545,0.0001845295,0.31529507,0.0050066835,0.6785228],"study_design_scores_gemma":[0.0017668506,0.003474937,0.01541452,0.0001468996,0.0000510761,0.0005770247,0.004329876,0.09773034,0.011444041,0.023774642,0.84060407,0.0006857366],"about_ca_topic_score_codex":4.372345e-7,"about_ca_topic_score_gemma":1.0124604e-7,"teacher_disagreement_score":0.8355974,"about_ca_system_score_codex":0.00008423161,"about_ca_system_score_gemma":0.00035841,"threshold_uncertainty_score":0.25082585},"labels":[],"label_agreement":null},{"id":"W4231754131","doi":"10.31219/osf.io/bshpc","title":"Unit Visualizations for Visual Storytelling","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Newspaper; Storytelling; Unit (ring theory); Visualization; Computer science; Data visualization; Computer graphics (images); Media studies; Psychology; Artificial intelligence; Art; Sociology; Mathematics education; Narrative; Literature","score_opus":0.09494962281553658,"score_gpt":0.38178800252412126,"score_spread":0.28683837970858467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231754131","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00003463216,0.0000463294,0.99475586,0.0014639358,0.00067503966,0.00035374283,0.0000642083,0.0005890021,0.0020172657],"genre_scores_gemma":[0.17211333,0.00042689068,0.7889578,0.017192166,0.0018066984,0.00026256873,0.005589668,0.0002020578,0.013448851],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984468,0.000051305164,0.0003691273,0.00064309145,0.000269305,0.00022031947],"domain_scores_gemma":[0.998744,0.00010739784,0.0001778872,0.0005323837,0.00026767564,0.00017063094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018394526,0.00022660273,0.00026993416,0.00017002833,0.00015056998,0.000582,0.0013062413,0.00015983508,0.00006704989],"category_scores_gemma":[0.00014393612,0.00023209775,0.0001461401,0.00038585163,0.000027102209,0.00021793,0.0013481969,0.00019434282,0.00009027302],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021001829,0.00009474646,0.00005438426,0.0001593138,0.00004876091,0.0000023115692,0.00039876942,0.003965367,0.000047142395,0.9705109,0.021220366,0.003495845],"study_design_scores_gemma":[0.00013898058,0.00003472076,0.0000125946735,0.000031403888,0.000021841879,5.2623363e-7,0.00003491921,0.87406135,0.0003501889,0.011550612,0.113486834,0.00027606075],"about_ca_topic_score_codex":0.000009616714,"about_ca_topic_score_gemma":0.000007685712,"teacher_disagreement_score":0.9589603,"about_ca_system_score_codex":0.000029769635,"about_ca_system_score_gemma":0.00030780383,"threshold_uncertainty_score":0.94646716},"labels":[],"label_agreement":null},{"id":"W4231757369","doi":"10.1007/978-3-030-04506-7_5","title":"Data Visualization","year":2019,"lang":"en","type":"book-chapter","venue":"SpringerBriefs in health care management and economics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Visualization; Artificial intelligence","score_opus":0.03998653374777412,"score_gpt":0.3024470009355109,"score_spread":0.2624604671877368,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231757369","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000026529391,0.0069487956,0.12651098,0.0015343461,0.0023097747,0.0016379366,0.00041809762,0.0002594909,0.86035407],"genre_scores_gemma":[0.0026695968,0.15390567,0.03477569,0.018624088,0.0007344412,0.00002161043,0.0092584975,0.00030656546,0.77970386],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99816215,0.000014869074,0.00060426025,0.0008499266,0.00010552947,0.00026329007],"domain_scores_gemma":[0.998034,0.000023338831,0.00033742393,0.0014824052,0.00002608976,0.000096760516],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003945504,0.00024373173,0.00036295198,0.00034917728,0.00007626782,0.0002691656,0.001136477,0.0001151931,0.000030303285],"category_scores_gemma":[0.0000051746765,0.0002988362,0.000030609346,0.000050568186,0.000027791686,0.00047089683,0.0021254977,0.00013775265,0.00009783821],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016417838,0.0000050111935,0.00010845119,0.0007629903,0.00002312767,0.0000033329309,0.00012997532,0.00010092233,2.4945106e-9,0.9604514,0.0032691276,0.035144016],"study_design_scores_gemma":[0.000251905,0.000028373786,0.0001090554,0.0002150082,0.000008847871,8.9829484e-7,0.000041893923,0.042371716,1.1942073e-7,0.0035864378,0.9530954,0.00029036598],"about_ca_topic_score_codex":0.000026558175,"about_ca_topic_score_gemma":0.00023662085,"teacher_disagreement_score":0.95686495,"about_ca_system_score_codex":0.00022967109,"about_ca_system_score_gemma":0.00012710964,"threshold_uncertainty_score":0.99994636},"labels":[],"label_agreement":null},{"id":"W4231805351","doi":"10.1007/978-0-387-39940-9_2865","title":"Information Visualization on Networks","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Information visualization; Computer science; Visualization; Artificial intelligence","score_opus":0.01432295428884122,"score_gpt":0.25794932520445846,"score_spread":0.24362637091561723,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231805351","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[3.8568572e-7,0.00019758014,0.49628097,0.000021675522,0.00090506213,0.0002797929,0.00032921316,0.00011947002,0.50186586],"genre_scores_gemma":[0.002596706,0.018334962,0.0044735083,0.0023040222,0.0028578262,0.00004511539,0.048036072,0.00017364738,0.92117816],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99780625,0.000046994384,0.0009255066,0.0002898221,0.00072491955,0.00020649843],"domain_scores_gemma":[0.9974545,0.00007807144,0.000899921,0.0011841493,0.00025794512,0.00012539698],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00038514347,0.00033427135,0.00043923757,0.00045380354,0.00007196408,0.00017125065,0.00084039534,0.00023835256,0.000050819108],"category_scores_gemma":[0.00007140131,0.0003223096,0.00009538276,0.00016495578,0.000032069165,0.0014590506,0.00018849934,0.00020657644,0.000280589],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000037738075,0.000022194885,0.000002938228,0.000116846546,0.000024043806,0.00000403058,0.000082657694,0.0013556894,3.2650715e-7,0.91936207,0.06636643,0.012658979],"study_design_scores_gemma":[0.00019547547,0.00010176241,0.000005555746,0.0006190207,0.000026016205,0.000005203736,0.000009794423,0.111409515,0.0000026991977,0.00030943903,0.8869904,0.00032511936],"about_ca_topic_score_codex":0.000018183619,"about_ca_topic_score_gemma":0.000002798938,"teacher_disagreement_score":0.91905266,"about_ca_system_score_codex":0.00006113396,"about_ca_system_score_gemma":0.00012238526,"threshold_uncertainty_score":0.9999229},"labels":[],"label_agreement":null},{"id":"W4231872027","doi":"10.1007/978-1-4939-7131-2_101435","title":"Visual Social Network Analysis, Visual Analytics","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Visual analytics; Interactive visual analysis; Computer science; Social network analysis; Data science; Analytics; Cultural analytics; Visualization; World Wide Web; Artificial intelligence; Semantic analytics; Social media; The Internet","score_opus":0.02771770258366149,"score_gpt":0.32006118801570366,"score_spread":0.29234348543204214,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231872027","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000025540185,0.000047702175,0.64878315,0.00015944889,0.00033699017,0.00008719746,0.000028060333,0.0002836487,0.35027122],"genre_scores_gemma":[0.0018426015,0.0001127383,0.0070402673,0.002728479,0.003014225,0.0000020757616,0.0008531736,0.0000681691,0.9843383],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9968703,0.000042408243,0.0007404151,0.0009304782,0.0008895067,0.0005269138],"domain_scores_gemma":[0.99813634,0.00007056288,0.0004832187,0.00067814765,0.00040647245,0.0002252644],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00042964294,0.0005269877,0.0008536292,0.00063495676,0.00034697217,0.0006528463,0.0014084838,0.0004886005,0.0037813878],"category_scores_gemma":[0.000017670982,0.0005038228,0.0006571956,0.00082634686,0.00019264285,0.000325088,0.0008880558,0.0003122007,0.0015171196],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000030458232,0.00004033272,0.000037990296,0.000010931719,0.0014899928,0.000023532548,0.00007383876,0.00009796969,4.8059934e-7,0.8331982,0.16254087,0.0024828224],"study_design_scores_gemma":[0.00019311497,0.00012670833,0.000049753286,0.00002069504,0.0012658644,0.0000036444364,0.000008796393,0.39130878,0.0000056115964,0.021658622,0.58448017,0.00087824796],"about_ca_topic_score_codex":0.000007487919,"about_ca_topic_score_gemma":0.00010575057,"teacher_disagreement_score":0.8115396,"about_ca_system_score_codex":0.00009479464,"about_ca_system_score_gemma":0.00020831103,"threshold_uncertainty_score":0.9997413},"labels":[],"label_agreement":null},{"id":"W4232406120","doi":"10.1002/9780471740360.ebs0337","title":"Data Visualization","year":2006,"lang":"en","type":"other","venue":"Wiley Encyclopedia of Biomedical Engineering","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Western University","funders":"","keywords":"Visualization; Computer science; Statistical graphics; Information visualization; Data visualization; Scientific visualization; Graphics; Computer graphics; Information retrieval; Process (computing); Data science; Data mining; Computer graphics (images)","score_opus":0.012505331928144648,"score_gpt":0.2669692050192574,"score_spread":0.2544638730911128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232406120","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[1.8861466e-7,0.00065120816,0.8728883,0.00004107611,0.00082512933,0.0000891821,0.00041522662,0.0004756416,0.12461402],"genre_scores_gemma":[0.00016293558,0.015840167,0.3094906,0.00040121496,0.005454661,0.00003100653,0.032759465,0.0015294951,0.63433045],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99833775,0.000016783037,0.00040293246,0.00046210975,0.0005484498,0.0002319539],"domain_scores_gemma":[0.9983841,0.000041243333,0.0002023256,0.0012115256,0.000024989615,0.000135814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017017261,0.00022616127,0.00032127477,0.0005134365,0.00001274573,0.00003799423,0.0019292709,0.00025144682,0.00013741868],"category_scores_gemma":[0.00016203184,0.00022102303,0.000041125626,0.0007394175,0.00004087638,0.00017599024,0.00069699594,0.000118045406,0.0000388784],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.643878e-7,0.000062145926,0.000007759537,0.00017794428,0.00002657743,0.00000850846,0.0000095611895,0.00003549692,0.000009626899,0.011786907,0.9824101,0.0054652058],"study_design_scores_gemma":[0.00010839405,0.000011989255,0.0000071763416,0.00026824107,0.000013915129,0.0000018727212,7.543404e-7,0.22307038,0.0000025792167,0.000015770314,0.776318,0.0001808895],"about_ca_topic_score_codex":0.00006973261,"about_ca_topic_score_gemma":0.000012124545,"teacher_disagreement_score":0.5633977,"about_ca_system_score_codex":0.000016695678,"about_ca_system_score_gemma":0.0000938581,"threshold_uncertainty_score":0.90130574},"labels":[],"label_agreement":null},{"id":"W4232685372","doi":"10.1109/infvis.2004.53","title":"PhylloTrees: Harnessing Nature&amp;#146;s Phyllotactic Patterns for Tree Layout","year":2005,"lang":"en","type":"article","venue":"IEEE Symposium on Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Tree (set theory); Mathematics; Combinatorics","score_opus":0.019122861836254248,"score_gpt":0.31590468664355503,"score_spread":0.2967818248073008,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232685372","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004334107,0.000010954906,0.9890462,0.001206807,0.0011008915,0.00050573854,0.00007740901,0.00050920976,0.0032086791],"genre_scores_gemma":[0.97889304,0.000057523215,0.008276819,0.009488441,0.0006151592,0.000107021995,0.0016797372,0.00004332988,0.00083893654],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977403,0.000080264675,0.0007918343,0.00034581986,0.00065387675,0.0003878913],"domain_scores_gemma":[0.99806935,0.000117881136,0.00054316805,0.0006380636,0.00048245516,0.00014909987],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00041284703,0.00030836288,0.00024658223,0.00056976354,0.00037755352,0.0010569941,0.00069397595,0.0002377744,0.000030104136],"category_scores_gemma":[0.0001348823,0.0003049303,0.00013156484,0.00074012973,0.000028107952,0.006392167,0.00006567606,0.00017451859,0.00039349572],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012481736,0.0008305654,0.0015736384,0.0006354723,0.00014969397,0.0000010256708,0.011468426,0.055532757,0.0035630588,0.800567,0.047257964,0.07829562],"study_design_scores_gemma":[0.0012723609,0.00014199929,0.00039601175,0.000117207805,0.000027739132,0.0000065402387,0.00009689979,0.71623814,0.008607779,0.00024833213,0.2723334,0.00051357277],"about_ca_topic_score_codex":0.000006793132,"about_ca_topic_score_gemma":0.000023448285,"teacher_disagreement_score":0.9807694,"about_ca_system_score_codex":0.0001843768,"about_ca_system_score_gemma":0.000105365696,"threshold_uncertainty_score":0.99998003},"labels":[],"label_agreement":null},{"id":"W4234488793","doi":"10.1145/2037692.2037695","title":"Visualizing and understanding players' behavior in video games","year":2011,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Visualization; Game design; Game Developer; Data visualization; Game mechanics; Human–computer interaction; Task (project management); Video game; Video game design; Video game development; Game art design; Screening game; Data science; Sequential game; Multimedia; Game theory; Artificial intelligence","score_opus":0.12818998688315342,"score_gpt":0.3259557865690352,"score_spread":0.19776579968588176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234488793","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017311065,0.000027348773,0.9718745,0.000047724287,0.0000699174,0.000057706893,8.180106e-7,0.00009024814,0.010520693],"genre_scores_gemma":[0.9885708,0.000024336776,0.01080036,0.0003244289,0.0000056171866,0.0000024741933,0.0000013266081,0.000003806476,0.00026685884],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99945956,0.000018400833,0.00012474954,0.00017950153,0.0000909477,0.0001268614],"domain_scores_gemma":[0.99973786,0.00002247185,0.000026403512,0.00015020548,0.000009355625,0.000053678352],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013895165,0.000059798844,0.000071500726,0.00014145563,0.000039861497,0.00010133397,0.0001998965,0.00002515966,0.00005930762],"category_scores_gemma":[0.000014667412,0.000054265645,0.0000121783705,0.0002311297,0.000024897216,0.0004796793,0.00013914944,0.000037547983,0.000011094048],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010900515,0.00004485271,0.026941046,0.0000051881193,0.0000024062845,0.000015320638,0.0014829739,4.937121e-7,0.00010096245,0.969603,0.00032981383,0.0014728628],"study_design_scores_gemma":[0.003896982,0.0005891332,0.18387204,0.0002828448,0.000067916815,0.00012066617,0.016399438,0.71417785,0.01398261,0.05794802,0.0064676027,0.0021948898],"about_ca_topic_score_codex":0.00006195039,"about_ca_topic_score_gemma":0.000072381285,"teacher_disagreement_score":0.9712597,"about_ca_system_score_codex":0.00002754375,"about_ca_system_score_gemma":0.000014526065,"threshold_uncertainty_score":0.22128887},"labels":[],"label_agreement":null},{"id":"W4234689778","doi":"10.4018/978-1-4666-6339-8.ch028","title":"Agent-Based Wellness Indicator","year":2014,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Visualization; Computer science; Software; Human–computer interaction; Process management; Engineering; Data mining","score_opus":0.020783261808304733,"score_gpt":0.26960001660199134,"score_spread":0.24881675479368662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234689778","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000012982013,0.00003205381,0.36634555,0.00009450162,0.00042428615,0.00009820299,0.00008414938,0.00020706965,0.6327129],"genre_scores_gemma":[0.18049571,0.000010617985,0.015198259,0.029941803,0.0013533595,0.000029921506,0.00023358109,0.00019864933,0.77253807],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982164,0.000026084599,0.00035133387,0.0005850008,0.00053939346,0.0002817692],"domain_scores_gemma":[0.9983014,0.000027219234,0.000292531,0.0010737072,0.00006445825,0.00024067471],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00015093775,0.0003451577,0.00035069176,0.00010928231,0.00010592943,0.00029435987,0.0015303355,0.0002874328,0.000082454855],"category_scores_gemma":[0.0000145912245,0.00033909606,0.00017738229,0.00003190287,0.00008794697,0.00005013465,0.0003361289,0.00016686709,0.0016408652],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000017801585,0.000006440267,0.000006163114,0.000024976422,0.000025189145,0.00002625592,0.000007857572,0.0000051995794,0.0000010048394,0.96853983,0.016315484,0.01503981],"study_design_scores_gemma":[0.0003557537,0.000053506472,0.000008271691,0.000121129204,0.000042549847,0.000008789113,8.0910604e-7,0.0051763533,0.00011432654,0.15957995,0.8339673,0.00057122135],"about_ca_topic_score_codex":0.000009504591,"about_ca_topic_score_gemma":0.000011602467,"teacher_disagreement_score":0.81765187,"about_ca_system_score_codex":0.00011764819,"about_ca_system_score_gemma":0.00029133825,"threshold_uncertainty_score":0.9999061},"labels":[],"label_agreement":null},{"id":"W4234822349","doi":"10.4018/9781599045917.ch011","title":"Crime Simulation Using GIS and Artificial Intelligent Agents","year":2011,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Esri (Canada)","funders":"","keywords":"Computer science; Reinforcement learning; Mobile agent; Crime analysis; Artificial intelligence; Computer security; Data science; Distributed computing; Criminology","score_opus":0.1209200232104979,"score_gpt":0.34144628027329904,"score_spread":0.22052625706280116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234822349","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000387693,0.000054312444,0.4498415,0.000005474338,0.00034827474,0.00012364374,0.000044816625,0.00008693643,0.5494563],"genre_scores_gemma":[0.9111766,0.000027200123,0.0140024945,0.0023701114,0.00072098663,0.000003101876,0.000040784475,0.00009558076,0.07156315],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99878347,0.000015145329,0.00033164668,0.00041767312,0.00027379705,0.00017825978],"domain_scores_gemma":[0.9991397,0.00001434441,0.00019217473,0.00041884367,0.0001058017,0.00012910794],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008714857,0.00023592958,0.0002217962,0.000079163954,0.00009586251,0.00023338218,0.0003794603,0.00018040332,0.000043614058],"category_scores_gemma":[0.000014235294,0.00024368387,0.00007469794,0.000022495733,0.000060388593,0.000119927856,0.00035379495,0.00009489146,0.00011143495],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000030270494,0.0000070426777,0.000004197805,0.000010837445,0.000026293235,0.000014023993,0.000075141834,0.0001726635,0.0000035521653,0.98371357,0.00019917575,0.015770506],"study_design_scores_gemma":[0.00010366819,0.000057052308,0.000029983148,0.00014440571,0.000083365114,0.000014820854,0.000004012386,0.31370944,0.00009935873,0.6441499,0.041083444,0.00052053516],"about_ca_topic_score_codex":0.000039975577,"about_ca_topic_score_gemma":0.000008426665,"teacher_disagreement_score":0.9111378,"about_ca_system_score_codex":0.00009045004,"about_ca_system_score_gemma":0.0000829451,"threshold_uncertainty_score":0.993714},"labels":[],"label_agreement":null},{"id":"W4235463506","doi":"10.1145/3099023.3099055","title":"Impact of Individual Differences on User Experience with a Visualization Interface for Public Engagement","year":2017,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Mitacs","keywords":"Visualization; User engagement; Human–computer interaction; Computer science; Information visualization; Cognition; Eye tracking; Task (project management); User experience design; User interface; Public engagement; User interface design; Cognitive psychology; Psychology; World Wide Web; Artificial intelligence; Engineering","score_opus":0.1266948298683887,"score_gpt":0.40946325215627716,"score_spread":0.28276842228788845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4235463506","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23121712,0.0000018792416,0.7679454,0.000110128916,0.000045667453,0.00013305305,0.000012234012,0.000034541026,0.0004999501],"genre_scores_gemma":[0.9944709,0.0000042804327,0.0050796513,0.00008020461,0.000012138978,0.000016273863,0.000011182972,0.0000049094797,0.00032048093],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9991441,0.00003233897,0.00015624799,0.00023127209,0.0002871834,0.0001489001],"domain_scores_gemma":[0.99894845,0.000051413987,0.00020943843,0.0005884208,0.00013928917,0.00006298705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020894306,0.00010003286,0.00012081946,0.000090911584,0.00023241062,0.0008056138,0.001269069,0.000023005148,0.00005005892],"category_scores_gemma":[0.00015680052,0.00006299933,0.000039294646,0.000102304395,0.0000703235,0.0009045491,0.00025362286,0.000030253766,0.000003562531],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039376973,0.00065832416,0.20303768,0.00003332655,0.00016117482,0.0000010197866,0.0062855235,0.00011802115,0.00031794512,0.7671082,0.0033205454,0.018918844],"study_design_scores_gemma":[0.0027223967,0.004568502,0.6438788,0.00017390089,0.000034158198,0.000003268602,0.00096662116,0.32895595,0.01333501,0.0011984063,0.0034054166,0.00075755245],"about_ca_topic_score_codex":0.000019382242,"about_ca_topic_score_gemma":0.000015008785,"teacher_disagreement_score":0.7659098,"about_ca_system_score_codex":0.00001781494,"about_ca_system_score_gemma":0.00006448301,"threshold_uncertainty_score":0.7768553},"labels":[],"label_agreement":null},{"id":"W4235520738","doi":"10.1057/ivs.2009.4","title":"Quantifying the Space-Efficiency of 2D Graphical Representations of Trees","year":2009,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Metric (unit); Representation (politics); Tree (set theory); Set (abstract data type); Range (aeronautics); Theoretical computer science; Space (punctuation); Metric space; Exponent; Algorithm; Discrete mathematics; Mathematics; Combinatorics","score_opus":0.03653578750096735,"score_gpt":0.35539063551795796,"score_spread":0.3188548480169906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4235520738","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0076756147,0.00001696006,0.98931795,0.0008388938,0.000118130185,0.00015075905,0.0000084019775,0.000070096496,0.0018032185],"genre_scores_gemma":[0.99773884,0.000042093474,0.0017347413,0.00035362353,0.000012574957,0.0000021980347,0.00009685528,0.0000020760112,0.000016970263],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99868107,0.0000696571,0.00062021695,0.000090608184,0.00043306238,0.00010538298],"domain_scores_gemma":[0.9986551,0.00007448355,0.00047556823,0.0003826125,0.00037988045,0.000032399745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037984469,0.00007957185,0.000121391306,0.0003073861,0.00011879653,0.00010573414,0.0004516362,0.000044188702,0.000013322218],"category_scores_gemma":[0.00028046267,0.00006086911,0.000060037873,0.0015838792,0.000062210056,0.0019975733,0.000049572314,0.000043444947,0.0000095973965],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000027204587,0.00006413421,0.0011909712,0.000015660886,0.000005648085,6.214634e-8,0.0024691469,0.0027503073,0.00038877927,0.9880123,0.0009415629,0.004158699],"study_design_scores_gemma":[0.00036972962,0.00013085679,0.029900124,0.00004532513,0.000016327243,0.0000034185562,0.00061147625,0.9521463,0.010456229,0.0031412453,0.0030424846,0.00013650786],"about_ca_topic_score_codex":0.00001297805,"about_ca_topic_score_gemma":0.0000056219283,"teacher_disagreement_score":0.99006325,"about_ca_system_score_codex":0.000010326006,"about_ca_system_score_gemma":0.000053642005,"threshold_uncertainty_score":0.24821705},"labels":[],"label_agreement":null},{"id":"W4235583821","doi":"10.1007/978-1-4939-7131-2_100445","title":"Graph Visualization","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Visualization; Geology; Artificial intelligence","score_opus":0.031574040979748974,"score_gpt":0.29879902464679015,"score_spread":0.26722498366704117,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4235583821","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[5.3801013e-8,0.000018347962,0.5111816,0.000045607918,0.00017610985,0.000036155558,0.000004918606,0.00016889935,0.48836833],"genre_scores_gemma":[0.000033221768,0.00013597631,0.005162809,0.001507478,0.00017548329,7.9723117e-7,0.00016997743,0.000023048833,0.99279124],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989893,0.0000072627618,0.0002288469,0.00035890177,0.00029726423,0.00011844067],"domain_scores_gemma":[0.9989863,0.0000143699735,0.00013222739,0.0006112453,0.00017978798,0.0000760698],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00010128877,0.00017558523,0.0001551702,0.00022395351,0.00006400468,0.0002165097,0.0007053394,0.0001523491,0.0030809678],"category_scores_gemma":[0.000010874833,0.00015933573,0.00007718173,0.00008034426,0.000051903306,0.0002673331,0.00024849124,0.00005972492,0.0023542433],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.7450351e-7,0.000004359202,7.034031e-7,0.0000056967024,0.000011679942,0.000001874204,0.000027326632,4.0081386e-7,9.262028e-7,0.8701053,0.12855123,0.0012902714],"study_design_scores_gemma":[0.00005868503,0.000032746662,0.0000010842423,0.00003139735,0.000009781541,0.0000030219985,0.0000011563798,0.0116961785,0.000036535665,0.14661898,0.8412875,0.00022294649],"about_ca_topic_score_codex":0.0000014462745,"about_ca_topic_score_gemma":0.000006543722,"teacher_disagreement_score":0.72348636,"about_ca_system_score_codex":0.00001769623,"about_ca_system_score_gemma":0.000051340456,"threshold_uncertainty_score":0.99842256},"labels":[],"label_agreement":null},{"id":"W4235785290","doi":"10.1007/978-1-4939-7131-2_100742","title":"Network or Graph Visualization","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Graph drawing; Computer science; Visualization; Graph; Theoretical computer science; Artificial intelligence","score_opus":0.04408594892021888,"score_gpt":0.3055391088666309,"score_spread":0.261453159946412,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4235785290","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[3.4349966e-8,0.000030260015,0.57533103,0.000060537146,0.0003453685,0.000063491796,0.000004830803,0.0002127919,0.42395163],"genre_scores_gemma":[0.00001462562,0.00019344887,0.010936973,0.0034787576,0.0006199191,0.0000014955326,0.00018752702,0.00003210527,0.98453516],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99870646,0.000013598263,0.00031320355,0.00043413247,0.0003327349,0.00019989401],"domain_scores_gemma":[0.9987968,0.000035006666,0.00018841204,0.00069283176,0.00018956383,0.0000973887],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001627495,0.00023008772,0.0002224505,0.00014809452,0.000110085006,0.00028077076,0.00082919863,0.00019814132,0.004910619],"category_scores_gemma":[0.000016528093,0.00017786205,0.00007520644,0.00016372492,0.00006046794,0.00028076614,0.00033378784,0.000079085665,0.0014675384],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000011606297,0.0000040819145,0.0000010981139,0.0000064812334,0.000013678209,0.0000040333866,0.000018940284,0.0000068429254,9.9077916e-8,0.6855722,0.31342486,0.00094653387],"study_design_scores_gemma":[0.000082427556,0.00006870028,0.000001260944,0.00006763283,0.000015821708,0.0000054976426,0.0000012195154,0.0195042,0.000003893148,0.14073275,0.83924264,0.0002739443],"about_ca_topic_score_codex":0.0000017552089,"about_ca_topic_score_gemma":0.000026363256,"teacher_disagreement_score":0.56439406,"about_ca_system_score_codex":0.000021006208,"about_ca_system_score_gemma":0.00009610984,"threshold_uncertainty_score":0.99930996},"labels":[],"label_agreement":null},{"id":"W4236751024","doi":"10.1007/978-1-4939-7131-2_101234","title":"Spatial Interaction","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Geography; Computer science","score_opus":0.03848686791282423,"score_gpt":0.3071964806882198,"score_spread":0.26870961277539557,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4236751024","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[6.883479e-8,0.0000028426912,0.48502684,0.00007841223,0.00039036022,0.000018969278,0.0000026580544,0.00007611886,0.5144037],"genre_scores_gemma":[0.00022321993,0.00002532881,0.0038084344,0.0008360611,0.00034821883,3.6725308e-7,0.000060830032,0.000010436492,0.9946871],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993857,0.0000037485613,0.00014535474,0.00023136321,0.00016475092,0.00006909272],"domain_scores_gemma":[0.99937075,0.000012200362,0.00009133591,0.0003952196,0.00008653695,0.000043924076],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000049001635,0.00010778998,0.00009784144,0.00009665677,0.000031919193,0.00015771555,0.0004279026,0.000087638895,0.005508609],"category_scores_gemma":[0.0000071033796,0.0000953655,0.00004902729,0.00001622413,0.00002273108,0.0002212026,0.00021184645,0.00007810111,0.0042946944],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.3589895e-7,0.0000036504744,4.0952133e-7,0.000003149464,0.000010339882,0.0000024879182,0.000026095067,2.4961864e-7,0.0000011385151,0.86869615,0.11344182,0.017814068],"study_design_scores_gemma":[0.000037856676,0.000029191002,9.537578e-7,0.000024032963,0.0000051268194,0.0000043336113,0.0000010691322,0.027217563,0.000041146697,0.018535517,0.95397705,0.00012613465],"about_ca_topic_score_codex":0.0000102287495,"about_ca_topic_score_gemma":0.00003763826,"teacher_disagreement_score":0.85016066,"about_ca_system_score_codex":0.000022960805,"about_ca_system_score_gemma":0.000032346343,"threshold_uncertainty_score":0.9964806},"labels":[],"label_agreement":null},{"id":"W4236803254","doi":"10.1145/3173574.3173797","title":"DataInk","year":2018,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":78,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Human–computer interaction; Visualization; Data visualization; Graphics; Bridge (graph theory); Graphical user interface; Interface (matter); User interface; Point (geometry); Computer graphics (images); Programming language; Artificial intelligence","score_opus":0.03386072323653286,"score_gpt":0.3289222514085546,"score_spread":0.2950615281720217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4236803254","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000052789124,0.0000012338651,0.9125961,0.0005304791,0.00008044526,0.0000074067925,6.516148e-7,0.000092558774,0.086638354],"genre_scores_gemma":[0.6633142,0.000008859961,0.28155237,0.01830027,0.00040705092,0.0000010537881,0.000030389192,0.0000063524494,0.03637939],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99976367,0.000004912078,0.000038220194,0.000081745566,0.00005754706,0.00005393248],"domain_scores_gemma":[0.99965537,0.0000047176436,0.000007720208,0.00027490538,0.000031273044,0.000025988675],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000053613912,0.000018936495,0.0000187677,0.000019688612,0.000032414926,0.00008005519,0.00038383738,0.0000063566745,0.00021630847],"category_scores_gemma":[0.000013319243,0.000014818669,0.000005323058,0.00015263274,0.000017859757,0.000252052,0.00013925342,0.000008430039,0.001099549],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.9576652e-8,0.00000524461,0.00007043005,2.7936304e-7,8.3446326e-7,3.7757823e-7,0.000026627511,8.3173724e-8,0.000029629527,0.9141994,0.07794362,0.007723405],"study_design_scores_gemma":[0.00005305611,0.000021980155,0.00021688087,0.0000010513457,5.1477514e-7,0.0000017468398,0.000007146408,0.21841815,0.0016995348,0.0037288957,0.7758,0.00005104676],"about_ca_topic_score_codex":0.0000030028825,"about_ca_topic_score_gemma":0.0000037401442,"teacher_disagreement_score":0.91047055,"about_ca_system_score_codex":0.0000020424543,"about_ca_system_score_gemma":0.000010478866,"threshold_uncertainty_score":0.9996782},"labels":[],"label_agreement":null},{"id":"W4236862227","doi":"10.1007/978-1-4614-6170-8_110120","title":"Visualization Framework","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Visualization; Computer science; Artificial intelligence","score_opus":0.026394060687272666,"score_gpt":0.30300463952055035,"score_spread":0.27661057883327766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4236862227","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[8.273148e-9,0.000019514768,0.54412925,0.000114455805,0.00018951335,0.000033894612,0.000002350023,0.00018308418,0.45532793],"genre_scores_gemma":[0.0001194486,0.0001120572,0.024969693,0.003610451,0.00022265276,9.920483e-7,0.000119188095,0.00002949989,0.970816],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989251,0.000010954149,0.00025014504,0.00036591478,0.00032307988,0.00012480222],"domain_scores_gemma":[0.99884665,0.000059234968,0.0001524301,0.00074276904,0.000113222515,0.00008569018],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00012433412,0.00019030704,0.00019946776,0.00015122717,0.000059093,0.00024886287,0.00077036425,0.0002652049,0.0010723525],"category_scores_gemma":[0.000044727065,0.00017544902,0.000076284254,0.00005930837,0.000026898757,0.00012987424,0.0002517557,0.00013185274,0.0018271742],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.4886645e-7,0.0000030057572,0.0000010981267,0.0000100693105,0.000010019831,0.0000014107922,0.000017182858,0.0000043198806,2.7242675e-7,0.95967215,0.03314227,0.0071380283],"study_design_scores_gemma":[0.000030811254,0.000016998709,8.634681e-7,0.00006439837,0.0000076162764,0.0000016754279,3.7548992e-7,0.036267117,0.000008726837,0.20687324,0.75652856,0.00019965034],"about_ca_topic_score_codex":0.0000010388335,"about_ca_topic_score_gemma":0.0000016165308,"teacher_disagreement_score":0.7527989,"about_ca_system_score_codex":0.000022256254,"about_ca_system_score_gemma":0.0000431714,"threshold_uncertainty_score":0.9998408},"labels":[],"label_agreement":null},{"id":"W4237076065","doi":"10.1198/jcgs.2011.09166b","title":"Comment","year":2011,"lang":"en","type":"article","venue":"Journal of Computational and Graphical Statistics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Perspective (graphical); Relation (database); Computer science; Cognition; Table (database); Psychology; Cognitive psychology; Artificial intelligence; Data mining","score_opus":0.03274139259601863,"score_gpt":0.28920280013943866,"score_spread":0.25646140754342006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237076065","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006975202,0.000042255368,0.9977356,0.0012082438,0.00010429227,0.000015573538,0.000019345549,0.0000068301065,0.0001702912],"genre_scores_gemma":[0.33025908,0.000060651826,0.6672439,0.0023841453,0.000031248703,1.9324831e-7,0.0000070428337,0.000002887284,0.0000108363065],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992651,0.000037648802,0.00029844025,0.000064631255,0.00026191326,0.00007231226],"domain_scores_gemma":[0.9992471,0.00014595622,0.00017340206,0.00005183215,0.00026370687,0.00011805785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000195171,0.000055517514,0.00010832691,0.00010127311,0.000055196357,0.00005319506,0.00020609608,0.00001944257,0.000022887967],"category_scores_gemma":[0.000046600806,0.00004334652,0.0000277097,0.00016612362,0.000058961265,0.00016875134,0.000054904907,0.000086157415,0.0000027560634],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000050802264,0.00008338589,0.00095379935,0.0000052505857,0.000021359869,0.000023996396,0.00015625052,0.00006873106,7.2878083e-7,0.9840953,0.0068678143,0.0077183256],"study_design_scores_gemma":[0.000360032,0.00022822295,0.027491784,0.000012235238,0.000013598465,0.00010152141,0.000015288659,0.090066135,0.00000821402,0.8722765,0.009343857,0.00008261421],"about_ca_topic_score_codex":0.0000017295363,"about_ca_topic_score_gemma":4.4131312e-7,"teacher_disagreement_score":0.33049172,"about_ca_system_score_codex":0.0000049743303,"about_ca_system_score_gemma":0.000034190187,"threshold_uncertainty_score":0.17676198},"labels":[],"label_agreement":null},{"id":"W4238263457","doi":"10.31219/osf.io/c4ruf","title":"How do taxes, benefits and public spending evolve for a taxpayer during their lifetime ?","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Polytechnique Montréal; Université de Sherbrooke","funders":"","keywords":"Taxpayer; Narrative; Affect (linguistics); Public finance; Public spending; Public life; Public economics; Political science; Sociology; Public relations; Economics; Law; Art; Literature","score_opus":0.06912753307729362,"score_gpt":0.2826681925172543,"score_spread":0.21354065943996065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4238263457","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0028574022,0.0007842731,0.9822067,0.01174379,0.0004342397,0.00054255326,0.0003817134,0.00037297513,0.00067636033],"genre_scores_gemma":[0.8831697,0.00084879034,0.11091259,0.0011133318,0.0006704699,0.000084238935,0.00037960836,0.00006964187,0.0027516405],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99821407,0.00003377257,0.000250828,0.00089629093,0.00025701337,0.00034802247],"domain_scores_gemma":[0.99861276,0.00007339966,0.00022127712,0.00069331337,0.00012695642,0.00027231537],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00018994618,0.00030253446,0.00034700023,0.00019858354,0.00016311389,0.0035461895,0.0012388597,0.00015511316,0.000028259095],"category_scores_gemma":[0.00020045554,0.0002563835,0.0001261238,0.0002581142,0.000030986037,0.0006197909,0.0033149174,0.00023137809,0.000011265332],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000072293587,0.00011417574,0.0028870679,0.0008241637,0.00029236774,0.000013496283,0.0009290513,0.00018053995,0.00032004548,0.94460475,0.014265718,0.03556137],"study_design_scores_gemma":[0.0011987546,0.000093104085,0.0013729322,0.00042718917,0.000057896534,0.000029806568,0.000424993,0.8840894,0.0027390812,0.019989489,0.088012725,0.0015646089],"about_ca_topic_score_codex":0.000010398208,"about_ca_topic_score_gemma":0.000021934338,"teacher_disagreement_score":0.92461526,"about_ca_system_score_codex":0.000041059742,"about_ca_system_score_gemma":0.000092970564,"threshold_uncertainty_score":0.99998885},"labels":[],"label_agreement":null},{"id":"W4238484894","doi":"10.21307/connections-2019-009","title":"Hairball Buster: A Graph Triage Method for Viewing and Comparing Graphs","year":2019,"lang":"en","type":"article","venue":"Connections","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Adjacency list; Computer science; Centrality; Graph Layout; Visualization; Graph; Graph drawing; Theoretical computer science; Node (physics); Representation (politics); Data visualization; Data mining; Algorithm; Combinatorics; Mathematics","score_opus":0.053155206246071715,"score_gpt":0.3380385660064367,"score_spread":0.284883359760365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4238484894","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005915386,0.000087201115,0.99177897,0.00038636904,0.00039672514,0.00021093259,0.000005850366,0.00013080439,0.0010877402],"genre_scores_gemma":[0.8386163,0.000058043464,0.15847151,0.0011415598,0.0000542682,0.0000447131,0.000029903958,0.00001680804,0.0015668906],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99933475,0.0000423524,0.000160771,0.00025540544,0.000068577,0.00013813216],"domain_scores_gemma":[0.99935734,0.00017983814,0.000057293993,0.00028180538,0.000062163286,0.0000615369],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030064624,0.000076717144,0.00014913874,0.00016234902,0.00017057218,0.00019888341,0.0002194215,0.000028768598,0.000012162483],"category_scores_gemma":[0.000065484164,0.00007492457,0.00006434241,0.00040682708,0.000013576039,0.00032572853,0.00009764773,0.000051185827,0.000015009324],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000042845318,0.00005383719,0.005058224,0.00005794019,0.000054373293,6.5457596e-7,0.0007642823,0.0004358293,0.00049653585,0.9829323,0.003137036,0.007004696],"study_design_scores_gemma":[0.00090184796,0.000062448154,0.00079262286,0.000031642758,0.000025351466,0.000014040444,0.00012715142,0.9213237,0.00017261412,0.011920894,0.06445065,0.00017699623],"about_ca_topic_score_codex":0.00001762815,"about_ca_topic_score_gemma":0.000020996933,"teacher_disagreement_score":0.9710114,"about_ca_system_score_codex":0.000008633175,"about_ca_system_score_gemma":0.000016909284,"threshold_uncertainty_score":0.30553353},"labels":[],"label_agreement":null},{"id":"W4238553268","doi":"10.31219/osf.io/7cbsq","title":"Paper Maps: Improving the Readability of Scientific Papers via Concept Maps","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Automatic summarization; Readability; Visualization; Computer science; Data science; Management science; Information retrieval; Work (physics); Data mining; Engineering","score_opus":0.022222632451383454,"score_gpt":0.27528618577857883,"score_spread":0.2530635533271954,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4238553268","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0035167285,0.0004496646,0.9719437,0.003379373,0.003719234,0.0006426478,0.00019805979,0.0003143582,0.015836265],"genre_scores_gemma":[0.9525641,0.00004350285,0.033969566,0.0027894862,0.00013461245,0.000024666117,0.000925622,0.000028150747,0.009520259],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99748623,0.0002080852,0.00052477646,0.00091991003,0.00061026064,0.00025071666],"domain_scores_gemma":[0.9964571,0.00012699259,0.00029613386,0.00263676,0.00039378583,0.000089228764],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0010333539,0.00021567344,0.00030602617,0.000075994125,0.00019846502,0.0010627839,0.0022736655,0.00014333946,0.00039435187],"category_scores_gemma":[0.00021204483,0.00014674706,0.00019861295,0.00051782455,0.0004154393,0.00042217792,0.0036095758,0.0003208016,0.000013939947],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011569481,0.0011448102,0.0020535295,0.0017753404,0.00049599167,0.00004517443,0.012230861,0.0034008469,0.04134268,0.4117937,0.059966385,0.4657391],"study_design_scores_gemma":[0.0007699967,0.00015895069,0.003393232,0.0007549065,0.00031283614,0.00003714772,0.005501601,0.6345106,0.10204432,0.032945223,0.21636085,0.0032103704],"about_ca_topic_score_codex":0.00025973332,"about_ca_topic_score_gemma":0.000097863376,"teacher_disagreement_score":0.9490474,"about_ca_system_score_codex":0.000053452455,"about_ca_system_score_gemma":0.0005049686,"threshold_uncertainty_score":0.9999742},"labels":[],"label_agreement":null},{"id":"W4238961244","doi":"10.1007/978-1-4939-7131-2_100993","title":"Research in Network Visualization","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Visualization; Computer science; Graph drawing; Artificial intelligence","score_opus":0.11728747951574761,"score_gpt":0.40539803504025695,"score_spread":0.28811055552450937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4238961244","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[2.7618282e-7,0.000055260214,0.32736188,0.00012245873,0.00018863224,0.000090732385,0.0000018128792,0.00007777929,0.67210114],"genre_scores_gemma":[0.00022376465,0.00026959227,0.004239106,0.00066337833,0.0005560375,0.0000027310662,0.00011258611,0.000028213688,0.9939046],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983373,0.000056173005,0.00030149394,0.0004447032,0.0005717642,0.0002885383],"domain_scores_gemma":[0.998836,0.00008085701,0.00007422735,0.00065598026,0.00027879872,0.00007417022],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0010714966,0.00014002074,0.00017416204,0.00043716084,0.00008433076,0.00025637276,0.0009182829,0.00020803716,0.0013445027],"category_scores_gemma":[0.00001707869,0.00013334352,0.000036523994,0.00035420875,0.00008535336,0.0002455093,0.000568282,0.0002179997,0.0019100192],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.6421953e-7,0.000006313576,0.0000066049524,0.000007652658,0.0000038488747,0.0000066147404,0.000036019497,0.000018396046,1.3035284e-7,0.8507979,0.14757152,0.0015444638],"study_design_scores_gemma":[0.00007361693,0.00003998021,0.0000067916944,0.00013389354,0.0000014841097,0.0000014366199,0.0000036492966,0.06412435,0.0000032931184,0.2009863,0.73446465,0.00016057202],"about_ca_topic_score_codex":0.00000961429,"about_ca_topic_score_gemma":0.000101660255,"teacher_disagreement_score":0.64981157,"about_ca_system_score_codex":0.00007006292,"about_ca_system_score_gemma":0.00012645593,"threshold_uncertainty_score":0.9995684},"labels":[],"label_agreement":null},{"id":"W4239489989","doi":"10.1007/978-0-387-39940-9_3957","title":"Visual Data Analysis","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science","score_opus":0.0344148225700345,"score_gpt":0.3046331750968784,"score_spread":0.2702183525268439,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4239489989","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[6.7221805e-7,0.0014661608,0.4576481,0.000046348658,0.00068672275,0.00025672105,0.004498747,0.00014291298,0.5352536],"genre_scores_gemma":[0.00045975947,0.0069221733,0.011328759,0.00020843216,0.0010344881,0.000005783901,0.055482104,0.00007708713,0.9244814],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9963261,0.000071008064,0.0010936218,0.0011888468,0.0010280695,0.0002923568],"domain_scores_gemma":[0.99333274,0.00012617081,0.0008902669,0.0052210004,0.00021134806,0.00021849343],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00076159637,0.00044103095,0.001008853,0.00088061416,0.00007281947,0.00017852787,0.003999398,0.00021801863,0.0001773627],"category_scores_gemma":[0.00010030554,0.00042199204,0.00020225154,0.0005243566,0.000068437796,0.0010567413,0.0016784507,0.00026545965,0.00024938278],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005255241,0.00014320889,0.00007743791,0.0003361358,0.0016614103,0.00013832815,0.00009108178,0.00019925502,0.000005672414,0.7971379,0.18375796,0.016446339],"study_design_scores_gemma":[0.00015002013,0.000044701635,0.000014482243,0.00020154446,0.0007873325,0.0000071660356,0.000008750873,0.11101243,0.0000018579192,0.00021648406,0.88708436,0.00047089113],"about_ca_topic_score_codex":0.00011167117,"about_ca_topic_score_gemma":0.000054237014,"teacher_disagreement_score":0.79692143,"about_ca_system_score_codex":0.000039660845,"about_ca_system_score_gemma":0.000268687,"threshold_uncertainty_score":0.9998232},"labels":[],"label_agreement":null},{"id":"W4239966611","doi":"10.1109/infvis.2004.11","title":"BinX: Dynamic Exploration of Time Series Datasets Across Aggregation Levels","year":2005,"lang":"en","type":"article","venue":"IEEE Symposium on Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Visualization; Series (stratigraphy); Data mining; Time series; Data visualization; Range (aeronautics); Machine learning","score_opus":0.02034649842198702,"score_gpt":0.3175644552374403,"score_spread":0.29721795681545327,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4239966611","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0033437079,0.000005803072,0.99341863,0.0008611196,0.00036139786,0.00033321424,0.0005486328,0.00029351786,0.0008339582],"genre_scores_gemma":[0.97574896,0.00024195506,0.009251555,0.0022833834,0.00016834076,0.000057845245,0.011425496,0.000037914007,0.00078455656],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997798,0.00010370128,0.00093018054,0.00024263772,0.0006730346,0.00025242745],"domain_scores_gemma":[0.9981416,0.000043914795,0.00071425736,0.0005818808,0.00042991643,0.00008844814],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00050561153,0.00022267844,0.00021526562,0.00037714106,0.0002340846,0.00043489106,0.0005325361,0.00012577543,0.000045405202],"category_scores_gemma":[0.00009039818,0.00022902687,0.000059493086,0.0010085246,0.00005798907,0.020060856,0.00008924659,0.000074159245,0.0007610725],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013337983,0.000670472,0.00016356577,0.00041091922,0.00011205294,0.0000015417294,0.025626706,0.3011925,0.022020789,0.54098445,0.025595792,0.08308786],"study_design_scores_gemma":[0.0007119466,0.00019320751,0.00015316285,0.000087926535,0.000011603395,0.000005917447,0.00015267379,0.9078507,0.062294204,0.00038757102,0.027812064,0.00033906472],"about_ca_topic_score_codex":0.0000059838912,"about_ca_topic_score_gemma":0.000010049351,"teacher_disagreement_score":0.9841671,"about_ca_system_score_codex":0.00013087182,"about_ca_system_score_gemma":0.000083712424,"threshold_uncertainty_score":0.9936451},"labels":[],"label_agreement":null},{"id":"W4241323313","doi":"10.32920/ryerson.14654745","title":"Information-assisted volume rendering and visual evaluation through machine intelligence","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Visualization; Usability; Cluster analysis; Machine learning; Artificial intelligence; Data mining; Rendering (computer graphics); USable; Data visualization; Classifier (UML); Information visualization; Raw data; Human–computer interaction; Information retrieval","score_opus":0.05508364877892811,"score_gpt":0.35873324274523244,"score_spread":0.3036495939663043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4241323313","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00051760254,0.00025154956,0.99351764,0.00064828305,0.0004566427,0.0001915647,0.000011463668,0.00016964362,0.0042355973],"genre_scores_gemma":[0.8818714,0.00059380376,0.113585375,0.0015978853,0.00006459607,0.00003403446,0.0017411936,0.000013028271,0.0004986966],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983134,0.000106990294,0.0004929148,0.00032982696,0.00059739134,0.00015946203],"domain_scores_gemma":[0.9987228,0.00003387396,0.0002356336,0.00048775238,0.00045006763,0.000069868474],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00054401945,0.00019773531,0.00021512443,0.00012910918,0.000105156025,0.0014484824,0.00051159813,0.00013843185,0.00019119577],"category_scores_gemma":[0.0002138828,0.00019405865,0.000054293134,0.00036201303,0.000033818524,0.0018877714,0.0020457273,0.00024000977,0.000036941143],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003673553,0.00013975496,0.0007559374,0.0004118432,0.00014258779,0.000005251782,0.0065215,0.00548566,0.000031574364,0.053663623,0.0035937817,0.9292448],"study_design_scores_gemma":[0.0000822604,0.000014711862,0.0011102022,0.000074616364,0.000024521098,0.000010415149,0.00034357523,0.99338233,0.00030308915,0.0014462358,0.0029697581,0.00023830566],"about_ca_topic_score_codex":0.00017681155,"about_ca_topic_score_gemma":0.000055713586,"teacher_disagreement_score":0.9878966,"about_ca_system_score_codex":0.00007678974,"about_ca_system_score_gemma":0.00031867434,"threshold_uncertainty_score":0.99958813},"labels":[],"label_agreement":null},{"id":"W4241426501","doi":"10.4135/9781529776904","title":"VisualEyes","year":2021,"lang":"it","type":"book","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science","score_opus":0.0371504236003266,"score_gpt":0.3214498577642014,"score_spread":0.28429943416387476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4241426501","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[5.510919e-7,0.00020243622,0.4476441,0.00045218132,0.0008522982,0.000072253075,0.000033178356,0.00013170729,0.55061126],"genre_scores_gemma":[0.00006164957,0.00089742924,0.007242799,0.0041332864,0.00047496243,0.0000021266142,0.0007336361,0.000032529697,0.9864216],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99738026,0.00010269725,0.00054693635,0.000899904,0.0006820799,0.00038810458],"domain_scores_gemma":[0.99776924,0.00011423796,0.00022412562,0.0012637244,0.00038200902,0.00024668867],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00024365401,0.000396762,0.0004987698,0.00019791149,0.00016471813,0.0012438965,0.0014844886,0.00030418037,0.008294755],"category_scores_gemma":[0.00009166142,0.00038636822,0.00024312986,0.00048757825,0.00010463173,0.0004275714,0.0011974166,0.00029295063,0.0042463937],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.5481554e-7,0.00007039938,0.000014183662,0.00007307405,0.000059482572,0.00008416076,0.00007987517,0.000006032428,0.000006600667,0.6684377,0.32519606,0.00597204],"study_design_scores_gemma":[0.0001511747,0.000043299482,0.00001723659,0.00022087383,0.000043801967,0.000019293147,0.00003349332,0.06383911,0.0001187793,0.001313073,0.9337025,0.00049734494],"about_ca_topic_score_codex":0.000010301407,"about_ca_topic_score_gemma":0.0000072435,"teacher_disagreement_score":0.6671246,"about_ca_system_score_codex":0.000091783986,"about_ca_system_score_gemma":0.0012691834,"threshold_uncertainty_score":0.9998588},"labels":[],"label_agreement":null},{"id":"W4241919617","doi":"10.1145/568813.568817","title":"Designing a component-based framework for visualization in software engineering and knowledge engineering","year":2002,"lang":"en","type":"article","venue":"Proceedings of the 14th international conference on Software engineering and knowledge engineering - SEKE '02","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Software engineering; Component (thermodynamics); Visualization; Domain (mathematical analysis); Business process reengineering; Systems engineering; Engineering; Data mining","score_opus":0.03413249829158149,"score_gpt":0.276546273699248,"score_spread":0.2424137754076665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4241919617","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02739219,0.00047720582,0.9700104,0.00011729896,0.0009966823,0.0003692252,0.000030757554,0.000564784,0.000041433283],"genre_scores_gemma":[0.78796536,0.00009828486,0.21142523,0.000032637327,0.00019004587,0.00009567354,0.0000149904345,0.00008393918,0.00009385984],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980045,0.0000087124245,0.0005798916,0.00059854146,0.00033495927,0.00047342503],"domain_scores_gemma":[0.9984797,0.00051413884,0.00017713205,0.00022666669,0.0004188506,0.00018350863],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004141131,0.00048052808,0.0004437284,0.0007953382,0.00011029582,0.00041311138,0.00090817857,0.00020437373,0.000010230637],"category_scores_gemma":[0.0024716337,0.0004798016,0.00011466992,0.00071912346,0.000038185437,0.00052255875,0.00033104818,0.00042053746,0.000004201784],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035535384,0.00050526945,0.0054143686,0.0032085683,0.00026906785,0.000004649695,0.004829938,0.15094414,0.011753605,0.8163529,0.00046943643,0.006212511],"study_design_scores_gemma":[0.0006428706,0.00008379753,0.0011716561,0.0019697994,0.000021792352,0.000010274417,0.00002786787,0.9878598,0.0055629998,0.000106284555,0.002041062,0.00050180283],"about_ca_topic_score_codex":0.0000042048623,"about_ca_topic_score_gemma":8.448487e-7,"teacher_disagreement_score":0.8369157,"about_ca_system_score_codex":0.00014939159,"about_ca_system_score_gemma":0.000049642797,"threshold_uncertainty_score":0.99976534},"labels":[],"label_agreement":null},{"id":"W4242126313","doi":"10.1007/978-1-4614-6170-8_100801","title":"Visual Analytics","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Visual analytics; Computer science; Analytics; Data science; Artificial intelligence; Visualization","score_opus":0.02963404047050453,"score_gpt":0.2954099495830136,"score_spread":0.26577590911250903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4242126313","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[2.629046e-8,0.000012589139,0.5067632,0.00013170856,0.00012032241,0.000024222545,0.0000030922554,0.00012080099,0.49282402],"genre_scores_gemma":[0.0002111547,0.000067028544,0.0063306317,0.0022791857,0.00017511554,3.7574176e-7,0.000076017415,0.000022722483,0.99083775],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99882764,0.000007703621,0.00027482794,0.00038113687,0.00035295723,0.00015574857],"domain_scores_gemma":[0.9989279,0.00003859267,0.00014061414,0.0006572984,0.00011422877,0.000121378536],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00013573225,0.00021578338,0.00025568047,0.00018854627,0.000050445764,0.00023781574,0.00087708415,0.00017048638,0.00079577515],"category_scores_gemma":[0.000016438778,0.0001920955,0.000114928385,0.000051703413,0.00003870825,0.000107126456,0.00036684037,0.00014201847,0.002183485],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.6312597e-7,0.0000042348615,0.0000012161915,0.0000075892117,0.000020582096,0.000004777307,0.0000051944876,0.000006371066,4.768776e-7,0.936903,0.05292749,0.010118888],"study_design_scores_gemma":[0.00006244938,0.00003212272,0.0000012431199,0.000021042857,0.000016813192,0.0000036377246,4.6478127e-7,0.14272252,0.000009346929,0.018983418,0.8379033,0.00024360201],"about_ca_topic_score_codex":0.0000017125751,"about_ca_topic_score_gemma":0.0000058796395,"teacher_disagreement_score":0.9179196,"about_ca_system_score_codex":0.000025708981,"about_ca_system_score_gemma":0.0000686169,"threshold_uncertainty_score":0.99859345},"labels":[],"label_agreement":null},{"id":"W4243486428","doi":"10.1007/978-1-4614-6170-8_100567","title":"Graph-Based Visual Analysis","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Graph; Computer science; Power graph analysis; Theoretical computer science","score_opus":0.020101095537927088,"score_gpt":0.28587046025285934,"score_spread":0.26576936471493223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4243486428","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[1.3480557e-7,0.00001591409,0.6471241,0.0001516478,0.00006858051,0.000031036394,0.000008595695,0.00015700827,0.35244298],"genre_scores_gemma":[0.0010977886,0.00001632066,0.010443034,0.004432334,0.000077846176,0.0000013612869,0.0004104204,0.000022247545,0.98349863],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985953,0.000016553196,0.0003031072,0.00049858243,0.00042534224,0.00016108788],"domain_scores_gemma":[0.9986872,0.000054361026,0.00017871844,0.00081904966,0.0001309237,0.00012972798],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00017519562,0.00023984269,0.00038493995,0.00087820034,0.00006378589,0.00024747816,0.0008884227,0.00016387732,0.0012367795],"category_scores_gemma":[0.00001070536,0.00021088778,0.00039299892,0.00033678382,0.00004854301,0.00008674217,0.00015376577,0.00011691576,0.0006046196],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.1868225e-7,0.000009113321,0.000016236878,0.0000074434256,0.00023773337,0.0000041382673,0.0000031449893,0.00016637676,5.475909e-7,0.98144215,0.014623211,0.0034894769],"study_design_scores_gemma":[0.000112357935,0.000039277133,0.000011993483,0.0000132715495,0.00034294234,4.1289226e-7,4.0073553e-7,0.45639548,0.000020511303,0.006591071,0.5361158,0.0003564813],"about_ca_topic_score_codex":0.000009725936,"about_ca_topic_score_gemma":0.00003070159,"teacher_disagreement_score":0.9748511,"about_ca_system_score_codex":0.000018780422,"about_ca_system_score_gemma":0.00006894506,"threshold_uncertainty_score":0.9996762},"labels":[],"label_agreement":null},{"id":"W4243580845","doi":"10.1007/978-1-4614-6170-8_100571","title":"Visual Social Network Analysis","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Social network analysis; Computer science; World Wide Web; Social media","score_opus":0.021965169902918066,"score_gpt":0.2972691944959132,"score_spread":0.27530402459299513,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4243580845","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[6.512075e-8,0.000015783738,0.57134604,0.00014295643,0.00010560945,0.00002267964,0.0000046136406,0.000114659975,0.42824757],"genre_scores_gemma":[0.00067337736,0.000021057513,0.004426734,0.0023565737,0.0008423921,7.970608e-7,0.00023716323,0.000018815546,0.9914231],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99868846,0.000018871624,0.00029507765,0.00042292097,0.00036807093,0.000206599],"domain_scores_gemma":[0.9991852,0.00003693501,0.00019154248,0.00040222914,0.00010007581,0.00008398737],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00020862026,0.00021348448,0.00041304575,0.00023711407,0.00014540256,0.00026988238,0.00078554585,0.00020281124,0.0009954934],"category_scores_gemma":[0.0000055752253,0.00019696365,0.000333098,0.0002455123,0.00004029815,0.000088681,0.00033854813,0.00013557132,0.0006742545],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.8858298e-7,0.0000034933269,0.0000073265346,0.0000031665938,0.00031479972,0.0000029797377,0.000013190958,0.0000762947,6.296356e-8,0.9122005,0.08051754,0.006860363],"study_design_scores_gemma":[0.0000601477,0.000017350152,0.000017214616,0.000005555087,0.00032680642,6.868971e-7,6.2966103e-7,0.16394731,6.209123e-7,0.019289022,0.81603205,0.00030257186],"about_ca_topic_score_codex":0.000004040952,"about_ca_topic_score_gemma":0.00003363858,"teacher_disagreement_score":0.8929115,"about_ca_system_score_codex":0.000024478977,"about_ca_system_score_gemma":0.0000457196,"threshold_uncertainty_score":0.99991775},"labels":[],"label_agreement":null},{"id":"W4244513036","doi":"10.1007/978-0-387-39940-9_1127","title":"Distortion Techniques","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Distortion (music); Computer science; Telecommunications","score_opus":0.017738916780870445,"score_gpt":0.2654140392704605,"score_spread":0.24767512248959003,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4244513036","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[3.1980477e-7,0.000839764,0.28644392,0.000036467078,0.0005985468,0.00027330275,0.0006220664,0.00023323037,0.7109524],"genre_scores_gemma":[0.00020816115,0.005906569,0.011033056,0.00012585131,0.0007690895,0.000014651357,0.003238064,0.000054272627,0.9786503],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980291,0.000032523854,0.000704789,0.00048764667,0.00057176774,0.00017415558],"domain_scores_gemma":[0.99765736,0.00004083733,0.00061942486,0.0014036088,0.00016532015,0.0001134663],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00032962539,0.00029125853,0.00045912608,0.00029070867,0.000050362516,0.000073984076,0.0009930523,0.0001829049,0.000050893406],"category_scores_gemma":[0.00004131758,0.0002784456,0.00011043315,0.00008841681,0.000048038874,0.00054057897,0.00025687536,0.00018865005,0.00011502104],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001703362,0.000035939265,0.000006171515,0.00022390117,0.000029353,0.00003036545,0.000048172376,0.0000021696121,0.000017841363,0.8482915,0.11184652,0.03946635],"study_design_scores_gemma":[0.000062643674,0.000054690026,0.0000032364119,0.0005551084,0.000029514753,0.000011576445,0.000003270795,0.00078341225,0.000055811426,0.0009553889,0.99717927,0.0003060562],"about_ca_topic_score_codex":0.00003731886,"about_ca_topic_score_gemma":0.000007172733,"teacher_disagreement_score":0.88533276,"about_ca_system_score_codex":0.00006294178,"about_ca_system_score_gemma":0.0001323925,"threshold_uncertainty_score":0.9999668},"labels":[],"label_agreement":null},{"id":"W4244554172","doi":"10.1007/978-0-387-39940-9_1372","title":"Dynamic Graphics","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Computer graphics (images); Graphics","score_opus":0.01626787403273615,"score_gpt":0.26476674611917284,"score_spread":0.24849887208643667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4244554172","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[9.986783e-7,0.0023623833,0.19826493,0.00008101521,0.0013874808,0.00035651575,0.0017184038,0.00019888364,0.7956294],"genre_scores_gemma":[0.00027536083,0.01424696,0.0067721587,0.00025556792,0.00028540002,0.000008079002,0.0034203052,0.000076633696,0.97465956],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975194,0.000041132393,0.0008158476,0.0006229331,0.00074629515,0.00025438837],"domain_scores_gemma":[0.9969677,0.00010169357,0.00065194914,0.001907536,0.00020152054,0.00016960998],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00038468686,0.00038572977,0.00059931877,0.00045184838,0.00006504973,0.00010000251,0.0015322166,0.0002296689,0.00006123698],"category_scores_gemma":[0.00006656134,0.00037453405,0.0001626998,0.0001648757,0.00007472734,0.0005050908,0.0003632463,0.00029656355,0.0002015928],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001266712,0.000029130457,0.000003849969,0.00021908688,0.000047766905,0.00004683297,0.000043421045,0.000014343174,0.000003913723,0.9564307,0.039002206,0.0041575073],"study_design_scores_gemma":[0.00013568345,0.00005688695,0.0000062346057,0.0007398202,0.000049660357,0.000022123988,0.000005803958,0.020690324,0.0000015317944,0.0019547695,0.9758989,0.0004382616],"about_ca_topic_score_codex":0.000035598678,"about_ca_topic_score_gemma":0.000021513564,"teacher_disagreement_score":0.9544759,"about_ca_system_score_codex":0.000042922016,"about_ca_system_score_gemma":0.00020773502,"threshold_uncertainty_score":0.99987066},"labels":[],"label_agreement":null},{"id":"W4245022905","doi":"10.1109/infvis.2005.1532132","title":"An evaluation of content browsing techniques for hierarchical spacefilling visualizations","year":2005,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Zoom; Computer science; Distortion (music); Context (archaeology); Task (project management); Hierarchy; Representation (politics); Information retrieval; Visualization; Data mining","score_opus":0.14189911292060534,"score_gpt":0.4167735004888917,"score_spread":0.2748743875682864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245022905","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0022730767,0.000016139182,0.9957246,0.00060342904,0.000031525073,0.00024149744,0.0000064042165,0.00014448985,0.0009588004],"genre_scores_gemma":[0.612093,0.0000068685817,0.38729236,0.00038555847,0.000058129597,0.000014863464,0.000051193707,0.0000057160664,0.00009232758],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990872,0.000069588765,0.00023754063,0.00017834087,0.00032230405,0.00010500774],"domain_scores_gemma":[0.9990165,0.000046992132,0.00008101917,0.0002683275,0.00053376716,0.00005337496],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008456158,0.000060641716,0.000090814,0.00012381356,0.000076827884,0.00009111376,0.00027622096,0.000032834694,0.000028244269],"category_scores_gemma":[0.00012828715,0.00005468696,0.000036098245,0.00023015418,0.00002488008,0.000587987,0.00003707262,0.000024927314,0.0000020376888],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021257715,0.00018524114,0.00016101796,0.000009837343,0.000009499556,3.6446973e-8,0.00034646102,0.0018973263,0.008666483,0.8358612,0.0005706849,0.15229009],"study_design_scores_gemma":[0.00018429407,0.00005859759,0.00007509225,0.000013653298,0.000013910596,7.688356e-7,0.00004283807,0.94702005,0.04670736,0.002004504,0.0038065463,0.00007235485],"about_ca_topic_score_codex":0.0000069470375,"about_ca_topic_score_gemma":0.000020677475,"teacher_disagreement_score":0.9451228,"about_ca_system_score_codex":0.00003184941,"about_ca_system_score_gemma":0.00007662769,"threshold_uncertainty_score":0.22300695},"labels":[],"label_agreement":null},{"id":"W4245885544","doi":"10.14361/dcs-2019-0104","title":"Accounting for Visual Bias in Tangible Data Design","year":2019,"lang":"en","type":"article","venue":"Digital Culture & Society","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Citizen journalism; Computer science; Citizenship; Citizen science; Civic engagement; Data science; Representation (politics); Literacy; Open data; Public relations; Sociology; World Wide Web; Political science","score_opus":0.0900248887271399,"score_gpt":0.34171503968378264,"score_spread":0.2516901509566427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245885544","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036876872,0.00010165476,0.993528,0.0001774798,0.0001730419,0.0003295374,0.00014279877,0.00013641144,0.0017234056],"genre_scores_gemma":[0.89756036,0.00007218827,0.09039474,0.0034054483,0.00025758933,0.000016743807,0.0024769113,0.000038685448,0.005777357],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998976,0.000011066813,0.0001793733,0.00039732712,0.00020478616,0.00023145683],"domain_scores_gemma":[0.9992561,0.00007093245,0.00007364504,0.00047875848,0.00007752346,0.000043070188],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032037005,0.000112456895,0.00013126864,0.000017685366,0.00005542696,0.0009109505,0.001048184,0.00007035583,0.0000062994795],"category_scores_gemma":[0.000102920014,0.00009197986,0.00008120962,0.00044481718,0.000017069775,0.002783109,0.00048411387,0.00007822282,0.00007429167],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020798858,0.0008554328,0.025293292,0.000388591,0.00018831324,0.0000067813316,0.015379454,0.0015380436,0.001810391,0.07975221,0.84062874,0.034137942],"study_design_scores_gemma":[0.0006176945,0.000060480925,0.00019307136,0.000042923777,0.000005454566,0.0000025476515,0.0009886231,0.8210166,0.00025839038,0.0009995175,0.17552938,0.0002853218],"about_ca_topic_score_codex":0.0000028692136,"about_ca_topic_score_gemma":0.0000016214673,"teacher_disagreement_score":0.9031332,"about_ca_system_score_codex":0.000030977444,"about_ca_system_score_gemma":0.0000613626,"threshold_uncertainty_score":0.8784316},"labels":[],"label_agreement":null},{"id":"W4246079046","doi":"10.1007/978-1-4939-7131-2_100446","title":"Graph-Based Visual Analysis","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Psychology","score_opus":0.02521247095985135,"score_gpt":0.29996079197568587,"score_spread":0.2747483210158345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4246079046","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[4.8769766e-7,0.000017584112,0.63630676,0.00010334142,0.00008822844,0.00003436378,0.000015436663,0.00016093311,0.36327285],"genre_scores_gemma":[0.0003358413,0.000017317225,0.013378115,0.003158091,0.00011640489,0.0000011954114,0.00037955205,0.00002113766,0.98259234],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99857885,0.000012252864,0.00029306245,0.0005215148,0.00042758128,0.00016676952],"domain_scores_gemma":[0.9986529,0.000035206063,0.00016877396,0.0008207425,0.00019685816,0.00012551728],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00014744507,0.00023673505,0.00033406544,0.00089451997,0.000072942035,0.00026439576,0.00092025363,0.00016711575,0.0054537724],"category_scores_gemma":[0.000009221192,0.0002074498,0.00035965294,0.00041853645,0.00008610705,0.0001542636,0.00018666958,0.000096582706,0.0012474685],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.1844015e-7,0.000022153958,0.000019188863,0.000008120816,0.00045268753,0.000009566622,0.000013375528,0.000034318375,9.542802e-7,0.93716264,0.0607495,0.0015265682],"study_design_scores_gemma":[0.00014674303,0.00008469464,0.000014232108,0.00002038175,0.00050047436,6.982703e-7,0.0000015930373,0.34550676,0.000058446156,0.015724113,0.6374356,0.0005062403],"about_ca_topic_score_codex":0.000008109781,"about_ca_topic_score_gemma":0.000040626586,"teacher_disagreement_score":0.9214385,"about_ca_system_score_codex":0.00002200891,"about_ca_system_score_gemma":0.00009575018,"threshold_uncertainty_score":0.9995302},"labels":[],"label_agreement":null},{"id":"W4246417065","doi":"10.1007/978-0-387-39940-9_3949","title":"View Expression","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Expression (computer science); Computer science; Programming language","score_opus":0.022944200120654432,"score_gpt":0.2718390003324926,"score_spread":0.24889480021183816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4246417065","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[4.3891026e-7,0.003866302,0.1441618,0.000043907872,0.0011050622,0.00032214483,0.0007444698,0.00014492492,0.8496109],"genre_scores_gemma":[0.00009087991,0.01311878,0.008235053,0.00018980051,0.0006979515,0.000009697371,0.0023186745,0.000057715493,0.9752814],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99765325,0.000050747567,0.0007875051,0.0005873188,0.0007042476,0.0002169114],"domain_scores_gemma":[0.9971632,0.00007258571,0.000633576,0.001805287,0.00015853792,0.00016686028],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003542246,0.00034748306,0.00059746864,0.00025152892,0.00005953012,0.000089814515,0.0013591539,0.00018844992,0.00014048023],"category_scores_gemma":[0.000047693495,0.0003088275,0.00012601382,0.00009565494,0.00004188126,0.00057339546,0.00044928896,0.00021891309,0.0003324902],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002202326,0.000046930552,0.0000037780933,0.00052098045,0.000031238927,0.00005897976,0.00008188552,0.000013735857,0.000056328623,0.7855641,0.19420508,0.019414742],"study_design_scores_gemma":[0.0001420804,0.000040096347,0.0000016136933,0.0016283916,0.000026157753,0.000012819287,0.0000048132842,0.0015109798,0.000038049642,0.00062018365,0.9956384,0.0003364554],"about_ca_topic_score_codex":0.00001609348,"about_ca_topic_score_gemma":0.0000027270974,"teacher_disagreement_score":0.80143327,"about_ca_system_score_codex":0.000033074957,"about_ca_system_score_gemma":0.00016004557,"threshold_uncertainty_score":0.9999364},"labels":[],"label_agreement":null},{"id":"W4246930330","doi":"10.22215/etd/2011-09190","title":"Remote medical monitoring decision support system and user interface usability","year":2011,"lang":"en","type":"dissertation","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Canadian Heritage; Library and Archives Canada","funders":"","keywords":"Usability; Computer science; Graphical user interface; Visualization; Human–computer interaction; Data mining; User interface; Decision support system; Data visualization; Segmentation; Interface (matter); Data science; Artificial intelligence","score_opus":0.030558633461654796,"score_gpt":0.35122613014925147,"score_spread":0.3206674966875967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4246930330","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017661998,0.00007242078,0.9654591,0.000022275712,0.0023386276,0.0001372566,0.0000041604976,0.00026520644,0.014038971],"genre_scores_gemma":[0.76045877,0.0006018819,0.17583843,0.00017993088,0.00048844906,0.0000081755215,0.00038097776,0.0000909902,0.061952397],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99812424,0.0000517292,0.0004579059,0.00054076227,0.00064715755,0.000178192],"domain_scores_gemma":[0.9987482,0.00009091715,0.00014376227,0.0006245063,0.00016345385,0.00022916895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059563917,0.00019425638,0.00027027083,0.00011703835,0.00007955445,0.00021612612,0.00090666703,0.0002763524,0.0001787385],"category_scores_gemma":[0.00022316123,0.00016034645,0.000051291423,0.00019633766,0.000022796848,0.00036147345,0.0002460352,0.00020080685,0.00011003087],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000081032405,0.00021247884,0.007867096,0.0017267198,0.00013986036,0.00011414913,0.0033246097,0.0000046702553,0.00007559327,0.10151702,0.012146249,0.8727905],"study_design_scores_gemma":[0.0030540142,0.0007456659,0.04705056,0.010309358,0.00031664257,0.0003414821,0.00876607,0.79893315,0.022328753,0.0039651156,0.09969297,0.004496247],"about_ca_topic_score_codex":0.00011940874,"about_ca_topic_score_gemma":0.00010259143,"teacher_disagreement_score":0.8682943,"about_ca_system_score_codex":0.000046072226,"about_ca_system_score_gemma":0.00015573547,"threshold_uncertainty_score":0.6538738},"labels":[],"label_agreement":null},{"id":"W4247556202","doi":"10.1109/infvis.2005.1532129","title":"Elastic hierarchies: combining treemaps and node-link diagrams","year":2005,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Interleaving; Link (geometry); Theoretical computer science; Node (physics); Tree (set theory); Visualization; Software; Graphical model; Depiction; Data mining; Artificial intelligence; Programming language; Mathematics","score_opus":0.018471051467271606,"score_gpt":0.27209724729062085,"score_spread":0.2536261958233492,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247556202","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036614612,0.000066049484,0.98301965,0.0039064973,0.00008444832,0.000041670486,0.0000020456291,0.00019826488,0.009019922],"genre_scores_gemma":[0.9244331,0.00005908517,0.06831107,0.0035197695,0.00012330216,0.000002734871,0.000015980177,0.00000866703,0.003526265],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99933493,0.000022149863,0.00014646309,0.00020553118,0.00013536094,0.00015554218],"domain_scores_gemma":[0.99950844,0.00008801034,0.00003124154,0.0002517202,0.000024198918,0.000096408054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000110554865,0.00007907849,0.00009221096,0.0000736918,0.00008776032,0.00023506318,0.00031271292,0.00002401202,0.000045537403],"category_scores_gemma":[0.00004287234,0.00006597895,0.000017215363,0.00022104896,0.000041459054,0.0004108773,0.00018812781,0.000057681966,0.000108397755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000014914765,0.00008417409,0.0016344251,0.000014716174,0.000018215098,0.000005374322,0.0008593251,0.00058988127,0.00009179598,0.72694725,0.0074510397,0.26230228],"study_design_scores_gemma":[0.00039294927,0.000044406566,0.0010676498,0.000015595575,0.000005315483,0.000008833193,0.000026891634,0.95818084,0.00017022384,0.0021654377,0.037752304,0.00016954856],"about_ca_topic_score_codex":0.000005809255,"about_ca_topic_score_gemma":0.000022977812,"teacher_disagreement_score":0.95759094,"about_ca_system_score_codex":0.000008368526,"about_ca_system_score_gemma":0.000017849365,"threshold_uncertainty_score":0.26905435},"labels":[],"label_agreement":null},{"id":"W4247885906","doi":"10.31219/osf.io/ws7j9","title":"A Micro-Phenomenological Lens for Evaluating Narrative Visualization","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Narrative; Context (archaeology); Computer science; Visualization; Phenomenology (philosophy); Set (abstract data type); Narrative inquiry; Human–computer interaction; Psychology; Data science; Cognitive psychology; Epistemology; Artificial intelligence","score_opus":0.15561489976471388,"score_gpt":0.42940207735799424,"score_spread":0.27378717759328036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247885906","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0022656447,0.000038229377,0.99238485,0.00059545255,0.00060913747,0.0005960871,0.00003936484,0.0003380978,0.003133133],"genre_scores_gemma":[0.09087556,0.00008371329,0.89560497,0.004780045,0.0007683324,0.00028486573,0.0016352346,0.00006045521,0.0059068147],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980287,0.00013921884,0.00044379453,0.00080348714,0.00030444868,0.00028037876],"domain_scores_gemma":[0.99816656,0.00011308504,0.00031562962,0.0006691974,0.000669979,0.00006552864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007008323,0.00024943767,0.00030159435,0.00015396907,0.00022315347,0.0005153919,0.0011213458,0.00023839864,0.00016225762],"category_scores_gemma":[0.00039204775,0.00021410258,0.00011554365,0.0002523434,0.00007527266,0.00028122426,0.0015229163,0.00013851578,0.000059021364],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018825756,0.00029635802,0.00012508698,0.00022404047,0.00016509688,0.0000018428038,0.012847231,0.00086318183,0.00089161575,0.9355803,0.043536715,0.0054496946],"study_design_scores_gemma":[0.00037935135,0.00026605645,0.0000330815,0.000071442635,0.000026116113,0.0000019698668,0.0003539178,0.9492022,0.0007860243,0.04098635,0.007482883,0.000410615],"about_ca_topic_score_codex":0.0000053237773,"about_ca_topic_score_gemma":0.0000051096263,"teacher_disagreement_score":0.948339,"about_ca_system_score_codex":0.000085889944,"about_ca_system_score_gemma":0.00023809138,"threshold_uncertainty_score":0.87308496},"labels":[],"label_agreement":null},{"id":"W4247924210","doi":"10.4018/9781609601027.ch013","title":"iVAS","year":2011,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Materials science","score_opus":0.03903417294552776,"score_gpt":0.27652107212080157,"score_spread":0.23748689917527382,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247924210","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[2.5928017e-7,0.00007888712,0.10959525,0.00003231305,0.00040392086,0.00007655012,0.000061549836,0.00022538974,0.8895259],"genre_scores_gemma":[0.006267051,0.000016325004,0.006029406,0.003244593,0.00030487104,0.0000034228146,0.000017352482,0.000040260056,0.98407674],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99878377,0.000008661266,0.00025626985,0.00043188772,0.0003055073,0.00021392018],"domain_scores_gemma":[0.99870896,0.000008458211,0.00015659253,0.000878167,0.00009464825,0.00015316228],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00006868186,0.0002588558,0.0002470968,0.000055555825,0.000060691284,0.0001705169,0.0012122944,0.0002120236,0.00010224717],"category_scores_gemma":[0.000008191602,0.00025120226,0.00013598478,0.000019386487,0.00005618628,0.00009322471,0.00048420014,0.00012954076,0.0015619692],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.925304e-7,0.000004320711,0.0000019262102,0.000007455616,0.000027264336,0.000035082212,0.000023640663,1.8561593e-7,4.91421e-7,0.97348756,0.017429277,0.008981879],"study_design_scores_gemma":[0.00007765786,0.000025729421,0.000003346786,0.000044091114,0.000016154383,0.000016823506,4.4940936e-7,0.0001773447,0.000012318819,0.6011449,0.3982449,0.00023628568],"about_ca_topic_score_codex":0.000019716497,"about_ca_topic_score_gemma":0.000016857843,"teacher_disagreement_score":0.3808156,"about_ca_system_score_codex":0.000066648754,"about_ca_system_score_gemma":0.00015025362,"threshold_uncertainty_score":0.99999404},"labels":[],"label_agreement":null},{"id":"W4248438847","doi":"10.1007/978-1-4614-6170-8_110029","title":"Visual Exploration","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Psychology; Computer science","score_opus":0.04486058213340195,"score_gpt":0.30011530862612557,"score_spread":0.2552547264927236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4248438847","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[1.6475795e-8,0.0000066949397,0.5383526,0.00019199788,0.00012142278,0.000025737721,0.0000011503269,0.00011322522,0.46118715],"genre_scores_gemma":[0.0001888804,0.000057679255,0.0049809357,0.0014834749,0.00016658426,0.0000010837849,0.00012343086,0.00001501742,0.9929829],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992128,0.0000071260947,0.00018474457,0.00026868074,0.00024069563,0.00008594235],"domain_scores_gemma":[0.9993594,0.000018522884,0.000099332734,0.00038236796,0.00007993117,0.000060394603],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009611556,0.00013605281,0.00013797838,0.00011275359,0.000041875708,0.00019805919,0.00044175112,0.0001082392,0.0004281925],"category_scores_gemma":[0.000009361675,0.00012226001,0.000053444932,0.000026838408,0.000017392133,0.0002901855,0.00017680886,0.000075542965,0.0022109416],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.4511845e-7,0.000002640838,1.6412362e-7,0.0000043529267,0.0000055729843,0.0000012374843,0.000013407028,0.0000037505552,0.000001255503,0.9461215,0.03424215,0.019603835],"study_design_scores_gemma":[0.000051596136,0.000030592317,3.1300192e-7,0.000017661656,0.000005248292,0.0000012689059,9.06799e-7,0.069999106,0.000026652579,0.04178819,0.8879069,0.00017153454],"about_ca_topic_score_codex":0.0000010483395,"about_ca_topic_score_gemma":0.000004555177,"teacher_disagreement_score":0.9043333,"about_ca_system_score_codex":0.000015411819,"about_ca_system_score_gemma":0.0000361478,"threshold_uncertainty_score":0.998566},"labels":[],"label_agreement":null},{"id":"W4249762089","doi":"10.1109/tvcg.2014.28","title":"IEEE Visualization and Graphics Technical Committee","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ontario Institute of Technology","funders":"","keywords":"Computer science; Visualization; Graphics; Computer graphics (images); Data visualization; Computer graphics; Information visualization; Artificial intelligence","score_opus":0.019158344928986465,"score_gpt":0.28603747172961286,"score_spread":0.2668791268006264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4249762089","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002711787,0.00003372796,0.9954918,0.00015694456,0.00065266155,0.00024189249,0.000015241835,0.00059055537,0.00010540012],"genre_scores_gemma":[0.9901993,0.0009737394,0.0025656724,0.005931157,0.00011999354,0.00002409484,0.00004407695,0.000049102757,0.000092855444],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975404,0.0003058743,0.0005574067,0.000738205,0.0005236067,0.00033450604],"domain_scores_gemma":[0.9984585,0.00022176775,0.00018311774,0.0005988463,0.0002558579,0.000281923],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00052373344,0.0003650483,0.00034640974,0.0007540792,0.00062447676,0.0005784008,0.00046557255,0.00025138166,0.000010510619],"category_scores_gemma":[0.000011970101,0.00037159355,0.00010692038,0.0015882691,0.00024036694,0.00071806903,0.000018831466,0.00027062162,0.000011633036],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008055669,0.0002535886,0.00014248255,0.000049450453,0.00003153202,0.0000015363637,0.0003003043,0.00018181326,0.000031397292,0.9916446,0.0010038747,0.006351326],"study_design_scores_gemma":[0.0007878636,0.0003595588,0.00053315976,0.00006759721,0.000044854125,0.000038797494,0.00001604242,0.9850354,0.00080740376,0.0035011482,0.008351787,0.00045634556],"about_ca_topic_score_codex":0.000015514848,"about_ca_topic_score_gemma":0.00004264111,"teacher_disagreement_score":0.9929261,"about_ca_system_score_codex":0.000022349099,"about_ca_system_score_gemma":0.000038041413,"threshold_uncertainty_score":0.9998736},"labels":[],"label_agreement":null},{"id":"W4250284255","doi":"10.31234/osf.io/894zt","title":"Dyadic and triadic search: Benefits, costs, and predictors of group performance","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Task (project management); Set (abstract data type); Visual search; Gaze; Variance (accounting); Scale (ratio); Psychology; Group (periodic table); Cognitive psychology; Computer science; Social psychology; Artificial intelligence; Economics; Geography","score_opus":0.03852607505788484,"score_gpt":0.2799432388993827,"score_spread":0.24141716384149786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4250284255","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7482988,0.0032901159,0.24141948,0.00039284682,0.0009835131,0.00077185314,0.00019279489,0.0002174443,0.004433143],"genre_scores_gemma":[0.9884014,0.006755864,0.0037532044,0.0001861244,0.000050327784,0.0000040409586,0.00010638222,0.000012326136,0.00073028984],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99869096,0.000050516162,0.00030275615,0.00046616147,0.0003151279,0.00017449619],"domain_scores_gemma":[0.9989812,0.00006881992,0.00013091654,0.00061296945,0.00008091337,0.00012522742],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042820472,0.00017000626,0.00030001032,0.00020763653,0.00004409322,0.00018029357,0.00061930215,0.00013556189,0.000018118399],"category_scores_gemma":[0.00002531468,0.0001458397,0.000033545,0.00017891287,0.00009421761,0.00027919072,0.0018256307,0.00021514714,0.000007665443],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043391447,0.00031550307,0.32738152,0.0035821176,0.0003641677,0.0000053365584,0.0020145117,0.0021732445,0.0000903018,0.44137585,0.008819198,0.21383487],"study_design_scores_gemma":[0.0008760661,0.00024467855,0.07356883,0.00043194267,0.000040496074,0.000010822805,0.000057901252,0.92034996,0.00030468332,0.00020350062,0.0035122081,0.00039890475],"about_ca_topic_score_codex":0.00005882415,"about_ca_topic_score_gemma":0.000008356853,"teacher_disagreement_score":0.9181767,"about_ca_system_score_codex":0.000024209301,"about_ca_system_score_gemma":0.00008993335,"threshold_uncertainty_score":0.5947171},"labels":[],"label_agreement":null},{"id":"W4250319003","doi":"10.1007/978-1-4419-1153-7_1112","title":"Visualization","year":2013,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Visualization; Computer science; Artificial intelligence","score_opus":0.03165544607690019,"score_gpt":0.2909592387324891,"score_spread":0.2593037926555889,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4250319003","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[1.47927555e-8,0.000020239346,0.4758668,0.00008170225,0.00010451898,0.00004451165,0.0000021221242,0.00014638569,0.52373374],"genre_scores_gemma":[0.00003178598,0.0001149077,0.0055674515,0.0014311179,0.000075672084,0.0000014046683,0.00012315459,0.000018498407,0.992636],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991706,0.0000050825497,0.00020189349,0.0002790777,0.00024387147,0.00009946424],"domain_scores_gemma":[0.9991745,0.0000144733785,0.00010871913,0.00050531037,0.00012632052,0.00007069469],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000052622458,0.00015103792,0.00013896034,0.0001314448,0.000040017407,0.00026510513,0.00058714615,0.00013186736,0.004352638],"category_scores_gemma":[0.0000084682215,0.00013347158,0.00005387343,0.000039717106,0.000018891838,0.00034279327,0.00022052079,0.00006341624,0.0069882753],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.8485553e-8,0.0000030773147,3.0884726e-7,0.0000051392167,0.0000072703133,0.0000011243467,0.000009184201,0.0000010698699,0.0000010204154,0.870411,0.12329329,0.006267524],"study_design_scores_gemma":[0.000042748354,0.000012671011,0.0000011800132,0.000020731066,0.0000054357247,0.0000020788284,5.51721e-7,0.046581704,0.00001715904,0.057341225,0.89578784,0.00018671062],"about_ca_topic_score_codex":0.0000031319264,"about_ca_topic_score_gemma":0.0000018194888,"teacher_disagreement_score":0.81306976,"about_ca_system_score_codex":0.00002041863,"about_ca_system_score_gemma":0.000043246782,"threshold_uncertainty_score":0.99655753},"labels":[],"label_agreement":null},{"id":"W4250473012","doi":"10.31219/osf.io/5vyzj","title":"Data Visualization + Scrollytelling for Election News Stories : Challenges and Perspectives","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Newspaper; Narrative; Context (archaeology); Visualization; Computer science; Media studies; Sociology; History; Art; Literature; Data mining","score_opus":0.1610773299808418,"score_gpt":0.3783403905368621,"score_spread":0.2172630605560203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4250473012","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000075010554,0.0055983653,0.9906563,0.0012604124,0.0005952368,0.0004167087,0.000079116384,0.00022521029,0.0010936314],"genre_scores_gemma":[0.31780422,0.243159,0.4112843,0.0016333155,0.0031132963,0.00016238108,0.008655111,0.0002524759,0.013935916],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983379,0.00005724012,0.00024090997,0.00098705,0.00020743471,0.00016944448],"domain_scores_gemma":[0.9981501,0.00009997344,0.00018980414,0.0012394062,0.0002672413,0.000053471118],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003917529,0.00020106345,0.00025201088,0.0001962401,0.00010937456,0.0005506543,0.0010412072,0.00015809716,0.0000058052315],"category_scores_gemma":[0.00017033657,0.00019134015,0.00003599592,0.0001315162,0.000029867077,0.00079977926,0.0017991092,0.000120952995,0.0000056735594],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009320527,0.000092085014,0.00006026571,0.00044041514,0.00009506579,3.2536366e-7,0.005447381,0.0007424787,0.000023076147,0.933717,0.004615918,0.054756645],"study_design_scores_gemma":[0.00020264092,0.00005832287,0.00009890768,0.00006524982,0.000029902947,0.0000017130479,0.0018626702,0.9443307,0.000088589295,0.0073737293,0.04558606,0.00030152337],"about_ca_topic_score_codex":0.000030678075,"about_ca_topic_score_gemma":0.0001567031,"teacher_disagreement_score":0.9435882,"about_ca_system_score_codex":0.000043778688,"about_ca_system_score_gemma":0.000141813,"threshold_uncertainty_score":0.7802625},"labels":[],"label_agreement":null},{"id":"W4250636153","doi":"10.1007/978-1-4614-6170-8_100305","title":"Research in Network Visualization","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Visualization; Computer science; Artificial intelligence","score_opus":0.09695450705031675,"score_gpt":0.39032470807282393,"score_spread":0.2933702010225072,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4250636153","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[6.10874e-8,0.000039793053,0.48079827,0.00014247574,0.00011716683,0.00006529705,8.085795e-7,0.000060383434,0.51877576],"genre_scores_gemma":[0.0007158416,0.0002542336,0.0033323462,0.00092960557,0.00037342517,0.0000031024808,0.00012136265,0.000029657742,0.9942404],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983396,0.000075488075,0.0003117165,0.00042544588,0.0005688816,0.0002788813],"domain_scores_gemma":[0.99888015,0.00012390078,0.000078532554,0.00065463316,0.00018617978,0.00007658866],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0012672957,0.00014182314,0.00020032318,0.00042883362,0.000073962234,0.00024001884,0.000886484,0.00020403818,0.00030681308],"category_scores_gemma":[0.0000197585,0.0001355187,0.000039849503,0.0002860757,0.000048560098,0.00013861056,0.00046919592,0.0002628976,0.00092803786],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.2732287e-7,0.0000043225123,0.000009144084,0.000011592161,0.0000033611495,0.000004753189,0.000014160117,0.00014383407,1.2371781e-7,0.9288966,0.06511304,0.00579864],"study_design_scores_gemma":[0.00007613525,0.000025267607,0.000007678582,0.00011818792,0.0000013757942,0.0000011530354,0.0000012522781,0.13195138,0.0000015676823,0.12292059,0.7447426,0.00015283424],"about_ca_topic_score_codex":0.000011553722,"about_ca_topic_score_gemma":0.000077075565,"teacher_disagreement_score":0.80597603,"about_ca_system_score_codex":0.000060077855,"about_ca_system_score_gemma":0.00009151053,"threshold_uncertainty_score":0.99984986},"labels":[],"label_agreement":null},{"id":"W4250775590","doi":"10.1016/s1365-6937(04)00487-3","title":"Alfa Laval AB, Sweden","year":2004,"lang":"en","type":"article","venue":"Filtration Industry Analyst","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Computer graphics (images); Byte; Source code; Ray tracing (physics); Identifier; Code (set theory); Programming language; Physics; Optics; Set (abstract data type)","score_opus":0.033848595058528476,"score_gpt":0.3045120762053717,"score_spread":0.2706634811468432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4250775590","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0121072,0.000025911042,0.96977377,0.005017285,0.00030336177,0.00009676189,0.000026079433,0.00028191274,0.012367741],"genre_scores_gemma":[0.99094427,0.00001261881,0.005370279,0.0013059105,0.00024455806,0.00000561917,0.00016324877,0.000007737671,0.00194575],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99892414,0.000039866154,0.0002696537,0.00028271292,0.00030457744,0.00017907555],"domain_scores_gemma":[0.9991986,0.000015962318,0.000110383975,0.00045161587,0.00010051383,0.000122888],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018614397,0.00011233315,0.00011899947,0.00013109024,0.00016035771,0.00032476036,0.0005488994,0.00018849452,0.00019202975],"category_scores_gemma":[0.00006516289,0.00010896838,0.000059110713,0.0008477419,0.000031452342,0.0008423246,0.00006920169,0.0002642953,0.0002613143],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005343864,0.00040225947,0.010891847,0.000023114173,0.00014827908,0.00007293921,0.0008782397,0.031683087,0.0031399403,0.8815227,0.0659136,0.00531861],"study_design_scores_gemma":[0.0065620127,0.000597353,0.056642633,0.00035038922,0.0003216769,0.0003255668,0.0017544421,0.36719918,0.105276145,0.042035297,0.41525334,0.0036819766],"about_ca_topic_score_codex":0.000066272565,"about_ca_topic_score_gemma":0.000039594426,"teacher_disagreement_score":0.9788371,"about_ca_system_score_codex":0.00004680123,"about_ca_system_score_gemma":0.00017201758,"threshold_uncertainty_score":0.44436017},"labels":[],"label_agreement":null},{"id":"W4251997178","doi":"10.14236/ewic/eva2014.65","title":"Data Materiality","year":2014,"lang":"en","type":"article","venue":"Electronic workshops in computing","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Materiality (auditing); Raw data; Object (grammar); Meaning (existential); Presentation (obstetrics); Computer science; Aesthetics; Sublime; Epistemology; Art; Artificial intelligence; Philosophy","score_opus":0.031679394883441715,"score_gpt":0.3204867691386554,"score_spread":0.2888073742552137,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251997178","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00761701,0.00006276691,0.98964494,0.0006103849,0.00032926133,0.000055967,0.0000021760275,0.00017958831,0.0014978797],"genre_scores_gemma":[0.9859734,0.00001117916,0.013045824,0.0006294385,0.00018091015,5.36077e-7,0.00007232978,0.000008726229,0.00007763475],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983563,0.00016711393,0.00029548505,0.00049392367,0.00018514294,0.00050205796],"domain_scores_gemma":[0.99839747,0.00014211879,0.00009052452,0.0012988551,0.000024162122,0.00004689285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016588579,0.00011090643,0.00015766194,0.000083866405,0.00009119668,0.00027994745,0.0022551636,0.000047609366,0.00001573259],"category_scores_gemma":[0.0001807647,0.000113281276,0.000017474938,0.00060314196,0.00002200185,0.00038623143,0.0012442006,0.00020386474,0.000039571492],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000031296347,0.0000934548,0.0018455223,0.000019295705,0.000013631775,0.0000036582717,0.00018664132,0.002364384,0.00008602269,0.76810265,0.004208348,0.22307323],"study_design_scores_gemma":[0.0002049977,0.000014482012,0.0008488301,0.00003043903,0.0000018460648,0.0000051595816,0.00000719793,0.9515472,0.00006684948,0.0055247555,0.041602366,0.00014584976],"about_ca_topic_score_codex":0.000011653183,"about_ca_topic_score_gemma":0.00004880102,"teacher_disagreement_score":0.9783564,"about_ca_system_score_codex":0.00006806215,"about_ca_system_score_gemma":0.00008529746,"threshold_uncertainty_score":0.46194765},"labels":[],"label_agreement":null},{"id":"W4252036084","doi":"10.1007/978-1-4939-7131-2_101434","title":"Visual Exploration","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Psychology","score_opus":0.0563078377444451,"score_gpt":0.31515211889096295,"score_spread":0.25884428114651786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252036084","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[6.90872e-8,0.000007578113,0.51645684,0.00012770089,0.00016169499,0.000029135072,0.0000022113065,0.00011787968,0.4830969],"genre_scores_gemma":[0.000053373504,0.00006278376,0.0066099963,0.0010411575,0.00026406042,9.603998e-7,0.00011597806,0.00001449927,0.9918372],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992031,0.0000051440156,0.00017811405,0.00028225387,0.00024212089,0.00008926661],"domain_scores_gemma":[0.99932855,0.000011563094,0.000093337134,0.0003832565,0.00012500341,0.000058303212],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00007989193,0.00013414657,0.00011819192,0.00011522947,0.00004839015,0.00021309582,0.0004594137,0.00011059249,0.0022021816],"category_scores_gemma":[0.0000079731735,0.00012009378,0.000048543057,0.0000339807,0.000032429787,0.00054679747,0.00021857934,0.000061442,0.0049191406],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.2040476e-7,0.0000044839016,1.2831893e-7,0.0000030665071,0.000007222326,0.0000019927156,0.000042092342,4.306308e-7,0.0000014866254,0.89484113,0.10000015,0.0050975946],"study_design_scores_gemma":[0.00004947653,0.00005052459,2.7261345e-7,0.00002016619,0.000005679771,0.0000016095453,0.0000029512773,0.029875923,0.00006042871,0.0761631,0.89358956,0.00018033579],"about_ca_topic_score_codex":8.53955e-7,"about_ca_topic_score_gemma":0.0000061881647,"teacher_disagreement_score":0.818678,"about_ca_system_score_codex":0.000018246916,"about_ca_system_score_gemma":0.00005167857,"threshold_uncertainty_score":0.9987099},"labels":[],"label_agreement":null},{"id":"W4252086586","doi":"10.31219/osf.io/3b7fc","title":"A Design Space for Visualization Onboarding in Data-Driven Stories","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Onboarding; Visualization; Computer science; Storytelling; Process (computing); Narrative; Human–computer interaction; Space (punctuation); Abstraction; Data visualization; Data science; Multimedia; Artificial intelligence; Psychology","score_opus":0.14539201491181475,"score_gpt":0.3885485196970393,"score_spread":0.24315650478522455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252086586","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000078070356,0.00008566454,0.99787855,0.0005187472,0.0006307009,0.0004061096,0.000041361243,0.00017040526,0.00019039775],"genre_scores_gemma":[0.027378988,0.00022405523,0.9667145,0.00053871877,0.0001587054,0.00005983871,0.00351251,0.000034094675,0.0013785914],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981653,0.00014559293,0.0003448193,0.00085400953,0.00027432953,0.000215913],"domain_scores_gemma":[0.9978947,0.00016667011,0.00017369048,0.0014986744,0.00020638021,0.000059906553],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006395903,0.00019400194,0.00031044302,0.00021691907,0.00006625582,0.0009900845,0.0018497875,0.00015006824,0.000018257086],"category_scores_gemma":[0.00033968856,0.00020056314,0.000046388686,0.00045908813,0.000018460036,0.00077211094,0.0034345146,0.0001367071,0.000004695794],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014046359,0.00035771448,0.00047679504,0.00069033547,0.00015686231,0.00003462838,0.005676604,0.14397097,0.0003070126,0.7998504,0.042985633,0.0054789986],"study_design_scores_gemma":[0.00019689165,0.000012281449,0.000022430633,0.00012706676,0.000014271199,9.876338e-7,0.00020121556,0.99188805,0.00041214636,0.0012791825,0.0055966354,0.00024885568],"about_ca_topic_score_codex":0.00006229829,"about_ca_topic_score_gemma":0.00016726383,"teacher_disagreement_score":0.8479171,"about_ca_system_score_codex":0.00009350849,"about_ca_system_score_gemma":0.000441777,"threshold_uncertainty_score":0.95474076},"labels":[],"label_agreement":null},{"id":"W4252225706","doi":"10.22215/etd/2015-10964","title":"Constructing Visual Narratives of Museum Experiences","year":2015,"lang":"en","type":"dissertation","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Visualization; Usability; Narrative; Operability; Flexibility (engineering); Computer science; Construct (python library); Presentation (obstetrics); World Wide Web; Multimedia; Human–computer interaction; Creative visualization; Software engineering; Artificial intelligence","score_opus":0.029116540821076974,"score_gpt":0.36745127232945196,"score_spread":0.338334731508375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252225706","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3551142,0.00044211218,0.31197557,0.0002918342,0.007988133,0.00041463893,0.000029280214,0.0005887538,0.32315546],"genre_scores_gemma":[0.9518154,0.000017254533,0.03674443,0.0000827576,0.00009134084,0.00001843505,0.00085368485,0.000020856407,0.0103558265],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9989026,0.00003978817,0.000319137,0.00026013667,0.00036427294,0.000114074035],"domain_scores_gemma":[0.9990834,0.00002932334,0.0002964992,0.0002121499,0.00031367966,0.000064959815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014154825,0.00013420093,0.00023094093,0.00014913196,0.000043515174,0.000114287344,0.00058578345,0.000088757675,0.00012606931],"category_scores_gemma":[0.00010795021,0.00011446593,0.000046122568,0.00034623127,0.000049534552,0.00039787038,0.00006009332,0.0000699359,0.000012308864],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014443748,0.00019574472,0.00036039663,0.00024382537,0.00010800921,0.000008844371,0.34131432,0.0000054200623,0.00064378715,0.59230524,0.017258886,0.04754106],"study_design_scores_gemma":[0.00025217168,0.00013788772,0.000030687606,0.00014993566,0.000010462461,0.000005246065,0.9588681,0.020758323,0.013441599,0.0026307758,0.0032533768,0.00046145095],"about_ca_topic_score_codex":0.000015814321,"about_ca_topic_score_gemma":0.000089605615,"teacher_disagreement_score":0.6175538,"about_ca_system_score_codex":0.000016154518,"about_ca_system_score_gemma":0.00025998117,"threshold_uncertainty_score":0.46677855},"labels":[],"label_agreement":null},{"id":"W4252419279","doi":"10.1057/palgrave.ivs.9500005","title":"Filtering and Brushing with Motion","year":2002,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Colligo (Canada); Simon Fraser University","funders":"","keywords":"Computer science; Motion (physics); Pairwise comparison; Visualization; Computer vision; Filter (signal processing); Structure from motion; Artificial intelligence; Perception; Vocabulary; Human–computer interaction","score_opus":0.01898284192553616,"score_gpt":0.2502139247567247,"score_spread":0.23123108283118857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252419279","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0028108777,0.00001195857,0.9937409,0.00018669188,0.00005559466,0.000080776736,0.0000022980505,0.00020953765,0.0029013702],"genre_scores_gemma":[0.9886226,0.000067238565,0.009890662,0.0011585719,0.00002625962,0.0000062693784,0.000103770966,0.0000061525375,0.00011845102],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993553,0.000021383306,0.00021114286,0.00009476077,0.00021418522,0.00010319652],"domain_scores_gemma":[0.99954516,0.000013692585,0.00012341645,0.00015965269,0.00010759483,0.000050485705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011667005,0.00007791761,0.000063164734,0.00017652893,0.00013262987,0.00053665286,0.00013742538,0.00003175302,0.0000449928],"category_scores_gemma":[0.000040533676,0.000070022674,0.000009041656,0.00042144276,0.00001614068,0.0060215234,0.000058174624,0.000032475662,0.00007422349],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000037635139,0.000053353793,0.0024795975,0.00010187948,0.000018205454,0.0000014970977,0.009100495,0.002746772,0.000105669,0.7916996,0.003248312,0.19044088],"study_design_scores_gemma":[0.00026503293,0.000034695127,0.0010295333,0.000022659004,0.0000032295143,0.000014178217,0.00007628993,0.982734,0.00035131944,0.00014516983,0.015207731,0.000116153795],"about_ca_topic_score_codex":0.000004633463,"about_ca_topic_score_gemma":0.0000014873294,"teacher_disagreement_score":0.98581177,"about_ca_system_score_codex":0.000019581677,"about_ca_system_score_gemma":0.0000050133813,"threshold_uncertainty_score":0.51749563},"labels":[],"label_agreement":null},{"id":"W4252910698","doi":"10.1007/978-1-4939-7131-2_101330","title":"Temporal Networks or Graphs","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science","score_opus":0.04113799223574016,"score_gpt":0.28904913108491503,"score_spread":0.24791113884917487,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252910698","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[4.4837787e-8,0.000027146218,0.52699614,0.00007846884,0.00030000284,0.000044094395,0.000004828142,0.00015423157,0.47239503],"genre_scores_gemma":[0.00007596912,0.00012709183,0.010458601,0.0020231772,0.00022566401,7.8444566e-7,0.00010087257,0.000020316435,0.9869675],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989892,0.0000069093644,0.00024008793,0.0003711742,0.00023085797,0.0001617557],"domain_scores_gemma":[0.99893373,0.000023406707,0.00012675131,0.0007069802,0.00010384854,0.000105261955],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000111141686,0.00019874494,0.0001989041,0.0001305087,0.00006500892,0.0002351463,0.00094910595,0.00018480889,0.0044263094],"category_scores_gemma":[0.0000067078713,0.00014256442,0.00008898895,0.00007595215,0.000071225026,0.00020047251,0.00035982943,0.00012062839,0.0008084607],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.217499e-7,0.0000038508933,0.0000028347024,0.000003200022,0.000015151776,0.000011099442,0.000009566009,0.0000023019447,2.0841293e-8,0.7360959,0.26151887,0.0023362644],"study_design_scores_gemma":[0.00007473644,0.000057282716,0.0000011586588,0.000036660236,0.00000918888,0.0000073047436,0.0000011609242,0.07243357,0.0000010388057,0.035947137,0.8911902,0.00024059256],"about_ca_topic_score_codex":0.0000048963852,"about_ca_topic_score_gemma":0.000053024047,"teacher_disagreement_score":0.7001488,"about_ca_system_score_codex":0.000012660259,"about_ca_system_score_gemma":0.00007330611,"threshold_uncertainty_score":0.99996954},"labels":[],"label_agreement":null},{"id":"W4253058568","doi":"10.31219/osf.io/pyqac","title":"Just TYPEical: Visualizing Common Function Type Signatures in R","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Programming language; Visualization; Data type; Abstraction; Function (biology); Task (project management); Type (biology); Artificial intelligence","score_opus":0.0806900216393894,"score_gpt":0.36618207776237127,"score_spread":0.2854920561229819,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4253058568","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009300475,0.0003498582,0.9685059,0.0028414652,0.0021210266,0.00026275287,0.000010177724,0.00070515875,0.024273595],"genre_scores_gemma":[0.9826302,0.00013770093,0.008619468,0.0068219197,0.0002294122,0.000006358708,0.0002621463,0.000028303211,0.0012644692],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99867177,0.000089276065,0.0002994719,0.0005068345,0.00026505583,0.00016756519],"domain_scores_gemma":[0.9991669,0.0000456624,0.000107805565,0.00051118265,0.00007776541,0.00009067003],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017222576,0.00017792957,0.00025191216,0.00016576059,0.00003650573,0.00031652313,0.0008652619,0.00022108862,0.00013630021],"category_scores_gemma":[0.000074220174,0.000166219,0.000055669992,0.00058777846,0.000017993187,0.00017219917,0.0014536472,0.000510121,0.00016120705],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025530644,0.00018636925,0.0010795754,0.00023949337,0.00005737013,0.000046013516,0.0005591792,0.0067196717,0.0002910882,0.8647911,0.11606005,0.009944558],"study_design_scores_gemma":[0.0002116069,0.000080536985,0.0021911429,0.000111580135,0.000020834648,6.9806157e-7,0.000059626105,0.9263179,0.00017456483,0.01341319,0.05699763,0.00042071872],"about_ca_topic_score_codex":0.00007505247,"about_ca_topic_score_gemma":0.00007265202,"teacher_disagreement_score":0.9817002,"about_ca_system_score_codex":0.000045339308,"about_ca_system_score_gemma":0.000111693604,"threshold_uncertainty_score":0.67782146},"labels":[],"label_agreement":null},{"id":"W4253515427","doi":"10.1063/1.2405673","title":"Focus on Software","year":2001,"lang":"en","type":"article","venue":"Physics Today","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Focus (optics); Software; Computer science; Software engineering; Physics; Programming language; Optics","score_opus":0.028381705397240938,"score_gpt":0.2918741442060938,"score_spread":0.26349243880885287,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4253515427","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00044374695,0.000008134829,0.98891926,0.0006098113,0.00013634063,0.000028468812,0.0000034170835,0.00016295954,0.00968785],"genre_scores_gemma":[0.97091126,0.00004673807,0.021329839,0.0037658536,0.00044874716,0.000005868724,0.00002867256,0.000018921333,0.0034441168],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99945474,0.000014864327,0.000071313385,0.00016765717,0.00016470863,0.0001267264],"domain_scores_gemma":[0.9994847,0.000026582898,0.000030397165,0.00037448987,0.000034135497,0.0000496499],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000046035755,0.000065561464,0.00006389184,0.000021236277,0.000059395967,0.000094449824,0.00039571244,0.000015066634,0.00002126563],"category_scores_gemma":[0.000019096187,0.000059031685,0.000032521744,0.000301077,0.000011429903,0.00024745133,0.000088881614,0.0000475625,0.0005586052],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001021899,0.00010243675,0.0005757736,0.0000020697628,0.000006151298,0.000008388431,0.000117028925,0.00019675447,0.000033031858,0.8561999,0.011317659,0.13143975],"study_design_scores_gemma":[0.00075581257,0.00020074064,0.0016857712,0.000053326512,0.0000129393,0.0000087122025,0.000017574654,0.20804514,0.009339061,0.47149274,0.30770245,0.00068573887],"about_ca_topic_score_codex":0.000004769069,"about_ca_topic_score_gemma":0.0000010606545,"teacher_disagreement_score":0.9704675,"about_ca_system_score_codex":0.000012335188,"about_ca_system_score_gemma":0.00001759999,"threshold_uncertainty_score":0.7179926},"labels":[],"label_agreement":null},{"id":"W4254490032","doi":"10.31219/osf.io/8b9xs","title":"Evaluating 'Graphical Perception' with CNNs","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Visualization; Perception; Convolutional neural network; Task (project management); Artificial intelligence; Visual perception; Human–computer interaction; Pattern recognition (psychology); Psychology; Engineering","score_opus":0.09518307370229437,"score_gpt":0.40709417920390134,"score_spread":0.31191110550160694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254490032","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005653355,0.0000054344728,0.9833611,0.0008131519,0.00023569717,0.00011986179,0.000006385882,0.0003001741,0.009504798],"genre_scores_gemma":[0.22813995,0.000034332872,0.7650101,0.0024512848,0.00042561835,0.000022221528,0.00017335718,0.000025288353,0.003717846],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99844104,0.0000776799,0.00021239524,0.0005778338,0.00051335664,0.00017766943],"domain_scores_gemma":[0.9985369,0.000027843507,0.00011023019,0.0009441001,0.00028246347,0.0000984484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041953125,0.00016771989,0.00016763063,0.00013697997,0.00010333119,0.00049198,0.0010963385,0.00012524426,0.0004681566],"category_scores_gemma":[0.00004604927,0.00012286974,0.00006117175,0.00028381558,0.00008522428,0.00017485226,0.0013371599,0.00023410219,0.00022800826],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026097745,0.0007074736,0.009022461,0.00042880807,0.00041809026,0.00003963054,0.004070495,0.004963293,0.00037282187,0.7672418,0.109733835,0.10297521],"study_design_scores_gemma":[0.00015890245,0.00012728789,0.0020844724,0.00008341506,0.000020947135,0.00000784988,0.00003517575,0.98863167,0.000020414855,0.006344446,0.0021950302,0.00029041545],"about_ca_topic_score_codex":0.000021752732,"about_ca_topic_score_gemma":0.000018634282,"teacher_disagreement_score":0.9836683,"about_ca_system_score_codex":0.000026989977,"about_ca_system_score_gemma":0.00018989418,"threshold_uncertainty_score":0.51259863},"labels":[],"label_agreement":null},{"id":"W4254923946","doi":"10.4018/9781605660103.ch316","title":"Visualization Techniques for Confidence Based Data","year":2011,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of Guelph; Mount Allison University","funders":"","keywords":"Computer science; Visualization; Decision support system; Context (archaeology); Data visualization; Certainty; Interfacing; Visual analytics; Data mining; Data science; Artificial intelligence; Human–computer interaction; Mathematics","score_opus":0.07953017313347176,"score_gpt":0.3397596192978399,"score_spread":0.2602294461643681,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254923946","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[1.5029292e-8,0.00004028246,0.5832662,0.000027371216,0.00014936017,0.00028006526,0.0006103113,0.00029657874,0.4153298],"genre_scores_gemma":[0.012624178,0.0001238496,0.5290883,0.025186662,0.0017190573,0.00019248719,0.0051397737,0.00040702222,0.42551866],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981734,0.000018115836,0.00041689773,0.0007979807,0.00035537852,0.00023823057],"domain_scores_gemma":[0.9971634,0.000043888354,0.00033976862,0.002024562,0.00030411518,0.0001242346],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00027383777,0.0003195943,0.0003180531,0.00009890601,0.00010265038,0.00028057967,0.0027469166,0.00028324302,0.00003284931],"category_scores_gemma":[0.00006423697,0.00032615472,0.000091550144,0.000036785783,0.00008216497,0.0002825889,0.0007032078,0.000087562774,0.00006562779],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004815517,0.0000095100695,0.0000013714117,0.000041852352,0.000019859152,0.000004984517,0.000008640447,2.999876e-7,0.00000407005,0.9696866,0.020652669,0.009565275],"study_design_scores_gemma":[0.00016180535,0.00008930474,7.340027e-7,0.00021058557,0.00005178386,0.000006033038,7.5389687e-7,0.026802044,0.0003623901,0.49829158,0.47359583,0.00042713297],"about_ca_topic_score_codex":0.000027564658,"about_ca_topic_score_gemma":0.000034953497,"teacher_disagreement_score":0.47139505,"about_ca_system_score_codex":0.00007323522,"about_ca_system_score_gemma":0.00038058788,"threshold_uncertainty_score":0.99991906},"labels":[],"label_agreement":null},{"id":"W4255566302","doi":"10.4018/978-1-59904-941-0.ch131","title":"Explaining Algorithms","year":2008,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Acadia University","funders":"","keywords":"Traverse; Computer science; Abstraction; Visualization; Focus (optics); Hierarchy; Theoretical computer science; Graph; Algorithm; Artificial intelligence","score_opus":0.03742194145397162,"score_gpt":0.2852821823026135,"score_spread":0.24786024084864186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4255566302","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[4.994422e-7,0.00015232866,0.16486895,0.00004288121,0.0004330457,0.00007850487,0.000069221955,0.00027448052,0.8340801],"genre_scores_gemma":[0.0060266713,0.0001535747,0.056299344,0.006477472,0.001150699,0.000012025501,0.00007481571,0.000109734465,0.92969567],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99837583,0.000011386934,0.00032859656,0.00052869116,0.00047938325,0.00027610632],"domain_scores_gemma":[0.99874145,0.000019365993,0.00018847213,0.0007679582,0.00010609324,0.00017664797],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007350566,0.0003145654,0.00031488785,0.000075346215,0.00013785488,0.00019660247,0.0010886453,0.00022998541,0.000027717406],"category_scores_gemma":[0.000012589283,0.00032083658,0.00015150651,0.00003139824,0.00006964695,0.0001294318,0.0004625611,0.00017826486,0.00059169886],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.19586e-7,0.000003821093,0.0000016353778,0.0000053989174,0.000027459251,0.00014040686,0.00006439442,0.0000031300472,3.9000886e-7,0.959654,0.024691127,0.015407533],"study_design_scores_gemma":[0.00029228898,0.000065125525,0.0000053134077,0.00014575223,0.000023108609,0.00020340548,0.000005702215,0.008754721,0.00001900433,0.12490508,0.86490047,0.0006800211],"about_ca_topic_score_codex":0.00001043813,"about_ca_topic_score_gemma":0.0000073084143,"teacher_disagreement_score":0.84020936,"about_ca_system_score_codex":0.00008107186,"about_ca_system_score_gemma":0.00020270114,"threshold_uncertainty_score":0.99992436},"labels":[],"label_agreement":null},{"id":"W4255889623","doi":"10.1145/3186728.3164139","title":"The ubiquity of large graphs and surprising challenges of graph processing","year":2017,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":145,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Suite; Scalability; Visualization; Graph; Software; Data science; Theoretical computer science; World Wide Web; Data mining; Programming language; Database","score_opus":0.03165215848905461,"score_gpt":0.305877498930536,"score_spread":0.2742253404414814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4255889623","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9529137,0.007738642,0.006533025,0.010939031,0.0005543471,0.0009844365,0.00003565786,0.00011266666,0.020188492],"genre_scores_gemma":[0.9978432,0.0012031455,0.00087847805,0.000024760504,0.000007285321,0.0000030242907,1.3508314e-7,0.000004299002,0.000035663452],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99908924,0.0000071133745,0.0002628044,0.00016793047,0.00032059662,0.00015233086],"domain_scores_gemma":[0.998675,0.00002990881,0.00071509834,0.00028590407,0.00026181832,0.00003225958],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007855187,0.00008632643,0.00016136603,0.00005110719,0.0004098463,0.0001434559,0.0013143467,0.000025910542,4.5393205e-7],"category_scores_gemma":[0.00016295596,0.000049952338,0.000060141978,0.00011976994,0.00021860497,0.00040133944,0.0008019978,0.000057699766,1.0948424e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000084984595,0.00012533937,0.008416948,0.00044228576,0.00004221077,9.78765e-8,0.0024625405,9.151604e-7,0.008176235,0.9540617,0.00021869251,0.026044562],"study_design_scores_gemma":[0.0019692439,0.000305938,0.09130651,0.0016058898,0.00013939007,0.000015429207,0.004136856,0.012937432,0.6419738,0.2406629,0.0044353297,0.00051129085],"about_ca_topic_score_codex":0.00002105556,"about_ca_topic_score_gemma":0.0000108046615,"teacher_disagreement_score":0.71339875,"about_ca_system_score_codex":0.0000064206993,"about_ca_system_score_gemma":0.000021782223,"threshold_uncertainty_score":0.3152248},"labels":[],"label_agreement":null},{"id":"W4255938757","doi":"10.1145/882262.882291","title":"TreeJuxtaposer","year":2003,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":183,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"University of Texas at Austin; National Science Foundation","keywords":"Computer science; Visibility; Tree (set theory); Focus (optics); Node (physics); Visualization; Context (archaeology); Graph; Task (project management); Artificial intelligence; Theoretical computer science; Geography; Mathematics","score_opus":0.032123736241318944,"score_gpt":0.2892077405405375,"score_spread":0.25708400429921857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4255938757","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00034304528,0.00001798527,0.99558073,0.00093957863,0.0002576887,0.000048560385,0.000007275599,0.00016737559,0.002637783],"genre_scores_gemma":[0.93514365,0.0002655603,0.057533823,0.005210484,0.0000151713175,0.000012999462,0.000007785839,0.000019361107,0.0017911614],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99920523,0.00005705145,0.00014011595,0.00023025091,0.00020635933,0.00016098583],"domain_scores_gemma":[0.9988636,0.00007302923,0.000029596695,0.0008920102,0.000054274948,0.00008750468],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014452169,0.00009768475,0.00008068855,0.0002077635,0.00018435153,0.00010057291,0.00061779603,0.000054073036,0.000091688606],"category_scores_gemma":[0.00003933434,0.00009290348,0.00008328481,0.0009490861,0.00003552911,0.0003094894,0.0000040650125,0.00013638783,0.00010574921],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000019743331,0.00030465514,0.00012361667,0.000006250787,0.000036509322,0.0000059515082,0.00017211975,0.00033733764,0.00006474238,0.97874177,0.0016647078,0.018540366],"study_design_scores_gemma":[0.0018007503,0.00041057178,0.0010755345,0.000045872086,0.00007840204,0.00006669613,0.00015836122,0.039686896,0.015595803,0.19027062,0.74971694,0.0010935295],"about_ca_topic_score_codex":0.000003459871,"about_ca_topic_score_gemma":0.0000183535,"teacher_disagreement_score":0.9380469,"about_ca_system_score_codex":0.000010255564,"about_ca_system_score_gemma":0.000038464932,"threshold_uncertainty_score":0.3788494},"labels":[],"label_agreement":null},{"id":"W4256214268","doi":"10.1007/978-1-4939-7131-2_100756","title":"Network Visualization","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Visualization; Computer science; Artificial intelligence","score_opus":0.035099765061418105,"score_gpt":0.2955651383176495,"score_spread":0.2604653732562314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4256214268","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[1.5660088e-8,0.000030322606,0.50937265,0.000057088833,0.00025940285,0.000037700167,0.0000024031958,0.00016415399,0.49007627],"genre_scores_gemma":[0.00001721483,0.00008113514,0.009153136,0.0030344257,0.0006799061,7.742543e-7,0.0001646852,0.000024701654,0.986844],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989748,0.000008951093,0.00023992537,0.0003489323,0.0002712769,0.00015609473],"domain_scores_gemma":[0.9990004,0.000019730374,0.00014578145,0.00060296955,0.00015772705,0.00007344364],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001345814,0.00017616806,0.00016725589,0.000086042404,0.00007988241,0.00022681615,0.000690224,0.00016270259,0.0031818012],"category_scores_gemma":[0.000009716919,0.00016194794,0.00005636587,0.0000750841,0.000040596526,0.0002266716,0.0003187911,0.00006481434,0.0028145632],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.8001796e-7,0.000002135318,7.950816e-7,0.0000033771466,0.0000075910784,0.000001437603,0.000013087826,0.0000054778784,1.0396436e-7,0.6822092,0.31687316,0.00088347506],"study_design_scores_gemma":[0.000042172524,0.000026635515,9.0657267e-7,0.00003728748,0.0000083382065,0.0000022142206,4.4299915e-7,0.033495218,0.0000034112954,0.15552884,0.8106665,0.00018803158],"about_ca_topic_score_codex":9.1298506e-7,"about_ca_topic_score_gemma":0.000005809527,"teacher_disagreement_score":0.52668035,"about_ca_system_score_codex":0.000022861674,"about_ca_system_score_gemma":0.000058744743,"threshold_uncertainty_score":0.9979619},"labels":[],"label_agreement":null},{"id":"W4281490671","doi":"10.1111/cgf.14515","title":"Seeking Patterns of Visual Pattern Discovery for Knowledge Building","year":2022,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Visual analytics; Computer science; Interactive visual analysis; Salient; Data science; Visualization; Cultural analytics; Visual reasoning; Empirical research; Exploratory data analysis; Data visualization; Process (computing); Eye tracking; Construct (python library); Analytics; Human–computer interaction; Information visualization; Artificial intelligence; Data mining","score_opus":0.022538683845789668,"score_gpt":0.30015239503322394,"score_spread":0.2776137111874343,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281490671","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015873292,0.00006884179,0.98223376,0.0002801449,0.0011180926,0.00018798043,0.00011530499,0.00010224444,0.000020349966],"genre_scores_gemma":[0.99312615,0.000011241033,0.005436811,0.0010841121,0.00011732445,0.000031809508,0.000096035394,0.000022568704,0.00007395629],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99845034,0.00008343464,0.0003783709,0.0004282643,0.0003010543,0.00035851388],"domain_scores_gemma":[0.9989845,0.00018033375,0.000205048,0.00045594404,0.00010394248,0.00007020095],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003771563,0.00016556506,0.00023680899,0.00036156154,0.0003603062,0.0002077815,0.0012183781,0.000033888122,0.000006559572],"category_scores_gemma":[0.000010326983,0.00017708394,0.00020348461,0.0006098588,0.000029609631,0.00053546665,0.0017723208,0.0001488708,0.0000012232788],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000075105218,0.0005855455,0.03591593,0.00018928437,0.000107983135,0.000008424656,0.0009970458,0.0006577506,0.00026865164,0.9027707,0.0055748816,0.05291631],"study_design_scores_gemma":[0.0005060054,0.00031552024,0.00088703807,0.000038673617,0.000013082628,0.000010054016,0.00008403174,0.9703492,0.00042365285,0.0035671468,0.023542576,0.0002630083],"about_ca_topic_score_codex":0.000014109277,"about_ca_topic_score_gemma":0.000012705111,"teacher_disagreement_score":0.97725284,"about_ca_system_score_codex":0.000032991888,"about_ca_system_score_gemma":0.00006282597,"threshold_uncertainty_score":0.7221274},"labels":[],"label_agreement":null},{"id":"W4282565028","doi":"10.1016/j.buildenv.2022.109275","title":"A virtual meter-based visualization tool to present energy flows in multiple zone variable air volume air handling unit systems","year":2022,"lang":"en","type":"article","venue":"Building and Environment","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Visualization; Data visualization; Computer science; Energy consumption; Analytics; Simulation; Engineering; Data mining","score_opus":0.01833945980858131,"score_gpt":0.23636134676069515,"score_spread":0.21802188695211383,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4282565028","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07757695,0.00008359034,0.92171633,0.00019541028,0.00017305925,0.00015160239,0.000023241193,0.000059950667,0.000019873129],"genre_scores_gemma":[0.9850084,0.000019829567,0.0134722125,0.0005025874,0.000043228825,0.00011305953,0.00006752759,0.000016365004,0.0007568005],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99843955,0.00016430124,0.00030191816,0.0004424515,0.00039741746,0.00025438363],"domain_scores_gemma":[0.99940753,0.000060312424,0.00007704115,0.0003424598,0.000008670292,0.000103959355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046599557,0.00014338456,0.000176369,0.00021391537,0.00027617463,0.00010009162,0.00033474012,0.000032311807,0.00004061763],"category_scores_gemma":[0.00002413869,0.00015617454,0.000025661704,0.00037505617,0.000014194768,0.00018117599,0.00054909,0.00007081466,0.0000062764234],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009338852,0.0001628835,0.00096207415,0.000012109471,0.0000101285195,0.0000069535936,0.00019191462,0.9806082,0.001939629,0.013178003,0.0002954732,0.0026232668],"study_design_scores_gemma":[0.0004730198,0.0001362693,0.00024337141,0.00002334644,0.0000065541567,0.0000030746396,0.00008794277,0.84295744,0.00051395415,0.0000304648,0.155345,0.00017955879],"about_ca_topic_score_codex":0.00040696206,"about_ca_topic_score_gemma":0.0000070098145,"teacher_disagreement_score":0.90824413,"about_ca_system_score_codex":0.00015444067,"about_ca_system_score_gemma":0.00003188124,"threshold_uncertainty_score":0.6368613},"labels":[],"label_agreement":null},{"id":"W4282570134","doi":"10.1109/pacificvis53943.2022.00024","title":"SET-STAT-MAP: Extending Parallel Sets for Visualizing Mixed Data","year":2022,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Canada First Research Excellence Fund","keywords":"Computer science; Geospatial analysis; Parallel coordinates; Categorical variable; Data mining; Merge (version control); Visualization; Set (abstract data type); Scalability; Data visualization; Spatial analysis; Visual analytics; Data set; Information retrieval; Artificial intelligence; Database; Machine learning; Cartography; Mathematics; Geography","score_opus":0.13905456514807965,"score_gpt":0.40008179567255325,"score_spread":0.26102723052447363,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4282570134","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00016500434,0.000062949024,0.99689466,0.0011234574,0.0005138916,0.00017380113,0.0003064947,0.00023214522,0.0005275762],"genre_scores_gemma":[0.2685629,0.00006217919,0.6970849,0.010237442,0.00023796876,0.00016587236,0.008845049,0.00008275141,0.014720919],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99853253,0.000079188525,0.0002481299,0.00052357005,0.00033114935,0.00028545552],"domain_scores_gemma":[0.99856174,0.00012969422,0.00009308227,0.001086657,0.000040106097,0.0000887072],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007130462,0.00011034878,0.00013346222,0.00011417035,0.0004636644,0.00028267538,0.0023017055,0.000016607983,0.00020023159],"category_scores_gemma":[0.00006781601,0.00011007873,0.00003960333,0.00036736482,0.000015479098,0.0007928632,0.0027229148,0.000075772245,0.00003284187],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006283314,0.00008710574,0.00017465034,0.000034157285,0.000037058788,0.000013082022,0.0005278793,0.0007382168,0.000090542526,0.6021068,0.38128942,0.0148948105],"study_design_scores_gemma":[0.00024767435,0.00003160684,0.000018768153,0.0000025691063,0.000005413513,0.000005268466,0.00036490298,0.6241103,0.000032960343,0.0015794454,0.37347397,0.00012712512],"about_ca_topic_score_codex":0.000016817618,"about_ca_topic_score_gemma":0.000009520391,"teacher_disagreement_score":0.6233721,"about_ca_system_score_codex":0.000038266695,"about_ca_system_score_gemma":0.000074603704,"threshold_uncertainty_score":0.44888803},"labels":[],"label_agreement":null},{"id":"W4282969634","doi":"10.21606/drs.2022.257","title":"Data-painting: Expressive free-form visualisation","year":2022,"lang":"en","type":"article","venue":"Proceedings of DRS","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; European Commission; Alberta Innovates - Technology Futures","keywords":"Visualization; Computer science; Representation (politics); Data visualization; Expressive power; Human–computer interaction; Expressivity; Information visualization; Painting; External Data Representation; Data science; Artificial intelligence; Theoretical computer science; Visual arts","score_opus":0.04447041341731357,"score_gpt":0.30515625844669514,"score_spread":0.2606858450293816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4282969634","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4420751,0.00039242968,0.44220176,0.010705336,0.0021922416,0.0016841069,0.0017378089,0.0021588465,0.096852355],"genre_scores_gemma":[0.9806649,0.000012392688,0.017887898,0.00060045277,0.00008248414,0.000018873723,0.00016420145,0.000014644025,0.0005541636],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988404,0.0000056515737,0.00023888225,0.00030698624,0.0004610679,0.00014703877],"domain_scores_gemma":[0.9991614,0.000025658162,0.00026988715,0.0003263623,0.00016798898,0.000048667596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005446743,0.000077309356,0.00011080089,0.00013254485,0.00017757258,0.0001290768,0.0024689299,0.000016518,0.00006275957],"category_scores_gemma":[0.0002585734,0.00008093271,0.000024467294,0.00051894604,0.000028323815,0.0012704075,0.0026353688,0.000089260655,0.0000047654835],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000907378,0.00026291385,0.0033590773,0.00011200572,0.000041559633,0.0000017422383,0.0045260224,0.00004330188,0.009897384,0.78779066,0.18402334,0.0099329315],"study_design_scores_gemma":[0.0011384776,0.00030273906,0.00087802316,0.000048751514,0.000040095176,0.00002288299,0.0060286396,0.65538824,0.022415986,0.027542735,0.2855971,0.00059634494],"about_ca_topic_score_codex":0.000009618755,"about_ca_topic_score_gemma":4.41884e-7,"teacher_disagreement_score":0.76024795,"about_ca_system_score_codex":0.000028112529,"about_ca_system_score_gemma":0.00003862291,"threshold_uncertainty_score":0.45879272},"labels":[],"label_agreement":null},{"id":"W4283725749","doi":"10.3233/shti220680","title":"Towards the Adoption of Novel Visualizations in Public Health","year":2022,"lang":"en","type":"review","venue":"Studies in health technology and informatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Visualization; Computer science; Data science; Social media; Health informatics; World Wide Web; Knowledge management; Public health; Medicine; Nursing; Data mining","score_opus":0.30437748594833347,"score_gpt":0.47549508645362365,"score_spread":0.17111760050529018,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283725749","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[7.9368255e-7,0.9327434,0.062874384,0.0032843957,0.00024830148,0.0006017294,0.00004076217,0.000069636495,0.00013665008],"genre_scores_gemma":[0.000027272412,0.9930078,0.005858375,0.00090232166,0.0000062308823,0.00010649242,0.0000729256,0.0000069292205,0.000011673547],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9971998,0.00016442082,0.0019105457,0.00015630567,0.00021599505,0.00035296273],"domain_scores_gemma":[0.9979716,0.00019322467,0.0012182468,0.00051337515,0.000063646396,0.000039895654],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023021847,0.0001939459,0.0010785693,0.0016252849,0.00030475654,0.000026926351,0.0008884501,0.00014254714,0.0000025179902],"category_scores_gemma":[0.00058904866,0.0001401942,0.00004979398,0.004516627,0.0003243946,0.00028953527,0.0012242943,0.0005335983,0.0000012194956],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.102985e-8,0.000051905383,0.000013988029,0.009074168,0.000019162337,1.6308026e-7,0.0025310153,0.0000072516495,1.0316438e-10,0.41254655,0.00027733314,0.5754784],"study_design_scores_gemma":[0.00015052782,0.00011688654,0.0000060304787,0.0019038249,0.000005228258,0.000017877075,0.0043880534,0.006942553,5.655929e-9,0.00071857614,0.98564243,0.00010801267],"about_ca_topic_score_codex":0.000015090122,"about_ca_topic_score_gemma":0.000048732953,"teacher_disagreement_score":0.9853651,"about_ca_system_score_codex":0.0003107737,"about_ca_system_score_gemma":0.0010989441,"threshold_uncertainty_score":0.5716953},"labels":[],"label_agreement":null},{"id":"W4283749850","doi":"10.31234/osf.io/gk2t9","title":"Visual decision aids: Improving laypeople’s understanding of forensic science evidence","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"University of Sydney","keywords":"Forensic science; Decision aids; Psychology; Economic Justice; Domain (mathematical analysis); Control (management); Social psychology; Criminology; Computer science; Medicine; Artificial intelligence; Political science; Pathology; Alternative medicine; Law; Mathematics","score_opus":0.09656678462342119,"score_gpt":0.3741109605433858,"score_spread":0.2775441759199646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283749850","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013162174,0.00014315985,0.9839384,0.0000820149,0.001185356,0.0002063674,0.000010560844,0.00015762525,0.0011143236],"genre_scores_gemma":[0.8910564,0.000120069526,0.10830506,0.00023119999,0.000037569065,0.000007894865,0.000011989348,0.0000145766235,0.00021520961],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9965996,0.00007335321,0.0005985742,0.0010153011,0.0013444514,0.00036868098],"domain_scores_gemma":[0.99742377,0.0004419725,0.00046607835,0.0012568529,0.0002624969,0.00014884467],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0020315251,0.00023802996,0.00035604092,0.0007866322,0.0003779949,0.00067804736,0.003490295,0.00008416512,0.00016428748],"category_scores_gemma":[0.0010086645,0.00022292405,0.00013480893,0.0018562655,0.00027726678,0.0011885817,0.01134437,0.00036456442,0.000009445523],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011977616,0.000119255776,0.0015716464,0.00027794042,0.00002493192,0.000013417683,0.001074509,0.005442997,0.0016240298,0.94093037,0.0009704725,0.04793845],"study_design_scores_gemma":[0.00021505382,0.00024573345,0.00029415163,0.00057683967,0.00003203362,0.000007747357,0.0010439212,0.9400466,0.004168778,0.052554876,0.000268256,0.0005460049],"about_ca_topic_score_codex":0.00021891882,"about_ca_topic_score_gemma":0.00006357308,"teacher_disagreement_score":0.93460363,"about_ca_system_score_codex":0.0005618089,"about_ca_system_score_gemma":0.0012004072,"threshold_uncertainty_score":0.9966517},"labels":[],"label_agreement":null},{"id":"W4284976463","doi":"10.2196/33978","title":"Developing Educational Animations on HIV Pre-exposure Prophylaxis (PrEP) for Women: Qualitative Study","year":2022,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Focus group; Medicine; Stakeholder; Family medicine; Pre-exposure prophylaxis; Human immunodeficiency virus (HIV); Medical education; Nursing; Psychology; Men who have sex with men","score_opus":0.11583671745501829,"score_gpt":0.5005057267106237,"score_spread":0.3846690092556054,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4284976463","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.57123595,0.000028762306,0.4069661,0.011063578,0.0004338779,0.0053992984,0.00067308365,0.00020237888,0.0039969874],"genre_scores_gemma":[0.9884359,0.0000015213218,0.0033308342,0.00017981774,0.00004361926,0.0045341244,0.00014110454,0.000012032131,0.0033210253],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.99633914,0.0011729666,0.00036616353,0.00037265435,0.0012952309,0.0004538636],"domain_scores_gemma":[0.99768925,0.0009346866,0.00012446362,0.00044078132,0.0007043346,0.00010648837],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0033351397,0.00012445272,0.00015558058,0.0005614218,0.0015172799,0.00029635473,0.0010854385,0.000023246916,0.00016010465],"category_scores_gemma":[0.0003308697,0.00011553796,0.00004406632,0.0017512011,0.00007038066,0.00082415796,0.00076510303,0.00036731665,0.00008582899],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045725952,0.001298737,0.00015498558,0.000067803034,0.000047354893,7.254686e-7,0.52906066,0.00016249408,0.000013126956,0.4518632,0.015187688,0.0020974823],"study_design_scores_gemma":[0.002963603,0.01516821,0.014805578,0.00006402267,0.0000040839486,0.0000079435895,0.72137475,0.07554536,0.0002840087,0.10554395,0.06339873,0.00083973515],"about_ca_topic_score_codex":0.000004772929,"about_ca_topic_score_gemma":0.0000033729395,"teacher_disagreement_score":0.41719997,"about_ca_system_score_codex":0.0007714924,"about_ca_system_score_gemma":0.00073877,"threshold_uncertainty_score":0.9997826},"labels":[],"label_agreement":null},{"id":"W4285147651","doi":"10.1007/978-3-030-93119-3_13","title":"VisIRML: Visualization with an Interactive Information Retrieval and Machine Learning Classifier","year":2022,"lang":"en","type":"book-chapter","venue":"Studies in computational intelligence","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"JDA Software (Canada)","funders":"","keywords":"Computer science; Artificial intelligence; Visualization; Information visualization; Classifier (UML); Machine learning; Information retrieval","score_opus":0.08270468612619733,"score_gpt":0.36905094288281654,"score_spread":0.2863462567566192,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285147651","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000029239269,0.0005505027,0.9795604,0.00020348825,0.00031754657,0.00027232023,0.000047029065,0.0001347848,0.018884705],"genre_scores_gemma":[0.67695963,0.02542612,0.1686231,0.009935568,0.00087146874,0.00017699038,0.015622351,0.00046402588,0.10192076],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980894,0.00008815933,0.00056375726,0.0004487498,0.0006441077,0.00016585522],"domain_scores_gemma":[0.99836916,0.00040650528,0.0004415189,0.00020839275,0.0005095415,0.0000649084],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003864213,0.0002931211,0.0003241473,0.00051264506,0.00028209467,0.00020844619,0.00042319184,0.000078999394,0.000107868014],"category_scores_gemma":[0.00016961359,0.0002792583,0.000034403718,0.0002946048,0.00021068359,0.0019021191,0.0006075539,0.000481706,0.00002177026],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008067548,0.00002757645,0.000057727866,0.000064625005,0.00010174037,0.000016970287,0.0038244487,0.0794666,1.2672481e-7,0.9028564,0.00010281483,0.013400272],"study_design_scores_gemma":[0.0001763766,0.00057260867,0.00005279274,0.00020392,0.000022434062,0.000042344527,0.0008216036,0.88649756,0.000007476613,0.062311575,0.048838656,0.00045264658],"about_ca_topic_score_codex":0.000010725229,"about_ca_topic_score_gemma":0.000027535041,"teacher_disagreement_score":0.8405448,"about_ca_system_score_codex":0.00022548619,"about_ca_system_score_gemma":0.00011670698,"threshold_uncertainty_score":0.99996597},"labels":[],"label_agreement":null},{"id":"W4285255856","doi":"10.18653/v1/2022.findings-acl.177","title":"ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning","year":2022,"lang":"en","type":"article","venue":"Findings of the Association for Computational Linguistics: ACL 2022","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":246,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Question answering; Benchmark (surveying); Vocabulary; Chart; Visual reasoning; Artificial intelligence; Qualitative reasoning; Variety (cybernetics); Natural language processing; Linguistics","score_opus":0.00984609113906177,"score_gpt":0.2772540827683285,"score_spread":0.26740799162926676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285255856","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.051231354,0.00009587705,0.9426915,0.0013993764,0.0016432581,0.0011545327,0.0011050332,0.00014171156,0.0005373669],"genre_scores_gemma":[0.97387546,0.0000031071359,0.024541767,0.00034128988,0.00019780867,0.000075693584,0.000436613,0.000014894078,0.00051339157],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99859494,0.00006930058,0.00030311814,0.00028631618,0.00055235677,0.00019394698],"domain_scores_gemma":[0.9980562,0.00072964036,0.0004786123,0.00011291611,0.0005785397,0.000044133914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009637872,0.00011435193,0.00017905184,0.00010721139,0.00070209097,0.00012803577,0.0003711482,0.000037958478,0.000009585857],"category_scores_gemma":[0.002997548,0.00010330335,0.000079649624,0.00032876385,0.000026247233,0.00008537086,0.00029568985,0.00011963167,6.0289915e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006087657,0.00013689988,0.03254679,0.00006951487,0.000105528576,6.297278e-7,0.00060275535,0.043048702,0.00004593078,0.9187155,0.004246948,0.0004199284],"study_design_scores_gemma":[0.0010522482,0.00033597133,0.02319528,0.000048347385,0.0000535307,0.000004370799,0.00007413731,0.9250005,0.00010079757,0.017291093,0.032619264,0.00022444437],"about_ca_topic_score_codex":0.000005535547,"about_ca_topic_score_gemma":0.0000021386113,"teacher_disagreement_score":0.9226441,"about_ca_system_score_codex":0.00021144107,"about_ca_system_score_gemma":0.000107505395,"threshold_uncertainty_score":0.5399987},"labels":[],"label_agreement":null},{"id":"W4285601420","doi":"10.1109/mcg.2022.3180573","title":"Visual Analysis and Processing of Diverse Data","year":2022,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Zhàng; Editor in chief; Queue; Data visualization; Computer graphics; Data science; Computer graphics (images); Visualization; Artificial intelligence; Programming language; History; Management","score_opus":0.038223454907226125,"score_gpt":0.3214826440038426,"score_spread":0.28325918909661646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285601420","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0045665735,0.00011492361,0.9948978,0.0001519667,0.000022812615,0.000085380845,0.00010398511,0.000034907443,0.00002165882],"genre_scores_gemma":[0.9818816,0.00013212592,0.017192012,0.00050242536,0.00004320049,0.000022988197,0.00020423476,0.0000046728196,0.000016727467],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992192,0.000028761091,0.00016301873,0.00033978577,0.00016844287,0.00008082383],"domain_scores_gemma":[0.99926496,0.000033696546,0.0001043498,0.00048598959,0.000054354565,0.000056655208],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019239115,0.00006487398,0.000121474615,0.00026781924,0.0003408975,0.00011287392,0.0006492036,0.000013338913,0.0000036744982],"category_scores_gemma":[0.0000010791722,0.000067285306,0.000024131903,0.0014904881,0.000071637936,0.0002161761,0.0010293489,0.000066616514,3.7060215e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000026439498,0.00048526734,0.017926894,0.00008402569,0.00033786643,0.0000027866593,0.0006462464,0.0010112101,0.00012714186,0.6780599,0.0023638073,0.2989522],"study_design_scores_gemma":[0.000097525575,0.000021819578,0.0032983825,0.0000015888851,0.00008430632,0.0000033682315,0.000028244378,0.97839606,0.000013347688,0.001310085,0.016658815,0.00008643626],"about_ca_topic_score_codex":0.000022313334,"about_ca_topic_score_gemma":0.0000073099723,"teacher_disagreement_score":0.9777058,"about_ca_system_score_codex":0.0000032071118,"about_ca_system_score_gemma":0.000024657693,"threshold_uncertainty_score":0.27438152},"labels":[],"label_agreement":null},{"id":"W4285605323","doi":"10.24963/ijcai.2022/685","title":"Threshold Designer Adaptation: Improved Adaptation for Designers in Co-creative Systems","year":2022,"lang":"en","type":"article","venue":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Universities Space Research Association; Alberta Machine Intelligence Institute","keywords":"Adaptation (eye); Computer science; Quality (philosophy); Human–computer interaction; Psychology","score_opus":0.13205578501426393,"score_gpt":0.3260284103045427,"score_spread":0.19397262529027878,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285605323","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027742777,0.000019632878,0.9821184,0.0040712096,0.001224599,0.0012089163,0.00007907655,0.00009144878,0.008412403],"genre_scores_gemma":[0.99307096,0.00002222146,0.005763755,0.00029122847,0.00006864932,0.0003007422,0.000022356278,0.0000163328,0.00044374683],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99752116,0.00004014661,0.0008203923,0.0005243299,0.00082501565,0.00026896235],"domain_scores_gemma":[0.9979904,0.00014413046,0.0006644745,0.0002202211,0.00091426243,0.000066474255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011183788,0.00022159198,0.00026186614,0.00038772743,0.0003567881,0.00036970066,0.0018542273,0.00005619201,0.00009614734],"category_scores_gemma":[0.00040113393,0.00019188247,0.00012909336,0.00067990605,0.00012642499,0.0006450772,0.00033009375,0.0002631533,0.000011153466],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014391262,0.00022291699,0.00008596377,0.000027503791,0.000029277873,6.327763e-7,0.0036922917,0.05714385,0.0027262776,0.9310064,0.00038245678,0.0045385673],"study_design_scores_gemma":[0.00011108929,0.00023399942,0.00005116276,0.00010526902,0.000009501875,0.000004809811,0.006844384,0.9449387,0.012788038,0.034315005,0.0003885066,0.00020951539],"about_ca_topic_score_codex":0.00013010368,"about_ca_topic_score_gemma":0.000033733224,"teacher_disagreement_score":0.99029666,"about_ca_system_score_codex":0.00028345603,"about_ca_system_score_gemma":0.0001983543,"threshold_uncertainty_score":0.78247404},"labels":[],"label_agreement":null},{"id":"W4285685569","doi":"10.2139/ssrn.4152198","title":"Visual Decision Aids: Improving Laypeople’s Understanding of Forensic Science Evidence","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Ontario Museum; Queen's University; University of Toronto","funders":"","keywords":"Forensic science; Scientific evidence; Psychology; Decision aids; Medicine; Epistemology; Alternative medicine; Philosophy","score_opus":0.03235842495289115,"score_gpt":0.3179317606253595,"score_spread":0.28557333567246834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285685569","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06379271,0.0006568018,0.9348812,0.0001421492,0.00035416565,0.000059969105,0.0000012598312,0.000032279615,0.00007945715],"genre_scores_gemma":[0.995921,0.0004013305,0.003401303,0.000118667376,0.000044201137,0.000001550702,8.399358e-7,0.000008838958,0.00010223351],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9967304,0.00009328591,0.00037366603,0.00032087995,0.0011611076,0.0013206922],"domain_scores_gemma":[0.9989539,0.00016800236,0.00032127317,0.00030787938,0.00014943695,0.00009953717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0051611583,0.000111681846,0.00015961273,0.0004943075,0.0009974424,0.00024523828,0.0016791843,0.000018087654,0.000024306193],"category_scores_gemma":[0.00041754192,0.000105251354,0.00008256605,0.001900204,0.00012661585,0.0014577387,0.000839522,0.00080447627,0.0000039537954],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014889918,0.000048609276,0.0008321152,0.000004927014,0.0000148873605,0.0000035598773,0.00030958623,0.0005996722,0.0028604825,0.93203837,0.000049296334,0.06322359],"study_design_scores_gemma":[0.00096322544,0.0023930385,0.00026846403,0.00011800425,0.000040526083,0.0010130488,0.010166232,0.2762407,0.002040032,0.7058221,0.00045846368,0.00047617083],"about_ca_topic_score_codex":0.00003638517,"about_ca_topic_score_gemma":0.00010048807,"teacher_disagreement_score":0.9321283,"about_ca_system_score_codex":0.0021498392,"about_ca_system_score_gemma":0.0044302633,"threshold_uncertainty_score":0.78590965},"labels":[],"label_agreement":null},{"id":"W4285717939","doi":"10.52842/conf.caadria.2020.1.557","title":"What do Design Data say About Your Model? - A Case Study on Reliability and Validity","year":2020,"lang":"en","type":"article","venue":"Proceedings of the International Conference on Computer-Aided Architectural Design Research in Asia","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Mitacs; Boeing","keywords":"Computer science; Cohesion (chemistry); Workflow; Data science; Parametric design; Reliability (semiconductor); Analytics; Parametric statistics; Software engineering; Database","score_opus":0.4747671265344694,"score_gpt":0.44461437661706493,"score_spread":0.030152749917404464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285717939","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38989714,0.000022504346,0.58056164,0.02652352,0.00037332173,0.0020802564,0.000047258585,0.00011939357,0.00037495187],"genre_scores_gemma":[0.96232134,0.000052035524,0.037022747,0.0004420149,0.00008799135,0.000027277565,0.0000046238174,0.000013844638,0.00002809946],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9959121,0.0004117682,0.00054980704,0.0011243747,0.0016136927,0.00038827705],"domain_scores_gemma":[0.9973861,0.0007359751,0.00021991576,0.0006508099,0.0007799261,0.00022728866],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0036836811,0.0002634315,0.0003117308,0.00034475068,0.00021128335,0.0016541807,0.005172799,0.00005475505,0.000007871425],"category_scores_gemma":[0.00091281225,0.00019036818,0.000053144086,0.0007639388,0.00022563874,0.0012414163,0.0034882724,0.0007930181,0.0000072290077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031548059,0.0054899193,0.00830647,0.0007121129,0.00054269383,0.0013533038,0.05009327,0.16002652,0.011879029,0.4057173,0.014924117,0.33780044],"study_design_scores_gemma":[0.00059035904,0.00090100575,0.00049399503,0.00033225823,0.000005201276,0.000120879944,0.0008934796,0.9757451,0.0009774622,0.019726163,0.00002663504,0.00018747685],"about_ca_topic_score_codex":0.0000553887,"about_ca_topic_score_gemma":0.0000053993126,"teacher_disagreement_score":0.8157186,"about_ca_system_score_codex":0.00009703508,"about_ca_system_score_gemma":0.00023161578,"threshold_uncertainty_score":0.9993822},"labels":[],"label_agreement":null},{"id":"W4285826283","doi":"10.48550/arxiv.1908.00679","title":"Investigating Direct Manipulation of Graphical Encodings as a Method for\\n User Interaction","year":2019,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Leverage (statistics); Human–computer interaction; Graphical user interface; Visualization; Graphical model; Artificial intelligence; Programming language","score_opus":0.13610218982380287,"score_gpt":0.2826426919093563,"score_spread":0.14654050208555344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285826283","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06979326,0.000010760107,0.92597866,0.00010081482,0.00095419865,0.000607868,0.000036946174,0.00009203635,0.00242545],"genre_scores_gemma":[0.97557116,0.00015436707,0.02155599,0.00022173228,0.00008119152,0.000001243743,0.00013303511,0.000030803487,0.0022504532],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9967184,0.00043857587,0.00069333275,0.0015442285,0.00021743187,0.00038801084],"domain_scores_gemma":[0.99593365,0.00067785406,0.0013347582,0.0011262045,0.0006949726,0.00023253149],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010712029,0.00044362238,0.0006816729,0.00072705914,0.00022483911,0.00023859389,0.0014026782,0.0004339569,0.00007090891],"category_scores_gemma":[0.00049532147,0.0005484384,0.0004936611,0.0015665921,0.00015629211,0.0012721505,0.0013162232,0.0005147845,0.00005469908],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005234286,0.00016913933,0.01067187,0.0004835967,0.00023345201,0.0000090274325,0.0008440304,0.32325634,0.0006567524,0.6619243,0.00024967705,0.0014494815],"study_design_scores_gemma":[0.00066525984,0.00016612546,0.0010354538,0.000498676,0.00026900647,0.000004977277,0.0002772536,0.9650259,0.0014360887,0.028182844,0.0019252793,0.00051314686],"about_ca_topic_score_codex":0.0003929517,"about_ca_topic_score_gemma":0.000036712143,"teacher_disagreement_score":0.90577793,"about_ca_system_score_codex":0.00020543553,"about_ca_system_score_gemma":0.00030921967,"threshold_uncertainty_score":0.99969673},"labels":[],"label_agreement":null},{"id":"W4286611169","doi":"10.1145/3528223.3530111","title":"Perception of letter glyph parameters for InfoTypography","year":2022,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Glyph (data visualization); Font; Computer science; Visualization; Range (aeronautics); Sentence; Typography; Perception; Natural language processing; Artificial intelligence; Interval (graph theory); Chinese characters; Information retrieval; Mathematics","score_opus":0.03172951379207583,"score_gpt":0.2858545176409286,"score_spread":0.2541250038488528,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286611169","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0061789146,0.0000063476523,0.99108845,0.0020593281,0.00028551766,0.00015900424,0.00010740408,0.000076554636,0.000038469778],"genre_scores_gemma":[0.92716193,0.000053363747,0.06605968,0.0064360676,0.000013715158,0.00011434297,0.00005887404,0.000014133539,0.000087883294],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991268,0.000052219133,0.00020498097,0.00021214521,0.00026962353,0.00013426365],"domain_scores_gemma":[0.9990771,0.00012419083,0.000076444616,0.00061621587,0.000064780106,0.0000412915],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019829864,0.000087251356,0.00010423973,0.00045588557,0.00030324425,0.00003819799,0.0007132494,0.000030657728,0.000046934132],"category_scores_gemma":[0.000012923542,0.000093334296,0.00019245879,0.0010784346,0.00005427105,0.00022429471,0.000017736484,0.00014356396,0.0000024250662],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003659525,0.0046622558,0.0034265348,0.00038521204,0.0009630072,0.000009618607,0.007907323,0.07462346,0.0060281125,0.45635834,0.05680508,0.3884651],"study_design_scores_gemma":[0.0053899838,0.0043417793,0.005709255,0.00006799508,0.00039860597,0.00004291874,0.0026662499,0.39714575,0.004585427,0.114162214,0.46348357,0.0020062472],"about_ca_topic_score_codex":0.000013705681,"about_ca_topic_score_gemma":0.0000050977887,"teacher_disagreement_score":0.9250288,"about_ca_system_score_codex":0.000015406482,"about_ca_system_score_gemma":0.000023594597,"threshold_uncertainty_score":0.3806062},"labels":[],"label_agreement":null},{"id":"W4287396300","doi":"","title":"Visualizer management and attention guidance","year":2021,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Computer science","score_opus":0.017519829405747027,"score_gpt":0.2678073595136513,"score_spread":0.2502875301079043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4287396300","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007931506,0.001284745,0.9606757,0.0048744376,0.00025174182,0.00023813438,0.000018348746,0.0002663367,0.024459017],"genre_scores_gemma":[0.40862912,0.0043911804,0.5432984,0.0008704875,0.000037691963,0.00009081887,0.001264774,0.00006580964,0.04135168],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9954116,0.0023810258,0.00047460315,0.0009824983,0.00047569297,0.00027461557],"domain_scores_gemma":[0.99566674,0.0002401909,0.00037131037,0.00231008,0.0012484827,0.00016320101],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0029011422,0.0002766915,0.00028894865,0.0001936452,0.00026002942,0.0015869566,0.0015554319,0.00016502514,0.000056601388],"category_scores_gemma":[0.00029142204,0.0003106588,0.00013123684,0.00048630327,0.000118552176,0.0003517784,0.004355369,0.00029118516,0.000026811858],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000017673977,0.00047921485,0.0020197197,0.00044968002,0.00013901433,0.000027164242,0.0032098126,0.000038840986,0.00043125928,0.92274344,0.003739966,0.06672014],"study_design_scores_gemma":[0.002041234,0.0000010673999,0.041648127,0.009019926,0.00022810491,0.00005686648,0.00058430224,0.78282696,0.016916174,0.022064345,0.122231305,0.002381616],"about_ca_topic_score_codex":0.00012845692,"about_ca_topic_score_gemma":0.00016572166,"teacher_disagreement_score":0.90067905,"about_ca_system_score_codex":0.00006463061,"about_ca_system_score_gemma":0.00010320217,"threshold_uncertainty_score":0.99993455},"labels":[],"label_agreement":null},{"id":"W4287668439","doi":"10.48550/arxiv.2009.05936","title":"Geo-Spatial Data Visualization and Critical Metrics Predictions for\\n Canadian Elections","year":2020,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visualization; Geospatial analysis; Computer science; Data science; Process (computing); Traverse; Interpretation (philosophy); Data visualization; Information visualization; Creative visualization; Data mining; Information retrieval; World Wide Web; Geography; Cartography","score_opus":0.1761569196610239,"score_gpt":0.2748119488850941,"score_spread":0.09865502922407018,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4287668439","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00033059382,0.0000753418,0.9921149,0.0013322065,0.0013540182,0.00062337494,0.0034031882,0.00018446558,0.00058190816],"genre_scores_gemma":[0.99198514,0.0013242034,0.0019529704,0.0006575763,0.0003683724,0.0000021738674,0.003011754,0.000042669388,0.00065514236],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.995964,0.00024592257,0.0005054314,0.0023960224,0.00019906227,0.000689566],"domain_scores_gemma":[0.9952276,0.00045872855,0.00025192075,0.0018802517,0.00085448875,0.0013270148],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.00046870255,0.00046193312,0.0004683089,0.0011137584,0.0014891487,0.0009106131,0.0025587084,0.00047712956,0.000101206584],"category_scores_gemma":[0.0019261076,0.0006408557,0.00013845369,0.0033324861,0.00034155312,0.0015255342,0.0027730274,0.0005517354,0.000046602283],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021470112,0.00017266585,0.0017916008,0.00020553396,0.00021281885,0.000059751826,0.0002984001,0.018449968,0.000004980261,0.9703426,0.00760459,0.0008356711],"study_design_scores_gemma":[0.00048524316,0.0001514852,0.0006453531,0.00006336669,0.00057724497,0.000009751001,0.00016604565,0.949747,0.0000071685963,0.010114637,0.037463885,0.0005688113],"about_ca_topic_score_codex":0.029865066,"about_ca_topic_score_gemma":0.06343891,"teacher_disagreement_score":0.9916545,"about_ca_system_score_codex":0.0004244166,"about_ca_system_score_gemma":0.002116947,"threshold_uncertainty_score":0.99981076},"labels":[],"label_agreement":null},{"id":"W4287671863","doi":"10.48550/arxiv.2009.02373","title":"Table Scraps: An Actionable Framework for Multi-Table Data Wrangling\\n From An Artifact Study of Computational Journalism","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Parallels; Table (database); Artifact (error); Context (archaeology); Journalism; Data science; Task (project management); Code (set theory); Set (abstract data type); Data mining; Artificial intelligence; Engineering; Political science","score_opus":0.29210021247293033,"score_gpt":0.32060746151576425,"score_spread":0.028507249042833915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4287671863","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.060680408,0.00001754672,0.93717915,0.00008119235,0.00040763375,0.000409216,0.0010589907,0.00013303802,0.00003282503],"genre_scores_gemma":[0.8619446,0.00002363461,0.13507226,0.00018245462,0.00015142643,0.000001119129,0.0024308825,0.00002622123,0.0001673898],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99756795,0.00019589467,0.00038593754,0.0013699313,0.0002184383,0.00026183645],"domain_scores_gemma":[0.9966143,0.00018345298,0.0005599309,0.001894315,0.00046673493,0.00028126978],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00037719944,0.00027283316,0.0004373953,0.00021115472,0.00027977367,0.00041161722,0.0036574139,0.00019856494,0.00007556313],"category_scores_gemma":[0.00014363522,0.0003233767,0.0000734281,0.0007455655,0.000053111013,0.0020354658,0.0020420167,0.00045365578,0.0000125242705],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000614338,0.0019386987,0.0028150994,0.00005562073,0.00031822006,0.00006396146,0.0010805574,0.9156543,0.000017367272,0.07704677,0.0006692265,0.000278755],"study_design_scores_gemma":[0.0009148656,0.00017339301,0.0004981479,0.000060297152,0.0001314467,9.2026113e-7,0.0009329614,0.93219423,0.00003328999,0.06398997,0.0007600455,0.0003104444],"about_ca_topic_score_codex":0.0007069565,"about_ca_topic_score_gemma":0.00014291308,"teacher_disagreement_score":0.8021069,"about_ca_system_score_codex":0.000060847313,"about_ca_system_score_gemma":0.00035681756,"threshold_uncertainty_score":0.99992186},"labels":[],"label_agreement":null},{"id":"W4287685446","doi":"10.48550/arxiv.2008.11310","title":"Why Shouldn't All Charts Be Scatter Plots? Beyond Precision-Driven\\n Visualizations","year":2020,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Scatter plot; Visualization; Computer science; Plot (graphics); Variable (mathematics); Chart; Argument (complex analysis); Information visualization; Visual analytics; Pie chart; Formative assessment; Perception; Data visualization; Artificial intelligence; Mathematics; Statistics; Psychology; Machine learning","score_opus":0.15013273354088247,"score_gpt":0.26110621392773786,"score_spread":0.1109734803868554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4287685446","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0034435678,0.00008206045,0.98191935,0.00708627,0.001806068,0.0009290062,0.00055398856,0.00054081157,0.0036388522],"genre_scores_gemma":[0.9436257,0.003318131,0.0037171387,0.03896102,0.0006040381,0.000004739313,0.0016247934,0.00019592507,0.007948549],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9926821,0.00065685296,0.0010794341,0.003852525,0.00062921434,0.0010998953],"domain_scores_gemma":[0.9932974,0.00032740267,0.0010291019,0.0031136137,0.0009532981,0.0012791944],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00044461738,0.001173296,0.001111652,0.00091891596,0.00078649796,0.0012950015,0.0055240314,0.0007907812,0.0016132247],"category_scores_gemma":[0.00021484272,0.0014664972,0.0007496615,0.0033420795,0.00053791143,0.0020624516,0.0072842576,0.0011887292,0.0012140578],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000945904,0.0013228086,0.0027031575,0.0003816225,0.0009893549,0.00091360405,0.003873867,0.16246055,0.00018307565,0.66665083,0.15920791,0.0012185995],"study_design_scores_gemma":[0.00090078695,0.0001573459,0.00021959025,0.00022978136,0.00046855828,0.000010311338,0.00020175497,0.8285482,0.00014808957,0.011815395,0.15595227,0.0013479115],"about_ca_topic_score_codex":0.00011185629,"about_ca_topic_score_gemma":0.0001006947,"teacher_disagreement_score":0.9782022,"about_ca_system_score_codex":0.00039375963,"about_ca_system_score_gemma":0.0006678293,"threshold_uncertainty_score":0.99985653},"labels":[],"label_agreement":null},{"id":"W4287722756","doi":"10.5281/zenodo.3947191","title":"Well-Behaved Variants Seldom Make the Apparatus: Stemmata and Apparatus in Digital Research","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computational biology; Biology; Computer science","score_opus":0.07616261146095174,"score_gpt":0.2947534550684666,"score_spread":0.21859084360751488,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4287722756","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06501142,0.00076686643,0.38889018,0.038893577,0.0004646047,0.0038708677,0.0010669891,0.0035842299,0.49745128],"genre_scores_gemma":[0.9967875,0.00013780221,0.00033981793,0.00070556754,0.00011850987,9.176491e-8,0.0005430486,0.00038727873,0.0009803756],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976958,0.0004069137,0.00029142204,0.0005674426,0.00060679164,0.0004315983],"domain_scores_gemma":[0.9985986,0.00007039516,0.000069347836,0.0006266052,0.0003857288,0.00024934256],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0011112782,0.000132382,0.00014666977,0.0001990502,0.0012549023,0.0038649035,0.0022559774,0.000056334262,0.00069028523],"category_scores_gemma":[0.000647541,0.000113467286,0.00002614578,0.0017151791,0.00020558474,0.00070163416,0.003226869,0.000411846,0.0041355896],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001309815,0.00047933386,0.00013229315,0.00018708878,0.00008133645,0.0001840472,0.014079503,0.0002987336,0.0016677199,0.27613917,0.55109924,0.15552053],"study_design_scores_gemma":[0.0005684333,0.00016070632,0.00060177594,0.000026000105,0.0000036245565,0.000051265666,0.00081672025,0.06304307,0.00008186585,0.0005718317,0.9338995,0.00017520445],"about_ca_topic_score_codex":0.000007817621,"about_ca_topic_score_gemma":5.7407277e-7,"teacher_disagreement_score":0.9317761,"about_ca_system_score_codex":0.000050972245,"about_ca_system_score_gemma":0.00001100515,"threshold_uncertainty_score":0.9971692},"labels":[],"label_agreement":null},{"id":"W4287958464","doi":"10.1080/13658816.2022.2102636","title":"Automated generation of concentric circles metro maps using mixed-integer optimization","year":2022,"lang":"en","type":"article","venue":"International Journal of Geographical Information Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Schematic; Integer programming; Readability; Integer (computer science); Line (geometry); Computer science; Linear programming; Scale (ratio); Network planning and design; Concentric; Simple (philosophy); Artificial intelligence; Algorithm; Engineering; Mathematics; Cartography; Geography; Geometry; Programming language","score_opus":0.030223186002876042,"score_gpt":0.295319477933206,"score_spread":0.26509629193032996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4287958464","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012673068,0.00011380546,0.98363674,0.00024228595,0.0029434543,0.00010670532,0.00008749889,0.00006474036,0.00013172686],"genre_scores_gemma":[0.99292207,0.000037901387,0.0064825937,0.00022696407,0.00013103911,0.0000034389404,0.00018506119,0.0000049175574,0.0000060426573],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99685264,0.00020929823,0.0013240707,0.000089925175,0.0014033286,0.00012073621],"domain_scores_gemma":[0.99630785,0.000062095634,0.0016185845,0.00016170723,0.0017697803,0.00007997531],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009865267,0.000103380175,0.00022645849,0.0010443205,0.00012259674,0.00035216322,0.000928335,0.00004714573,0.000039101826],"category_scores_gemma":[0.00013591402,0.00009934252,0.00014387532,0.0010497432,0.00003796045,0.0024812852,0.00020631572,0.0001617731,0.0000027966817],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015202489,0.00007413543,0.0016361972,0.000012816695,0.00014463064,0.0000046511223,0.00024101656,0.9633136,0.00015997088,0.03147541,0.002173318,0.0007490699],"study_design_scores_gemma":[0.0005708152,0.00007636761,0.00016400612,0.00002771331,0.000016509688,0.00016706933,0.0003765125,0.9912467,0.0001489225,0.00004200061,0.0070672664,0.00009610016],"about_ca_topic_score_codex":0.00003771391,"about_ca_topic_score_gemma":5.59563e-7,"teacher_disagreement_score":0.980249,"about_ca_system_score_codex":0.00014650557,"about_ca_system_score_gemma":0.00014147509,"threshold_uncertainty_score":0.40510702},"labels":[],"label_agreement":null},{"id":"W4288089758","doi":"10.48550/arxiv.1910.10376","title":"Emanation Graph: A Plane Geometric Spanner with Steiner Points","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Combinatorics; Spanner; Delaunay triangulation; Bounded function; Mathematics; Graph; Spatial network; Discrete mathematics; Computer science; Mathematical analysis","score_opus":0.05702576016548093,"score_gpt":0.19534267920539514,"score_spread":0.13831691903991422,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4288089758","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04991584,0.000023994879,0.9463785,0.00012492368,0.00032942384,0.00022243033,0.000040767274,0.00019487925,0.0027691987],"genre_scores_gemma":[0.9920324,0.000112259906,0.0013490713,0.0002416497,0.000039904564,3.521575e-7,0.00021315044,0.000017372375,0.0059938193],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99839026,0.0000800625,0.00016643926,0.00091300975,0.00018287034,0.00026737808],"domain_scores_gemma":[0.9981254,0.000058121834,0.0002743314,0.0011770957,0.00023099041,0.00013410421],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00019805509,0.00026340006,0.00027958656,0.0011075541,0.00008124631,0.0002076495,0.00143374,0.00017795297,0.000055330012],"category_scores_gemma":[0.000027620492,0.0002535112,0.000100569734,0.0021702533,0.000053298394,0.00051714666,0.0010537668,0.00030630498,0.0002820804],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049916718,0.00031459902,0.019193301,0.00024587105,0.00034893482,0.00045811315,0.00021552292,0.4575094,0.00000680346,0.5139155,0.0069421306,0.00079993735],"study_design_scores_gemma":[0.001252682,0.00015886976,0.005582597,0.00016618178,0.0001434915,0.0000103995035,0.000076770964,0.97778034,0.00007446899,0.009507085,0.0043751183,0.0008719988],"about_ca_topic_score_codex":0.00008571627,"about_ca_topic_score_gemma":0.000040246523,"teacher_disagreement_score":0.9450295,"about_ca_system_score_codex":0.00009810355,"about_ca_system_score_gemma":0.00014144971,"threshold_uncertainty_score":0.9999917},"labels":[],"label_agreement":null},{"id":"W4289522513","doi":"10.3390/info13080368","title":"Q4EDA: A Novel Strategy for Textual Information Retrieval Based on User Interactions with Visual Representations of Time Series","year":2022,"lang":"en","type":"article","venue":"Information","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Information retrieval; Scope (computer science); Replica; Visualization; Selection (genetic algorithm); Construct (python library); Exploratory search; Visual analytics; Chart; Series (stratigraphy); World Wide Web; Data mining; Artificial intelligence","score_opus":0.02049080150419802,"score_gpt":0.3085334779593474,"score_spread":0.28804267645514936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4289522513","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0021841915,3.720022e-7,0.99321735,0.0004545996,0.00009284087,0.0003468635,0.00037235848,0.00009038475,0.0032410428],"genre_scores_gemma":[0.9710297,0.0000013143505,0.021820594,0.0016056529,0.000035242858,0.000115521114,0.0047989683,0.00000931542,0.000583708],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989452,0.000025628604,0.00042318527,0.000078846395,0.00041337628,0.00011377135],"domain_scores_gemma":[0.9989603,0.00009221862,0.0003563703,0.00023672165,0.00031673635,0.000037648802],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023041635,0.00008871861,0.00009850626,0.00035878635,0.0002592494,0.00021439519,0.00025758948,0.000020576244,0.00008749282],"category_scores_gemma":[0.00010343542,0.000084166764,0.000040527688,0.000671386,0.00002627139,0.007031955,0.000077743054,0.0000882858,0.000033915203],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007247685,0.0003845433,0.00018362506,0.00010900296,0.000060547147,3.7556418e-7,0.0038120328,0.7435608,0.00033433287,0.22409981,0.015484689,0.011245448],"study_design_scores_gemma":[0.0008848656,0.0006230245,0.00038483768,0.00001151385,0.000010305722,0.0000074038476,0.0011109362,0.94803625,0.00095578085,0.000055641467,0.04780176,0.000117680815],"about_ca_topic_score_codex":0.000015636027,"about_ca_topic_score_gemma":0.0000037077448,"teacher_disagreement_score":0.97139674,"about_ca_system_score_codex":0.000071088616,"about_ca_system_score_gemma":0.00020202476,"threshold_uncertainty_score":0.5097997},"labels":[],"label_agreement":null},{"id":"W4292865164","doi":"","title":"Designing Portable Solutions to Support Collaborative Workflow in Long-Term Care: a Five Point Strategy","year":2014,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario College of Art and Design","funders":"","keywords":"Workflow; Computer science; Term (time); Point (geometry); Point of care; Process management; Collaborative software; Software engineering; Knowledge management; Database; Engineering; Nursing; Medicine","score_opus":0.017331411177936785,"score_gpt":0.2657090397944694,"score_spread":0.24837762861653262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292865164","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0048787226,0.00011154944,0.9738929,0.002876396,0.000077949226,0.00027768186,0.000020787362,0.00014792036,0.017716043],"genre_scores_gemma":[0.8553828,0.00006361695,0.13985936,0.00044453246,0.000013300808,0.00004162461,0.00028678167,0.000020160716,0.0038878259],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99642074,0.0019077477,0.0004097097,0.00053918076,0.00031548092,0.0004071179],"domain_scores_gemma":[0.99649143,0.00045498976,0.00018631986,0.0011794593,0.0014599516,0.00022786942],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028534662,0.00017923201,0.00022068393,0.0002557827,0.00031656228,0.00060000346,0.0011461213,0.00007568499,0.0000732245],"category_scores_gemma":[0.0007547795,0.00019572758,0.000056157052,0.001607746,0.00007563009,0.0005596034,0.00051032624,0.00016122368,0.000089461944],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010805706,0.000757465,0.013289633,0.00008264753,0.000045694,0.0000264766,0.04177014,0.0021920677,0.0030082683,0.78321284,0.0068335016,0.14877048],"study_design_scores_gemma":[0.0072762417,0.000042814958,0.111757584,0.005200337,0.00013434245,0.00008781099,0.005586302,0.6600571,0.14090465,0.016455663,0.048087984,0.0044091716],"about_ca_topic_score_codex":0.00023354065,"about_ca_topic_score_gemma":0.003767544,"teacher_disagreement_score":0.8505041,"about_ca_system_score_codex":0.00011524789,"about_ca_system_score_gemma":0.0003386218,"threshold_uncertainty_score":0.79815394},"labels":[],"label_agreement":null},{"id":"W4292897939","doi":"10.1109/tvcg.2013.48","title":"IEEE Visualization and Graphics Technical Committee (VGTC)","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ontario Institute of Technology","funders":"","keywords":"Computer science; Visualization; Graphics; Computer graphics (images); Data visualization; Computer graphics; Information visualization; Artificial intelligence","score_opus":0.020313054104188755,"score_gpt":0.28265461933877195,"score_spread":0.2623415652345832,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292897939","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0056080236,0.000054494383,0.99233663,0.00023947838,0.000604852,0.000442928,0.000017506612,0.0006108444,0.000085265136],"genre_scores_gemma":[0.98955154,0.0014233108,0.0025941778,0.0060261795,0.00009653585,0.00006574061,0.000050181436,0.000054412492,0.00013793315],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99747056,0.00022824417,0.000617725,0.00075770495,0.00054654223,0.00037924366],"domain_scores_gemma":[0.9983387,0.00017398482,0.0001901387,0.0006026416,0.0003695371,0.00032502593],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003086706,0.00039777008,0.00035205908,0.00080681173,0.0006255945,0.0008727262,0.0004967851,0.00027323456,0.000038839255],"category_scores_gemma":[0.00000792569,0.00039535886,0.00011427621,0.0017750806,0.00025989886,0.0012325133,0.00002196374,0.00029606925,0.000033671906],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005958131,0.00037602807,0.00022179399,0.00005984479,0.00005133891,0.0000028413447,0.00044182927,0.00013473227,0.000081086575,0.98910654,0.0032957715,0.0062222215],"study_design_scores_gemma":[0.00076132827,0.00030087074,0.0014148058,0.000070185495,0.0000425921,0.00004696842,0.00003625411,0.98927474,0.0008506913,0.0036420582,0.00304136,0.00051813346],"about_ca_topic_score_codex":0.00005035286,"about_ca_topic_score_gemma":0.00003547884,"teacher_disagreement_score":0.98974246,"about_ca_system_score_codex":0.00002798244,"about_ca_system_score_gemma":0.000049465874,"threshold_uncertainty_score":0.99984986},"labels":[],"label_agreement":null},{"id":"W4293082770","doi":"10.4324/9781003282396-25","title":"Interview 5: Peter Mettler, Digital and Live Cinema Artist","year":2022,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Movie theater; Art; Art history; Visual arts","score_opus":0.036262857322063316,"score_gpt":0.26871375489063976,"score_spread":0.23245089756857645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293082770","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[3.699069e-7,0.00041603888,0.12303906,0.0006549856,0.00020860655,0.0000892673,0.00012349339,0.00012620466,0.87534195],"genre_scores_gemma":[0.00025801576,0.00054331817,0.0014298599,0.0028753246,0.000059226673,0.0000030903564,0.00017613742,0.000023654091,0.99463135],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989753,0.000010908711,0.00024528478,0.00040097415,0.0002484035,0.00011912281],"domain_scores_gemma":[0.99925417,0.00003587859,0.0001070791,0.00046353036,0.00004546639,0.000093879615],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009669299,0.00019561237,0.00023448665,0.00011751174,0.00006293745,0.0005072598,0.0005483388,0.00005166037,0.0055284537],"category_scores_gemma":[0.000012879657,0.00017093102,0.00008628926,0.000037608526,0.000046584257,0.0004790382,0.0011981784,0.00014672264,0.00042491374],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.4561025e-7,0.000009553101,0.0000018300118,0.000026377236,0.000034904926,0.00002358907,0.00005281086,2.4460962e-7,2.4914067e-7,0.9167289,0.04793363,0.035187475],"study_design_scores_gemma":[0.000065935914,0.00006760515,0.0000032152348,0.000042398944,0.000014868257,0.00002585403,0.000005402853,0.0023864503,0.0000016297955,0.007293239,0.9898656,0.00022781163],"about_ca_topic_score_codex":0.0000020006535,"about_ca_topic_score_gemma":0.0000047949993,"teacher_disagreement_score":0.94193196,"about_ca_system_score_codex":0.00002156484,"about_ca_system_score_gemma":0.000029818033,"threshold_uncertainty_score":0.99538064},"labels":[],"label_agreement":null},{"id":"W4293247395","doi":"10.31219/osf.io/eypgm","title":"Scoping the Future of Visualization Literacy: A Review","year":2022,"lang":"en","type":"review","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visualization; Literacy; Diversity (politics); Interpretation (philosophy); Computer science; Information visualization; Data visualization; Visual literacy; Work (physics); Data science; Human–computer interaction; Psychology; Mathematics education; Pedagogy; Sociology; Engineering; Artificial intelligence","score_opus":0.06805983713562043,"score_gpt":0.4276199528991404,"score_spread":0.35956011576352,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293247395","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[1.0621327e-10,0.8847701,0.11328801,0.00012680182,0.00030153652,0.00055011065,0.000012126358,0.000056881334,0.0008944406],"genre_scores_gemma":[3.1785456e-9,0.9965442,0.00088549464,0.0015647168,0.00010032574,0.000049819755,0.00027286258,0.00001391556,0.0005686814],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.998066,0.00040647865,0.00071236596,0.00030240105,0.00039177664,0.00012097299],"domain_scores_gemma":[0.99819237,0.00015841391,0.000598372,0.0009431846,0.00007333636,0.000034351233],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006445375,0.0001932567,0.00083652104,0.00011911762,0.00011180438,0.00013419693,0.0017435828,0.000050115017,0.00075023645],"category_scores_gemma":[0.000063389874,0.00011084026,0.00029405064,0.0018311804,0.000018285846,0.00028206513,0.0006573964,0.00014818905,0.000028161823],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.0751637e-8,0.000011775018,3.1155828e-8,0.060298897,0.0000147978735,7.069238e-7,0.000022725406,1.2530474e-7,8.8201557e-10,0.09704335,0.0073584253,0.8352491],"study_design_scores_gemma":[0.000015620879,0.0000100045145,1.0891734e-8,0.06643159,0.00011659728,0.0000111435575,0.0000025536115,0.00071115606,3.734384e-8,0.000042022686,0.93254125,0.00011801695],"about_ca_topic_score_codex":0.000001544672,"about_ca_topic_score_gemma":8.903473e-7,"teacher_disagreement_score":0.9251828,"about_ca_system_score_codex":0.000026891037,"about_ca_system_score_gemma":0.00032261672,"threshold_uncertainty_score":0.82145625},"labels":[],"label_agreement":null},{"id":"W4293416488","doi":"10.52842/conf.caadria.2011.133","title":"Graph visualization in computer-aided design: An exploration of alternative representations for GenerativeComponentsTM Symbolic View","year":2011,"lang":"en","type":"article","venue":"Proceedings of the International Conference on Computer-Aided Architectural Design Research in Asia","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Mitacs","keywords":"Computer science; Visualization; USable; Graph; CAD; Theoretical computer science; Human–computer interaction; Computer Aided Design; Readability; Programming language; Data mining; Engineering drawing; World Wide Web","score_opus":0.41377413562637655,"score_gpt":0.43508261154254163,"score_spread":0.02130847591616508,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293416488","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04612574,0.000008971108,0.95084655,0.00086779846,0.00032723643,0.0014635357,0.00001869806,0.00004473364,0.00029672068],"genre_scores_gemma":[0.80851597,0.00005087852,0.19103178,0.00008291911,0.00009077587,0.0001608881,0.000027341895,0.00001859636,0.000020824573],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.996294,0.0004830683,0.000955567,0.0007374453,0.0011198948,0.0004100199],"domain_scores_gemma":[0.99684167,0.00048448087,0.00052967214,0.0003503768,0.0016780539,0.00011576167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022689647,0.0002708637,0.00039826793,0.0014425223,0.00014558199,0.0002739196,0.0029240826,0.000072695606,0.000015178026],"category_scores_gemma":[0.0002340445,0.00022468802,0.00011643777,0.0014526013,0.00024090441,0.0018119257,0.0005845244,0.000336947,0.0000030971207],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040774507,0.0010110246,0.0009108221,0.00013087416,0.00009641379,0.000004814807,0.009358017,0.023449045,0.01877847,0.9135186,0.0001862859,0.03214789],"study_design_scores_gemma":[0.0007917486,0.00068723556,0.0022015134,0.00046891236,0.000004198633,0.000007089809,0.0001330079,0.7837897,0.050124165,0.16160029,0.000008932735,0.00018322683],"about_ca_topic_score_codex":0.00016758853,"about_ca_topic_score_gemma":0.000033670418,"teacher_disagreement_score":0.76239026,"about_ca_system_score_codex":0.00013851517,"about_ca_system_score_gemma":0.00018712734,"threshold_uncertainty_score":0.9162512},"labels":[],"label_agreement":null},{"id":"W4293570427","doi":"10.1109/vr.2013.6549335","title":"IEEE Visualization and Graphics Technical Committee (VGTC)","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ontario Institute of Technology","funders":"","keywords":"Computer science; Graphics; Computer graphics (images); Visualization; Computer graphics; Artificial intelligence","score_opus":0.02161091237816882,"score_gpt":0.29649641579936015,"score_spread":0.27488550342119134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293570427","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0022008608,0.000014423612,0.9926246,0.0009297603,0.000073642106,0.00009368504,8.7555253e-7,0.00025242928,0.0038097335],"genre_scores_gemma":[0.976512,0.00010532368,0.017158959,0.00508691,0.000038335693,0.000010868627,0.000017006529,0.000009632147,0.0010609555],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99934757,0.000029292665,0.00015167295,0.00019000191,0.00016074917,0.00012069616],"domain_scores_gemma":[0.99946105,0.000037625676,0.0000362991,0.00029323806,0.00008773116,0.00008406692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011553892,0.00007343678,0.000078984514,0.000093180526,0.00007981265,0.00029514288,0.00032736696,0.000049479768,0.00007460774],"category_scores_gemma":[0.000028724251,0.00006078034,0.000018391032,0.00041218346,0.0000496144,0.00061197527,0.00013407922,0.00004877589,0.000105115665],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.2239407e-7,0.00003237371,0.0010430237,0.0000048207567,0.0000028350537,4.6445282e-7,0.000034871016,0.0000017055225,0.0003662723,0.9560168,0.040392984,0.0021037261],"study_design_scores_gemma":[0.0003529542,0.00008059523,0.013515935,0.000014720351,0.000007746979,0.000020356867,0.00003777824,0.93059844,0.001331487,0.024476105,0.02923292,0.0003309349],"about_ca_topic_score_codex":0.000034016666,"about_ca_topic_score_gemma":0.000010866283,"teacher_disagreement_score":0.97546566,"about_ca_system_score_codex":0.000006009965,"about_ca_system_score_gemma":0.000012565378,"threshold_uncertainty_score":0.28460696},"labels":[],"label_agreement":null},{"id":"W4294837602","doi":"10.1007/978-3-031-15146-0_15","title":"Tables as Powerful Representational Tools","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Gestalt psychology; Computer science; Notation; Table (database); Identification (biology); Perception; Cognition; Information retrieval; Cognitive science; Artificial intelligence; Theoretical computer science; Data mining; Psychology; Linguistics","score_opus":0.03067867280457398,"score_gpt":0.3066730428419283,"score_spread":0.27599437003735433,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294837602","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000011315407,0.00017762085,0.9709808,0.0013394225,0.0014356585,0.000204427,0.000039421517,0.00013280561,0.025678534],"genre_scores_gemma":[0.046131313,0.0005509439,0.89345944,0.028911173,0.0019942834,0.000039164643,0.0008943452,0.00018695141,0.027832415],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.996113,0.000041447314,0.00047862277,0.0013789972,0.0015312225,0.00045669414],"domain_scores_gemma":[0.997543,0.000456959,0.00026881107,0.0013642515,0.00020863555,0.00015834052],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00072169676,0.0003559128,0.00035005462,0.00075057585,0.000321116,0.001100637,0.0037706557,0.00013404948,0.0012094846],"category_scores_gemma":[0.00023087424,0.00035503687,0.00011213918,0.0008667308,0.00039066063,0.0013416867,0.0024908732,0.00055042224,0.00018292312],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000040508917,0.000047453297,0.00007748361,0.000020394056,0.000016554357,0.00017358767,0.0004883411,0.03978802,0.00004860479,0.72018194,0.00086095306,0.23829265],"study_design_scores_gemma":[0.00035391666,0.00019598774,0.000096698706,0.0001314823,0.000011218553,0.00017199312,7.884947e-7,0.4655002,0.00048189118,0.34017518,0.19189347,0.0009871703],"about_ca_topic_score_codex":0.000032782686,"about_ca_topic_score_gemma":0.000028234359,"teacher_disagreement_score":0.4257122,"about_ca_system_score_codex":0.00024364324,"about_ca_system_score_gemma":0.00086689566,"threshold_uncertainty_score":0.99993634},"labels":[],"label_agreement":null},{"id":"W4295183029","doi":"10.1016/j.vrih.2021.09.006","title":"Balanced-partitioning treemapping method for digital hierarchical dataset","year":2022,"lang":"en","type":"article","venue":"Virtual Reality & Intelligent Hardware","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Partition (number theory); Rectangle; sort; Sorting; Node (physics); Cardinality (data modeling); Sequence (biology); Algorithm; Heuristic; Theoretical computer science; Data mining; Mathematics; Artificial intelligence; Information retrieval; Combinatorics","score_opus":0.06111483150897703,"score_gpt":0.36119671988951085,"score_spread":0.30008188838053385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4295183029","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00008340382,0.000025117875,0.9829396,0.0015241534,0.00031791537,0.0002513925,0.014288585,0.00015504182,0.00041481623],"genre_scores_gemma":[0.6510286,0.00014180927,0.15204161,0.018274583,0.0011710005,0.00095631194,0.1696315,0.00016677225,0.006587845],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978019,0.00017975646,0.00047660497,0.0006196381,0.0005472439,0.00037487823],"domain_scores_gemma":[0.99847174,0.00037412322,0.00014458662,0.000734634,0.00009084038,0.00018406377],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080448197,0.00018050038,0.0002498969,0.00014224323,0.0005579693,0.0004991221,0.0011899844,0.00003743864,0.00019605686],"category_scores_gemma":[0.000417706,0.00018862235,0.00014661848,0.0005227402,0.00004584285,0.0006242971,0.00104369,0.00022834446,0.000047504458],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006312017,0.00045134078,0.00018188175,0.000057068282,0.00012353505,0.000024439787,0.0014873873,0.016875453,0.00016886515,0.58169276,0.23697084,0.16190332],"study_design_scores_gemma":[0.00017571157,0.00018243188,0.000019433557,0.000013822892,0.000010754591,0.0000134043785,0.00041396133,0.35218173,0.00045811172,0.004340618,0.64197195,0.00021808509],"about_ca_topic_score_codex":0.000032621178,"about_ca_topic_score_gemma":0.000010095542,"teacher_disagreement_score":0.830898,"about_ca_system_score_codex":0.00013333006,"about_ca_system_score_gemma":0.000118002245,"threshold_uncertainty_score":0.76917964},"labels":[],"label_agreement":null},{"id":"W4295333250","doi":"10.1109/ldav.2013.6675148","title":"IEEE Visualization and Graphics Technical Committee (VGTC)","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ontario Institute of Technology","funders":"","keywords":"Computer science; Computer graphics (images); Graphics; Visualization; Computer graphics; Data visualization; Artificial intelligence","score_opus":0.02161091237816882,"score_gpt":0.29649641579936015,"score_spread":0.27488550342119134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4295333250","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0022008608,0.000014423612,0.9926246,0.0009297603,0.000073642106,0.00009368504,8.7555253e-7,0.00025242928,0.0038097335],"genre_scores_gemma":[0.976512,0.00010532368,0.017158959,0.00508691,0.000038335693,0.000010868627,0.000017006529,0.000009632147,0.0010609555],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99934757,0.000029292665,0.00015167295,0.00019000191,0.00016074917,0.00012069616],"domain_scores_gemma":[0.99946105,0.000037625676,0.0000362991,0.00029323806,0.00008773116,0.00008406692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011553892,0.00007343678,0.000078984514,0.000093180526,0.00007981265,0.00029514288,0.00032736696,0.000049479768,0.00007460774],"category_scores_gemma":[0.000028724251,0.00006078034,0.000018391032,0.00041218346,0.0000496144,0.00061197527,0.00013407922,0.00004877589,0.000105115665],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.2239407e-7,0.00003237371,0.0010430237,0.0000048207567,0.0000028350537,4.6445282e-7,0.000034871016,0.0000017055225,0.0003662723,0.9560168,0.040392984,0.0021037261],"study_design_scores_gemma":[0.0003529542,0.00008059523,0.013515935,0.000014720351,0.000007746979,0.000020356867,0.00003777824,0.93059844,0.001331487,0.024476105,0.02923292,0.0003309349],"about_ca_topic_score_codex":0.000034016666,"about_ca_topic_score_gemma":0.000010866283,"teacher_disagreement_score":0.97546566,"about_ca_system_score_codex":0.000006009965,"about_ca_system_score_gemma":0.000012565378,"threshold_uncertainty_score":0.28460696},"labels":[],"label_agreement":null},{"id":"W4296954347","doi":"10.31219/osf.io/kdws9","title":"Embracing Disciplinary Diversity in Visualization","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Discipline; Visualization; Diversity (politics); Storytelling; Data science; Data visualization; Computer science; Citizen journalism; Engineering ethics; Sociology; World Wide Web; Narrative; Engineering; Social science; Artificial intelligence","score_opus":0.06401566936500698,"score_gpt":0.35531199271895225,"score_spread":0.2912963233539453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4296954347","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0038802228,0.00003156022,0.9677403,0.00039520758,0.00088570145,0.00015952034,0.000018771027,0.00024918254,0.02663956],"genre_scores_gemma":[0.9832907,0.0000819772,0.0088792285,0.0011253116,0.00010751711,0.0000196982,0.00087082566,0.000021049555,0.0056037297],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986206,0.000113070775,0.0002391056,0.0005031082,0.00036879253,0.0001552937],"domain_scores_gemma":[0.9991624,0.000029707662,0.00012298783,0.00059911265,0.00003445554,0.000051334526],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.00035258697,0.00013337556,0.00016854353,0.00031315058,0.0002550498,0.00019908548,0.0013992803,0.00007391702,0.00028038034],"category_scores_gemma":[0.000027747974,0.00014277107,0.000057670073,0.0005427173,0.000014499894,0.00034357712,0.028190563,0.0002599324,0.000018435863],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000050450267,0.0002814604,0.018610414,0.00014629232,0.000020496314,0.000055666453,0.0040234607,0.028475363,0.0000067078095,0.94222295,0.004745369,0.0014067771],"study_design_scores_gemma":[0.00018310307,0.000019973118,0.009742891,0.000045174223,0.0000072842754,0.0000014307476,0.0002458786,0.94024336,0.000021607184,0.04750458,0.0016374415,0.00034728038],"about_ca_topic_score_codex":0.00013159483,"about_ca_topic_score_gemma":0.00006532302,"teacher_disagreement_score":0.9794104,"about_ca_system_score_codex":0.00014220613,"about_ca_system_score_gemma":0.00009381567,"threshold_uncertainty_score":0.9796693},"labels":[],"label_agreement":null},{"id":"W4297156401","doi":"10.1145/3546155.3546656","title":"How Well Do Experts Understand End-Users’ Perceptions of Manipulative Patterns?","year":2022,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Perception; Computer science; Interface (matter); End user; Human–computer interaction; World Wide Web; Psychology","score_opus":0.0729633361783003,"score_gpt":0.30752534444801816,"score_spread":0.23456200826971785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297156401","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01060658,0.000011836163,0.98247904,0.0013145494,0.00013184683,0.000069512804,0.000030458643,0.00006382538,0.0052923555],"genre_scores_gemma":[0.99205923,0.00001394649,0.0021500648,0.0005082579,0.000012855405,0.0000038455546,0.000029286824,0.000005331717,0.0052172057],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991909,0.00006418627,0.00011754625,0.00020911399,0.00030180786,0.00011641056],"domain_scores_gemma":[0.99947876,0.000027644981,0.00006182178,0.00034492303,0.000037808848,0.000049053804],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000088971574,0.0000715785,0.0000914453,0.0001008013,0.00015400254,0.0001341872,0.00048248205,0.000013308977,0.0021385353],"category_scores_gemma":[0.0000055884393,0.000066614935,0.000046959005,0.00027633703,0.000026680229,0.00034150243,0.00039961515,0.00004717774,0.000007904328],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000042210568,0.00031125802,0.015218938,0.00002323382,0.000051205516,0.000016762637,0.011686458,0.000727614,0.0009806679,0.9316084,0.036672704,0.0026985633],"study_design_scores_gemma":[0.0025273708,0.0008262247,0.028115587,0.00004657139,0.000054804077,0.000068306275,0.2923814,0.5292232,0.0023162453,0.014051364,0.12891531,0.001473616],"about_ca_topic_score_codex":0.000025803742,"about_ca_topic_score_gemma":0.000021506772,"teacher_disagreement_score":0.98145264,"about_ca_system_score_codex":0.00005118411,"about_ca_system_score_gemma":0.000025333999,"threshold_uncertainty_score":0.99877363},"labels":[],"label_agreement":null},{"id":"W4297877462","doi":"10.5194/hess-2022-305","title":"Uncertainty in three dimensions: the challenges of communicating probabilistic flood forecasts maps","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ministère de l’Environnement, de la Lutte contre les changements climatiques, de la Faune et des Parcs; Ministère des Ressources naturelles et des Forêts; Université de Sherbrooke; Université du Québec à Rimouski","funders":"","keywords":"Probabilistic logic; Flood myth; Streamflow; Flood forecasting; Scale (ratio); Computer science; Watershed; Point (geometry); Representation (politics); Hydrological modelling; Event (particle physics); Operations research; Geography; Mathematics; Climatology; Artificial intelligence; Geology; Cartography; Machine learning","score_opus":0.09222542166008994,"score_gpt":0.3252920567146602,"score_spread":0.23306663505457026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297877462","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06355116,0.040314913,0.6201754,0.09282022,0.0047966847,0.011757984,0.00089729665,0.002044361,0.16364194],"genre_scores_gemma":[0.97999847,0.0013290488,0.017912274,0.0003762872,0.000022399958,0.00014155188,0.00010690144,0.000018580255,0.000094480696],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982032,0.0003178443,0.0005167755,0.00040573292,0.00036816782,0.00018828212],"domain_scores_gemma":[0.996658,0.00046878634,0.0003051879,0.0024309335,0.00010061246,0.000036481375],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0011670269,0.0001733915,0.00029890958,0.00012473171,0.00012258417,0.00007636405,0.0034024457,0.00007589792,0.000047028185],"category_scores_gemma":[0.00029254693,0.00012175314,0.000085961,0.0003272818,0.000091376234,0.000083566294,0.009104083,0.0005410272,0.0000035429618],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000015697941,0.00014956419,0.00016009776,0.00013275868,0.000023942119,0.000001957383,0.0013819337,0.039148763,0.0000016804142,0.951598,0.0001752177,0.0072245016],"study_design_scores_gemma":[0.00014922157,0.00003284478,0.00042259003,0.00016445272,0.00001068832,0.0000020809848,0.00056628464,0.7830484,0.000004912711,0.21431448,0.0011168572,0.00016723179],"about_ca_topic_score_codex":0.00033389774,"about_ca_topic_score_gemma":0.0023234305,"teacher_disagreement_score":0.91644734,"about_ca_system_score_codex":0.00006918327,"about_ca_system_score_gemma":0.00017625066,"threshold_uncertainty_score":0.99891007},"labels":[],"label_agreement":null},{"id":"W4298179957","doi":"10.1007/978-1-4939-7131-2_100516","title":"Information Visualization","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Information visualization; Visualization; Artificial intelligence","score_opus":0.022541346105439692,"score_gpt":0.28500518553994314,"score_spread":0.26246383943450347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4298179957","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[4.8617828e-8,0.000004293722,0.51110446,0.000046548783,0.000149367,0.000040987536,0.000006153197,0.0001485972,0.48849955],"genre_scores_gemma":[0.00005228337,0.00008280375,0.0050818413,0.0028055904,0.00014945524,0.0000011965963,0.0006827114,0.000012774736,0.99113137],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992004,0.0000049321334,0.00028163212,0.00012367436,0.00029665654,0.00009270219],"domain_scores_gemma":[0.99904656,0.00001048587,0.00018594756,0.00044651298,0.00025394376,0.00005654313],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000103050384,0.00014158632,0.00011738711,0.00021993007,0.000057467834,0.00034320995,0.00051499787,0.00014370638,0.0021910714],"category_scores_gemma":[0.000018364357,0.00013057291,0.00004635981,0.000059078102,0.000028813518,0.0013940452,0.00020841995,0.00005165753,0.0060904133],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.1385543e-7,0.0000018031859,3.266314e-7,0.000008100983,0.0000065704353,2.0892085e-7,0.000098173325,8.6136134e-7,1.8695123e-7,0.87406206,0.12120925,0.004612263],"study_design_scores_gemma":[0.000060286013,0.000025549652,0.0000011147996,0.000024600284,0.0000059195463,0.0000021477385,0.0000034300206,0.03537756,0.00002150484,0.03390187,0.9304074,0.00016861247],"about_ca_topic_score_codex":0.0000013118023,"about_ca_topic_score_gemma":0.00000223385,"teacher_disagreement_score":0.8401602,"about_ca_system_score_codex":0.000029721003,"about_ca_system_score_gemma":0.000064018874,"threshold_uncertainty_score":0.99872106},"labels":[],"label_agreement":null},{"id":"W4299614486","doi":"10.51952/9781847425737.ch008","title":"Social alarms (PRS) in North America","year":2003,"lang":"en","type":"book-chapter","venue":"Policy Press eBooks","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"History; Psychology","score_opus":0.059303758168227534,"score_gpt":0.32456835438709863,"score_spread":0.2652645962188711,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4299614486","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000018559881,0.000073371004,0.015699012,0.00027225827,0.0000978325,0.00017049455,0.00009233281,0.00011793717,0.9834749],"genre_scores_gemma":[0.0005642702,0.00012576311,0.0009454186,0.0067064553,0.00048558446,0.000016214766,0.000091371076,0.000061048486,0.9910039],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99843925,0.000037694335,0.00036886532,0.0004641152,0.0003474514,0.00034259798],"domain_scores_gemma":[0.9989974,0.000025779622,0.00023507721,0.0005661752,0.000061647646,0.00011390681],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00006553827,0.00029989766,0.00035793328,0.00032161866,0.00008406151,0.00019583749,0.0010249846,0.00017683345,0.000016306776],"category_scores_gemma":[0.000021544794,0.00031096447,0.00011896995,0.00004114315,0.000111518035,0.000104871266,0.00038047647,0.00029704437,0.00006741122],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001277799,0.000011935239,0.00000665146,0.000022556447,0.000024111176,0.000018616813,0.00075177813,0.000008250732,6.416956e-7,0.9680735,0.015398677,0.015682029],"study_design_scores_gemma":[0.00019277177,0.000015700449,0.000016815866,0.000019672008,0.000010729587,0.000002944393,0.0000013759329,0.0012665031,0.000012615484,0.010189343,0.98793405,0.0003374732],"about_ca_topic_score_codex":0.0002896123,"about_ca_topic_score_gemma":0.00013669442,"teacher_disagreement_score":0.9725354,"about_ca_system_score_codex":0.00007724199,"about_ca_system_score_gemma":0.00015910472,"threshold_uncertainty_score":0.99993426},"labels":[],"label_agreement":null},{"id":"W4299945874","doi":"10.1007/978-1-4614-6170-8_100795","title":"Information Visualization","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Information visualization; Visualization; Artificial intelligence","score_opus":0.018026185635070663,"score_gpt":0.2714875419252381,"score_spread":0.2534613562901674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4299945874","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[1.1985222e-8,0.0000038798685,0.5224313,0.000071115515,0.00011564282,0.00003713427,0.000003314998,0.00014601422,0.47719157],"genre_scores_gemma":[0.00018226771,0.00007812895,0.003990268,0.0040824856,0.000097466895,0.0000013790309,0.00074103934,0.00001354209,0.99081343],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991994,0.0000067627793,0.0002917939,0.000117829535,0.00029488959,0.00008931407],"domain_scores_gemma":[0.99911827,0.000016560462,0.0001975678,0.00044548642,0.00016362451,0.000058471865],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00012295049,0.00014353053,0.00013657167,0.0002148792,0.0000500051,0.0003191202,0.0004951616,0.00014069011,0.00043360752],"category_scores_gemma":[0.000021422497,0.00013286437,0.000050893093,0.00004698492,0.000015718784,0.00074568193,0.00016929899,0.00006306899,0.0027500696],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.531584e-7,0.0000011589573,4.4159768e-7,0.000012385356,0.0000055244363,1.4108426e-7,0.00003441693,0.000007719782,1.7030823e-7,0.9340772,0.046893183,0.0189675],"study_design_scores_gemma":[0.000064110434,0.000016040647,0.0000012888792,0.000022119384,0.000005594409,0.0000017424995,0.000001094756,0.0814804,0.00000974966,0.018752519,0.8994816,0.0001637683],"about_ca_topic_score_codex":0.0000016165276,"about_ca_topic_score_gemma":0.0000016543485,"teacher_disagreement_score":0.9153247,"about_ca_system_score_codex":0.00002533262,"about_ca_system_score_gemma":0.000045198372,"threshold_uncertainty_score":0.99802643},"labels":[],"label_agreement":null},{"id":"W4300495476","doi":"10.1109/compsac54236.2022.00266","title":"A Data Science Solution for Mining Weather Data and Transportation Data for Smart Cities","year":2022,"lang":"en","type":"article","venue":"2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Snow; Computer science; Data science; Big data; Smart city; Software; Meteorology; Data mining; Computer security; Internet of Things; Geography","score_opus":0.08830481576105496,"score_gpt":0.3268774279990724,"score_spread":0.2385726122380174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4300495476","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00078871,0.00022735492,0.9598175,0.0006370321,0.00028827265,0.00096639467,0.03706637,0.00019061554,0.00001773644],"genre_scores_gemma":[0.1469328,0.00037529776,0.7920616,0.0017252548,0.0003989983,0.00075275707,0.057329398,0.000057436162,0.00036642357],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99696773,0.000056161272,0.0004450265,0.0016790035,0.00044021234,0.0004118914],"domain_scores_gemma":[0.99581933,0.00038240346,0.00024719862,0.0031030346,0.00026546037,0.00018255877],"candidate_categories":["metaepi_narrow","sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.0013086109,0.00023489057,0.0002796908,0.00023595526,0.0017100743,0.0006099102,0.005908374,0.000042659893,0.000010408657],"category_scores_gemma":[0.00007913844,0.00026050722,0.000024183162,0.00069747865,0.00035147308,0.002925636,0.002360915,0.00013861392,0.0000014290009],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009541298,0.0006897426,0.0041090106,0.0006023646,0.0001910263,0.000003648722,0.0051864493,0.0005857917,0.00029591526,0.23314992,0.1471674,0.6079233],"study_design_scores_gemma":[0.00050209777,0.000093784685,0.00049840607,0.000016301938,0.00004748783,0.0000071778572,0.0007197053,0.71121967,0.000007685452,0.0017696178,0.28482652,0.00029155458],"about_ca_topic_score_codex":0.000056941328,"about_ca_topic_score_gemma":0.00010036087,"teacher_disagreement_score":0.7106339,"about_ca_system_score_codex":0.000033406686,"about_ca_system_score_gemma":0.0004411289,"threshold_uncertainty_score":0.99998474},"labels":[],"label_agreement":null},{"id":"W4300584018","doi":"","title":"CARTOD / MAPOD. Une application de visualisation de la demande de transport locale par déformation des arêtes et des sommets pour augmenter la lisibilité","year":2014,"lang":"fr","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ministère des Transports","funders":"","keywords":"Physics; Computer science","score_opus":0.016192397848410516,"score_gpt":0.27628673701776507,"score_spread":0.26009433916935454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4300584018","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13252784,0.00045548897,0.84814835,0.006249348,0.000051351584,0.0002627079,0.000048510075,0.00019470631,0.012061717],"genre_scores_gemma":[0.8725554,0.0009816097,0.12189061,0.00068989967,0.00003874916,0.000056298424,0.0005428104,0.000041144318,0.0032034735],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.98848957,0.009159286,0.0007026201,0.00060854666,0.00042884843,0.0006111381],"domain_scores_gemma":[0.9947009,0.0019939046,0.0004459061,0.0012106827,0.0012900004,0.00035862453],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.013874445,0.0003349041,0.00030475564,0.00021117438,0.0006163858,0.000798224,0.0010448002,0.00029802055,0.00007041822],"category_scores_gemma":[0.0014311512,0.00038176458,0.00017223896,0.00088643364,0.0007447854,0.0012725696,0.0002211155,0.0003382505,0.00007512554],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019744677,0.0017721792,0.061395537,0.00053526676,0.00008495339,0.000005958267,0.0639469,0.0023601158,0.007219517,0.66529185,0.0016165073,0.19575144],"study_design_scores_gemma":[0.001076718,0.0000036053577,0.05988615,0.0010483642,0.00010358601,0.000081100705,0.00046906652,0.7962685,0.04471127,0.050739907,0.045135733,0.0004759934],"about_ca_topic_score_codex":0.002088147,"about_ca_topic_score_gemma":0.002780518,"teacher_disagreement_score":0.7939084,"about_ca_system_score_codex":0.00036788324,"about_ca_system_score_gemma":0.00049572956,"threshold_uncertainty_score":0.99986345},"labels":[],"label_agreement":null},{"id":"W4300778753","doi":"10.48550/arxiv.1707.01921","title":"A Visual Narrative Path from Switching to Resuming a Requirements\\n Engineering Task","year":2017,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Visualization; Visual analytics; Task (project management); Process (computing); Human–computer interaction; Creative visualization; Software visualization; Task analysis; Data visualization; Software; Software development; Artificial intelligence; Systems engineering; Component-based software engineering; Engineering","score_opus":0.08102167196208267,"score_gpt":0.24694601329060553,"score_spread":0.16592434132852285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4300778753","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18672034,0.000013098355,0.8118439,0.00009119117,0.00055747916,0.0001760901,0.000039537066,0.00020688155,0.00035148402],"genre_scores_gemma":[0.99265665,0.000034059838,0.006328095,0.00018079772,0.00013472815,9.810599e-7,0.00007099704,0.000022353961,0.00057133264],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99800116,0.00007330571,0.00023974763,0.0011712876,0.00016152268,0.0003530051],"domain_scores_gemma":[0.997807,0.00006599341,0.00031865304,0.0013969315,0.00014382089,0.00026759662],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00026066316,0.000329452,0.0003479814,0.00031050816,0.00033615372,0.0006018243,0.0023925714,0.00017256313,0.000016671254],"category_scores_gemma":[0.0001825747,0.00039753152,0.0001382323,0.0003225987,0.000023335913,0.0007653153,0.003650284,0.0004132533,0.00008051346],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012247662,0.0005958311,0.0060163923,0.00032260155,0.0012845306,0.0029535976,0.03550455,0.6376687,0.009500305,0.2951291,0.004811537,0.006090336],"study_design_scores_gemma":[0.00032342458,0.00003220689,0.00065135077,0.0004200453,0.00003754523,7.534146e-7,0.00027623147,0.9927174,0.0001605236,0.0033408036,0.0015115218,0.0005281857],"about_ca_topic_score_codex":0.00035667763,"about_ca_topic_score_gemma":0.000045340432,"teacher_disagreement_score":0.8059363,"about_ca_system_score_codex":0.0002215944,"about_ca_system_score_gemma":0.00017463056,"threshold_uncertainty_score":0.99984765},"labels":[],"label_agreement":null},{"id":"W4301730816","doi":"10.1007/978-3-031-02602-7","title":"Design of Visualizations for Human-Information Interaction","year":2016,"lang":"en","type":"book","venue":"Synthesis lectures on visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Visualization; Human–computer interaction; Computer science; Information visualization; Data science; Artificial intelligence","score_opus":0.04034409199296487,"score_gpt":0.3405915419777906,"score_spread":0.3002474499848258,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4301730816","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[7.7766674e-7,0.000030117686,0.9791697,0.00010115035,0.00046070438,0.0009707216,0.00019151445,0.00027458643,0.018800728],"genre_scores_gemma":[0.09644569,0.0030132693,0.075827464,0.013862662,0.0056287553,0.0044056806,0.03204953,0.0018420805,0.76692486],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9973071,0.00022797252,0.0010212502,0.00049667107,0.0006562531,0.00029071368],"domain_scores_gemma":[0.99594426,0.0010692055,0.0013248385,0.00078372116,0.0007886487,0.00008935237],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00054931146,0.0004509413,0.00054713106,0.0011434258,0.00028312844,0.00029080026,0.00087819394,0.00043607404,0.00014611128],"category_scores_gemma":[0.0009312568,0.00038897418,0.0002116731,0.00036360076,0.00006966986,0.0012340739,0.00010221811,0.00011036067,0.000093088885],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038327755,0.0001017642,0.0000011772548,0.00027975833,0.0001259498,3.059653e-7,0.00030641002,0.0019802486,0.0004389823,0.91058296,0.07443336,0.011710755],"study_design_scores_gemma":[0.0013039985,0.0010766383,0.000012482555,0.0027891363,0.00041976385,0.000007636091,0.00003301254,0.28839442,0.0633596,0.099472985,0.5412529,0.0018774208],"about_ca_topic_score_codex":0.0000026046107,"about_ca_topic_score_gemma":0.0000024729675,"teacher_disagreement_score":0.90334225,"about_ca_system_score_codex":0.00031893144,"about_ca_system_score_gemma":0.00038923297,"threshold_uncertainty_score":0.99985623},"labels":[],"label_agreement":null},{"id":"W4306681012","doi":"10.1609/aiide.v18i1.21972","title":"EM-Glue: A Platform for Decoupling Experience Managers and Environments","year":2022,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Rannís","keywords":"Decoupling (probability); Computer science; Software; Human–computer interaction; Visualization; Field (mathematics); Software engineering; Engineering; Operating system; Artificial intelligence","score_opus":0.05359777811706851,"score_gpt":0.30566719534683545,"score_spread":0.25206941722976695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4306681012","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8139962,0.000028746676,0.18009278,0.0013858174,0.0003930861,0.00093884475,0.00008728422,0.00004185295,0.0030354257],"genre_scores_gemma":[0.99884224,0.00003406973,0.00027250854,0.00038581228,0.000010946303,0.00008698911,0.0000043875043,0.000007587586,0.00035544296],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99876446,0.00000423508,0.00031937734,0.00039630552,0.00031322648,0.00020241222],"domain_scores_gemma":[0.9994372,0.000068423156,0.00023447807,0.00013018632,0.000059570684,0.000070137474],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014075637,0.00015675522,0.00015445187,0.00009322716,0.00028613795,0.0005042086,0.00066442037,0.00001887677,0.000022997108],"category_scores_gemma":[0.00007581074,0.00012763395,0.00006213825,0.00014621722,0.000119707336,0.0010077491,0.0008514159,0.000121345605,0.0000030380932],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022317648,0.00046920337,0.0007234306,0.00004322306,0.000075470336,9.137717e-7,0.013360641,0.00010784062,0.0046055885,0.8014553,0.00010365549,0.17883153],"study_design_scores_gemma":[0.0002716358,0.0016914475,0.00033571455,0.00025611726,0.000038408863,0.000024105731,0.07061413,0.6814701,0.16303504,0.07457913,0.006978038,0.0007061489],"about_ca_topic_score_codex":0.0000036361764,"about_ca_topic_score_gemma":7.393988e-7,"teacher_disagreement_score":0.7268762,"about_ca_system_score_codex":0.00007009146,"about_ca_system_score_gemma":0.000014220869,"threshold_uncertainty_score":0.52047616},"labels":[],"label_agreement":null},{"id":"W4307717096","doi":"10.1145/3549508","title":"NCAlt: Alternatives and Difference Visualizations for Behavior Trees in Game Development Learning","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Usability; Computer science; Plug-in; Workflow; Tree (set theory); Outcome (game theory); Visualization; Human–computer interaction; Video game development; Test (biology); Scale (ratio); Multimedia; Artificial intelligence; Game design; Programming language","score_opus":0.07385034738253368,"score_gpt":0.369488436201907,"score_spread":0.29563808881937337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307717096","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9535441,0.0000074371524,0.0453277,0.0004242341,0.0002572518,0.00030435383,0.0000031733955,0.00005872409,0.00007302435],"genre_scores_gemma":[0.9932885,0.000004037742,0.0060653198,0.00017775911,0.000037465274,0.00011259533,0.000010548891,0.000009381587,0.00029437162],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99901044,0.000019868798,0.0002952671,0.00029873295,0.00024529235,0.00013041783],"domain_scores_gemma":[0.9993484,0.00007310342,0.0002733362,0.00016099837,0.000116616546,0.000027532988],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021557344,0.00011152353,0.00013321445,0.00023764689,0.00031015917,0.00016885292,0.0011356849,0.00001779076,0.000009368136],"category_scores_gemma":[0.000113799644,0.00009631515,0.000040359675,0.0002647165,0.000026029344,0.00036971396,0.0012632296,0.00017041723,7.1893976e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021727769,0.0038995184,0.1515119,0.00039341574,0.00020203256,0.0000041249277,0.06488277,0.009787927,0.06301365,0.42385224,0.0040729125,0.27816224],"study_design_scores_gemma":[0.0017873143,0.0010343234,0.24882019,0.00031200272,0.000036887035,0.0000296283,0.0016291892,0.6869814,0.03335748,0.008139357,0.017212912,0.0006593199],"about_ca_topic_score_codex":0.0000071408035,"about_ca_topic_score_gemma":0.0000059165586,"teacher_disagreement_score":0.67719346,"about_ca_system_score_codex":0.00009209413,"about_ca_system_score_gemma":0.000016093607,"threshold_uncertainty_score":0.39276177},"labels":[],"label_agreement":null},{"id":"W4308990726","doi":"10.1145/3567711","title":"Tangible Chromatin: Tangible and Multi-surface Interactions for Exploring Datasets from High-Content Microscopy Experiments","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Replication (statistics); Human–computer interaction; Interpretation (philosophy); Complement (music); Visualization; Data science; Data mining; Chemistry; Biology","score_opus":0.22629324744269483,"score_gpt":0.3875791301823386,"score_spread":0.16128588273964375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4308990726","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9442451,0.000034106983,0.051342394,0.0009941638,0.0023522258,0.00053206255,0.00032358264,0.0001402413,0.000036134883],"genre_scores_gemma":[0.86722493,0.000010656498,0.1313765,0.0005949283,0.00016903107,0.0001485117,0.00018657804,0.000029379202,0.00025945224],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99853307,0.000022782788,0.00040697996,0.000522554,0.0003036766,0.00021096267],"domain_scores_gemma":[0.99869454,0.00010857529,0.00043253886,0.00057132647,0.00013298551,0.00006004641],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021328544,0.00019757038,0.00022161503,0.00015241998,0.0006035105,0.0003648153,0.0018321035,0.000023683117,0.000042285214],"category_scores_gemma":[0.000070286296,0.0001749789,0.00009629259,0.00025537892,0.0000323841,0.0015901285,0.002413086,0.0002048588,0.0000063870234],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011496389,0.0011075279,0.0011288159,0.00011663211,0.0002525998,0.0000011777951,0.005693265,0.0010407332,0.91716754,0.011578883,0.056745782,0.0050520976],"study_design_scores_gemma":[0.001914108,0.000522874,0.0017627042,0.0003000729,0.00005662727,0.000019987374,0.0017027461,0.23997974,0.7327612,0.0015233086,0.018974373,0.00048227765],"about_ca_topic_score_codex":0.00015355702,"about_ca_topic_score_gemma":0.00000476575,"teacher_disagreement_score":0.23893902,"about_ca_system_score_codex":0.00016267423,"about_ca_system_score_gemma":0.000012669064,"threshold_uncertainty_score":0.71354324},"labels":[],"label_agreement":null},{"id":"W4311605308","doi":"10.5430/wjel.v13n1p234","title":"The Sequential Schematic Scene-building Theory in Dan Brown’s The Da Vinci Code: A Cognitive Semantic Study","year":2022,"lang":"en","type":"article","venue":"World Journal of English Language","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Schematic; Computer science; Object (grammar); Motion (physics); Code (set theory); Artificial intelligence; Programming language; Electrical engineering","score_opus":0.019440835524200867,"score_gpt":0.3112407237836152,"score_spread":0.2917998882594144,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311605308","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9365062,0.0022230414,0.05489272,0.00089428935,0.00221755,0.0007029473,0.000030585856,0.00007905832,0.0024535672],"genre_scores_gemma":[0.998604,0.00001098281,0.00028224208,0.0004347667,0.00022002081,0.000008303808,0.0000022587524,0.000012165543,0.0004252461],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9974615,0.0009539812,0.00051239587,0.00016533524,0.0006692911,0.00023750601],"domain_scores_gemma":[0.9981812,0.0007606643,0.00041185765,0.00036039777,0.0002236321,0.00006222716],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004006287,0.00012281713,0.00020321313,0.00024652388,0.00048084976,0.00044752442,0.0015032245,0.00001116655,0.000056595538],"category_scores_gemma":[0.0013924798,0.00007530435,0.000096150354,0.0010677105,0.000070836235,0.00035553265,0.00064328354,0.0005550545,0.0000017458252],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003695016,0.0034741906,0.014550761,0.00011987674,0.0011564348,0.0035474712,0.5481839,0.006444675,0.001283856,0.3583464,0.009178005,0.0533449],"study_design_scores_gemma":[0.010214534,0.0012097976,0.004550053,0.00086844014,0.00057329325,0.00041186888,0.8193489,0.11054843,0.0018744871,0.0061181295,0.04299827,0.0012837986],"about_ca_topic_score_codex":0.000009152094,"about_ca_topic_score_gemma":0.00028531198,"teacher_disagreement_score":0.35222828,"about_ca_system_score_codex":0.00009756728,"about_ca_system_score_gemma":0.00013055246,"threshold_uncertainty_score":0.43154883},"labels":[],"label_agreement":null},{"id":"W4312719900","doi":"10.1109/ismar-adjunct57072.2022.00036","title":"HybridAxes: An Immersive Analytics Tool With Interoperability Between 2D and Immersive Reality Modes","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Human–computer interaction; Usability; Analytics; Virtuality (gaming); Virtual reality; Visualization; Interoperability; Task (project management); Virtual desktop; Visual analytics; Immersive technology; Data visualization; Cognitive load; Process (computing); Multimedia; Cognition; Data science; Virtual machine; World Wide Web; Artificial intelligence; Engineering; Psychology","score_opus":0.03372771988868928,"score_gpt":0.2913771951417361,"score_spread":0.2576494752530468,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312719900","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6499862,0.00011161862,0.3256383,0.01421114,0.0018732542,0.0012606019,0.003910897,0.00019162676,0.0028163355],"genre_scores_gemma":[0.99452615,0.00023361169,0.00037408498,0.0018639867,0.00022680349,0.00007252745,0.00173791,0.000044078854,0.0009208281],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9944192,0.00085853983,0.0009424405,0.0016254634,0.001567992,0.0005863228],"domain_scores_gemma":[0.9972225,0.00032456112,0.0005341872,0.0010935026,0.00040307414,0.00042222117],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0015844138,0.000609422,0.0006862065,0.00035388983,0.00083007966,0.0005017583,0.001484618,0.00011637975,0.00017554493],"category_scores_gemma":[0.00008959548,0.0005421395,0.0001825636,0.0007097366,0.0003668215,0.0011466326,0.0011091535,0.00071609055,0.000011368883],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00890929,0.017177306,0.12779178,0.0014166108,0.013480688,0.0015034867,0.027750231,0.12428755,0.10932174,0.36136463,0.12367037,0.0833263],"study_design_scores_gemma":[0.012716525,0.0070209554,0.04344013,0.00042077524,0.00095021806,0.0003654584,0.013992077,0.8042292,0.0436849,0.0066411933,0.06205761,0.004480986],"about_ca_topic_score_codex":0.0009296132,"about_ca_topic_score_gemma":0.00015738308,"teacher_disagreement_score":0.6799416,"about_ca_system_score_codex":0.0005754894,"about_ca_system_score_gemma":0.00017743131,"threshold_uncertainty_score":0.999703},"labels":[],"label_agreement":null},{"id":"W4312868234","doi":"10.1109/ismar-adjunct57072.2022.00035","title":"XVCollab: An Immersive Analytics Tool for Asymmetric Collaboration across the Virtuality Spectrum","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Virtuality (gaming); Computer science; Analytics; Human–computer interaction; Visualization; Data visualization; Virtual collaboration; Collaborative software; Virtual reality; Data science; World Wide Web; Multimedia; Artificial intelligence","score_opus":0.02656991288908998,"score_gpt":0.3202221384113752,"score_spread":0.2936522255222852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312868234","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.124619976,0.00022542929,0.7590211,0.08161511,0.016185788,0.0037491268,0.010898083,0.00036309633,0.0033222986],"genre_scores_gemma":[0.9851446,0.00026923063,0.0003544219,0.0062697227,0.0006130247,0.00030954482,0.0026605946,0.00005501322,0.0043238206],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9948943,0.000680135,0.0009452207,0.0011781731,0.0016855424,0.00061660586],"domain_scores_gemma":[0.9970412,0.0005265915,0.00064997544,0.0010476809,0.0005023832,0.00023211465],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0025032412,0.00046704692,0.00045818085,0.00032040503,0.0016273133,0.0009039215,0.0019403043,0.00012313115,0.00012791487],"category_scores_gemma":[0.00025431364,0.00040058742,0.0002477295,0.0022343246,0.00017417342,0.00092882576,0.0007812386,0.00043009294,0.000017714196],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019977146,0.0053446256,0.0035215402,0.00018992896,0.0021242613,0.00010425825,0.0073835533,0.06091222,0.029203996,0.6207125,0.24716838,0.02133701],"study_design_scores_gemma":[0.0056231422,0.0021548385,0.003650067,0.000047390302,0.0002085766,0.00006310207,0.0066860453,0.6395289,0.016788376,0.005796213,0.3180229,0.0014304712],"about_ca_topic_score_codex":0.00023132353,"about_ca_topic_score_gemma":0.00031885877,"teacher_disagreement_score":0.86052465,"about_ca_system_score_codex":0.0007191934,"about_ca_system_score_gemma":0.00024564585,"threshold_uncertainty_score":0.9998446},"labels":[],"label_agreement":null},{"id":"W4312918387","doi":"10.1109/ismar-adjunct57072.2022.00057","title":"Layouts of 3D Data Visualizations Small Multiples around Users in Immersive Environments","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Visualization; Computer science; Human–computer interaction; Data visualization; Data exploration; Space (punctuation); Virtual reality; Information visualization; Creative visualization; Computer graphics (images); Data mining","score_opus":0.0536547198432478,"score_gpt":0.30455444573244583,"score_spread":0.250899725889198,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312918387","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.26197964,0.0007110677,0.6832227,0.015840013,0.012503272,0.003036675,0.015314888,0.00023171809,0.007160023],"genre_scores_gemma":[0.9880432,0.0007179146,0.00070192723,0.0016897626,0.00013453372,0.000076655175,0.0064964388,0.000045668152,0.0020939177],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.995891,0.00047248628,0.0009241908,0.0011017479,0.0012097284,0.0004008812],"domain_scores_gemma":[0.9978015,0.00026087472,0.00053519645,0.0011432486,0.000083215484,0.00017597583],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008422802,0.0003700904,0.00042484634,0.00044927673,0.00033947176,0.0001568738,0.0023063216,0.00009210049,0.00019477667],"category_scores_gemma":[0.000118005795,0.0003855199,0.0001054034,0.00075846806,0.00015984909,0.0006685457,0.0018664201,0.00037772887,0.000019251882],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00173353,0.01956067,0.06945001,0.0005257132,0.003628718,0.00057464844,0.014009285,0.27173734,0.33730188,0.18174703,0.08240121,0.017329982],"study_design_scores_gemma":[0.0059797675,0.0005991559,0.0072132996,0.0001834066,0.0001332622,0.00004323227,0.0037208158,0.8574528,0.013765429,0.0007170095,0.10903706,0.0011547313],"about_ca_topic_score_codex":0.00065914285,"about_ca_topic_score_gemma":0.0003071592,"teacher_disagreement_score":0.72606355,"about_ca_system_score_codex":0.0003493061,"about_ca_system_score_gemma":0.00010874014,"threshold_uncertainty_score":0.9998597},"labels":[],"label_agreement":null},{"id":"W4312939477","doi":"10.1007/978-3-031-16990-8_5","title":"Data Visualization","year":2022,"lang":"en","type":"book-chapter","venue":"International series in management science/operations research/International series in operations research & management science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Public Health Ontario; York University","funders":"","keywords":"Graphics; Computer science; Visualization; Outlier; Information visualization; Artificial intelligence; Data visualization; Information retrieval; Computer graphics (images); Pattern recognition (psychology); Data mining","score_opus":0.1407635745079986,"score_gpt":0.4716575880095431,"score_spread":0.3308940135015445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312939477","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00019162374,0.00013119623,0.023854287,0.021121897,0.004635444,0.0036858341,0.0007713372,0.00027509802,0.9453333],"genre_scores_gemma":[0.044383492,0.018908417,0.0465873,0.00080347457,0.00058685744,0.0016756336,0.005157749,0.00017504254,0.88172203],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.97479606,0.0005311921,0.0020157867,0.004305895,0.01635306,0.0019979908],"domain_scores_gemma":[0.99103457,0.00021663978,0.0001641783,0.004674677,0.0034511695,0.0004587556],"candidate_categories":["metaepi_narrow","bibliometrics","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["sts","scholarly_communication","open_science"],"category_scores_codex":[0.025653735,0.00071599364,0.0005353463,0.017924944,0.004909493,0.009934337,0.031597327,0.00018510692,0.004981122],"category_scores_gemma":[0.001688767,0.0007901045,0.0001196273,0.01013322,0.0066538905,0.023607709,0.033588514,0.0019244208,0.00062101334],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052893312,0.00038453654,0.000075092896,0.00005289542,0.00009307976,0.0003091977,0.0005225314,0.053128097,0.00010172577,0.93598276,0.0055407444,0.0037564693],"study_design_scores_gemma":[0.0007075015,0.0001409968,0.00054798124,0.00031444532,0.0000107225005,0.000034982888,0.0017770606,0.3468641,0.00006454585,0.019746471,0.6290151,0.00077608746],"about_ca_topic_score_codex":0.0006029849,"about_ca_topic_score_gemma":0.0051878947,"teacher_disagreement_score":0.9162363,"about_ca_system_score_codex":0.005806882,"about_ca_system_score_gemma":0.0015746028,"threshold_uncertainty_score":0.999455},"labels":[],"label_agreement":null},{"id":"W4313384919","doi":"10.1007/978-3-031-18223-5_2","title":"Data Discovery: A Human-Centered View","year":2022,"lang":"en","type":"book-chapter","venue":"Synthesis lectures on information concepts, retrieval, and services","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Terminology; Data science; Context (archaeology); Computer science; History; Linguistics; Philosophy","score_opus":0.041807603587334895,"score_gpt":0.3069004210427164,"score_spread":0.26509281745538155,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313384919","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00019515118,0.008661606,0.06371057,0.0050595384,0.0028477309,0.0026826249,0.017464055,0.001535912,0.8978428],"genre_scores_gemma":[0.23257661,0.11416563,0.008078549,0.19830285,0.0039386633,0.0002620482,0.13295472,0.0009207626,0.30880016],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9973937,0.00007944859,0.00077269645,0.00057509466,0.00091002585,0.00026898648],"domain_scores_gemma":[0.996927,0.0002834146,0.0007689157,0.0017601933,0.00013068088,0.00012979184],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00046393045,0.0004647003,0.0005360385,0.0003817069,0.0005729383,0.0016951499,0.0026959707,0.00022237728,0.0010888102],"category_scores_gemma":[0.000084143445,0.00041062568,0.000109204244,0.00017432717,0.00009931281,0.004762455,0.0013750759,0.00037787136,0.000121408906],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009670091,0.000045859673,0.000007925208,0.0011781795,0.00032121313,0.000008190592,0.001679314,0.00007148272,0.000009876757,0.93443596,0.016040815,0.046104494],"study_design_scores_gemma":[0.00025512165,0.000094712275,0.000018595541,0.00032084243,0.00007842926,0.000008039665,0.000097026656,0.0068373005,0.0000728138,0.0023600615,0.9893493,0.0005077398],"about_ca_topic_score_codex":0.000027402415,"about_ca_topic_score_gemma":0.00003706744,"teacher_disagreement_score":0.9733085,"about_ca_system_score_codex":0.000076216704,"about_ca_system_score_gemma":0.00012901281,"threshold_uncertainty_score":0.99983454},"labels":[],"label_agreement":null},{"id":"W4315697839","doi":"10.1007/978-3-030-94452-0_8","title":"Lewis Carroll’s Almost Diagrammatic Logic Notation","year":2022,"lang":"en","type":"book-chapter","venue":"Studies in universal logic","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bishop's University","funders":"","keywords":"Diagrammatic reasoning; Notation; Symbol (formal); Computer science; Object (grammar); Proposition; Mathematics; Epistemology; Programming language; Artificial intelligence; Arithmetic; Philosophy","score_opus":0.09019739851246239,"score_gpt":0.32589037987366415,"score_spread":0.23569298136120176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4315697839","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000018078072,0.0036480986,0.031922348,0.0016494985,0.0020141143,0.0005775936,0.00009680213,0.00034835856,0.9597251],"genre_scores_gemma":[0.06400227,0.019880947,0.010187909,0.005758082,0.00044586515,0.00005042271,0.00086108915,0.00015014372,0.8986633],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99830055,0.000068445304,0.0003680176,0.00056064996,0.00043423788,0.0002681078],"domain_scores_gemma":[0.99879396,0.00020966213,0.00027934622,0.00052984507,0.00013183393,0.000055367025],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002494807,0.00032028588,0.00048225353,0.00039552976,0.00022518504,0.000053718348,0.0009468056,0.00011558668,0.00028251694],"category_scores_gemma":[0.00011454362,0.00030649322,0.00011968098,0.00025513917,0.00021721778,0.00021282544,0.0011593049,0.00033875124,0.0001121541],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000032648306,0.000019987838,0.000018914328,0.0000564358,0.000088126006,0.00027941572,0.0011537716,0.0005060587,5.708157e-7,0.9925106,0.0034836943,0.0018791193],"study_design_scores_gemma":[0.0010371923,0.00045572902,0.000049532893,0.0001884342,0.00015169253,0.000025193893,0.002628036,0.012908445,0.0000025902395,0.47403133,0.50728285,0.0012389601],"about_ca_topic_score_codex":0.0000216127,"about_ca_topic_score_gemma":0.00009567068,"teacher_disagreement_score":0.51847935,"about_ca_system_score_codex":0.00048567014,"about_ca_system_score_gemma":0.000090765905,"threshold_uncertainty_score":0.9999387},"labels":[],"label_agreement":null},{"id":"W4317393977","doi":"10.1007/978-3-031-22203-0","title":"Graph Drawing and Network Visualization","year":2023,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Ioannina; National Technical University of Athens; Università degli Studi di Perugia; Julius-Maximilians-Universität Würzburg; Universität Zürich; National and Kapodistrian University of Athens; Ben-Gurion University of the Negev; Brown University; University of California, San Diego; Universität Passau; University of Crete; University of Aizu; University of Waterloo; Université de Montpellier; Universität Trier; Eidgenössische Technische Hochschule Zürich; Technische Universität Wien; Christian-Albrechts-Universität zu Kiel; Universität Konstanz; Univerzita Karlova v Praze; Centre National de la Recherche Scientifique; Università degli Studi Roma Tre; Universität zu Köln; Monash University; Universität Osnabrück","keywords":"Graph drawing; Visualization; Computer science; Graph; Theoretical computer science; Artificial intelligence","score_opus":0.018498061630371487,"score_gpt":0.2911656766106998,"score_spread":0.2726676149803283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317393977","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000108345785,0.00023290286,0.9967591,0.00025652978,0.0016585068,0.00017829474,0.000003871469,0.0003323566,0.00056757324],"genre_scores_gemma":[0.028473541,0.0016240742,0.92793274,0.019406987,0.006125108,0.00004271566,0.000443953,0.00033018834,0.01562068],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99705803,0.000060530536,0.00040940035,0.0011559651,0.000751105,0.0005649933],"domain_scores_gemma":[0.99830246,0.00037037488,0.0002078417,0.0008087626,0.00015885163,0.00015168164],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001011695,0.0003285531,0.00037041286,0.00078592426,0.00033337987,0.0011301629,0.0018748731,0.00020609071,0.000004109623],"category_scores_gemma":[0.00014220022,0.00031708373,0.000058522248,0.003004988,0.0003906627,0.0007056977,0.0015261653,0.00032758072,0.000034433677],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000031465706,0.000050761417,0.00078705314,0.00020755416,0.000032944223,0.00013683645,0.0019137734,0.20724912,0.000028817738,0.19123466,0.0065708198,0.5917845],"study_design_scores_gemma":[0.00011780155,0.000044975197,0.00017408431,0.00030094484,0.000005824332,0.000013476762,1.2765113e-7,0.83361524,0.00003385224,0.16279292,0.0025339862,0.00036676947],"about_ca_topic_score_codex":0.000006243573,"about_ca_topic_score_gemma":0.000044400946,"teacher_disagreement_score":0.62636614,"about_ca_system_score_codex":0.00013363369,"about_ca_system_score_gemma":0.00056150835,"threshold_uncertainty_score":0.9999281},"labels":[],"label_agreement":null},{"id":"W4319987621","doi":"10.1109/tvcg.2023.3238989","title":"Path Tracing in 2D, 3D, and Physicalized Networks","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada; Microsoft Research","keywords":"Headset; Computer science; Enhanced Data Rates for GSM Evolution; Tracing; Virtual reality; Human–computer interaction; Path (computing); Augmented reality; Routing (electronic design automation); Computer graphics (images); Artificial intelligence; Computer network","score_opus":0.02038016393863623,"score_gpt":0.28594689644412496,"score_spread":0.26556673250548873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319987621","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008476089,0.00002464625,0.9905863,0.000087554276,0.00031578765,0.0001349771,0.0000067576634,0.00034499035,0.000022939563],"genre_scores_gemma":[0.99622583,0.0010235374,0.0008411891,0.0017419065,0.00004706021,0.000014541058,0.000024817804,0.000020069152,0.000061033606],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986942,0.000120633755,0.00029469415,0.00042798568,0.00022370706,0.00023879924],"domain_scores_gemma":[0.9994023,0.000114546325,0.00006503497,0.0002435105,0.000058164656,0.000116487354],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024338719,0.00017796368,0.00020250307,0.000539305,0.00022023807,0.000278554,0.00019132323,0.000093540824,0.000004063216],"category_scores_gemma":[0.0000025786703,0.00018135228,0.00004709986,0.0020674558,0.000064821215,0.00042855524,0.00001023071,0.00015871537,0.000007174913],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019981297,0.00040846795,0.0006236284,0.00010406193,0.00005554753,0.00002644132,0.0023012192,0.023722198,0.00001734693,0.9173315,0.0009470294,0.05444256],"study_design_scores_gemma":[0.0006177512,0.00007860012,0.0013556818,0.00006559032,0.000010171962,0.0000044053563,0.000029632467,0.9963818,0.000051125073,0.00077741686,0.00042397567,0.00020383473],"about_ca_topic_score_codex":0.000012121026,"about_ca_topic_score_gemma":0.00002475367,"teacher_disagreement_score":0.9897451,"about_ca_system_score_codex":0.000011817914,"about_ca_system_score_gemma":0.000019371157,"threshold_uncertainty_score":0.7395331},"labels":[],"label_agreement":null},{"id":"W4320920241","doi":"10.21105/joss.05073","title":"GeoHexViz: A Python package for the visualizinghexagonally binned geospatial data","year":2023,"lang":"en","type":"article","venue":"The Journal of Open Source Software","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Geospatial analysis; Python (programming language); Visualization; Computer science; R package; Data science; Data mining; Cartography; Geography; Computational science; Programming language","score_opus":0.10192835364787518,"score_gpt":0.38262598458862906,"score_spread":0.2806976309407539,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4320920241","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002308118,0.00016466842,0.99032265,0.0062048854,0.00041764104,0.00034594152,0.00011535822,0.00009252878,0.000028205637],"genre_scores_gemma":[0.6866152,0.0039651864,0.2196073,0.04324597,0.007377917,0.00009434117,0.00175245,0.0006963733,0.03664521],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9981557,0.00022949142,0.00051498093,0.00021438264,0.00057724956,0.00030820345],"domain_scores_gemma":[0.99595803,0.0014881853,0.00057999155,0.0015501658,0.00032120282,0.00010241867],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0045563453,0.0001523917,0.00025584592,0.00011265127,0.00060432754,0.0010392935,0.011323848,0.000044502285,0.00003432853],"category_scores_gemma":[0.00126947,0.000081369864,0.000097546086,0.00087688153,0.00007941514,0.0011966743,0.003827398,0.00021957434,0.00006615059],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023891445,0.0001910153,0.0011429464,0.00006535786,0.00049527915,0.000040724186,0.008439224,0.0032702177,0.0002950702,0.007036899,0.8280752,0.1507092],"study_design_scores_gemma":[0.0018744587,0.0003662571,0.0025221533,0.00016212928,0.00023398166,0.00018270592,0.0019430415,0.2265113,0.0002734501,0.0039104116,0.76163405,0.0003860355],"about_ca_topic_score_codex":0.000056006495,"about_ca_topic_score_gemma":0.000042728094,"teacher_disagreement_score":0.77071536,"about_ca_system_score_codex":0.000022297452,"about_ca_system_score_gemma":0.00024848038,"threshold_uncertainty_score":0.99999774},"labels":[],"label_agreement":null},{"id":"W4321175654","doi":"10.1145/3581641.3584099","title":"SeeChart: Enabling Accessible Visualizations Through Interactive Natural Language Interface For People with Visual Impairments","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Reading (process); Visualization; World Wide Web; Publication; Data visualization; Chart; Interface (matter); Human–computer interaction; User interface; Newspaper; Multimedia; Artificial intelligence","score_opus":0.03203773097157847,"score_gpt":0.3949505785432047,"score_spread":0.36291284757162623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321175654","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004676491,0.00006580483,0.99107397,0.00053088786,0.0012115265,0.00080992974,0.00013756157,0.00093728444,0.00055652414],"genre_scores_gemma":[0.9169771,0.00013880963,0.06804764,0.0009402821,0.0002756809,0.00031401287,0.002067787,0.00012763207,0.011111059],"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975718,0.00007862621,0.0004714211,0.0009917925,0.00043405083,0.00045230033],"domain_scores_gemma":[0.9981704,0.00022060763,0.0003793777,0.00073354866,0.0003936348,0.00010246371],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0002458501,0.00041290064,0.00046489062,0.00031179358,0.00022704928,0.0013467056,0.0015276838,0.00015717761,0.00005878604],"category_scores_gemma":[0.00014203365,0.00033742256,0.00014666565,0.00087678223,0.000034662306,0.0014299706,0.0026936512,0.00039467312,0.00008637576],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010157527,0.008193776,0.0113536455,0.010419032,0.008839579,0.0004232175,0.37222576,0.0959289,0.005830226,0.17054197,0.26396677,0.051261347],"study_design_scores_gemma":[0.000781535,0.00018598918,0.00017075059,0.0004561645,0.00006800634,0.0000107667465,0.0035110973,0.9847676,0.0060189236,0.0009309006,0.0023863534,0.00071188924],"about_ca_topic_score_codex":0.0002360646,"about_ca_topic_score_gemma":0.0004788657,"teacher_disagreement_score":0.9230263,"about_ca_system_score_codex":0.00013996435,"about_ca_system_score_gemma":0.00028194961,"threshold_uncertainty_score":0.9999078},"labels":[],"label_agreement":null},{"id":"W4321325529","doi":"10.2316/j.2023.206-0595","title":"METHOD BASED ON WORK–TIME NUMBERS FOR ATTRACTIVE SEGMENTS, 148-154.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Work (physics); Physics; Thermodynamics","score_opus":0.026246799411897778,"score_gpt":0.35304699953079016,"score_spread":0.3268002001188924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321325529","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00094379275,0.0000045637394,0.99336153,0.0048845205,0.0005016398,0.00006171358,0.000013560942,0.000042066076,0.00018660123],"genre_scores_gemma":[0.23820113,0.00006185085,0.75811785,0.0019643533,0.0004115858,0.0000055758405,0.00015392248,0.000025001655,0.0010587337],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990466,0.000043023145,0.00028698923,0.00011185995,0.0004227849,0.000088709065],"domain_scores_gemma":[0.9988563,0.00029546482,0.00032243688,0.00008073053,0.00039045862,0.000054621178],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005442163,0.00007415616,0.00010985227,0.00030149726,0.000059555747,0.00023237868,0.00033400505,0.000033845732,0.000010602116],"category_scores_gemma":[0.0001312238,0.00006599191,0.00006728302,0.00024135098,0.000011178206,0.00041844053,0.0000440702,0.00006277936,0.000020741812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006700132,0.00021264631,0.00078101014,0.000019134239,0.00021874152,0.000033018572,0.00045526144,0.80382127,0.00048140445,0.056798406,0.017660229,0.119451895],"study_design_scores_gemma":[0.00053517375,0.000073823045,0.0022756835,0.00007398618,0.000012566451,0.000010005152,0.000018739509,0.9921478,0.00028905098,0.0021402477,0.002351288,0.000071657174],"about_ca_topic_score_codex":9.470308e-7,"about_ca_topic_score_gemma":2.1057176e-7,"teacher_disagreement_score":0.23725733,"about_ca_system_score_codex":0.000053204036,"about_ca_system_score_gemma":0.00005512862,"threshold_uncertainty_score":0.2691072},"labels":[],"label_agreement":null},{"id":"W4321436298","doi":"10.2307/jj.362382.8","title":"Controversing Datafication through Media Architectures","year":2023,"lang":"en","type":"book-chapter","venue":"Amsterdam University Press eBooks","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Canadian Institute of Steel Construction","keywords":"Computer science","score_opus":0.05333013747018862,"score_gpt":0.2560197227915614,"score_spread":0.20268958532137277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321436298","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000022143931,0.000024953346,0.18020335,0.00010781965,0.0003963586,0.00019329322,0.0002850827,0.00048136097,0.81830555],"genre_scores_gemma":[0.00064523367,0.00010760698,0.002715055,0.00040310048,0.00013987055,3.0149613e-7,0.00041244496,0.00004154836,0.99553484],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985259,0.000043813543,0.00020184692,0.0005939592,0.0003995786,0.00023491037],"domain_scores_gemma":[0.9983257,0.0001996552,0.00026440385,0.0010011361,0.000104995364,0.00010411599],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00010172387,0.0002719613,0.0003027123,0.0001919836,0.00019327276,0.00018238349,0.0015510916,0.0002046625,0.000009102597],"category_scores_gemma":[0.000023343304,0.00030931397,0.00012695233,0.00002574489,0.0001450012,0.00025523547,0.0010380086,0.00027499895,0.000067518864],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000867806,0.0000068032086,3.7011358e-7,0.000028202523,0.00008340104,0.00006992688,0.0008277766,0.00001942363,0.000005909614,0.9860197,0.00772748,0.0052023334],"study_design_scores_gemma":[0.0005336201,0.00002450272,0.0000055638375,0.00014548536,0.00011334698,0.000005946873,0.00004275664,0.003155082,0.00005950089,0.008367873,0.9871553,0.00039103115],"about_ca_topic_score_codex":0.00007654313,"about_ca_topic_score_gemma":0.00003093448,"teacher_disagreement_score":0.9794278,"about_ca_system_score_codex":0.00007004696,"about_ca_system_score_gemma":0.000084657746,"threshold_uncertainty_score":0.9999359},"labels":[],"label_agreement":null},{"id":"W4323363529","doi":"10.1093/iwc/iwad019","title":"Evaluating Visual Analytics for Relevant Information Retrieval in Document Collections","year":2023,"lang":"en","type":"article","venue":"Interacting with Computers","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Computer science; Information retrieval; Visual analytics; Recall; Analytics; Precision and recall; Perspective (graphical); Process (computing); Data science; World Wide Web; Visualization; Data mining; Artificial intelligence; Psychology","score_opus":0.04359985564566519,"score_gpt":0.3863054692844198,"score_spread":0.34270561363875457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323363529","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025374234,0.000001662009,0.9714864,0.0009038052,0.0013896155,0.0003333919,0.0000053246226,0.00030170893,0.00020385705],"genre_scores_gemma":[0.8102718,0.000011917892,0.18746153,0.0010908188,0.0001473796,0.000038303115,0.00021265885,0.000025929234,0.0007396381],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986128,0.000060398303,0.0004523102,0.00024156412,0.0003510037,0.00028189356],"domain_scores_gemma":[0.99804395,0.0011887759,0.00023690301,0.00022928038,0.00023720019,0.000063883526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00078953576,0.00012801203,0.00015936569,0.00068604766,0.00021505918,0.0006903123,0.00036166285,0.000034511493,0.000003965561],"category_scores_gemma":[0.0008600506,0.00011828386,0.000047168465,0.0024824343,0.000016516875,0.0014913386,0.00018287514,0.00013354408,0.000036590794],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049859483,0.00031828982,0.0028498366,0.00034893004,0.0003319025,0.000056542398,0.016556447,0.74679446,0.0005595428,0.024646707,0.07892136,0.12811738],"study_design_scores_gemma":[0.0007367119,0.0003023895,0.00026877644,0.0002395124,0.0000085751,0.00001130364,0.000336317,0.992893,0.00023692238,0.00024400385,0.0045656315,0.00015686254],"about_ca_topic_score_codex":0.00002435319,"about_ca_topic_score_gemma":0.000019554715,"teacher_disagreement_score":0.78489757,"about_ca_system_score_codex":0.00016706219,"about_ca_system_score_gemma":0.0001284581,"threshold_uncertainty_score":0.66566974},"labels":[],"label_agreement":null},{"id":"W4360584052","doi":"10.1109/mlui52768.2018.10075561","title":"Providing Contextual Assistance in Response to Frustration in Visual Analytics Tasks","year":2018,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Frustration; Computer science; Visualization; Visual analytics; Eye tracking; Human–computer interaction; Skin conductance; Data visualization; Task (project management); Artificial intelligence; Machine learning; Psychology; Social psychology; Engineering","score_opus":0.037368769015710894,"score_gpt":0.35112116235304547,"score_spread":0.31375239333733457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4360584052","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28784692,0.0000035135931,0.708295,0.0018046008,0.000103205224,0.00015053077,0.0000028641819,0.00006652175,0.0017268233],"genre_scores_gemma":[0.98875254,8.8528196e-7,0.008495524,0.0013590239,0.000035842244,0.000004324516,0.0000042264496,0.0000046401465,0.001343017],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882334,0.00012598521,0.0003095003,0.00030862042,0.00021851277,0.00021402925],"domain_scores_gemma":[0.9994214,0.00009202037,0.000050077135,0.00025931638,0.00009479807,0.00008234118],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008437296,0.0000890915,0.00011966815,0.00035094432,0.000042013195,0.0002503378,0.00038289826,0.00004647735,0.00003193434],"category_scores_gemma":[0.00040101534,0.000086872285,0.000016199228,0.0013156672,0.000031822252,0.0005290986,0.000119434706,0.00007059774,0.00009462225],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009899049,0.0011256703,0.10614154,0.000038656857,0.00002687357,0.00015897186,0.009261996,0.0008280654,0.03256082,0.784524,0.024773486,0.039569963],"study_design_scores_gemma":[0.00079236994,0.00039576372,0.038353648,0.000065819986,0.0000021524002,0.0000026195894,0.0004814608,0.93960047,0.0044032973,0.00060376566,0.014992,0.0003066179],"about_ca_topic_score_codex":0.00006504175,"about_ca_topic_score_gemma":0.0021967199,"teacher_disagreement_score":0.93877244,"about_ca_system_score_codex":0.00009977709,"about_ca_system_score_gemma":0.0001350581,"threshold_uncertainty_score":0.3542549},"labels":[],"label_agreement":null},{"id":"W4361854718","doi":"10.2196/44644","title":"A Visual Analytic Tool (VIADS) to Assist the Hypothesis Generation Process in Clinical Research: Mixed Methods Usability Study","year":2023,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"U.S. National Library of Medicine; National Institute of General Medical Sciences","keywords":"Usability; Computer science; Think aloud protocol; Session (web analytics); Visualization; Protocol (science); Data visualization; Data collection; Information retrieval; Human–computer interaction; Data mining; Medicine; World Wide Web; Statistics","score_opus":0.43313348453808376,"score_gpt":0.585486880734297,"score_spread":0.15235339619621324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4361854718","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98458856,0.0000013782637,0.013705828,0.00043977727,0.00018776617,0.00086241076,0.0000056942226,0.00015217336,0.00005639473],"genre_scores_gemma":[0.9986119,9.4140273e-7,0.000649084,0.00014726353,0.00011132642,0.00012586245,0.000018910998,0.000014526813,0.00032016696],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9944584,0.0026795492,0.0007782595,0.00076047477,0.00089659274,0.00042671975],"domain_scores_gemma":[0.99724716,0.0012936622,0.00011170285,0.0009492657,0.00024943636,0.0001487817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0103768185,0.00017014117,0.0003065245,0.0005836462,0.0004420734,0.00064436765,0.0013974998,0.00008164053,0.00004069534],"category_scores_gemma":[0.0027695047,0.00011998922,0.00010067866,0.004128333,0.00012238247,0.000399521,0.0005732946,0.00034684653,0.00012462864],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021190623,0.0036053385,0.8936509,0.0000615694,0.000120450975,0.000026820528,0.020990713,0.0007417716,0.0008248046,0.0064178826,0.014175999,0.059362575],"study_design_scores_gemma":[0.0002619078,0.0003155492,0.9231364,0.000009195033,0.000008022359,1.891035e-7,0.0022528635,0.07193905,0.0003255213,0.0008086382,0.0007535937,0.00018908262],"about_ca_topic_score_codex":0.000045374978,"about_ca_topic_score_gemma":0.0004885744,"teacher_disagreement_score":0.07119728,"about_ca_system_score_codex":0.00011594637,"about_ca_system_score_gemma":0.00013592794,"threshold_uncertainty_score":0.6213652},"labels":[],"label_agreement":null},{"id":"W4362700320","doi":"10.31219/osf.io/d7pbh","title":"The Rational Agent Benchmark for Data Visualization","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Science North","funders":"","keywords":"Visualization; Computer science; Benchmark (surveying); Bounding overwatch; Information visualization; Task (project management); Data visualization; Rational agent; Creative visualization; Rational design; Human–computer interaction; Data mining; Machine learning; Artificial intelligence; Engineering; Systems engineering","score_opus":0.17094996800838996,"score_gpt":0.408702341540989,"score_spread":0.23775237353259904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362700320","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000003165973,0.000047119272,0.9926543,0.0039744955,0.0017744987,0.00039273375,0.00029232414,0.00026245034,0.00059891515],"genre_scores_gemma":[0.015037434,0.005408312,0.5121246,0.013308551,0.0046566026,0.0010609818,0.25397408,0.0003023029,0.19412713],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983776,0.000059001963,0.00035845744,0.0006274141,0.00039594228,0.00018156185],"domain_scores_gemma":[0.99715966,0.00033513052,0.0001831801,0.002045362,0.000220926,0.000055767818],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00096713693,0.0001419445,0.00012099589,0.0000746832,0.00033279677,0.0012047397,0.003646828,0.00009005471,0.000021511973],"category_scores_gemma":[0.00042266794,0.00010112841,0.00005613836,0.00024437017,0.000030965446,0.00029933616,0.0050399136,0.000091406975,0.000076859935],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.574288e-7,0.00001598617,0.000021996133,0.000023600061,0.000028286757,3.2853936e-7,0.000036140784,0.00058102066,0.0000014975118,0.62173295,0.37425905,0.0032982677],"study_design_scores_gemma":[0.00006356623,0.000006293137,0.00007304649,0.000013697104,0.000009079155,2.6897618e-7,0.000010581641,0.74078155,0.000015025826,0.023327246,0.23559281,0.00010684051],"about_ca_topic_score_codex":0.000018651579,"about_ca_topic_score_gemma":0.00008550179,"teacher_disagreement_score":0.7402005,"about_ca_system_score_codex":0.00003171358,"about_ca_system_score_gemma":0.00028946166,"threshold_uncertainty_score":0.9998321},"labels":[],"label_agreement":null},{"id":"W4366204133","doi":"10.1101/2023.04.17.537196","title":"mEMbrain: an interactive deep learning MATLAB tool for connectomic segmentation on commodity desktops","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; University of Toronto; Mount Sinai Hospital","funders":"National Institutes of Health","keywords":"Computer science; MATLAB; Segmentation; Commodity; Deep learning; Artificial intelligence; Human–computer interaction; Business; Operating system","score_opus":0.0349117459481966,"score_gpt":0.29164203422395346,"score_spread":0.25673028827575683,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366204133","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18702774,0.000024671388,0.8082831,0.00033164374,0.0016555703,0.0009875298,0.0003115149,0.0013725832,0.000005653792],"genre_scores_gemma":[0.9727084,0.000053743923,0.025842275,0.00068613695,0.00029799697,0.00026541718,0.000017425167,0.00011174987,0.000016864413],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970702,0.0003235945,0.0005402567,0.0012008835,0.00040791475,0.0004571843],"domain_scores_gemma":[0.9970325,0.0003739704,0.0005679069,0.0012885073,0.0005400993,0.00019700722],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0010109106,0.00046039288,0.000467734,0.00037476045,0.0003259018,0.0010519527,0.00130855,0.00028702168,0.00001850928],"category_scores_gemma":[0.00060731615,0.00051421026,0.00014364143,0.00052910595,0.00005632118,0.00074116065,0.0007506333,0.00062290975,0.00013462092],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006489044,0.003426314,0.01454278,0.004552625,0.002391389,0.0003013432,0.0017725845,0.059010204,0.57771254,0.32478026,0.010081547,0.00077953725],"study_design_scores_gemma":[0.0014812337,0.000360556,0.01669088,0.0005022643,0.00011108001,2.6386337e-8,0.00003774188,0.82859474,0.14601521,0.00009102969,0.004556192,0.0015590134],"about_ca_topic_score_codex":0.000022664175,"about_ca_topic_score_gemma":0.0000071780396,"teacher_disagreement_score":0.78568065,"about_ca_system_score_codex":0.00037315546,"about_ca_system_score_gemma":0.0002764068,"threshold_uncertainty_score":0.99998504},"labels":[],"label_agreement":null},{"id":"W4366547405","doi":"10.1145/3544548.3580726","title":"multiverse: Multiplexing Alternative Data Analyses in R Notebooks","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Science Foundation","keywords":"Computer science; Flexibility (engineering); Workflow; Learnability; Pruning; Syntax; Artificial intelligence; Database; Mathematics","score_opus":0.37207431827629606,"score_gpt":0.47345238395306516,"score_spread":0.1013780656767691,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366547405","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023403545,0.0000073366036,0.9911876,0.00034751886,0.00015731268,0.00008071584,0.00005753909,0.0003471918,0.005474471],"genre_scores_gemma":[0.952024,0.000043087988,0.042950958,0.0007766517,0.00005630752,0.0000031991833,0.00041946006,0.0000104901355,0.0037158495],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99908304,0.000043227923,0.00015646298,0.00035831484,0.00019211308,0.00016686482],"domain_scores_gemma":[0.9990462,0.00010897067,0.000040546816,0.0007240357,0.000034448105,0.00004581814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023068469,0.00007219504,0.000095463445,0.00028363406,0.00004429342,0.000121367586,0.0013969968,0.000019405403,0.000029350058],"category_scores_gemma":[0.00016425936,0.00006348811,0.000017162845,0.0008782811,0.000022584429,0.00072749925,0.0012130495,0.000055289172,0.0003360652],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021219537,0.0006200302,0.022277666,0.00008246911,0.00032716547,0.0010516036,0.014851482,0.06816392,0.013430339,0.59997666,0.08233858,0.1968589],"study_design_scores_gemma":[0.00027315022,0.000004726134,0.0016002958,0.000009398104,0.0000015096948,4.6161367e-7,0.00021815041,0.9920064,0.000874654,0.00034726725,0.004575501,0.00008845915],"about_ca_topic_score_codex":0.00031662683,"about_ca_topic_score_gemma":0.00022642822,"teacher_disagreement_score":0.94968367,"about_ca_system_score_codex":0.000016966287,"about_ca_system_score_gemma":0.000027633809,"threshold_uncertainty_score":0.431955},"labels":[],"label_agreement":null},{"id":"W4366548996","doi":"10.1145/3544548.3581091","title":"Charagraph: Interactive Generation of Charts for Realtime Annotation of Data-Rich Paragraphs","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Computer science; Merge (version control); Visualization; Information retrieval; Annotation; Filter (signal processing); sort; Data visualization; Data exploration; Natural language processing; Artificial intelligence","score_opus":0.1594003298816391,"score_gpt":0.39371286331399136,"score_spread":0.23431253343235225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366548996","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013903718,0.000010101303,0.9846788,0.0003455427,0.00017281366,0.00020705826,0.00021699668,0.000084937434,0.00038000115],"genre_scores_gemma":[0.9654382,0.00010444344,0.029718157,0.00021006734,0.000064554275,0.000016617847,0.0037867157,0.000009216188,0.00065204385],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991571,0.00003053166,0.0003129408,0.00023791766,0.00016583345,0.00009567601],"domain_scores_gemma":[0.9989065,0.00008695798,0.00020848644,0.0004932588,0.0002774946,0.000027327076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036471948,0.00006143647,0.00012750614,0.00025907718,0.000034724228,0.000030070327,0.0004823648,0.000025166406,0.000012373515],"category_scores_gemma":[0.00008864373,0.000054642027,0.000027177368,0.0010138894,0.000020072743,0.00086264627,0.00013844884,0.00002043255,0.000010826086],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003128531,0.00036126474,0.0012230291,0.00021048478,0.000190094,0.0000021857618,0.0035482992,0.0005651753,0.047404952,0.714556,0.15125646,0.080650784],"study_design_scores_gemma":[0.0002116779,0.000071106355,0.00085296965,0.000011373749,0.000008721826,5.1194e-7,0.00006917218,0.96859026,0.027611502,0.0008528309,0.0016489815,0.00007091004],"about_ca_topic_score_codex":0.000017723334,"about_ca_topic_score_gemma":0.0000121381,"teacher_disagreement_score":0.9680251,"about_ca_system_score_codex":0.0000042508614,"about_ca_system_score_gemma":0.000037029826,"threshold_uncertainty_score":0.22282372},"labels":[],"label_agreement":null},{"id":"W4366549398","doi":"10.1145/3544548.3581113","title":"ChartDetective: Easy and Accurate Interactive Data Extraction from Complex Vector Charts","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo; Agence Nationale de la Recherche","keywords":"Computer science; Raster data; Data mining; Raster graphics; Data extraction; Interface (matter); Artificial intelligence; Pattern recognition (psychology)","score_opus":0.12904133024302253,"score_gpt":0.3909459923106922,"score_spread":0.2619046620676697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366549398","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013344446,0.000019420788,0.9799753,0.0021816946,0.0006413686,0.00017808477,0.0004234088,0.00079618755,0.002440113],"genre_scores_gemma":[0.99346346,0.00008479081,0.00345569,0.0006981835,0.00012608788,0.0000046875957,0.00091836625,0.000010571129,0.0012381478],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99904776,0.00005266257,0.00014230306,0.00045265016,0.00016046404,0.0001441513],"domain_scores_gemma":[0.9989803,0.00015375664,0.00007280016,0.00066144037,0.000052859057,0.00007883165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015342014,0.000095569114,0.00010800537,0.00010225465,0.00010334022,0.00032218653,0.0006254684,0.0000281059,0.00019689443],"category_scores_gemma":[0.00010146597,0.0000859999,0.000013402373,0.00041722372,0.000025766365,0.0018043369,0.0008079615,0.000076903176,0.00047975144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000101962345,0.00054424367,0.002847885,0.00007377206,0.0005612853,0.00020081131,0.0064418972,0.00012737005,0.089961514,0.14218152,0.33166096,0.4252968],"study_design_scores_gemma":[0.00020294898,0.000020901683,0.033562448,0.000010754089,0.000005933731,0.0000036375147,0.00014229484,0.92345566,0.0011727788,0.0006256418,0.04065892,0.00013805597],"about_ca_topic_score_codex":0.00010392793,"about_ca_topic_score_gemma":0.000044110675,"teacher_disagreement_score":0.98011905,"about_ca_system_score_codex":0.000014553985,"about_ca_system_score_gemma":0.000021305845,"threshold_uncertainty_score":0.61663944},"labels":[],"label_agreement":null},{"id":"W4366549844","doi":"10.1145/3544548.3581271","title":"Dirty Data in the Newsroom: Comparing Data Preparation in Journalism and Data Science","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Workflow; Computer science; Data science; Context (archaeology); Big data; Thematic analysis; Data modeling; Journalism; Information retrieval; Data mining; Qualitative research; Database; Sociology","score_opus":0.26724470972598124,"score_gpt":0.4532393490338437,"score_spread":0.18599463930786247,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366549844","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.076561816,0.00026299685,0.892414,0.017938608,0.0006949437,0.0006868335,0.00046862086,0.00035863416,0.010613583],"genre_scores_gemma":[0.98912466,0.00029827905,0.00736207,0.00085666525,0.000050890478,0.0000010693368,0.0021427192,0.000004340849,0.00015931138],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983006,0.000088232526,0.0002607108,0.0007065995,0.000439796,0.00020407182],"domain_scores_gemma":[0.99465495,0.00011240964,0.00006115321,0.005101187,0.000023065477,0.000047239035],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.005052545,0.00006807409,0.000096344076,0.00023302449,0.00014354924,0.0011100209,0.0122253345,0.000015717067,0.0000043779078],"category_scores_gemma":[0.00046295073,0.000047124067,0.0000025278011,0.0023507122,0.00009674258,0.007395223,0.012192296,0.00010612193,0.000023731396],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014051187,0.0004123193,0.15249777,0.00007395767,0.000020653537,0.00012466521,0.008159131,0.0017060183,0.00054434885,0.38840365,0.3993128,0.04873063],"study_design_scores_gemma":[0.00014781441,0.0000046139535,0.02349321,0.000016286087,0.0000018559477,0.000008015878,0.00019571216,0.9607756,0.0000056126305,0.00041916277,0.014865626,0.00006649817],"about_ca_topic_score_codex":0.00032003017,"about_ca_topic_score_gemma":0.0021292137,"teacher_disagreement_score":0.95906955,"about_ca_system_score_codex":0.000011522682,"about_ca_system_score_gemma":0.00015854256,"threshold_uncertainty_score":0.9999269},"labels":[],"label_agreement":null},{"id":"W4366550073","doi":"10.1145/3544548.3580753","title":"Slide4N: Creating Presentation Slides from Computational Notebooks with Human-AI Collaboration","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Natural Science Foundation of China","keywords":"Computer science; Presentation (obstetrics); Personalization; Operationalization; Human–computer interaction; Key (lock); Code (set theory); Multimedia; World Wide Web; Programming language","score_opus":0.02978832905813799,"score_gpt":0.34389372082358916,"score_spread":0.31410539176545116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366550073","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023942549,0.000003010319,0.9684234,0.001224083,0.00007675747,0.00013803942,0.000024975128,0.0005507536,0.005616418],"genre_scores_gemma":[0.93339986,0.0000020400653,0.06059118,0.0012896829,0.00010192066,0.000015681399,0.0012247185,0.000014023533,0.0033608843],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99888515,0.00005257589,0.00022323085,0.00029438033,0.0004041438,0.00014049295],"domain_scores_gemma":[0.99921423,0.00014503511,0.00009666417,0.00022480781,0.0002598383,0.000059430058],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013539616,0.000099332065,0.00010115238,0.00015013535,0.00026292924,0.00061567227,0.0002846548,0.000032644308,0.000069655594],"category_scores_gemma":[0.00004022999,0.000086110085,0.000018445831,0.000867136,0.000027657406,0.0008684797,0.00010244434,0.0000511247,0.00017015073],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000105903655,0.000086122236,0.010712341,0.00002215222,0.00008083926,0.000027467584,0.004426044,0.100008056,0.0021485626,0.84086365,0.03672422,0.0048899297],"study_design_scores_gemma":[0.00044310442,0.000051136685,0.008353046,0.000022251652,0.000008539656,0.000001103377,0.00047535388,0.97403324,0.0016363359,0.013437886,0.0013730993,0.00016488093],"about_ca_topic_score_codex":0.00013652892,"about_ca_topic_score_gemma":0.00015715085,"teacher_disagreement_score":0.9094573,"about_ca_system_score_codex":0.000025437688,"about_ca_system_score_gemma":0.00008918957,"threshold_uncertainty_score":0.59369415},"labels":[],"label_agreement":null},{"id":"W4366550150","doi":"10.1145/3544548.3581119","title":"Showing Flow: Comparing Usability of Chord and Sankey Diagrams","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Chord (peer-to-peer); Usability; Computer science; Visualization; Interpretability; Engineering drawing; Human–computer interaction; Information retrieval; Data mining; Engineering; Artificial intelligence; Database","score_opus":0.06609989601488664,"score_gpt":0.3182332614233472,"score_spread":0.25213336540846054,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366550150","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2857431,0.000016517513,0.7089485,0.00036102018,0.00013489883,0.000063384905,0.0000027088304,0.00027317,0.0044567296],"genre_scores_gemma":[0.9915292,0.000016954222,0.008103445,0.00010186288,0.000011513866,7.87763e-7,0.00000789424,0.0000022288266,0.00022608422],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994477,0.000020316002,0.00014326637,0.00016161145,0.00012385717,0.00010322361],"domain_scores_gemma":[0.99959195,0.00006194689,0.00002356452,0.00024817447,0.000027612861,0.00004678124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026453304,0.000045940622,0.00010147848,0.0000527336,0.0000411732,0.00007418003,0.0002466244,0.000015037798,0.000015055275],"category_scores_gemma":[0.00006529443,0.000039560993,0.000018083427,0.00046339876,0.000032482145,0.00023431951,0.0003017961,0.000028145452,0.00002063603],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000028069378,0.00013312914,0.5661713,0.00015241228,0.00003949828,0.0000060827883,0.0017991965,0.0023556629,0.0009993117,0.2878647,0.009509825,0.13096608],"study_design_scores_gemma":[0.00009160786,0.000009898292,0.037998673,0.000009198968,0.0000019115528,5.0879675e-7,0.00005152687,0.95942044,0.0005409035,0.0008390158,0.0009784916,0.000057850844],"about_ca_topic_score_codex":0.000030015026,"about_ca_topic_score_gemma":0.00002884899,"teacher_disagreement_score":0.95706475,"about_ca_system_score_codex":0.000005241541,"about_ca_system_score_gemma":0.00001034791,"threshold_uncertainty_score":0.16132505},"labels":[],"label_agreement":null},{"id":"W4366597532","doi":"10.1145/3544549.3583748","title":"Making with Data (and Beyond)","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Agence Nationale de la Recherche; Bpifrance","keywords":"Intersection (aeronautics); Computer science; Visualization; Data science; Representation (politics); Data visualization; External Data Representation; Human–computer interaction; Data mining; Engineering; Artificial intelligence","score_opus":0.10663436858109435,"score_gpt":0.3666246985949885,"score_spread":0.25999033001389416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366597532","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00031400291,0.000005749879,0.9820626,0.0015722521,0.00003172379,0.00001814985,0.0000067455076,0.00024090816,0.015747877],"genre_scores_gemma":[0.7728812,0.000090543384,0.2027896,0.008545683,0.00008121348,0.0000020393982,0.0003058772,0.000017162476,0.015286692],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996406,0.000005555715,0.0000401364,0.00015655564,0.00008867047,0.00006850329],"domain_scores_gemma":[0.9994774,0.00001598881,0.000010988646,0.00046395545,0.0000107521655,0.000020918556],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010316702,0.00002750484,0.000029950168,0.00004121647,0.000038151265,0.00014437105,0.0005160002,0.000006511945,0.000014160725],"category_scores_gemma":[0.00001110371,0.00001934927,0.00000199262,0.00036378854,0.000011703925,0.00036863284,0.0006538007,0.000015095939,0.000087087225],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.289224e-7,0.000009095251,0.002164733,0.000008056402,0.000009386939,0.000020657002,0.0002146273,0.000020780324,0.000016609389,0.8855156,0.07726065,0.034759283],"study_design_scores_gemma":[0.00007085805,0.0000096513795,0.0006829155,0.000004398335,0.0000016815936,0.0000049834853,0.00005969319,0.925748,0.000017822122,0.00092288514,0.07242336,0.000053782423],"about_ca_topic_score_codex":0.0000014865922,"about_ca_topic_score_gemma":0.0000087738445,"teacher_disagreement_score":0.9257272,"about_ca_system_score_codex":0.0000011823769,"about_ca_system_score_gemma":0.000012067847,"threshold_uncertainty_score":0.13921733},"labels":[],"label_agreement":null},{"id":"W4376612861","doi":"10.2196/44549","title":"Evaluation of the EsteR Toolkit for COVID-19 Decision Support: Sensitivity Analysis and Usability Study","year":2023,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Leibniz-Gemeinschaft; Bundesministerium für Bildung und Forschung","keywords":"Usability; Computer science; Test (biology); Stability (learning theory); Coronavirus disease 2019 (COVID-19); Decision support system; Machine learning; Artificial intelligence; Human–computer interaction; Medicine","score_opus":0.22117296513400767,"score_gpt":0.5383628778568699,"score_spread":0.31718991272286223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376612861","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6418074,0.0000021280923,0.35617915,0.00066369906,0.000044249457,0.0011200982,0.00007082352,0.00002741373,0.00008508551],"genre_scores_gemma":[0.99949765,0.0000030433443,0.00026764342,0.00005878608,0.0000078163,0.000081068385,0.00002321297,0.0000027429369,0.000058021968],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9956815,0.0016159466,0.0002863385,0.00027400441,0.0019260185,0.0002161449],"domain_scores_gemma":[0.9962727,0.00166503,0.00009385076,0.000632347,0.0012348162,0.000101285856],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.025391666,0.000068485155,0.00016592606,0.00046167694,0.0003431391,0.00016513218,0.00038868093,0.000031928677,0.000023388171],"category_scores_gemma":[0.003037587,0.000045451503,0.0000812992,0.0039159767,0.00013936452,0.000589,0.0007472152,0.00010227479,0.000013942084],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001725859,0.0025935683,0.34561267,0.00045403893,0.0012608335,0.000006822357,0.13168395,0.009965137,0.00036694098,0.018275829,0.032559916,0.45704773],"study_design_scores_gemma":[0.00048076097,0.00014361864,0.2828464,0.0000038624926,0.000048783968,4.7524117e-7,0.0013328533,0.7109359,0.00012356463,0.0036739667,0.00036249156,0.000047352733],"about_ca_topic_score_codex":0.000041433126,"about_ca_topic_score_gemma":0.0003223014,"teacher_disagreement_score":0.70097077,"about_ca_system_score_codex":0.0001374589,"about_ca_system_score_gemma":0.00035274064,"threshold_uncertainty_score":0.88002956},"labels":[],"label_agreement":null},{"id":"W4378219828","doi":"10.3389/fbinf.2023.1153800","title":"ModEx: a general purpose computer model exploration system","year":2023,"lang":"en","type":"article","venue":"Frontiers in Bioinformatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Canadian Institutes of Health Research; Genome British Columbia","keywords":"Computer science; Flexibility (engineering); Workflow; Interface (matter); Key (lock); Variety (cybernetics); Data mining; Machine learning; Parameter space; Data exploration; Visualization; Artificial intelligence; Human–computer interaction; Software engineering; Theoretical computer science; Database; Operating system; Mathematics","score_opus":0.02890042162781355,"score_gpt":0.2599262772497422,"score_spread":0.23102585562192865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4378219828","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00053179794,0.000009546549,0.99675614,0.00017318862,0.00089998037,0.00016724209,0.000018146635,0.00047469,0.00096930115],"genre_scores_gemma":[0.010290031,0.000069123496,0.9882972,0.00048668252,0.00006867598,0.000019654251,0.00019445474,0.000012523199,0.0005616398],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99875677,0.00002623563,0.00046506082,0.00015707161,0.0003140871,0.00028078776],"domain_scores_gemma":[0.9992862,0.000008911767,0.00011589398,0.0004465118,0.00005972808,0.00008276085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031412442,0.00013279515,0.00018951888,0.00048043087,0.00008340388,0.0002670066,0.000640123,0.000072376846,5.1665177e-7],"category_scores_gemma":[0.000010640528,0.00012710324,0.000045808167,0.0011019899,0.000024322222,0.0018832338,0.00025785915,0.00008541084,0.00012607401],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002879558,0.000027403397,0.0003353432,0.0001572632,0.000014295733,0.000009118731,0.0037351693,0.6832605,0.0000028187528,0.10454078,0.1818602,0.026054218],"study_design_scores_gemma":[0.0002661319,0.0000156914,0.000020938834,0.000035582623,0.000003070773,0.0000024465878,0.0003621951,0.9960923,0.000021140073,0.0016433976,0.0013787444,0.00015832193],"about_ca_topic_score_codex":0.0000023577986,"about_ca_topic_score_gemma":0.0000012190773,"teacher_disagreement_score":0.31283182,"about_ca_system_score_codex":0.000100210156,"about_ca_system_score_gemma":0.0000643549,"threshold_uncertainty_score":0.518312},"labels":[],"label_agreement":null},{"id":"W4378474024","doi":"10.48550/arxiv.2305.14761","title":"UniChart: A Universal Vision-language Pretrained Model for Chart Comprehension and Reasoning","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Automatic summarization; Chart; Question answering; Natural language processing; Artificial intelligence; Variety (cybernetics); Comprehension; Programming language","score_opus":0.09585457566961357,"score_gpt":0.25122614171169594,"score_spread":0.15537156604208235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4378474024","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029435487,0.00003859997,0.96901184,0.00017536683,0.00021582736,0.0003352795,0.00014218054,0.00042980755,0.00021562833],"genre_scores_gemma":[0.9836197,0.0002893839,0.008634046,0.00016676645,0.000043881784,9.4776675e-7,0.00025913594,0.000033336004,0.0069528194],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983729,0.00006715505,0.00017314646,0.0009932406,0.000099888646,0.00029366373],"domain_scores_gemma":[0.99850655,0.00012603111,0.00018577398,0.00084681227,0.00014842128,0.00018643882],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00024743343,0.00025823797,0.00029451033,0.00031960517,0.00020687835,0.00018457031,0.0009787447,0.00020942793,0.0000059596887],"category_scores_gemma":[0.000057084122,0.0003029918,0.00012363351,0.00042476415,0.000084208485,0.00042951523,0.0020609202,0.00025105404,0.000020243197],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000577784,0.000104896506,0.00020256182,0.0003129797,0.00013247752,0.00018163004,0.0026881585,0.3620796,0.00015554095,0.6287548,0.0045315805,0.0007980077],"study_design_scores_gemma":[0.0006354075,0.000043704797,0.0000833842,0.0001657393,0.0000540702,0.0000018116885,0.00024096838,0.98943335,0.000017488053,0.008563671,0.00043706835,0.00032335104],"about_ca_topic_score_codex":0.00003624694,"about_ca_topic_score_gemma":0.000031549367,"teacher_disagreement_score":0.96037775,"about_ca_system_score_codex":0.000085725085,"about_ca_system_score_gemma":0.00015497925,"threshold_uncertainty_score":0.99994224},"labels":[],"label_agreement":null},{"id":"W4379381087","doi":"10.21428/bf6fb269.541455de","title":"Pathways to urban sustainability: Design perspectives on a data curation and visualization platform","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"McGill University","keywords":"Visualization; Sustainability; Data curation; Computer science; Data visualization; Data science; Information visualization; Human–computer interaction; Data mining; Ecology","score_opus":0.10521372123536622,"score_gpt":0.3559386514365441,"score_spread":0.25072493020117786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4379381087","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020158559,0.000008254662,0.995678,0.0012006318,0.000046710553,0.00026408993,0.000013563309,0.00040034342,0.0003725569],"genre_scores_gemma":[0.9848809,0.000059808506,0.012513071,0.0010463279,0.00007753452,0.000017064334,0.0003376485,0.00001720584,0.0010504387],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989313,0.00004743273,0.00014777678,0.0004854748,0.00023161797,0.000156392],"domain_scores_gemma":[0.99888897,0.00010289044,0.00003505716,0.0007225615,0.00015731633,0.00009323234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054455776,0.000091527225,0.00008442478,0.00023788669,0.00013793605,0.00035771457,0.0005234039,0.00003062474,0.0000089933665],"category_scores_gemma":[0.00057169626,0.00008035217,0.000009672418,0.0011109168,0.000019978912,0.0014236997,0.00049655966,0.00003290276,0.00006469783],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000051661464,0.00004418668,0.0001041131,0.000010524543,0.000005275476,0.0000030248639,0.0049854186,0.00037113155,0.000045326284,0.97077227,0.017564889,0.00608869],"study_design_scores_gemma":[0.00014267658,0.00015579908,0.0005414887,0.000008465934,0.0000033664162,0.0000010875926,0.004890892,0.98060846,0.00020105286,0.008969639,0.004336694,0.0001403598],"about_ca_topic_score_codex":0.000009110221,"about_ca_topic_score_gemma":0.0000052019627,"teacher_disagreement_score":0.9831649,"about_ca_system_score_codex":0.00006075054,"about_ca_system_score_gemma":0.000093399045,"threshold_uncertainty_score":0.34494498},"labels":[],"label_agreement":null},{"id":"W4380142754","doi":"10.2196/46275","title":"Visual Analytics of Multidimensional Oral Health Surveys: Data Mining Study","year":2023,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Natural Science Foundation of Zhejiang Province; National Natural Science Foundation of China","keywords":"Visual analytics; Computer science; Visualization; Data science; Data visualization; Analytics; Data mining; Population; Information retrieval; Machine learning; Medicine; Environmental health","score_opus":0.13137834044670668,"score_gpt":0.44499185758658366,"score_spread":0.31361351713987695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380142754","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19667315,0.00001823795,0.8000861,0.0010699484,0.0005877247,0.0005977422,0.00017503095,0.00052790355,0.00026420268],"genre_scores_gemma":[0.91855556,0.0001256783,0.0736664,0.0041470304,0.00015109824,0.000015365455,0.0028915529,0.000033780812,0.00041353604],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9963233,0.0002610215,0.0011484794,0.00019158813,0.0017255312,0.00035010223],"domain_scores_gemma":[0.9978246,0.00031612036,0.00036817798,0.00097506435,0.000146423,0.00036961026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0051211817,0.00014554292,0.00037248927,0.00030056998,0.00010789429,0.00007536077,0.001721584,0.00007667571,0.00004914193],"category_scores_gemma":[0.0006148372,0.000121499834,0.000037830425,0.0017220869,0.00009361065,0.0008169537,0.0020828696,0.00018144675,0.000120361736],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016212485,0.004160981,0.05997856,0.0009027694,0.0004959284,0.000120428784,0.0448684,0.0007187765,0.000004796938,0.012548789,0.38754883,0.48863554],"study_design_scores_gemma":[0.00065561786,0.00021808891,0.008234498,0.000060902144,0.000006026082,0.000004806982,0.00379671,0.98329467,0.000003545294,0.000015154562,0.0035823733,0.00012761085],"about_ca_topic_score_codex":0.000031181775,"about_ca_topic_score_gemma":0.00005934949,"teacher_disagreement_score":0.9825759,"about_ca_system_score_codex":0.000025060988,"about_ca_system_score_gemma":0.00058889453,"threshold_uncertainty_score":0.49546197},"labels":[],"label_agreement":null},{"id":"W4381054388","doi":"10.1111/anzs.12388","title":"Visual assessment of matrix‐variate normality","year":2023,"lang":"en","type":"article","venue":"Australian & New Zealand Journal of Statistics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Canada Research Chairs; E.W.R. Steacie Memorial Fund","keywords":"Random variate; Normality; Mathematics; Statistics; Multivariate normal distribution; Multivariate statistics; Scatter plot; Normal distribution; Matrix (chemical analysis); Artificial intelligence; Pattern recognition (psychology); Computer science; Random variable","score_opus":0.03670167800569257,"score_gpt":0.3825651669635166,"score_spread":0.34586348895782404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4381054388","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008698559,0.0000056125423,0.9883377,0.0019007182,0.00061095465,0.00006109123,0.0002358249,0.00003535531,0.000114169154],"genre_scores_gemma":[0.5842368,0.0004434126,0.38557965,0.00025502907,0.00047443202,6.2951295e-7,0.0001591991,0.00003057012,0.02882031],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.998281,0.00007866149,0.0007383487,0.000122235,0.00054632424,0.00023342283],"domain_scores_gemma":[0.9985234,0.00012662452,0.0006369506,0.00020145382,0.00027865826,0.00023287762],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066184474,0.00011551804,0.0002859084,0.00021941606,0.00004658548,0.00013077124,0.0005288011,0.00004696086,0.00008733976],"category_scores_gemma":[0.000079462065,0.00009902732,0.000065782224,0.000607181,0.00003678169,0.0003515236,0.000100582736,0.00016739288,0.000024692245],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019398904,0.00026201486,0.0373593,0.0001014422,0.00019389535,0.0003435404,0.00059260236,0.0023370737,0.00058569765,0.16737202,0.77929616,0.0115368655],"study_design_scores_gemma":[0.0044936156,0.0021299622,0.62399626,0.00028801055,0.0002737706,0.000291546,0.00028737215,0.16925439,0.001159575,0.03809623,0.1589729,0.00075639016],"about_ca_topic_score_codex":0.00006098794,"about_ca_topic_score_gemma":0.000007772633,"teacher_disagreement_score":0.62032324,"about_ca_system_score_codex":0.000029711977,"about_ca_system_score_gemma":0.00036144225,"threshold_uncertainty_score":0.40382168},"labels":[],"label_agreement":null},{"id":"W4381281743","doi":"10.1177/14738716231173730","title":"Waffster: Hierarchical waffle charts for budget visualization","year":2023,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Visualization; Representation (politics); Newspaper; Data visualization; Key (lock); Data science; Operations research; Politics; Data mining; Computer security; Political science","score_opus":0.023931884949956104,"score_gpt":0.32739173809721966,"score_spread":0.30345985314726354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4381281743","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013835467,0.0000060492544,0.9940973,0.00076617475,0.0006424644,0.00057463016,0.00006850931,0.0013905768,0.0010707283],"genre_scores_gemma":[0.9348922,0.00039230887,0.013026114,0.013497349,0.0008424219,0.00066004955,0.032715365,0.00013572983,0.00383847],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979405,0.0000817448,0.00074093125,0.00027551263,0.0005722828,0.0003890465],"domain_scores_gemma":[0.9984799,0.00011628862,0.00031457018,0.00044102894,0.0005047675,0.00014341414],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00070487085,0.00020635397,0.00020027964,0.00080173457,0.00035854348,0.0007191353,0.00056639826,0.00013869353,0.000039408],"category_scores_gemma":[0.0004031365,0.00021154691,0.0000917499,0.0021972589,0.000037079884,0.0050292397,0.00019105093,0.000060702205,0.0008447142],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011038825,0.00004907826,0.00025981572,0.0001188686,0.000017881983,5.564291e-7,0.0024707431,0.0014818371,0.00012296293,0.9310414,0.048013195,0.016412629],"study_design_scores_gemma":[0.0006246374,0.00007916419,0.00048208694,0.00002505414,0.000008251554,0.0000032347305,0.00011292887,0.79086065,0.0011370131,0.003284905,0.20313527,0.0002468254],"about_ca_topic_score_codex":0.0000039930997,"about_ca_topic_score_gemma":0.0000021823446,"teacher_disagreement_score":0.98107123,"about_ca_system_score_codex":0.00006734203,"about_ca_system_score_gemma":0.0001047485,"threshold_uncertainty_score":0.99993324},"labels":[],"label_agreement":null},{"id":"W4382317916","doi":"10.1609/aaai.v37i13.27088","title":"AnoViz: A Visual Inspection Tool of Anomalies in Multivariate Time Series","year":2023,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kootenay Association for Science & Technology","funders":"Samsung","keywords":"Anomaly detection; Visualization; Computer science; Rendering (computer graphics); Multivariate statistics; Series (stratigraphy); Data mining; Anomaly (physics); Data visualization; Visual inspection; Time series; Artificial intelligence; Geology; Machine learning; Physics","score_opus":0.05910017496436031,"score_gpt":0.32531417720003053,"score_spread":0.2662140022356702,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382317916","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9467094,0.000009396301,0.040547445,0.003678389,0.00057724945,0.000656138,0.000030388357,0.00050992187,0.0072817043],"genre_scores_gemma":[0.9985164,0.000028672444,0.0009564364,0.0000567409,0.00002315269,0.000008868715,0.0000021233682,0.000007577253,0.00040005377],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99857503,0.000018519177,0.0005292079,0.00030887872,0.00035186912,0.00021650121],"domain_scores_gemma":[0.99904996,0.000055035034,0.0003023278,0.00017832423,0.00038227928,0.00003207851],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047327802,0.00013933427,0.00022393937,0.00030255452,0.00008776998,0.00013684886,0.0009563678,0.000060489503,0.000035018555],"category_scores_gemma":[0.00045441644,0.00011231039,0.00006305695,0.0018702983,0.00019474704,0.0006574466,0.00036846087,0.00012140672,0.00012960922],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044920722,0.00015113984,0.0011535449,0.000048029164,0.000009783861,6.410728e-7,0.0017899154,0.00013776276,0.0939927,0.8878852,0.00016709745,0.014619273],"study_design_scores_gemma":[0.000034817822,0.00015507307,0.002529374,0.00017688746,0.000004851027,0.0000015748362,0.00060871785,0.51829994,0.430858,0.04710534,0.000068306974,0.00015711754],"about_ca_topic_score_codex":0.00004943744,"about_ca_topic_score_gemma":0.000014633496,"teacher_disagreement_score":0.84077984,"about_ca_system_score_codex":0.000026298418,"about_ca_system_score_gemma":0.00007700586,"threshold_uncertainty_score":0.45798847},"labels":[],"label_agreement":null},{"id":"W4383616598","doi":"10.1007/978-3-031-35908-8_8","title":"Objective Metrics for Assessing Visual Complexity of Vehicle Dashboards: A Machine-Learning Based Study","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Institute of Psychology, Chinese Academy of Sciences; Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Computer science; Dashboard; Animation; Visualization; Machine learning; Component (thermodynamics); Visual analytics; Human–computer interaction; Key (lock); Artificial intelligence; Data science","score_opus":0.0687990459284526,"score_gpt":0.35312753489081666,"score_spread":0.28432848896236407,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383616598","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00021106983,0.00004092903,0.997761,0.00013788264,0.0007149087,0.00063211494,0.000033090713,0.00022200847,0.00024696885],"genre_scores_gemma":[0.6842556,0.000006804904,0.31440383,0.00070803455,0.00020976602,0.000016936658,0.00006852432,0.00007509337,0.00025537703],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9962306,0.00011032999,0.0006653853,0.0012774208,0.0012283088,0.0004879359],"domain_scores_gemma":[0.99646866,0.0014296392,0.00055696955,0.00077608024,0.0006371642,0.00013145724],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0019175188,0.0004194657,0.00068146037,0.0016187867,0.0003710665,0.00071042444,0.0022827704,0.00017048042,0.00000693353],"category_scores_gemma":[0.00076323526,0.00039979888,0.0001651594,0.0022131652,0.00047021182,0.0005987086,0.001202368,0.00057635474,0.000008178374],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049719183,0.001211827,0.008269524,0.00056524365,0.0001955712,0.00014354345,0.0043480536,0.37081915,0.0003236012,0.06716793,0.000053621385,0.54685223],"study_design_scores_gemma":[0.000557182,0.00044109428,0.0005937287,0.00017738601,0.000022649934,0.0000017300684,0.000003477412,0.98112303,0.00042657118,0.016097924,0.00014594504,0.0004092768],"about_ca_topic_score_codex":0.000039596747,"about_ca_topic_score_gemma":0.00010527503,"teacher_disagreement_score":0.68404454,"about_ca_system_score_codex":0.00021768645,"about_ca_system_score_gemma":0.0006689127,"threshold_uncertainty_score":0.9998454},"labels":[],"label_agreement":null},{"id":"W4385079053","doi":"10.1145/3597465.3605226","title":"Visualizing a Tabular Data Repository to Facilitate Descriptive Tag Augmentation for New Tables","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Table (database); Computer science; Information retrieval; Inference; Data exploration; World Wide Web; Data mining; Data science; Visualization; Artificial intelligence","score_opus":0.22156053827413635,"score_gpt":0.37157896121894163,"score_spread":0.15001842294480527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385079053","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006271263,0.000018085728,0.9969729,0.0008346802,0.00030942846,0.00025849283,0.000105602296,0.00035053657,0.00052312884],"genre_scores_gemma":[0.041431785,0.00008141833,0.7523445,0.006282783,0.0005296045,0.00010905746,0.0056838016,0.00006969114,0.19346738],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99881494,0.0000322456,0.00023160389,0.00047330157,0.00022365678,0.00022424919],"domain_scores_gemma":[0.99891007,0.00007332584,0.00005194887,0.0007355618,0.00008384015,0.00014523465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003489795,0.00009632755,0.00010749833,0.00015834201,0.00015605902,0.0003766552,0.0009740528,0.000024731004,0.000014584114],"category_scores_gemma":[0.00014625219,0.00009188313,0.000025110905,0.0007892827,0.000011001203,0.0010693363,0.00061514735,0.00002503276,0.00016044168],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009453171,0.000034640907,0.00014773631,0.000034279503,0.000041641528,0.000008358688,0.0034013037,0.0007597979,0.007965638,0.0803788,0.89291304,0.014305275],"study_design_scores_gemma":[0.00035114447,0.00007705537,0.000111282294,0.00002488144,0.000012395701,0.0000014808999,0.0011929476,0.7123544,0.005275225,0.0012876238,0.279111,0.00020055489],"about_ca_topic_score_codex":0.00029735174,"about_ca_topic_score_gemma":0.000072119365,"teacher_disagreement_score":0.7115946,"about_ca_system_score_codex":0.000035522084,"about_ca_system_score_gemma":0.000106881795,"threshold_uncertainty_score":0.3746885},"labels":[],"label_agreement":null},{"id":"W4385399894","doi":"10.31219/osf.io/mpq32","title":"Enthusiastic and Grounded, Avoidant and Cautious: Understanding Public Receptivity to Data and Visualizations","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canada Research Chairs","keywords":"Openness to experience; Visualization; Qualitative property; Data visualization; Exploratory research; Qualitative research; Grounded theory; Information visualization; Public domain; Data science; Psychology; Social psychology; Computer science; Sociology; Geography; Social science; Data mining","score_opus":0.31550088796939957,"score_gpt":0.38433566470260994,"score_spread":0.06883477673321037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385399894","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007539406,0.00009339328,0.9929354,0.004466265,0.00031445347,0.00027855166,0.00025595125,0.0003428009,0.00055924227],"genre_scores_gemma":[0.9744876,0.0021876572,0.019299133,0.0011654154,0.00010445893,0.00001929822,0.0011882094,0.00005056089,0.0014976845],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99783444,0.00012361532,0.00031309217,0.0011448424,0.00030307655,0.00028090843],"domain_scores_gemma":[0.9980998,0.00023186809,0.00011642079,0.0011424797,0.00009003075,0.0003194012],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0007277228,0.00024714583,0.00028424297,0.00040399493,0.00032906554,0.0023731734,0.00086638256,0.00012707313,0.000014258314],"category_scores_gemma":[0.0005532222,0.00023957113,0.000014014713,0.0006645347,0.00012365403,0.0007487724,0.01084381,0.0002010406,0.000011823125],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021744759,0.000073009585,0.0020466368,0.0002933172,0.00010519597,0.000013174231,0.0024889796,0.00007146632,0.000018844508,0.97487384,0.016083673,0.003929678],"study_design_scores_gemma":[0.00022127872,0.000035548896,0.0018935926,0.00014650161,0.000042366402,0.000019921348,0.00093507883,0.9745037,0.0000029558284,0.017808486,0.0039337957,0.0004567832],"about_ca_topic_score_codex":0.0001503905,"about_ca_topic_score_gemma":0.0011836138,"teacher_disagreement_score":0.97443223,"about_ca_system_score_codex":0.00009006813,"about_ca_system_score_gemma":0.00016156968,"threshold_uncertainty_score":0.9986625},"labels":[],"label_agreement":null},{"id":"W4386088295","doi":"10.1109/mcg.2023.3307971","title":"Identifying Visualization Opportunities to Help Architects Manage the Complexity of Building Codes","year":2023,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Simon Fraser University; Autodesk (Canada)","funders":"","keywords":"Computer science; Sensemaking; Visualization; Ambiguity; Process (computing); Building design; Participatory design; Human–computer interaction; Design process; Software engineering; Architectural engineering; Work in process; Engineering; Artificial intelligence; Parallels; Programming language","score_opus":0.14959817035320966,"score_gpt":0.35470643825630094,"score_spread":0.20510826790309128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386088295","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0075780717,0.00002345222,0.99046195,0.0012960079,0.0000907996,0.0002660573,0.00003228829,0.0001792007,0.000072168186],"genre_scores_gemma":[0.9776163,0.00039832486,0.019914197,0.0016336389,0.00015237647,0.00009396225,0.00008246944,0.000016959024,0.00009178926],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99905074,0.000051751314,0.0002515518,0.0002664034,0.00022016287,0.00015936473],"domain_scores_gemma":[0.9991637,0.00010578477,0.00010518679,0.00042210563,0.00011682915,0.00008638033],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032940588,0.00010226197,0.00012958991,0.00034362916,0.0003556932,0.00026466453,0.0006471447,0.000025944086,0.0000011236021],"category_scores_gemma":[0.0000046661503,0.00008783971,0.00004358312,0.0011443918,0.00020401142,0.00015099811,0.00034218948,0.00005985806,0.0000065769077],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.6808672e-7,0.000020641754,0.00008100326,0.000038616126,0.00001401628,7.0682114e-7,0.00039252258,0.00033336843,0.00040254783,0.9896529,0.0011133589,0.007949998],"study_design_scores_gemma":[0.00012358437,0.000031778934,0.0041675367,0.000054112228,0.000016314523,0.0000056804115,0.00012421556,0.866588,0.0011072293,0.10467215,0.022904605,0.00020478596],"about_ca_topic_score_codex":0.000020781863,"about_ca_topic_score_gemma":0.000017508475,"teacher_disagreement_score":0.97054774,"about_ca_system_score_codex":0.0000054876837,"about_ca_system_score_gemma":0.00001764737,"threshold_uncertainty_score":0.35819995},"labels":[],"label_agreement":null},{"id":"W4386252546","doi":"10.31219/osf.io/7fdb5","title":"Educational Data Comics: What can Comics do for Education in Visualization?","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Austrian Science Fund","keywords":"Comics; Visualization; Computer science; Information visualization; Data visualization; World Wide Web; Data science; Subject (documents); Multimedia; Artificial intelligence","score_opus":0.1027133357837961,"score_gpt":0.4238256684920536,"score_spread":0.3211123327082575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386252546","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000053599164,0.00019102555,0.98695403,0.0065914383,0.002903078,0.00079680525,0.0005989474,0.00053146586,0.0013796228],"genre_scores_gemma":[0.012823563,0.006671958,0.61251116,0.012363755,0.0015728584,0.00069620536,0.16503651,0.00078929635,0.18753469],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981362,0.000060099876,0.0004503677,0.00088450656,0.00025341279,0.0002154104],"domain_scores_gemma":[0.9972332,0.00014732085,0.00027668188,0.0020884348,0.00015039611,0.00010394216],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00044918314,0.00021641563,0.0002467562,0.0006156461,0.00005793363,0.0013477063,0.002897295,0.00016968086,0.000029594205],"category_scores_gemma":[0.00018586907,0.00024301394,0.000040801835,0.00050754193,0.000036298556,0.0006737454,0.0026258356,0.00012662879,0.000026907699],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.3776473e-7,0.00017903766,0.0010451325,0.000103380175,0.000016676813,1.2812946e-7,0.00016693569,0.0002525567,7.686001e-7,0.51226807,0.48371437,0.0022520933],"study_design_scores_gemma":[0.0003101535,0.000009549235,0.00038816576,0.00041334372,0.000016993956,0.0000015648426,0.0005439439,0.8994844,0.000011264997,0.055269502,0.043089658,0.0004614486],"about_ca_topic_score_codex":0.0007437833,"about_ca_topic_score_gemma":0.0020386614,"teacher_disagreement_score":0.89923185,"about_ca_system_score_codex":0.00010544551,"about_ca_system_score_gemma":0.0022782723,"threshold_uncertainty_score":0.999689},"labels":[],"label_agreement":null},{"id":"W4386619352","doi":"10.59350/mhk2c-wsy50","title":"Co-located Collaborative Tree Comparison","year":2009,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Tree (set theory); Visualization; Geography; Computer science; Data science; World Wide Web; Cartography; Data mining; Mathematics; Combinatorics","score_opus":0.043847160599297254,"score_gpt":0.36806391870148897,"score_spread":0.3242167581021917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386619352","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00011592807,0.00011281499,0.91651404,0.0012444772,0.00027712245,0.00019862385,0.000038341826,0.0004572963,0.08104136],"genre_scores_gemma":[0.61315084,0.00054775906,0.35153934,0.009134207,0.0004568428,0.000044886183,0.0038800323,0.00006441292,0.021181688],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99839103,0.000112943955,0.0003918103,0.00054737204,0.0003536752,0.00020317557],"domain_scores_gemma":[0.99840206,0.00003653106,0.00022956291,0.0009041052,0.00030835313,0.000119377255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020061771,0.00023390664,0.00037545845,0.00016917926,0.00007589162,0.00064941205,0.0015124822,0.00018145179,0.00007911035],"category_scores_gemma":[0.000038701517,0.00021093214,0.0000623087,0.0005948928,0.000039636023,0.00018865343,0.0004414378,0.00028138972,0.00027392662],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000052350647,0.00039830143,0.0005422956,0.000043209628,0.0000704051,0.000016372369,0.0010431003,0.0028066682,0.00007822333,0.40263832,0.55694747,0.035410415],"study_design_scores_gemma":[0.00032847413,0.00008122914,0.00086462474,0.000061427716,0.0000194387,0.0000013468385,0.00010651884,0.90535897,0.004124553,0.0071678157,0.08135433,0.00053130585],"about_ca_topic_score_codex":0.000021565256,"about_ca_topic_score_gemma":0.00005035419,"teacher_disagreement_score":0.90255225,"about_ca_system_score_codex":0.000057241192,"about_ca_system_score_gemma":0.0003340108,"threshold_uncertainty_score":0.86015624},"labels":[],"label_agreement":null},{"id":"W4386840076","doi":"10.48550/arxiv.2309.08018","title":"The Effect of Smoothing on the Interpretation of Time Series Data: A COVID-19 Case Study","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Smoothing; Spurious relationship; Plot (graphics); Bar chart; Computer science; Coronavirus disease 2019 (COVID-19); Time series; Interpretation (philosophy); Series (stratigraphy); Window (computing); Econometrics; Data mining; Statistics; Mathematics; Machine learning; Computer vision; Geology","score_opus":0.12890463165723204,"score_gpt":0.28047867438459445,"score_spread":0.1515740427273624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386840076","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3605813,0.000013199623,0.63732666,0.00042151415,0.000387496,0.0007525932,0.00014515585,0.00014936268,0.000222705],"genre_scores_gemma":[0.99919343,0.000032148342,0.000027592172,0.00006424772,0.0000121503135,7.1835893e-7,0.000037034508,0.000008312977,0.00062436576],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984133,0.00062681333,0.00021294855,0.00050958,0.00012562748,0.000111707595],"domain_scores_gemma":[0.9959048,0.0015602914,0.0003647201,0.0020360025,0.00007882803,0.00005534414],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014737054,0.00014915921,0.00022183306,0.00013622546,0.00022009431,0.000120789366,0.0025471423,0.00007558168,0.0000055366936],"category_scores_gemma":[0.0007548646,0.000099531746,0.00007395097,0.0005681793,0.00014159035,0.00029703137,0.0033367053,0.00027676622,0.000020482497],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003951217,0.00036837967,0.013571233,0.0006935458,0.0012006221,0.003897861,0.010969868,0.7339554,0.000021289216,0.2269426,0.0063410792,0.0016430025],"study_design_scores_gemma":[0.00024910865,0.00027857767,0.000050323448,0.00006353933,0.000107334075,0.0000101076985,0.0013471583,0.9957992,0.000056103043,0.0017457202,0.00017747299,0.00011535705],"about_ca_topic_score_codex":0.00042291923,"about_ca_topic_score_gemma":0.00022144167,"teacher_disagreement_score":0.6386121,"about_ca_system_score_codex":0.000056789475,"about_ca_system_score_gemma":0.00013927242,"threshold_uncertainty_score":0.47332665},"labels":[],"label_agreement":null},{"id":"W4386846847","doi":"10.1007/s12652-023-04698-3","title":"Guest Editorial: machine learning for visual information processing &amp; understanding","year":2023,"lang":"en","type":"editorial","venue":"Journal of Ambient Intelligence and Humanized Computing","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Computational intelligence; Artificial intelligence; Data science; Cognitive science; Psychology","score_opus":0.06306143590303945,"score_gpt":0.35467850646592636,"score_spread":0.2916170705628869,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386846847","genre_codex":"methods","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"editorial","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000008561451,0.000088116714,0.52086085,0.000027941824,0.47885323,0.00007970413,0.0000056219137,0.00006322394,0.00001276949],"genre_scores_gemma":[0.0018678147,0.00055665505,0.006960226,0.00004047008,0.9901487,0.0000016178124,0.00026959935,0.00004120661,0.00011369012],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966815,0.000089001114,0.0013802053,0.0002819361,0.0011877777,0.00037954704],"domain_scores_gemma":[0.9948421,0.0012748878,0.0021558374,0.00016055527,0.0014165648,0.00015003482],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0023833865,0.00030909694,0.0005786195,0.00070249016,0.0006650472,0.0018976289,0.00085689005,0.00031871945,0.0000023756497],"category_scores_gemma":[0.0024540604,0.0002866385,0.00017353542,0.00049661554,0.00005916229,0.0015537367,0.00040080977,0.0009807108,0.000013983277],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000060471404,0.000054283628,0.000009572235,0.0005074855,0.00008915633,0.000004611234,0.0030275832,0.0020456365,0.000010826087,0.002746365,0.98134446,0.010099551],"study_design_scores_gemma":[0.00034386924,0.00031979516,3.686561e-7,0.0008431313,0.0000595396,0.000006544157,0.00050924736,0.19906129,0.000036311034,0.0014043986,0.7971218,0.0002936955],"about_ca_topic_score_codex":0.000012508756,"about_ca_topic_score_gemma":0.000010644423,"teacher_disagreement_score":0.51390064,"about_ca_system_score_codex":0.00024674565,"about_ca_system_score_gemma":0.00036195572,"threshold_uncertainty_score":0.9999586},"labels":[],"label_agreement":null},{"id":"W4386883447","doi":"10.1109/icmcis59922.2023.10253516","title":"Enabling Activity Based Intelligence with Visual Analytics","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Visual analytics; Computer science; Data science; Analytics; Intelligence analysis; Visualization; Domain (mathematical analysis); Currency; Data visualization; Social network analysis; Graph; Big data; Business intelligence; World Wide Web; Artificial intelligence; Knowledge management; Data mining; Social media; Computer security","score_opus":0.051000857257904174,"score_gpt":0.33853811857042226,"score_spread":0.2875372613125181,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386883447","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0048571415,0.0000013789851,0.9925411,0.00053961197,0.000053874923,0.000043516156,0.0000016544549,0.00048590256,0.0014758554],"genre_scores_gemma":[0.9853801,0.000009417848,0.012402004,0.00066127355,0.00002378732,0.0000021128233,0.000012019103,0.000007737694,0.0015015373],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999102,0.000027212047,0.00010647662,0.0002688757,0.0002864275,0.00020903564],"domain_scores_gemma":[0.9993678,0.00009584332,0.00004366995,0.00033429323,0.00007094686,0.0000874795],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023600021,0.00009034466,0.00009512184,0.000210987,0.0000882887,0.0002286148,0.0004589816,0.00002605097,0.00005061224],"category_scores_gemma":[0.00004555223,0.00006932369,0.000027233655,0.0021028945,0.000030859395,0.00040824205,0.00014579302,0.000064104155,0.00023110287],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004331039,0.00074413104,0.010176294,0.00014017055,0.0001396525,0.00025829978,0.00065450324,0.107969046,0.0029513235,0.53123194,0.012157266,0.33353403],"study_design_scores_gemma":[0.00006338369,0.00005496868,0.00036879085,0.000009422008,0.000003846254,0.0000010222002,0.000040947423,0.98598254,0.010773199,0.00020189416,0.0023817134,0.00011825458],"about_ca_topic_score_codex":0.00001491011,"about_ca_topic_score_gemma":0.000020091593,"teacher_disagreement_score":0.980523,"about_ca_system_score_codex":0.000017561264,"about_ca_system_score_gemma":0.00009643072,"threshold_uncertainty_score":0.29704368},"labels":[],"label_agreement":null},{"id":"W4386984671","doi":"10.1007/978-3-031-39035-7_7","title":"A Framework for the Design, Production, and Evaluation of Scientific Visualizations","year":2023,"lang":"en","type":"book-chapter","venue":"Biomedical visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Public Health Agency of Canada; Vale (Canada); University of Toronto","funders":"","keywords":"Visualization; Computer science; Process (computing); Information visualization; Product (mathematics); Data science; Scientific visualization; Quality (philosophy); Knowledge management; Management science; Human–computer interaction; Engineering; Artificial intelligence","score_opus":0.15858527676936202,"score_gpt":0.40384008322633946,"score_spread":0.24525480645697745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386984671","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000035028559,0.00031928075,0.99519026,0.0008491462,0.0017473226,0.0013420277,0.000072370785,0.00018267785,0.00029339333],"genre_scores_gemma":[0.06381796,0.008981038,0.2580885,0.0025650905,0.0072521484,0.0016725414,0.017815016,0.0012879653,0.63851976],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9967034,0.00012957567,0.0006649896,0.0006888601,0.0016100906,0.00020311303],"domain_scores_gemma":[0.99628854,0.00069840363,0.00054079166,0.0007237939,0.0016368997,0.000111582915],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031403343,0.00024308465,0.0002798213,0.0005530094,0.000489033,0.00033377335,0.0006127825,0.00032420616,0.000060384322],"category_scores_gemma":[0.0037661607,0.00018998288,0.000089236535,0.00082683156,0.0005327964,0.00026909413,0.00022771985,0.0001071647,0.000025584954],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000034623338,0.00004108078,0.0000024280082,0.00009701379,0.00006878377,1.5852234e-7,0.0002966062,0.000131713,0.00006757426,0.9739417,0.01601268,0.009336824],"study_design_scores_gemma":[0.00023354965,0.000106914915,0.000026612046,0.00045640135,0.00034070676,0.000003136005,0.000030689986,0.6356633,0.00024587222,0.29951018,0.063103594,0.00027904517],"about_ca_topic_score_codex":0.0000018460448,"about_ca_topic_score_gemma":0.0000053392155,"teacher_disagreement_score":0.7371018,"about_ca_system_score_codex":0.00006404295,"about_ca_system_score_gemma":0.00052281335,"threshold_uncertainty_score":0.7747277},"labels":[],"label_agreement":null},{"id":"W4387331767","doi":"10.1007/978-3-031-26588-4_12","title":"Filter, Map, Reduce","year":2023,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Ste. Anne's Hospital","funders":"","keywords":"Computer science; Filter (signal processing); Computer vision","score_opus":0.0721505274351174,"score_gpt":0.3086233061690127,"score_spread":0.23647277873389527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387331767","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[1.1290888e-8,0.000017866187,0.19832663,0.00083008065,0.0006483751,0.00004744061,0.00002514938,0.00046986595,0.7996346],"genre_scores_gemma":[0.0000063864586,0.00011413672,0.004580621,0.0008254456,0.00013833382,0.0000011487759,0.00013148702,0.00002610548,0.9941763],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99901927,0.000004899666,0.00020047247,0.00036671036,0.00027128056,0.00013734754],"domain_scores_gemma":[0.9990144,0.000031623877,0.00008076141,0.00073069293,0.00006267823,0.00007986591],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009350021,0.00016002795,0.0001594889,0.00014965066,0.0000436217,0.00019565555,0.0009451466,0.00012035598,0.0008231074],"category_scores_gemma":[0.000011380501,0.00014552302,0.00008063242,0.000053929947,0.000024895793,0.0001538981,0.00048614747,0.000118004464,0.010013467],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.436257e-8,0.0000019020501,1.1048967e-7,0.000007429528,0.000009032243,0.000008673698,0.0000093454055,0.0000010482984,0.0000010077275,0.6887229,0.3081685,0.0030699198],"study_design_scores_gemma":[0.00004881593,0.00001251353,0.0000012324682,0.000047425892,0.0000061651813,0.0000028249901,0.0000012296441,0.007888583,0.000023313776,0.06418901,0.927574,0.0002049236],"about_ca_topic_score_codex":0.0000034639809,"about_ca_topic_score_gemma":0.0000073077877,"teacher_disagreement_score":0.62453395,"about_ca_system_score_codex":0.000016769893,"about_ca_system_score_gemma":0.000058519236,"threshold_uncertainty_score":0.99075735},"labels":[],"label_agreement":null},{"id":"W4387339245","doi":"10.1080/1533256x.2023.2263871","title":"Development of a visual recurrence prevention tool","year":2023,"lang":"en","type":"article","venue":"Journal of Social Work Practice in the Addictions","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"The King's University; Dalhousie University; Simon Fraser University; University of Toronto; McMaster University","funders":"","keywords":"Addiction; Resource (disambiguation); Psychology; Infographic; Thematic analysis; Visual communication; Cognition; Relapse prevention; Alcohol addiction; Service (business); Addiction treatment; Applied psychology; Medical education; Psychotherapist; Computer science; Medicine; Multimedia; Psychiatry; Qualitative research","score_opus":0.04696557344930365,"score_gpt":0.39107830586600484,"score_spread":0.3441127324167012,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387339245","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06253231,0.00020853974,0.8924939,0.035432752,0.002300261,0.00043559246,0.000010772925,0.00011593415,0.006469906],"genre_scores_gemma":[0.9050437,0.00034748722,0.092615165,0.00069316284,0.000480546,0.000016131826,0.000021022415,0.000014252211,0.00076848717],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986021,0.00024962748,0.00052153494,0.00007124264,0.0004479946,0.00010752055],"domain_scores_gemma":[0.9984898,0.0005045483,0.0006566831,0.00009663365,0.00023198259,0.000020380156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00218924,0.00005281587,0.00010757996,0.00020444911,0.00026191902,0.000094617615,0.00048212177,0.00003507424,0.000022695081],"category_scores_gemma":[0.0010566046,0.000041613588,0.00006543077,0.0027612026,0.000022602835,0.0009895051,0.00008160997,0.00022696782,0.00003354026],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012419905,0.002754719,0.00056801137,0.000039961462,0.0003582761,0.00008425815,0.12144969,0.00065083586,0.00025406937,0.20495574,0.11098672,0.55777353],"study_design_scores_gemma":[0.0009032672,0.00024080751,0.023094295,0.00029238942,0.00012678617,0.00010425387,0.019574186,0.004395796,0.00012876275,0.005064468,0.9458178,0.00025716439],"about_ca_topic_score_codex":7.018571e-7,"about_ca_topic_score_gemma":0.0000030519125,"teacher_disagreement_score":0.8425114,"about_ca_system_score_codex":0.000041484353,"about_ca_system_score_gemma":0.00027089083,"threshold_uncertainty_score":0.20144957},"labels":[],"label_agreement":null},{"id":"W4387810005","doi":"10.2196/45828","title":"Connect Brain, a Mobile App for Studying Depth Perception in Angiography Visualization: Gamification Study","year":2023,"lang":"en","type":"article","venue":"JMIR Neurotechnology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Visualization; Computer science; Human–computer interaction; Rendering (computer graphics); Perception; Context (archaeology); Creative visualization; Mobile device; Multimedia; Android (operating system); Volume rendering; Data science; World Wide Web; Artificial intelligence; Psychology","score_opus":0.042129673230064925,"score_gpt":0.3600946178990866,"score_spread":0.31796494466902164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387810005","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4476583,0.000017922435,0.5459985,0.0013842914,0.0001878522,0.0028152636,0.000007667465,0.0018961586,0.00003400649],"genre_scores_gemma":[0.99744695,0.00001711249,0.00056091684,0.00042573106,0.000024974628,0.0013645155,0.00006808294,0.000020689316,0.00007102136],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99850684,0.00011984484,0.00033515075,0.00057494687,0.0001803765,0.00028285896],"domain_scores_gemma":[0.9990309,0.00012682349,0.00011496447,0.0005997303,0.000093490446,0.000034116885],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003803292,0.00014091517,0.00018795827,0.001286517,0.0001348286,0.000101171034,0.00067963335,0.00011728852,0.0000052908435],"category_scores_gemma":[0.00012167882,0.00015103017,0.00008077431,0.0040840134,0.000045816898,0.0002905741,0.00023007976,0.00011216062,0.0000533399],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012253625,0.006987919,0.19347073,0.0003760255,0.00024821685,0.00019590174,0.022822771,0.0068217837,0.039541587,0.3394202,0.04009775,0.34989458],"study_design_scores_gemma":[0.0033251126,0.0025773512,0.17378046,0.000035229452,0.000025621232,0.000018733273,0.0070556886,0.78352296,0.00045341588,0.003940199,0.02454781,0.00071741303],"about_ca_topic_score_codex":0.000005951663,"about_ca_topic_score_gemma":0.000041738836,"teacher_disagreement_score":0.77670115,"about_ca_system_score_codex":0.000025958827,"about_ca_system_score_gemma":0.000022512366,"threshold_uncertainty_score":0.6158832},"labels":[],"label_agreement":null},{"id":"W4387835444","doi":"10.1145/3586183.3606762","title":"Statslator: Interactive Translation of NHST and Estimation Statistics Reporting Styles in Scientific Documents","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Correctness; Computer science; Confidence interval; Range (aeronautics); Statistics; Code (set theory); Information retrieval; Data mining; Mathematics; Algorithm; Programming language","score_opus":0.05105259951536228,"score_gpt":0.3809565093601571,"score_spread":0.32990390984479484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387835444","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.069469616,0.0000061576097,0.9297817,0.00007644976,0.00008352038,0.00007672378,0.00002200121,0.000056040564,0.000427823],"genre_scores_gemma":[0.92476773,0.0000088918205,0.074852176,0.000012826889,0.0000023251068,0.0000015941564,0.000110938185,0.0000029702248,0.00024057509],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990196,0.000027961582,0.00048457392,0.00018337056,0.00019547276,0.00008897752],"domain_scores_gemma":[0.99934876,0.00009152504,0.0003211183,0.00014197138,0.00007026296,0.000026369227],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060813973,0.000047548358,0.00008762459,0.000260178,0.000046422298,0.00018390807,0.00010327786,0.000014893779,0.000009500832],"category_scores_gemma":[0.00022706311,0.000045462275,0.000008599439,0.000691749,0.000035801215,0.00072556036,0.000058012854,0.00003152218,0.000008321894],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013745169,0.00019374014,0.047665,0.00026503095,0.000040724848,0.000036158126,0.01555351,0.009502442,0.0048455773,0.40031123,0.0049611847,0.51661164],"study_design_scores_gemma":[0.00014313408,0.000013472321,0.0079961885,0.000027767426,0.0000022777722,9.509325e-7,0.00026204757,0.98536724,0.0010908952,0.00486001,0.00018343159,0.000052581334],"about_ca_topic_score_codex":0.00003365691,"about_ca_topic_score_gemma":0.000069138056,"teacher_disagreement_score":0.9758648,"about_ca_system_score_codex":0.0000137654415,"about_ca_system_score_gemma":0.00003751579,"threshold_uncertainty_score":0.18538977},"labels":[],"label_agreement":null},{"id":"W4387891525","doi":"10.1109/tvcg.2023.3326571","title":"Designing for Ambiguity in Visual Analytics: Lessons from Risk Assessment and Prediction","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Sensemaking; Visual analytics; Ambiguity; Computer science; Analytics; Visualization; Cultural analytics; Data science; Data visualization; Human–computer interaction; Interactive visual analysis; Knowledge management; Semantic analytics; Artificial intelligence","score_opus":0.04540525373415249,"score_gpt":0.3542721706343093,"score_spread":0.30886691690015683,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387891525","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015592059,0.000016199498,0.98307306,0.00012661873,0.0004061732,0.00027667402,0.00016787772,0.00033412102,0.0000072400394],"genre_scores_gemma":[0.98984075,0.0015492825,0.007716505,0.00056227826,0.0000652295,0.000050989303,0.0001594956,0.000025304182,0.000030185047],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99833745,0.00017652758,0.00039698533,0.0005694608,0.0002776557,0.00024191503],"domain_scores_gemma":[0.9990752,0.00030034778,0.00012866489,0.00024064185,0.00012712188,0.00012806707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051318674,0.00019989655,0.00022892811,0.00075140275,0.0003987087,0.00029907146,0.0001926132,0.00012284068,0.0000036279805],"category_scores_gemma":[0.000008484032,0.0002136588,0.000066619665,0.0014334413,0.00006431204,0.0005285222,0.00001274105,0.00017424075,0.000002847814],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000086343935,0.0014794825,0.02203252,0.00021107434,0.00044947574,0.000018381268,0.004740991,0.03478626,0.00025081885,0.8045736,0.0025022856,0.12886877],"study_design_scores_gemma":[0.0009093248,0.000200159,0.014807226,0.000054413817,0.000041953514,0.0000015439435,0.00008621091,0.9797052,0.0003387967,0.0033307634,0.0003206429,0.00020374346],"about_ca_topic_score_codex":0.000060609353,"about_ca_topic_score_gemma":0.00010515186,"teacher_disagreement_score":0.9753565,"about_ca_system_score_codex":0.000038404276,"about_ca_system_score_gemma":0.00006200125,"threshold_uncertainty_score":0.8712753},"labels":[],"label_agreement":null},{"id":"W4388035076","doi":"10.1109/tvcg.2023.3327152","title":"A Heuristic Approach for Dual Expert/End-User Evaluation of Guidance in Visual Analytics","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Vienna Science and Technology Fund","keywords":"Computer science; Visual analytics; Heuristics; Analytics; Heuristic; Set (abstract data type); Visualization; Quality (philosophy); Data science; Interactive visual analysis; Human–computer interaction; Data mining; Artificial intelligence","score_opus":0.0602134684587973,"score_gpt":0.3535105033117915,"score_spread":0.2932970348529942,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388035076","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004631216,0.000046343193,0.99426377,0.000041889853,0.00033043153,0.00044794282,0.00003362256,0.00017574686,0.00002906016],"genre_scores_gemma":[0.9934908,0.00025380967,0.0053506703,0.00051929115,0.000055517154,0.00010408102,0.00012615688,0.000028024162,0.000071623224],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99778175,0.00021874669,0.00056259026,0.0005052089,0.0006776988,0.00025398447],"domain_scores_gemma":[0.99877286,0.00017114604,0.00016436825,0.0003325376,0.00046519068,0.00009389358],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010710635,0.00020790477,0.0002756717,0.0010017769,0.00016027615,0.0001335629,0.0002709163,0.00011897118,0.0000072206735],"category_scores_gemma":[0.000022164193,0.00021765211,0.00010305187,0.00232896,0.00008362272,0.00036998148,0.000010446177,0.000100994206,0.0000030154529],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054306816,0.0014012083,0.00035175425,0.00024933642,0.0001383641,0.0000033004403,0.0026303842,0.099816516,0.000102768136,0.86797196,0.002175816,0.025104309],"study_design_scores_gemma":[0.0012074298,0.00018554128,0.000559116,0.000048312337,0.00003764374,0.0000033480435,0.00007084422,0.9956308,0.0008315552,0.0008901653,0.00030994005,0.00022531544],"about_ca_topic_score_codex":0.0000134359025,"about_ca_topic_score_gemma":0.000016143762,"teacher_disagreement_score":0.98891306,"about_ca_system_score_codex":0.000038906157,"about_ca_system_score_gemma":0.000109843786,"threshold_uncertainty_score":0.88755953},"labels":[],"label_agreement":null},{"id":"W4388405488","doi":"10.1109/iv60283.2023.00061","title":"Visual Knowledge Discovery from Public Transit Performance Data","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; University of Manitoba","keywords":"Public transport; Computer science; Process (computing); Transit (satellite); Service (business); Component (thermodynamics); Destinations; Service provider; Work (physics); Mode (computer interface); Knowledge extraction; Transport engineering; Data science; Business; Data mining; Engineering; Human–computer interaction; Marketing; Geography","score_opus":0.10222401871515638,"score_gpt":0.34612725666861466,"score_spread":0.24390323795345828,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388405488","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02412235,0.000035448487,0.9667353,0.0014398242,0.00040038032,0.000052223062,0.00010867018,0.0006248014,0.0064809793],"genre_scores_gemma":[0.9861465,0.00015356147,0.0021653285,0.000542438,0.0001363251,0.000002183377,0.0017754117,0.000010601439,0.00906762],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989872,0.000029858753,0.00016307468,0.00040562244,0.00019620571,0.00021803768],"domain_scores_gemma":[0.99882025,0.00005925145,0.00002628608,0.00097535143,0.000036235146,0.00008264369],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00022967755,0.00008906565,0.000099036806,0.00012259805,0.00010235752,0.0006368731,0.0019258875,0.000030424913,0.00008884141],"category_scores_gemma":[0.00003186449,0.000074784846,0.000021843192,0.0010870607,0.000026680695,0.0037079703,0.00095015677,0.00005753249,0.001654539],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005652303,0.00053456327,0.010767744,0.00006722544,0.00012355205,0.000025087886,0.0014486962,0.00010958714,0.0007346665,0.26674497,0.4162733,0.30316496],"study_design_scores_gemma":[0.00014100246,0.000014451688,0.0038822796,0.0000070652936,0.000003407713,5.638953e-7,0.000038582886,0.8992905,0.00021958278,0.0001428696,0.0961394,0.00012028581],"about_ca_topic_score_codex":0.00001753077,"about_ca_topic_score_gemma":0.00005543381,"teacher_disagreement_score":0.96457,"about_ca_system_score_codex":0.000010002835,"about_ca_system_score_gemma":0.00009756961,"threshold_uncertainty_score":0.9991228},"labels":[],"label_agreement":null},{"id":"W4388407686","doi":"10.1109/mcg.2023.3322888","title":"JNZNBRK: Physical Experiments in Light, Modulation, and Substrate","year":2023,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Beekeepers' Association","funders":"","keywords":"Computer science; Process (computing); Human–computer interaction; Multimedia; Computer graphics (images)","score_opus":0.03156367383214121,"score_gpt":0.31382597303635346,"score_spread":0.28226229920421225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388407686","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12957813,0.00003517114,0.8691737,0.0006696531,0.00006393781,0.00019110869,0.000007833228,0.00016274962,0.000117725074],"genre_scores_gemma":[0.9972407,0.0001591444,0.0020793502,0.00028101925,0.000103545965,0.000061338375,0.000026977605,0.0000069808684,0.00004094986],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927133,0.00001848975,0.0001470058,0.00031263207,0.00011230988,0.0001382067],"domain_scores_gemma":[0.99954104,0.000035849665,0.0000396137,0.0002671282,0.000039242008,0.00007713991],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009214162,0.000090345224,0.000100022684,0.00019553053,0.00012392199,0.0001815648,0.00022139677,0.000030305719,4.3383326e-7],"category_scores_gemma":[9.553927e-7,0.000089455505,0.000019645086,0.00087377045,0.000041810436,0.00021125845,0.000112405534,0.000061104794,0.00001540036],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.4421458e-7,0.00009256833,0.0022249697,0.000012213474,0.000009035581,0.000002046081,0.00055187085,0.0002513858,0.00050110783,0.9839649,0.0010206971,0.011368748],"study_design_scores_gemma":[0.00018576918,0.000013662873,0.021251973,0.000007562949,0.0000022295628,0.0000020886368,0.000010151044,0.94532067,0.00020641333,0.025397148,0.0074807215,0.00012160365],"about_ca_topic_score_codex":0.0000064440183,"about_ca_topic_score_gemma":0.000005226809,"teacher_disagreement_score":0.95856774,"about_ca_system_score_codex":0.00000424199,"about_ca_system_score_gemma":0.000011509422,"threshold_uncertainty_score":0.36478895},"labels":[],"label_agreement":null},{"id":"W4388427751","doi":"10.1109/iv60283.2023.00053","title":"A Data Discovery and Visualization Tool for Visual Analytics of Time Series in Digital Agriculture","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; University of Manitoba","keywords":"Computer science; Visual analytics; Variety (cybernetics); Visualization; Data science; Big data; Data visualization; Knowledge extraction; Analytics; Information visualization; Cultural analytics; Creative visualization; Data mining; World Wide Web; Artificial intelligence; Semantic analytics; The Internet","score_opus":0.02544834066719025,"score_gpt":0.31267196823049803,"score_spread":0.28722362756330777,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388427751","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02144802,0.00001158444,0.97708064,0.000271786,0.000047256908,0.00018444021,0.0006079697,0.00012375116,0.00022453087],"genre_scores_gemma":[0.93308705,0.00039615703,0.013947582,0.00060126284,0.00017758385,0.000020264742,0.017030265,0.000045018423,0.03469484],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992333,0.000009019322,0.00022779655,0.00025913754,0.00015002264,0.00012069196],"domain_scores_gemma":[0.9994812,0.00007091812,0.00006363464,0.0002937249,0.000064701126,0.000025790898],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017038242,0.00007810266,0.00013272173,0.0001327842,0.000030162217,0.00037666995,0.0004060984,0.000035267305,0.0000031550064],"category_scores_gemma":[0.00019122947,0.0000607722,0.000017507195,0.0009494566,0.000029194745,0.0030972424,0.0005353325,0.000020070614,0.0000087700855],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004462363,0.00051621,0.026462523,0.00039749744,0.0001196465,0.000014463159,0.0009635457,0.001413628,0.0032121278,0.8304772,0.1248123,0.011566262],"study_design_scores_gemma":[0.0003002549,0.000076913035,0.0026260396,0.000025546478,0.000008258475,0.0000024548194,0.00013165518,0.988847,0.0004905311,0.0014400127,0.0058999727,0.00015136207],"about_ca_topic_score_codex":0.0000031882228,"about_ca_topic_score_gemma":0.000017762419,"teacher_disagreement_score":0.9874334,"about_ca_system_score_codex":0.000006994397,"about_ca_system_score_gemma":0.000033699453,"threshold_uncertainty_score":0.3632237},"labels":[],"label_agreement":null},{"id":"W4388429739","doi":"10.1007/978-3-031-34738-2_5","title":"Supporting Diverse Research Methods for Observing Huge Variable Space in Empirical Studies for Visualization","year":2023,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Empirical research; Data science; Visualization; Visual analytics; Context (archaeology); Computer science; Pace; Diversity (politics); Space (punctuation); Variable (mathematics); Data visualization; Epistemology; Sociology; Artificial intelligence; Geography; Mathematics","score_opus":0.5368018901033829,"score_gpt":0.6122035467587638,"score_spread":0.0754016566553809,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388429739","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[7.0555944e-7,0.00010719793,0.9807464,0.0006281584,0.00043203583,0.0008437316,0.000044179465,0.00021098163,0.016986609],"genre_scores_gemma":[0.0000068793947,0.00022633186,0.46118984,0.00037470626,0.00014198225,0.000080444326,0.0002282214,0.00005859319,0.537693],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974351,0.00014036863,0.0006563432,0.00079439685,0.00042047253,0.0005533281],"domain_scores_gemma":[0.9951499,0.002964626,0.00024203134,0.0005429772,0.0010064212,0.000094016104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005572729,0.0002448149,0.00050740346,0.0006668812,0.00030174074,0.0002753981,0.00086573453,0.00023752224,0.000038840488],"category_scores_gemma":[0.0032292632,0.00023310947,0.00012003121,0.00051976216,0.00006502046,0.0003884629,0.0012698341,0.00020431301,0.000028336011],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005098861,0.00001702993,0.00002561662,0.0003035585,0.000056989415,0.000002727247,0.0005876083,0.00007099763,0.000019421503,0.95316124,0.042019237,0.0037304678],"study_design_scores_gemma":[0.00032968016,0.00010090016,0.000004443442,0.00023113312,0.000025208821,6.2433827e-7,0.00043226327,0.42083088,0.00006983544,0.2273678,0.3503134,0.00029384397],"about_ca_topic_score_codex":0.000016126964,"about_ca_topic_score_gemma":0.00006412568,"teacher_disagreement_score":0.7257934,"about_ca_system_score_codex":0.00017603587,"about_ca_system_score_gemma":0.00025232756,"threshold_uncertainty_score":0.9505929},"labels":[],"label_agreement":null},{"id":"W4388469749","doi":"10.1109/tvcg.2023.3327378","title":"Challenges and Opportunities in Data Visualization Education: A Call to Action","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Visualization; Data visualization; Call to action; Action (physics); Data science; Information visualization; Geovisualization; Human–computer interaction; Artificial intelligence","score_opus":0.18946053791745945,"score_gpt":0.37912753898058277,"score_spread":0.1896670010631233,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388469749","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002199019,0.00016638069,0.99511707,0.0010941158,0.00065313966,0.00025638985,0.000024412237,0.00038934484,0.00010014442],"genre_scores_gemma":[0.93949014,0.047513835,0.001914611,0.009200939,0.00022455952,0.00011031968,0.0005449503,0.00007836022,0.000922317],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982321,0.00016876467,0.00036505194,0.0006861958,0.00032211439,0.00022576257],"domain_scores_gemma":[0.99884826,0.00009501406,0.00008271073,0.0006297385,0.00014542506,0.00019884379],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044514216,0.00020982839,0.00020161369,0.0013070418,0.00021203331,0.00029631273,0.00044269927,0.00010925552,0.0000043083382],"category_scores_gemma":[0.000009275648,0.00022967895,0.000025073557,0.0013615917,0.00005256464,0.0010423092,0.00004101796,0.0001106528,0.000015075634],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008192864,0.00023604816,0.000027938398,0.00008718256,0.000020086169,0.0000039601073,0.0020747627,0.00029293398,0.000005957088,0.7843547,0.0019355277,0.21095273],"study_design_scores_gemma":[0.00032674937,0.00012199726,0.0013712411,0.00011590709,0.000014094574,0.000015665237,0.00034707488,0.9754877,0.00007707171,0.0009140372,0.020917134,0.00029129567],"about_ca_topic_score_codex":0.00001869385,"about_ca_topic_score_gemma":0.00023515637,"teacher_disagreement_score":0.99320245,"about_ca_system_score_codex":0.000024866158,"about_ca_system_score_gemma":0.000114195864,"threshold_uncertainty_score":0.93660355},"labels":[],"label_agreement":null},{"id":"W4388946115","doi":"10.3389/fcomm.2023.1250301","title":"Epistemological role of human reasoning in data-informed decision-making","year":2023,"lang":"en","type":"article","venue":"Frontiers in Communication","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Visual analytics; Intelligence analysis; Computer science; Data science; Analytics; Cultural analytics; Decision engineering; Analytic reasoning; Objectivity (philosophy); Decision analysis; Human intelligence; Decision support system; Management science; Business decision mapping; Knowledge management; Visualization; Artificial intelligence; Reasoning system; Semantic analytics; Epistemology","score_opus":0.04752972258442963,"score_gpt":0.37310275830191403,"score_spread":0.3255730357174844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388946115","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0710298,0.0008530166,0.920609,0.0006053622,0.00027927876,0.000296591,0.000025434145,0.00024001815,0.0060615237],"genre_scores_gemma":[0.83726716,0.00024443347,0.16220151,0.000045579203,0.000004065597,0.000004324974,0.00019976497,0.0000037891234,0.000029394518],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990114,0.00012875973,0.0003766726,0.00017729438,0.00017318172,0.000132718],"domain_scores_gemma":[0.9978905,0.00022650117,0.00014017316,0.001690447,0.000032529148,0.00001990278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009729372,0.000059294984,0.000151046,0.00026898264,0.00006836638,0.00005312946,0.0025803025,0.000053596697,0.0000034360423],"category_scores_gemma":[0.00057338935,0.000060208993,0.000016097758,0.0011153937,0.0000486385,0.00056811085,0.0013519868,0.00011937929,0.0000074109475],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021381613,0.00024126664,0.36804625,0.000048675334,0.000021629889,0.000010238007,0.004740555,0.0025134913,0.00015185184,0.19683875,0.031272165,0.39609376],"study_design_scores_gemma":[0.00021743716,0.000011917828,0.03621855,0.00023982722,0.0000016951398,8.201949e-7,0.0008336325,0.9270751,0.000028873266,0.032538474,0.0027435634,0.00009010786],"about_ca_topic_score_codex":0.000028998258,"about_ca_topic_score_gemma":0.00013715703,"teacher_disagreement_score":0.9245616,"about_ca_system_score_codex":0.000059844144,"about_ca_system_score_gemma":0.000042307143,"threshold_uncertainty_score":0.4794887},"labels":[],"label_agreement":null},{"id":"W4389108202","doi":"10.5539/cis.v16n4p65","title":"Proposal of a Visualization System for a Hierarchical Clustering Algorithm: The Visualize Proximity Matrix","year":2023,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Qassim University","keywords":"Computer science; Data mining; Cluster analysis; Visualization; Information overload; Process (computing); Data stream mining; Concept mining; Similarity (geometry); Data science; Information retrieval; Machine learning; Artificial intelligence; Web mining; Image (mathematics); World Wide Web","score_opus":0.019600481174563183,"score_gpt":0.3219468395410761,"score_spread":0.3023463583665129,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389108202","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012918497,0.000005428033,0.9972943,0.00033114225,0.00034433193,0.00038813122,0.000015360107,0.00020146961,0.00012799025],"genre_scores_gemma":[0.67159754,0.00008776596,0.3266846,0.0010552529,0.00024149753,0.00010734469,0.0001300914,0.000014435188,0.00008146145],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99869317,0.000036695288,0.0004038569,0.0001785802,0.00047471488,0.00021300095],"domain_scores_gemma":[0.9990079,0.000085715365,0.0001817589,0.00027745255,0.0003708233,0.000076385084],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014337596,0.00008907219,0.00012272474,0.00035116632,0.0003992385,0.0005988906,0.00076662254,0.00002859389,5.7722053e-7],"category_scores_gemma":[0.000069754926,0.00006190746,0.00003323507,0.0019560661,0.0002177045,0.0053633535,0.00055652024,0.000042991836,0.000011829296],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000053399244,0.000018129627,0.000053838074,0.00029440035,0.0000066280795,3.1845389e-7,0.0035661396,0.0012634511,0.00013682262,0.8367052,0.000846707,0.15710303],"study_design_scores_gemma":[0.00024733436,0.000071342714,0.00056618924,0.00003760548,0.000002935996,0.000011949761,0.00011250574,0.9938951,0.00056430476,0.00037075492,0.0040372126,0.00008272892],"about_ca_topic_score_codex":0.0000032003322,"about_ca_topic_score_gemma":2.92087e-7,"teacher_disagreement_score":0.9926317,"about_ca_system_score_codex":0.000024627163,"about_ca_system_score_gemma":0.00018120864,"threshold_uncertainty_score":0.5775116},"labels":[],"label_agreement":null},{"id":"W4389296829","doi":"10.1109/ismar-adjunct60411.2023.00045","title":"Hybrid User Interfaces for Multiple Views: why designer intuition is not enough","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Intuition; Computer science; Human–computer interaction; User interface; Cognitive science; Programming language; Psychology","score_opus":0.10032948849096991,"score_gpt":0.34003513663646057,"score_spread":0.23970564814549067,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389296829","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014362626,0.000007515618,0.9945641,0.0028100829,0.00023190292,0.00017641067,0.000038001028,0.00034029243,0.00039542],"genre_scores_gemma":[0.8406407,0.00013042652,0.1029962,0.030657591,0.00018450567,0.00010066518,0.0003110987,0.00003938956,0.024939407],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991473,0.000027719512,0.00019632303,0.00028288856,0.00015646893,0.00018931131],"domain_scores_gemma":[0.99936205,0.00012250681,0.000050774735,0.00031759046,0.00009395939,0.000053123003],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024107419,0.000093662944,0.00010801621,0.000114623435,0.00009346894,0.00024222788,0.0004866239,0.000023810546,0.00012225608],"category_scores_gemma":[0.00008898173,0.00007786736,0.000050451014,0.00032646497,0.000018345023,0.0005998461,0.00018978195,0.000032118478,0.00057031587],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005928659,0.000054751214,0.000068104884,0.00003353191,0.000020158612,0.0000022249271,0.00068332173,0.00011823517,0.0023758428,0.064386435,0.9141106,0.018140834],"study_design_scores_gemma":[0.00024703785,0.000046103345,0.000030994004,0.000012953279,0.0000041043945,0.0000010951596,0.00003683208,0.50833863,0.07685968,0.0017895504,0.41250932,0.0001237105],"about_ca_topic_score_codex":0.000015081283,"about_ca_topic_score_gemma":0.000013348783,"teacher_disagreement_score":0.8915679,"about_ca_system_score_codex":0.0000152249395,"about_ca_system_score_gemma":0.000019650137,"threshold_uncertainty_score":0.7330447},"labels":[],"label_agreement":null},{"id":"W4389302574","doi":"10.1109/ismar-adjunct60411.2023.00028","title":"Designing Situated Dashboards: Challenges and Opportunities","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Situated; Computer science; Visualization; Human–computer interaction; Field (mathematics); Augmented reality; Data science; Data visualization; The Internet; World Wide Web; Artificial intelligence","score_opus":0.19674595169569853,"score_gpt":0.3247657505099608,"score_spread":0.1280197988142623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389302574","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00077052234,0.00068553234,0.9633938,0.008413001,0.00009762244,0.000049761456,0.0000016836908,0.0011866217,0.025401467],"genre_scores_gemma":[0.7649788,0.08323817,0.094849326,0.008068342,0.0001769488,0.000014140467,0.00015139599,0.000051342762,0.04847152],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999576,0.00002133445,0.0000636954,0.00013647042,0.00009888121,0.000103634455],"domain_scores_gemma":[0.99970776,0.000036665,0.000016252106,0.00015614962,0.000027836386,0.000055322802],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019574094,0.00004583008,0.000056100296,0.00007256707,0.00006266866,0.00010234866,0.00018922651,0.000017126948,0.00002501093],"category_scores_gemma":[0.000016552834,0.000041336396,0.000008749024,0.00010160713,0.000021107204,0.00027506787,0.00017252177,0.000020195335,0.00011194054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.0472608e-7,0.000012051553,0.000020082187,0.000021288504,0.000014628153,0.000036736088,0.0034744581,0.000019021441,0.00023105707,0.65034926,0.020182766,0.32563826],"study_design_scores_gemma":[0.00033157083,0.00006658164,0.0013557485,0.000040059673,0.000007741571,0.000013381742,0.005320178,0.8795334,0.0008073253,0.01631697,0.095860414,0.00034664568],"about_ca_topic_score_codex":0.000002907599,"about_ca_topic_score_gemma":0.000005263282,"teacher_disagreement_score":0.87951434,"about_ca_system_score_codex":0.0000021116234,"about_ca_system_score_gemma":0.00001632808,"threshold_uncertainty_score":0.16856493},"labels":[],"label_agreement":null},{"id":"W4389520223","doi":"10.18653/v1/2023.emnlp-tutorial.1","title":"NLP+Vis: NLP Meets Visualization","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Leverage (statistics); Visualization; Artificial intelligence; Intersection (aeronautics); Natural language processing; Modalities; Focus (optics); Deep learning","score_opus":0.03612026689251242,"score_gpt":0.33937100465788983,"score_spread":0.3032507377653774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389520223","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00058487715,0.000009955633,0.98213774,0.0017187184,0.00029443146,0.000063351785,0.0000033410388,0.0012016973,0.013985899],"genre_scores_gemma":[0.92644686,0.0002784863,0.016241344,0.00824063,0.00026740142,0.000018888697,0.00044921684,0.000045764355,0.048011426],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991122,0.00003410927,0.00016637033,0.0002431397,0.00026277703,0.00018138679],"domain_scores_gemma":[0.99941957,0.000031730007,0.00004097346,0.00036057146,0.00007225402,0.00007490091],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00021889052,0.00007718287,0.000079616664,0.00018011968,0.000090070746,0.00022613346,0.0005069151,0.000033949116,0.00013321705],"category_scores_gemma":[0.000065698914,0.00006860482,0.000031278472,0.0014962889,0.000014650227,0.0005046508,0.00023858517,0.000026647303,0.0019208641],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.957748e-7,0.000024690733,0.00024537861,0.0000071218697,0.0000062677555,0.0000056198924,0.00017357396,0.00011725986,0.00017622631,0.8935639,0.10057781,0.00510184],"study_design_scores_gemma":[0.00013961252,0.000021826212,0.0008183564,0.000008205824,0.0000030059643,0.0000018987047,0.00004756798,0.80717474,0.0012302651,0.0021341755,0.18828207,0.00013826738],"about_ca_topic_score_codex":0.000009203382,"about_ca_topic_score_gemma":0.0000072039843,"teacher_disagreement_score":0.96589637,"about_ca_system_score_codex":0.000012720334,"about_ca_system_score_gemma":0.00003209587,"threshold_uncertainty_score":0.99885625},"labels":[],"label_agreement":null},{"id":"W4389959486","doi":"10.2196/53627","title":"Data Visualization Support for Tumor Boards and Clinical Oncology: Protocol for a Scoping Review","year":2023,"lang":"en","type":"review","venue":"JMIR Research Protocols","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Protocol (science); Visualization; Medicine; Medical physics; Computer science; Oncology; Alternative medicine; Data mining; Pathology","score_opus":0.877370669870584,"score_gpt":0.7828342816130393,"score_spread":0.09453638825754473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389959486","genre_codex":"protocol","genre_gemma":"protocol","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"protocol","genre_consensus":"protocol","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[2.4620972e-11,0.019066928,0.060630415,0.00020703771,0.000019555131,0.91907156,0.00067582977,0.00022947906,0.00009920244],"genre_scores_gemma":[7.709034e-12,0.26343238,0.0054517505,0.0002716565,0.00030884333,0.7284861,0.0011896427,0.00008293547,0.0007766881],"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","domain_scores_codex":[0.9915674,0.0019162829,0.0025912975,0.001930435,0.0010733395,0.0009212705],"domain_scores_gemma":[0.99150217,0.003066201,0.0011360307,0.0028221493,0.0010602536,0.0004131949],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.021778002,0.00045555498,0.0024145264,0.0004990016,0.00041873378,0.0008752418,0.0047294237,0.00039185825,0.00003496472],"category_scores_gemma":[0.006832459,0.00036002896,0.00037056196,0.0017770438,0.00025002734,0.00088200136,0.0041547613,0.0006527782,0.00011168676],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014898261,0.00023030734,6.6463224e-7,0.40033254,0.00003698795,0.0000066433427,0.0000041773023,1.0007075e-8,9.085412e-9,0.003476702,0.20683827,0.3890588],"study_design_scores_gemma":[0.00087540835,0.0011337945,9.338044e-8,0.37788057,0.00002531526,0.00000785274,0.0000013221025,0.0025053343,1.2125199e-7,0.00013891618,0.61719525,0.00023601044],"about_ca_topic_score_codex":0.0000014705578,"about_ca_topic_score_gemma":0.00001568689,"teacher_disagreement_score":0.410357,"about_ca_system_score_codex":0.00017204638,"about_ca_system_score_gemma":0.007870914,"threshold_uncertainty_score":0.99988514},"labels":[],"label_agreement":null},{"id":"W4389988436","doi":"10.1109/vis54172.2023.00019","title":"Visualizing Query Traversals Over Bounding Volume Hierarchies Using Treemaps","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Connaught Fund","keywords":"Tree traversal; Computer science; Bounding overwatch; Bounding volume; Rendering (computer graphics); Data structure; Computer graphics (images); Tree (set theory); Theoretical computer science; Volume rendering; Data mining; Artificial intelligence; Collision detection; Algorithm; Mathematics","score_opus":0.055496410399415386,"score_gpt":0.3490570143978627,"score_spread":0.2935606039984473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389988436","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.047084846,0.000019923824,0.9474966,0.00034794773,0.0005264433,0.00007460608,0.000007895855,0.0008483996,0.0035933394],"genre_scores_gemma":[0.9149528,0.00012400758,0.05129667,0.0028024707,0.00040259236,0.0000061517185,0.00010831613,0.00006457784,0.030242397],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99867,0.000071051734,0.00025186734,0.00032713177,0.00033369227,0.00034625834],"domain_scores_gemma":[0.99934155,0.00007993014,0.00006801018,0.00036834666,0.00003755101,0.00010463192],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043353398,0.00012759685,0.00015829045,0.0004024264,0.00024518566,0.00059040013,0.00052025664,0.00004319289,0.00012543262],"category_scores_gemma":[0.00007782935,0.000121287165,0.00007152327,0.0014334443,0.000045695404,0.0009518884,0.0003222156,0.00006928184,0.0002743954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003822969,0.00008101893,0.00891155,0.00007747904,0.000079897516,0.00009254743,0.0031943324,0.0014853876,0.009509787,0.9022118,0.06326412,0.011088298],"study_design_scores_gemma":[0.00017227899,0.000017080401,0.001424918,0.000033973756,0.000007059869,0.0000060904586,0.00021932546,0.9662764,0.00070808973,0.0021838224,0.028737338,0.00021358709],"about_ca_topic_score_codex":0.000084949075,"about_ca_topic_score_gemma":0.000018327717,"teacher_disagreement_score":0.96479106,"about_ca_system_score_codex":0.000044641652,"about_ca_system_score_gemma":0.00006814395,"threshold_uncertainty_score":0.5693242},"labels":[],"label_agreement":null},{"id":"W4389989049","doi":"10.1109/vis54172.2023.00044","title":"ProtoGraph: A Non-Expert Toolkit for Creating Animated Graphs","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Human–computer interaction; World Wide Web; Programming language","score_opus":0.03954350554478526,"score_gpt":0.3434310118204041,"score_spread":0.30388750627561883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389989049","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018602759,0.000004989722,0.98914945,0.0005395438,0.00010424772,0.00060842215,0.000010292523,0.00096356444,0.006759235],"genre_scores_gemma":[0.39553046,0.00019010475,0.5602099,0.01021305,0.00026979146,0.0018335071,0.0007136651,0.000111303634,0.030928236],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923813,0.000009770127,0.00015764046,0.00024051126,0.00014029111,0.00021364384],"domain_scores_gemma":[0.99948263,0.000053000087,0.00003972896,0.0002765679,0.00008781566,0.00006023555],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019312276,0.000079374026,0.00009228951,0.00019607255,0.0001438391,0.0002402931,0.00044656557,0.000028440107,0.00002617558],"category_scores_gemma":[0.000057178175,0.00006643966,0.00006411517,0.0014947533,0.000015372301,0.00032362845,0.00013451048,0.000024586328,0.00007217102],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007528099,0.00012041617,0.0023145876,0.00007065386,0.00005237693,0.00000847219,0.0014898701,0.000050944396,0.005270239,0.8087894,0.16676234,0.015063189],"study_design_scores_gemma":[0.00035830383,0.00008874099,0.00060393667,0.000021315256,0.000002779437,0.0000014859565,0.00014739395,0.9593476,0.002702741,0.0030569201,0.033495095,0.00017367362],"about_ca_topic_score_codex":0.000026026077,"about_ca_topic_score_gemma":0.0000062720446,"teacher_disagreement_score":0.95929664,"about_ca_system_score_codex":0.0000050816657,"about_ca_system_score_gemma":0.00002492021,"threshold_uncertainty_score":0.27093306},"labels":[],"label_agreement":null},{"id":"W4389990851","doi":"10.1109/vis54172.2023.00054","title":"HAiVA: Hybrid AI-assisted Visual Analysis Framework to Study the Effects of Cloud Properties on Climate Patterns","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Cloud computing; Computer science; Data science; Environmental science; Climatology; Geology","score_opus":0.028454982485726803,"score_gpt":0.3315924702081687,"score_spread":0.30313748772244187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389990851","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6363418,0.0000045463435,0.36170924,0.0010022551,0.0002745223,0.0003445345,0.000009482437,0.0002438104,0.00006978154],"genre_scores_gemma":[0.9970776,0.000011642569,0.00025431282,0.0023350357,0.0000392377,0.000023406765,0.000011770821,0.000009083625,0.0002379252],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984138,0.00019402278,0.00029459316,0.00035812135,0.0004847075,0.00025472927],"domain_scores_gemma":[0.9987351,0.00025631956,0.00008063091,0.00075385044,0.000095326795,0.00007880954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041462664,0.00014024663,0.0002573858,0.00032725596,0.0001582849,0.00024240493,0.00086709857,0.00002382309,0.000025008578],"category_scores_gemma":[0.00023041244,0.00008190501,0.00011235197,0.002885916,0.000021161322,0.00012726319,0.00057238946,0.00009910479,0.00016406801],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021826554,0.010864332,0.5964455,0.0009477013,0.010370753,0.0004998576,0.032381866,0.012205,0.002843109,0.14827728,0.038517457,0.14642888],"study_design_scores_gemma":[0.0008101031,0.0022939385,0.4312278,0.00022449983,0.0007493132,0.000001952044,0.002057913,0.5339284,0.02692576,0.0003728771,0.00072528096,0.00068215653],"about_ca_topic_score_codex":0.00004920151,"about_ca_topic_score_gemma":0.000026545682,"teacher_disagreement_score":0.5217234,"about_ca_system_score_codex":0.000014707078,"about_ca_system_score_gemma":0.000017107608,"threshold_uncertainty_score":0.33399895},"labels":[],"label_agreement":null},{"id":"W4390681285","doi":"10.1007/978-3-031-49275-4","title":"Graph Drawing and Network Visualization","year":2023,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Universitat Politècnica de Catalunya; Masarykova Univerzita; Università degli Studi di Perugia; Universität Konstanz; University of South Carolina; University of Waterloo; Brown University; University of Crete; Linköpings Universitet; Julius-Maximilians-Universität Würzburg; Technische Universität Berlin; Universität Wien; University of Ioannina; Universiteit Maastricht; Technische Universität Wien; Universiteit Utrecht; Swansea University; Università degli Studi Roma Tre; Universität Osnabrück; Univerzita Karlova v Praze","keywords":"Graph drawing; Computer science; Visualization; Graph; Computer graphics (images); Information visualization; Theoretical computer science; Artificial intelligence","score_opus":0.018498061630371487,"score_gpt":0.2911656766106998,"score_spread":0.2726676149803283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390681285","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000108345785,0.00023290286,0.9967591,0.00025652978,0.0016585068,0.00017829474,0.000003871469,0.0003323566,0.00056757324],"genre_scores_gemma":[0.028473541,0.0016240742,0.92793274,0.019406987,0.006125108,0.00004271566,0.000443953,0.00033018834,0.01562068],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99705803,0.000060530536,0.00040940035,0.0011559651,0.000751105,0.0005649933],"domain_scores_gemma":[0.99830246,0.00037037488,0.0002078417,0.0008087626,0.00015885163,0.00015168164],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001011695,0.0003285531,0.00037041286,0.00078592426,0.00033337987,0.0011301629,0.0018748731,0.00020609071,0.000004109623],"category_scores_gemma":[0.00014220022,0.00031708373,0.000058522248,0.003004988,0.0003906627,0.0007056977,0.0015261653,0.00032758072,0.000034433677],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000031465706,0.000050761417,0.00078705314,0.00020755416,0.000032944223,0.00013683645,0.0019137734,0.20724912,0.000028817738,0.19123466,0.0065708198,0.5917845],"study_design_scores_gemma":[0.00011780155,0.000044975197,0.00017408431,0.00030094484,0.000005824332,0.000013476762,1.2765113e-7,0.83361524,0.00003385224,0.16279292,0.0025339862,0.00036676947],"about_ca_topic_score_codex":0.000006243573,"about_ca_topic_score_gemma":0.000044400946,"teacher_disagreement_score":0.62636614,"about_ca_system_score_codex":0.00013363369,"about_ca_system_score_gemma":0.00056150835,"threshold_uncertainty_score":0.9999281},"labels":[],"label_agreement":null},{"id":"W4391093312","doi":"10.1109/bigdata59044.2023.10386099","title":"Visual Insight Recommendation: From Ranking Insight Visualizations to Insight Types","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Computer science; Visualization; Ranking (information retrieval); Categorical variable; Focus (optics); Variety (cybernetics); Recommender system; Visual analytics; Information retrieval; Rank (graph theory); Data visualization; Class (philosophy); Learning to rank; Human–computer interaction; Information visualization; Data science; Data mining; Machine learning; Artificial intelligence","score_opus":0.04002837939470994,"score_gpt":0.3355294241055158,"score_spread":0.29550104471080585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391093312","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002259432,0.000028812778,0.9650041,0.0051745367,0.0009326336,0.00021552143,0.000025769301,0.0012132071,0.02514603],"genre_scores_gemma":[0.8726519,0.0005454903,0.05329129,0.04230841,0.0012729949,0.00011661187,0.005641024,0.00016660332,0.024005717],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980807,0.00012846918,0.000463158,0.0006067797,0.00038991333,0.00033099361],"domain_scores_gemma":[0.9987868,0.00016415013,0.000098441444,0.0005104499,0.00021345071,0.00022671472],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00023487397,0.00021712536,0.00023771306,0.0005995315,0.00033555212,0.00062149396,0.00077949715,0.00009090976,0.0009511299],"category_scores_gemma":[0.00018691237,0.0002007881,0.000066725064,0.0038553474,0.000025653439,0.0011022025,0.0006786444,0.000104816616,0.0028137355],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017456083,0.0004636848,0.0024779881,0.000029669662,0.00021346573,0.000048833026,0.014151489,0.0014834284,0.002788984,0.6884334,0.17118786,0.1187037],"study_design_scores_gemma":[0.00037618453,0.000055816603,0.0017252979,0.00002890199,0.000013262197,0.0000014623629,0.000087083,0.28200603,0.0027168186,0.0012924303,0.7113349,0.00036181073],"about_ca_topic_score_codex":0.00007807635,"about_ca_topic_score_gemma":0.0001220518,"teacher_disagreement_score":0.91171277,"about_ca_system_score_codex":0.00005329531,"about_ca_system_score_gemma":0.00010643101,"threshold_uncertainty_score":0.99996215},"labels":[],"label_agreement":null},{"id":"W4391094077","doi":"10.1109/bigdata59044.2023.10386692","title":"Complex Networks Exploration With Triangles","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge; University of Northern British Columbia","funders":"","keywords":"Computer science","score_opus":0.10596400943727377,"score_gpt":0.320753748872084,"score_spread":0.21478973943481025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391094077","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00011310672,0.0000019333543,0.99384415,0.0014091356,0.00004913042,0.000038863825,7.041243e-7,0.00044718132,0.004095796],"genre_scores_gemma":[0.9327727,0.00008943405,0.050804008,0.0036057807,0.00019089083,0.00001694653,0.00044462612,0.000018344028,0.012057302],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995825,0.000017473914,0.00007423619,0.00011870915,0.00011218493,0.00009488734],"domain_scores_gemma":[0.99969184,0.000022354814,0.00002250108,0.00019533411,0.000033678894,0.00003427385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009657307,0.000041160132,0.00004854176,0.0000619657,0.000057031328,0.00015485048,0.00022577636,0.000012382752,0.000037146194],"category_scores_gemma":[0.000007364102,0.000029551346,0.000010447785,0.00082377,0.000011199873,0.00047301324,0.00006576257,0.000018885534,0.00019499664],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000030191698,0.000025116688,0.00038377513,0.0000035231742,0.000011145971,0.00001054088,0.00022367977,0.018814206,0.000027938166,0.79743904,0.15969297,0.023365011],"study_design_scores_gemma":[0.00014912941,0.00002426906,0.0005887008,0.0000026698497,0.0000011564382,8.044188e-7,0.000056423596,0.9745445,0.00002749953,0.0006873848,0.023862373,0.000055035707],"about_ca_topic_score_codex":0.0000033661752,"about_ca_topic_score_gemma":0.00001704447,"teacher_disagreement_score":0.9557303,"about_ca_system_score_codex":0.0000041708913,"about_ca_system_score_gemma":0.000011812609,"threshold_uncertainty_score":0.25063524},"labels":[],"label_agreement":null},{"id":"W4391646685","doi":"10.3390/app14041387","title":"A Design Language for Prototyping and Storyboarding Data-Driven Stories","year":2024,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Polytechnique Montréal","keywords":"Computer science; Persona; Storytelling; Human–computer interaction; Narrative; Pluralistic walkthrough; Design language; Visual language; Process (computing); Set (abstract data type); Software engineering; Engineering drawing; Usability; Programming language; Linguistics; Engineering","score_opus":0.1055296468185108,"score_gpt":0.36822724214057917,"score_spread":0.2626975953220684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391646685","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00040975073,0.00039831304,0.9976356,0.00028153637,0.00014623223,0.00033644857,0.0000146371785,0.00017743395,0.0006000367],"genre_scores_gemma":[0.5743737,0.00003579807,0.42468402,0.00041768735,0.00013733632,0.00011719347,0.000029595654,0.000008492357,0.0001961842],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991599,0.000015046515,0.00009029543,0.0004185299,0.00016658203,0.00014966275],"domain_scores_gemma":[0.9995117,0.00016639053,0.000022730566,0.00024780573,0.000012826299,0.000038541086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080383674,0.00006523164,0.00007408095,0.00008989001,0.00025396654,0.0008001286,0.0008111042,0.000016950713,0.0000028062925],"category_scores_gemma":[0.000034813613,0.000051627976,0.000008782111,0.00041131457,0.00012456259,0.0006719735,0.00028119326,0.000034475433,0.000009161791],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000275113,0.00001264167,0.000018520563,0.00010574724,0.000017754086,0.0000039433357,0.0065208157,0.00041575136,0.0038507814,0.9032334,0.008271596,0.07754626],"study_design_scores_gemma":[0.00006849089,0.000034661516,0.000004911913,0.000026546833,0.0000069954685,0.0000028299492,0.00069658825,0.9639421,0.0010739658,0.0019741948,0.032046035,0.00012264827],"about_ca_topic_score_codex":0.0000032064308,"about_ca_topic_score_gemma":0.0000026213627,"teacher_disagreement_score":0.96352637,"about_ca_system_score_codex":0.000009819957,"about_ca_system_score_gemma":0.00010308113,"threshold_uncertainty_score":0.77156585},"labels":[],"label_agreement":null},{"id":"W4391898411","doi":"10.31219/osf.io/3bxmg","title":"Struggles and Strategies in Understanding Information Visualizations","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Information visualization; Data science; Computer science; Epistemology; Visualization; Knowledge management; Philosophy; Artificial intelligence","score_opus":0.05606406378030079,"score_gpt":0.33785935392416144,"score_spread":0.2817952901438607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391898411","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00035314774,0.000086248685,0.98331374,0.00055466173,0.00025045243,0.000104100895,0.000023804701,0.0002113752,0.015102483],"genre_scores_gemma":[0.99115556,0.00028901018,0.007851491,0.00029367727,0.000023945848,0.000009077843,0.00022327939,0.0000073695187,0.00014658833],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99922395,0.000024728599,0.00028084076,0.00019995385,0.00016121668,0.00010928523],"domain_scores_gemma":[0.99960375,0.00002720025,0.00006460685,0.00023235091,0.000032852106,0.000039224233],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00015291151,0.0001208703,0.00011906972,0.0004558136,0.000041700845,0.0021971543,0.0002963881,0.00009727045,0.000016314321],"category_scores_gemma":[0.000019461733,0.000112388356,0.00002093273,0.0003680161,0.000028020702,0.0010482316,0.0013459147,0.00018311999,0.000022161516],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.7009849e-7,0.0000054806833,0.000055965058,0.00015159023,0.0000067201836,0.0000011834123,0.0012407269,0.0014499967,9.0504244e-7,0.9956106,0.0009423208,0.0005343571],"study_design_scores_gemma":[0.000046690875,0.0000047459866,0.00007634488,0.00010462225,0.000004098726,0.0000012140727,0.0016388574,0.55649036,0.0000055346,0.44077748,0.00073676626,0.000113271286],"about_ca_topic_score_codex":0.000055802575,"about_ca_topic_score_gemma":0.00014570274,"teacher_disagreement_score":0.9908024,"about_ca_system_score_codex":0.0000831206,"about_ca_system_score_gemma":0.00021121203,"threshold_uncertainty_score":0.99883866},"labels":[],"label_agreement":null},{"id":"W4391904239","doi":"10.24251/hicss.2023.151","title":"Pair Analytics in a Visual Analytics Context","year":2023,"lang":"en","type":"article","venue":"Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Internship; Computer science; Analytics; Visualization; Work (physics); Data science; Government (linguistics); Knowledge management; Engineering management; Engineering; Artificial intelligence; Medical education","score_opus":0.06607725529150023,"score_gpt":0.33223134455599984,"score_spread":0.2661540892644996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391904239","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05646252,0.000021066375,0.0003619499,0.011756095,0.0048144027,0.0010287084,0.0006857478,0.0003973676,0.92447215],"genre_scores_gemma":[0.9958183,0.000048629463,0.00036018272,0.0002994366,0.0002629501,0.00006489991,0.000009361353,0.000032247353,0.0031039736],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9889317,0.00008841709,0.0022857871,0.0018293303,0.005803295,0.0010614549],"domain_scores_gemma":[0.9897697,0.00030359946,0.0028050132,0.00045089415,0.0063770576,0.00029374406],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.005475152,0.0008016495,0.0010613892,0.0021189055,0.0009236258,0.0017261083,0.014881305,0.00030033517,0.00005321334],"category_scores_gemma":[0.0002973921,0.00054591015,0.00055729726,0.006332426,0.002009806,0.0035519018,0.0026361637,0.00067395344,0.0001168281],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000067041234,0.00022050002,0.012653198,0.00018942905,0.00010149962,0.0000030090475,0.0018544781,0.00041692425,0.0003916542,0.97916746,0.004310954,0.00062384835],"study_design_scores_gemma":[0.0014513406,0.0010561018,0.0073192623,0.0060878396,0.00006898464,0.000118707874,0.88274896,0.09086479,0.0018260098,0.005474817,0.0017906452,0.0011925404],"about_ca_topic_score_codex":0.0002903857,"about_ca_topic_score_gemma":0.00004558613,"teacher_disagreement_score":0.97369266,"about_ca_system_score_codex":0.0006213253,"about_ca_system_score_gemma":0.00085529446,"threshold_uncertainty_score":0.99969923},"labels":[],"label_agreement":null},{"id":"W4392033304","doi":"10.1080/10618600.2024.2322561","title":"Hammock Plots: Visualizing Categorical and Numerical Variables","year":2024,"lang":"en","type":"article","venue":"Journal of Computational and Graphical Statistics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Categorical variable; Mathematics; Statistics; Econometrics; Computer science; Artificial intelligence","score_opus":0.015345263605094658,"score_gpt":0.30025821888867443,"score_spread":0.2849129552835798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392033304","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007856259,0.00081908883,0.99673593,0.0013249444,0.00021504906,0.000023383926,0.00003242902,0.000027612987,0.00003591823],"genre_scores_gemma":[0.74892396,0.00027701393,0.2500044,0.0005805662,0.00015227399,5.3636336e-7,0.000018953528,0.000009733589,0.00003252495],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998826,0.00006353967,0.00041847583,0.00016344704,0.00040235935,0.00012617033],"domain_scores_gemma":[0.9987268,0.00072434376,0.000100015655,0.00005019575,0.00020280405,0.00019582652],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028788662,0.000103938764,0.00019266352,0.00019451881,0.00009912644,0.0004663472,0.00016040806,0.000044885448,0.000010041144],"category_scores_gemma":[0.00012380899,0.00008016427,0.000036786998,0.0004289445,0.000087037704,0.00033497237,0.00009130821,0.00019639933,0.0000027496685],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000051891393,0.00004567671,0.0002661819,0.00004398061,0.0000498803,0.0001238029,0.00011592403,0.0007321936,0.000008373754,0.9796451,0.004240862,0.014722834],"study_design_scores_gemma":[0.00014984899,0.00012406203,0.0020673107,0.00003025478,0.000023030647,0.00039636673,0.0000106839625,0.5485783,0.0000023867194,0.4398024,0.008729287,0.00008606679],"about_ca_topic_score_codex":0.0000036400697,"about_ca_topic_score_gemma":2.977186e-7,"teacher_disagreement_score":0.74813837,"about_ca_system_score_codex":0.000012951654,"about_ca_system_score_gemma":0.000098547054,"threshold_uncertainty_score":0.44969967},"labels":[],"label_agreement":null},{"id":"W4392605842","doi":"10.1007/978-3-031-52113-3_14","title":"Visualization of Bipartite Graphs in Limited Window Size","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Bipartite graph; Window (computing); Graph drawing; Visualization; Theoretical computer science; Algorithm; Artificial intelligence; Graph; World Wide Web","score_opus":0.019977074303522805,"score_gpt":0.28626083946068087,"score_spread":0.26628376515715807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392605842","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00013976212,0.0003646709,0.99548936,0.00031966774,0.0009960989,0.00022726071,0.000012110142,0.00012379234,0.002327257],"genre_scores_gemma":[0.83322066,0.00057745003,0.15903087,0.0038524212,0.0004085327,0.000014312435,0.000084221116,0.00012741568,0.002684111],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969431,0.000031078063,0.00070444244,0.0010730295,0.0008542742,0.00039404462],"domain_scores_gemma":[0.9981003,0.00037359138,0.00026356993,0.0009316269,0.00022526244,0.00010566645],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00071073195,0.00035743715,0.00046482697,0.0016079057,0.000061586536,0.00040192273,0.0019996346,0.00023269151,0.000025541576],"category_scores_gemma":[0.00017897054,0.00033449757,0.0001100606,0.0024986868,0.00041809637,0.0005811676,0.00091195543,0.00037023856,0.0000367278],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006524522,0.000100154284,0.00078524,0.00023872712,0.000022965025,0.00011189602,0.0015150004,0.03274724,0.0005747959,0.86291397,0.00007648926,0.10090703],"study_design_scores_gemma":[0.00021783881,0.00010425407,0.00030156385,0.00082604116,0.0000099215495,0.000012301104,2.2360508e-7,0.76893824,0.0015730639,0.2259771,0.0016085969,0.00043085834],"about_ca_topic_score_codex":0.000020456262,"about_ca_topic_score_gemma":0.00011526359,"teacher_disagreement_score":0.8364585,"about_ca_system_score_codex":0.0001243035,"about_ca_system_score_gemma":0.0003253028,"threshold_uncertainty_score":0.9999107},"labels":[],"label_agreement":null},{"id":"W4392617722","doi":"10.1145/3613904.3642001","title":"DeepSee: Multidimensional Visualizations of Seabed Ecosystems","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Division of Ocean Sciences; Schmidt Ocean Institute; Canadian Institute for Advanced Research; National Aeronautics and Space Administration; California Institute of Technology; Jet Propulsion Laboratory; Nuclear Safety and Security Commission; Center for Dark Energy Biosphere Investigations; National Science Foundation","keywords":"Workflow; Software deployment; Sample (material); Context (archaeology); Computer science; Biogeochemical cycle; Earth science; Seabed; Field (mathematics); Data science; Teamwork; Workspace; Sampling (signal processing); Oceanography; Ecology; Geography; Geology; Telecommunications; Artificial intelligence","score_opus":0.03002611906854111,"score_gpt":0.33272154018892525,"score_spread":0.3026954211203841,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392617722","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007146347,0.00028408816,0.98980653,0.0005609536,0.001616699,0.00023446369,0.00016434264,0.0004022478,0.0062160506],"genre_scores_gemma":[0.7329049,0.0003112034,0.22883004,0.0013280691,0.00046900078,0.00007999425,0.0022157014,0.00012186852,0.033739243],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982001,0.00007813771,0.00055592414,0.0005480104,0.00045268776,0.00016513109],"domain_scores_gemma":[0.99848026,0.00007029138,0.00019031676,0.00085922284,0.0002986989,0.00010123266],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028277797,0.00020680248,0.00031475947,0.00031529402,0.000044207864,0.0001933127,0.0008537619,0.00017074522,0.0001470462],"category_scores_gemma":[0.000058888865,0.00018161174,0.00015174175,0.00049838517,0.000031909927,0.00010018233,0.0033988943,0.00022260088,0.00024200998],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.0992696e-7,0.00008886051,0.000049812657,0.00038943882,0.000078997575,0.0000056017147,0.00022004345,0.0022235035,0.00019447868,0.9736619,0.022690237,0.00039659554],"study_design_scores_gemma":[0.00009367652,0.000012510175,0.00002136475,0.0002367899,0.00002875352,0.0000041261337,0.000021008167,0.9728315,0.0013612469,0.01533187,0.009842376,0.00021478608],"about_ca_topic_score_codex":0.000054753626,"about_ca_topic_score_gemma":0.00003278957,"teacher_disagreement_score":0.970608,"about_ca_system_score_codex":0.000040515322,"about_ca_system_score_gemma":0.00035668732,"threshold_uncertainty_score":0.7405912},"labels":[],"label_agreement":null},{"id":"W4392719529","doi":"10.1109/tvcg.2024.3372129","title":"Analyzing User Behaviour Patterns in a Cross-Virtuality Immersive Analytics System","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Virtuality (gaming); Computer science; Analytics; Visual analytics; Human–computer interaction; Data visualization; Visualization; Cultural analytics; Data science; World Wide Web; Semantic analytics; The Internet; Artificial intelligence","score_opus":0.023509137683006963,"score_gpt":0.31581627923412325,"score_spread":0.2923071415511163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392719529","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022287095,0.000062228646,0.9760641,0.00006009888,0.00090765645,0.00017605457,0.000070853865,0.00034607213,0.000025863073],"genre_scores_gemma":[0.9987404,0.0002379272,0.00037270715,0.00041098945,0.000052667554,0.0000135844075,0.00003609044,0.000027236336,0.0001084518],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997877,0.00017980802,0.00057461724,0.0006990831,0.00037172541,0.00029778853],"domain_scores_gemma":[0.99904,0.000119362914,0.00008787222,0.00043308572,0.00015626014,0.00016342763],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00042124782,0.00027641575,0.0002768249,0.0010734162,0.00023619006,0.00110396,0.0003943524,0.00015362169,0.000013391863],"category_scores_gemma":[0.0000026145235,0.00027984745,0.00014678462,0.0021154305,0.00007314117,0.00087761256,0.000014560359,0.00027928027,0.000016912798],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007949936,0.00023913836,0.0074368124,0.00025828282,0.00009667074,0.00006611391,0.0012518561,0.003391808,0.0000070055135,0.9846405,0.000117201096,0.0024866909],"study_design_scores_gemma":[0.00036281644,0.00009272829,0.0033031185,0.0002857569,0.000045598277,0.000024496318,0.00012754521,0.9946083,0.00035772042,0.00010659576,0.0003698767,0.00031545875],"about_ca_topic_score_codex":0.0000749106,"about_ca_topic_score_gemma":0.00007924625,"teacher_disagreement_score":0.9912165,"about_ca_system_score_codex":0.000096021344,"about_ca_system_score_gemma":0.000074086514,"threshold_uncertainty_score":0.99996537},"labels":[],"label_agreement":null},{"id":"W4392752805","doi":"10.6339/24-jds1121","title":"Testing Perceptual Accuracy in a U.S. General Population Survey Using Stacked Bar Charts","year":2024,"lang":"en","type":"article","venue":"Journal of Data Science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Bar chart; Visualization; Perception; Computer science; Bar (unit); Data visualization; Information visualization; Pie chart; Population; Key (lock); Data science; Survey data collection; Human–computer interaction; Data mining; Psychology; Statistics; Mathematics; Geography","score_opus":0.24662321875917856,"score_gpt":0.4300851825046271,"score_spread":0.18346196374544851,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392752805","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6868399,0.00011727346,0.31200036,0.00018574289,0.0006845215,0.000048558835,0.000069316906,0.000025007743,0.000029340048],"genre_scores_gemma":[0.924145,0.000017660717,0.075569615,0.00010625701,0.0001199243,6.949025e-8,0.000028038281,0.0000044613635,0.0000090075655],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99815625,0.00010308593,0.00047459736,0.00032955027,0.0007115194,0.00022501637],"domain_scores_gemma":[0.9987277,0.0002138615,0.00019419915,0.00050385593,0.0002452486,0.00011514407],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0044902605,0.000081775885,0.00013654905,0.00048614966,0.00012405164,0.0011021567,0.0023681545,0.000020639476,0.0000128328575],"category_scores_gemma":[0.0023480628,0.000067500616,0.000018058194,0.0025367087,0.00011149725,0.0111363465,0.00073210377,0.00015900322,0.000008169129],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026612552,0.00051085965,0.4794505,0.00017827441,0.000049193182,0.00087338424,0.005223976,0.017497225,0.10221811,0.04809641,0.0072043827,0.33867106],"study_design_scores_gemma":[0.00007382543,0.000023752049,0.14939281,0.000100103345,0.0000032360012,0.00009645964,0.000023174045,0.8497407,0.000041393956,0.00011936153,0.00030582806,0.00007937441],"about_ca_topic_score_codex":0.0002407559,"about_ca_topic_score_gemma":0.000038428763,"teacher_disagreement_score":0.83224344,"about_ca_system_score_codex":0.00010762006,"about_ca_system_score_gemma":0.0006612935,"threshold_uncertainty_score":0.9999348},"labels":[],"label_agreement":null},{"id":"W4392961583","doi":"10.5860/ital.v43i1.16867","title":"Supporting Information Visualization Research in an Academic Library","year":2024,"lang":"en","type":"article","venue":"Information Technology and Libraries","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; World Wide Web; Academic library; Visualization; Information visualization; Information retrieval; Information system; Library science; Political science; Data mining","score_opus":0.03258094154188437,"score_gpt":0.36769676261879525,"score_spread":0.33511582107691085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392961583","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03790281,0.00076080667,0.93608946,0.013852305,0.0003794143,0.00041593166,0.000031104184,0.0035034756,0.007064686],"genre_scores_gemma":[0.9918985,0.00030983944,0.005841606,0.0012392472,0.00003275878,0.000030299487,0.00052154606,0.0000069786893,0.00011927446],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989158,0.000052257772,0.00048216697,0.00011819613,0.00019990598,0.00023168745],"domain_scores_gemma":[0.99954665,0.00006821532,0.00007371546,0.0002133195,0.00005054522,0.000047549103],"candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0005049889,0.00008438188,0.000087835055,0.0029760334,0.00016118487,0.0015295248,0.0004928993,0.00024656957,0.00002394751],"category_scores_gemma":[0.00010703727,0.00008006917,0.0000103382745,0.0032972172,0.00014691618,0.063351296,0.00037472544,0.00038438747,0.00011193247],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000020802938,0.000003917015,0.0025257303,0.00006920119,0.0000019723595,0.00000129047,0.0022553946,0.000012167226,0.000004804945,0.89989996,0.0018656367,0.093357824],"study_design_scores_gemma":[0.00016056791,0.00007899665,0.0008922736,0.00011983286,0.0000017284964,0.000018281553,0.0019565625,0.42910698,0.0017245931,0.23396914,0.3318048,0.00016624507],"about_ca_topic_score_codex":0.0000019275826,"about_ca_topic_score_gemma":5.137161e-7,"teacher_disagreement_score":0.95399565,"about_ca_system_score_codex":0.000012002194,"about_ca_system_score_gemma":0.00015672445,"threshold_uncertainty_score":0.999507},"labels":[],"label_agreement":null},{"id":"W4393309602","doi":"10.20343/teachlearninqu.12.10","title":"Using Infographics to Go Public with SoTL","year":2024,"lang":"en","type":"article","venue":"Teaching & Learning Inquiry The ISSOTL Journal","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; MacEwan University; University of Calgary","funders":"University of British Columbia; University of South Dakota","keywords":"Infographic; Computer science; Data mining","score_opus":0.09414059842398834,"score_gpt":0.37049279762981757,"score_spread":0.2763521992058292,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393309602","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024542471,0.00017652285,0.9651016,0.008226299,0.0008534327,0.00006489372,5.618668e-7,0.0004223527,0.0006118535],"genre_scores_gemma":[0.9544759,0.00004389976,0.040808577,0.002150562,0.0009812644,0.0000018063556,0.0000043266014,0.00005345624,0.0014802562],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977272,0.00052167417,0.00033660122,0.0003033091,0.00065578683,0.0004553921],"domain_scores_gemma":[0.9988621,0.00021017407,0.00014779963,0.0004056031,0.00012010542,0.00025421372],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0030590603,0.00019866838,0.00016943824,0.00052351714,0.0013557657,0.004472146,0.0013435764,0.000055628963,0.000022944198],"category_scores_gemma":[0.0004189264,0.00011237035,0.00010037956,0.0010975964,0.00010073945,0.0013766788,0.00036693746,0.0019416672,0.00010697828],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022803284,0.0001623817,0.009728945,0.00007903172,0.00055169675,0.00051124534,0.0621685,0.10776005,0.0013691485,0.5649705,0.028963646,0.22371207],"study_design_scores_gemma":[0.00015318544,0.00017445417,0.00028194423,0.00032722604,0.000036474452,0.0013330852,0.001016739,0.441715,0.000019376977,0.00073701114,0.5539102,0.00029528307],"about_ca_topic_score_codex":0.0000091366355,"about_ca_topic_score_gemma":0.0000032020248,"teacher_disagreement_score":0.92993337,"about_ca_system_score_codex":0.000097538425,"about_ca_system_score_gemma":0.00028044882,"threshold_uncertainty_score":0.9999443},"labels":[],"label_agreement":null},{"id":"W4393476886","doi":"10.5281/zenodo.5173100","title":"Breakpoints into the wild: an exploratory study","year":2021,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Breakpoint; Biology; Genetics","score_opus":0.050239366274563026,"score_gpt":0.3019637521397403,"score_spread":0.25172438586517726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393476886","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00019273907,0.00018695758,0.032855876,0.0012842127,0.00075946545,0.0011840013,0.95929056,0.0014930326,0.002753177],"genre_scores_gemma":[0.0006423594,0.00019903548,0.00017407112,0.00080745266,0.00024715994,9.600913e-8,0.99701613,0.0006298306,0.0002838661],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9961176,0.0014398934,0.00039377046,0.0008523732,0.00084357185,0.00035279014],"domain_scores_gemma":[0.9961185,0.000033150005,0.00021566,0.0025893676,0.00079865963,0.00024466423],"candidate_categories":["sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0014104764,0.0002642714,0.00024711055,0.000302737,0.0028102878,0.004260073,0.006156411,0.00010239988,0.004228164],"category_scores_gemma":[0.0006118023,0.00022724002,0.00006467558,0.0012978918,0.00014936696,0.0008275863,0.006130848,0.00052197615,0.008140048],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000042560546,0.00048275752,1.9739625e-7,0.000030798416,0.0000520546,0.000053867374,0.0022308151,0.000010559267,0.000010290565,0.00059749815,0.9772395,0.019287417],"study_design_scores_gemma":[0.00027251706,0.0002650553,0.000013819206,0.000028553752,0.000028391729,0.00004326357,0.0016422126,0.0007987101,0.000008697379,0.000070693015,0.9965659,0.00026223704],"about_ca_topic_score_codex":0.000045505596,"about_ca_topic_score_gemma":0.0000149998195,"teacher_disagreement_score":0.03772559,"about_ca_system_score_codex":0.00012356915,"about_ca_system_score_gemma":0.000022716975,"threshold_uncertainty_score":0.9992207},"labels":[],"label_agreement":null},{"id":"W4393778003","doi":"10.5281/zenodo.10210701","title":"SyDRA: An Approach to Understand Game Engine Architecture","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Game engine; Architecture; Computer science; Visualization; Human–computer interaction; Artificial intelligence; Art; Visual arts","score_opus":0.05888743987234519,"score_gpt":0.2838341988056311,"score_spread":0.22494675893328592,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393778003","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000034652276,0.000014660448,0.38687947,0.00041490296,0.00016342488,0.0003511153,0.6077905,0.0011982854,0.0031841549],"genre_scores_gemma":[0.0000752547,0.000086591215,0.0017616096,0.00054609857,0.00023818268,4.370983e-8,0.995574,0.0009289036,0.0007893103],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9970821,0.0003794756,0.00033269107,0.0009449044,0.00074634387,0.0005144502],"domain_scores_gemma":[0.9973372,0.000026478183,0.0001345157,0.0016570165,0.00038077656,0.00046398115],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00073151215,0.00029723876,0.00027952285,0.00079435733,0.0010816408,0.0027381324,0.004734251,0.00015871978,0.0007077953],"category_scores_gemma":[0.0005287645,0.00030578437,0.00006729645,0.0019227569,0.0000929722,0.00037003733,0.003540912,0.00051086594,0.020963198],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007104391,0.00015466195,9.718293e-9,0.00009499414,0.00003742271,0.00001652442,0.0004444793,0.0008477023,0.000013978265,0.0036547629,0.9852024,0.009525971],"study_design_scores_gemma":[0.00022046747,0.00018935109,0.0000063288917,0.000039319642,0.000017405162,0.000060997223,0.00012753684,0.0055856174,0.0000059331287,0.00023889916,0.9931587,0.00034944894],"about_ca_topic_score_codex":0.000029557092,"about_ca_topic_score_gemma":0.0000013161585,"teacher_disagreement_score":0.3877835,"about_ca_system_score_codex":0.00016443948,"about_ca_system_score_gemma":0.00001266279,"threshold_uncertainty_score":0.99993944},"labels":[],"label_agreement":null},{"id":"W4393875972","doi":"10.5281/zenodo.5213971","title":"Breakpoints into the wild: an exploratory study","year":2021,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Breakpoint; Biology; Geography; Genetics; Gene","score_opus":0.050239366274563026,"score_gpt":0.3019637521397403,"score_spread":0.25172438586517726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393875972","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00019273907,0.00018695758,0.032855876,0.0012842127,0.00075946545,0.0011840013,0.95929056,0.0014930326,0.002753177],"genre_scores_gemma":[0.0006423594,0.00019903548,0.00017407112,0.00080745266,0.00024715994,9.600913e-8,0.99701613,0.0006298306,0.0002838661],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9961176,0.0014398934,0.00039377046,0.0008523732,0.00084357185,0.00035279014],"domain_scores_gemma":[0.9961185,0.000033150005,0.00021566,0.0025893676,0.00079865963,0.00024466423],"candidate_categories":["sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0014104764,0.0002642714,0.00024711055,0.000302737,0.0028102878,0.004260073,0.006156411,0.00010239988,0.004228164],"category_scores_gemma":[0.0006118023,0.00022724002,0.00006467558,0.0012978918,0.00014936696,0.0008275863,0.006130848,0.00052197615,0.008140048],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000042560546,0.00048275752,1.9739625e-7,0.000030798416,0.0000520546,0.000053867374,0.0022308151,0.000010559267,0.000010290565,0.00059749815,0.9772395,0.019287417],"study_design_scores_gemma":[0.00027251706,0.0002650553,0.000013819206,0.000028553752,0.000028391729,0.00004326357,0.0016422126,0.0007987101,0.000008697379,0.000070693015,0.9965659,0.00026223704],"about_ca_topic_score_codex":0.000045505596,"about_ca_topic_score_gemma":0.0000149998195,"teacher_disagreement_score":0.03772559,"about_ca_system_score_codex":0.00012356915,"about_ca_system_score_gemma":0.000022716975,"threshold_uncertainty_score":0.9992207},"labels":[],"label_agreement":null},{"id":"W4394805064","doi":"10.1109/tvcg.2024.3388560","title":"Struggles and Strategies in Understanding Information Visualizations","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Data visualization; Visualization; Information visualization; Human–computer interaction; Data science; Artificial intelligence","score_opus":0.03140170672593965,"score_gpt":0.29923130613066085,"score_spread":0.2678295994047212,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394805064","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009986135,0.00008910181,0.99771196,0.000115478615,0.0004374352,0.00014855806,0.000019945488,0.00035625914,0.00012264562],"genre_scores_gemma":[0.9976495,0.0008249892,0.00076515006,0.0006668747,0.00002228512,0.000011564032,0.000031469077,0.000012609328,0.000015543617],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99884176,0.00008013208,0.000357766,0.00030237966,0.00024152412,0.00017646304],"domain_scores_gemma":[0.99952173,0.00010536585,0.000047877584,0.00017406348,0.00005834558,0.000092612085],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0001996183,0.00018024123,0.0001445299,0.0010474768,0.00023039825,0.0015346636,0.00015605745,0.00009603569,0.00000960234],"category_scores_gemma":[0.0000025427537,0.00018150354,0.000037764043,0.0014754666,0.00008385461,0.0028181886,0.000008114658,0.00014493323,0.000006609893],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002250094,0.000041212348,0.000032237313,0.00008313952,0.000017764614,0.0000026426626,0.0019124446,0.0010024825,0.0000024902406,0.992368,0.000112907655,0.004422421],"study_design_scores_gemma":[0.00024996276,0.0000848697,0.00014097405,0.00011910401,0.000012061166,0.000015172641,0.00045040424,0.9818429,0.000058173966,0.015231562,0.0015904006,0.00020441947],"about_ca_topic_score_codex":0.000017235054,"about_ca_topic_score_gemma":0.000056267327,"teacher_disagreement_score":0.9969468,"about_ca_system_score_codex":0.000045780354,"about_ca_system_score_gemma":0.000070312126,"threshold_uncertainty_score":0.9995018},"labels":[],"label_agreement":null},{"id":"W4394805079","doi":"10.1109/tvcg.2024.3388517","title":"Animating Hypothetical Trips to Communicate Space-Based Temporal Uncertainty on Digital Maps","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Agence Nationale de la Recherche","keywords":"Computer science; Intersection (aeronautics); TRIPS architecture; Point (geometry); Task (project management); Visualization; Space (punctuation); Data science; Data visualization; Data mining; Geography; Cartography; Mathematics","score_opus":0.03160491896160697,"score_gpt":0.29798217659636406,"score_spread":0.26637725763475706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394805079","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017350005,0.000023039736,0.99572957,0.00092870864,0.0004954262,0.00022368447,0.00008834196,0.0006317219,0.00014451634],"genre_scores_gemma":[0.9921855,0.00004243955,0.0038119154,0.0036856914,0.000049853108,0.000016796079,0.00006725185,0.000034120752,0.00010648404],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99824154,0.0001330354,0.0003891642,0.0005488187,0.00042327985,0.0002641304],"domain_scores_gemma":[0.99879724,0.00025697652,0.000054265725,0.00054148847,0.00010892201,0.00024111118],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00025673644,0.00026849922,0.00022169712,0.0006730541,0.00033795036,0.0014645312,0.0004779523,0.00010372113,0.00001270209],"category_scores_gemma":[0.000006597037,0.00025076978,0.00012677455,0.0015461141,0.00009183299,0.00045677283,0.000014750067,0.000254516,0.000066672386],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025116922,0.00035837077,0.00002614637,0.0000651792,0.00004485131,0.000012098224,0.0005446012,0.008906784,0.000010853617,0.96515685,0.0015387333,0.023310421],"study_design_scores_gemma":[0.0003618122,0.00044191384,0.000021260981,0.00019816055,0.000016076257,0.000009286778,0.00002504871,0.98157495,0.0004087381,0.0011418804,0.015501847,0.00029900073],"about_ca_topic_score_codex":0.000008430901,"about_ca_topic_score_gemma":0.000010272181,"teacher_disagreement_score":0.99191767,"about_ca_system_score_codex":0.00004399088,"about_ca_system_score_gemma":0.00007722936,"threshold_uncertainty_score":0.99999446},"labels":[],"label_agreement":null},{"id":"W4395095858","doi":"10.1007/978-3-031-46549-9_14","title":"Designing and Evaluating Context-Sensitive Visualization Models for Deep Learning Text Classifiers","year":2024,"lang":"en","type":"book-chapter","venue":"Studies in computational intelligence","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Interpretability; Computer science; Artificial intelligence; Machine learning; Visualization; Salient; Context (archaeology); Quality (philosophy); Natural language processing","score_opus":0.21043550978854028,"score_gpt":0.4323086960692927,"score_spread":0.2218731862807524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395095858","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000036834213,0.004252252,0.9856495,0.0001708074,0.00045787517,0.00039140106,0.000016398471,0.000118646734,0.008939383],"genre_scores_gemma":[0.49382964,0.007698574,0.37768877,0.0022543934,0.0006657462,0.00020648222,0.0007420679,0.00030075028,0.11661357],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977714,0.000059709437,0.00067256385,0.0007887812,0.00046627445,0.00024130485],"domain_scores_gemma":[0.9968021,0.0018629318,0.0002928208,0.00014661199,0.0008350443,0.00006050632],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007768664,0.000344314,0.00043825357,0.0004156028,0.00027230085,0.00023730926,0.0002986543,0.00013826622,0.000005143196],"category_scores_gemma":[0.0003838649,0.00035839397,0.000089866124,0.0001936281,0.00027200332,0.0003874548,0.00044166992,0.00030718118,0.00002437717],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000051867214,0.000005353034,0.0000016855498,0.00012469808,0.0001043163,0.0000076448805,0.002947007,0.29321697,0.0000010638989,0.66905725,0.00009324,0.03443558],"study_design_scores_gemma":[0.000055996115,0.00008578604,6.934265e-7,0.0005406886,0.000028600505,0.0000070468786,0.0010145516,0.6030018,0.000013919395,0.39444113,0.0005881692,0.00022163626],"about_ca_topic_score_codex":0.0000029847554,"about_ca_topic_score_gemma":0.00001766117,"teacher_disagreement_score":0.60796076,"about_ca_system_score_codex":0.0002050302,"about_ca_system_score_gemma":0.00011054648,"threshold_uncertainty_score":0.9998868},"labels":[],"label_agreement":null},{"id":"W4396600643","doi":"10.1145/3613904.3642808","title":"Input Visualization: Collecting and Modifying Data with Visual Representations","year":2024,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Agence Nationale de la Recherche; Bpifrance","keywords":"Visualization; Computer science; Data visualization; Information visualization; Visual analytics; Interactive visual analysis; Human–computer interaction; Context (archaeology); Artifact (error); Set (abstract data type); Representation (politics); Modalities; Point (geometry); Creative visualization; Data set; Data science; Artificial intelligence","score_opus":0.07574915973723541,"score_gpt":0.3937754944377531,"score_spread":0.3180263347005177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396600643","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007965916,0.00012703474,0.992818,0.00065355387,0.000095340416,0.00007604161,0.000008449553,0.00038558885,0.005039373],"genre_scores_gemma":[0.9112315,0.00014378362,0.07978138,0.001155293,0.00016731939,0.0000093695635,0.00036930759,0.000030754676,0.00711125],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990212,0.000033319928,0.00015339788,0.0004636851,0.00020735686,0.00012106713],"domain_scores_gemma":[0.9992754,0.000109309556,0.000025467769,0.00046825426,0.000056669676,0.000064917855],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00021173389,0.00008136115,0.000076544704,0.00015121834,0.00018696534,0.0011994966,0.0004137315,0.000021875565,0.000034012974],"category_scores_gemma":[0.00006465363,0.00006478251,0.000007807846,0.0011694052,0.0000319341,0.0015082057,0.0005425132,0.00005210172,0.000018110863],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000029046275,0.00006289706,0.0021154545,0.000108476575,0.00008111666,0.00005276911,0.0014905714,0.00039297176,0.00018181468,0.95551836,0.023371585,0.01662109],"study_design_scores_gemma":[0.0001028257,0.000025997962,0.000103114435,0.0000404257,0.000010990449,0.000034441997,0.00016767127,0.9876774,0.00017485785,0.0003764925,0.011179473,0.000106318425],"about_ca_topic_score_codex":0.000029807758,"about_ca_topic_score_gemma":0.000033079836,"teacher_disagreement_score":0.9872844,"about_ca_system_score_codex":0.00001205309,"about_ca_system_score_gemma":0.00010209396,"threshold_uncertainty_score":0.99983734},"labels":[],"label_agreement":null},{"id":"W4396747732","doi":"10.21203/rs.3.rs-4357108/v1","title":"Visualization of Bipartite Graphs in Limited Window Size","year":2024,"lang":"en","type":"preprint","venue":"Research Square","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Bipartite graph; Window (computing); Visualization; Computer science; Graph drawing; Combinatorics; Mathematics; Theoretical computer science; Artificial intelligence; Graph; World Wide Web","score_opus":0.07999955568712017,"score_gpt":0.43272344387671235,"score_spread":0.3527238881895922,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396747732","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.47432512,0.015955616,0.43180662,0.01544876,0.0060009575,0.010725136,0.0018074644,0.0032597259,0.040670596],"genre_scores_gemma":[0.99692935,0.0007944828,0.001126889,0.000060204307,0.00006005834,0.000051269588,0.00019789727,0.000030339625,0.00074949116],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99649566,0.00054680917,0.00052882,0.0006907316,0.0013113318,0.0004266378],"domain_scores_gemma":[0.99763966,0.0004138121,0.00011067706,0.0010444405,0.0006611743,0.00013021615],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019343854,0.00018256232,0.0003137222,0.0015170452,0.000055258137,0.00045882046,0.0013413655,0.0002342267,0.000057804198],"category_scores_gemma":[0.0010352788,0.00017607612,0.00012437337,0.0038609076,0.00011856915,0.00017602654,0.0036971946,0.00079453835,0.00010417787],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022116168,0.0005937238,0.012773412,0.0050172172,0.00009286538,0.00012672688,0.0031471676,0.0025650829,0.001135091,0.95696807,0.011018856,0.006539676],"study_design_scores_gemma":[0.0006381228,0.00027145995,0.017340101,0.0050200582,0.000018906187,0.0000034119548,0.0002754753,0.7546974,0.0045098914,0.20823692,0.008338997,0.0006492526],"about_ca_topic_score_codex":0.00016850488,"about_ca_topic_score_gemma":0.00009762096,"teacher_disagreement_score":0.7521323,"about_ca_system_score_codex":0.00010849765,"about_ca_system_score_gemma":0.0005053019,"threshold_uncertainty_score":0.7180176},"labels":[],"label_agreement":null},{"id":"W4396752978","doi":"10.2139/ssrn.4820766","title":"Knowledge-Decks: Automatically Generating Presentation Slide Decks Through Provenance of Visualization Applications","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Presentation (obstetrics); Provenance; Visualization; Computer science; Data science; Computer graphics (images); Information retrieval; Engineering drawing; Artificial intelligence; Engineering; Geology; Paleontology","score_opus":0.019612205459977636,"score_gpt":0.3505790171309267,"score_spread":0.33096681167094905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396752978","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00042116086,0.0050519253,0.99042696,0.0005054391,0.00056373765,0.0005140571,0.000021310343,0.000220682,0.0022747342],"genre_scores_gemma":[0.8043362,0.02304987,0.15439774,0.0005231983,0.0030608443,0.0005713544,0.0010136487,0.00030179095,0.012745367],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9965077,0.00021488982,0.0010569595,0.0005890439,0.0005543676,0.0010770055],"domain_scores_gemma":[0.9978156,0.00007034102,0.000809176,0.0006454891,0.00057312736,0.00008627291],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0013837118,0.0003084727,0.000390303,0.00027596203,0.00022710263,0.0006336985,0.0013984605,0.00021953785,0.000010763902],"category_scores_gemma":[0.00015083459,0.00029827788,0.00020738118,0.0008342963,0.000065381566,0.00046958387,0.0010153415,0.0017154301,0.00009214653],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000020725313,0.0001424286,0.00003929774,0.00027295813,0.00016123745,0.0000010868845,0.00068456127,0.0014526526,0.00015476628,0.96227795,0.0012551118,0.033555888],"study_design_scores_gemma":[0.00014577228,0.0000366008,0.0000057467714,0.00021487277,0.0000713268,0.000046247987,0.00019074923,0.48390564,0.00045772456,0.5130386,0.0016733218,0.00021338703],"about_ca_topic_score_codex":0.000025507747,"about_ca_topic_score_gemma":0.00018409203,"teacher_disagreement_score":0.83602923,"about_ca_system_score_codex":0.00083213294,"about_ca_system_score_gemma":0.005419465,"threshold_uncertainty_score":0.99994695},"labels":[],"label_agreement":null},{"id":"W4396832678","doi":"10.1145/3613904.3641916","title":"Design Patterns for Data-Driven News Articles","year":2024,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Workflow; Construct (python library); Data science; Journalism; Subject (documents); Narrative; Chart; World Wide Web; Information retrieval; Database; Sociology","score_opus":0.1512676809492022,"score_gpt":0.365579258758603,"score_spread":0.21431157780940077,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396832678","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000054313856,0.00003111259,0.99735814,0.0017766664,0.00017713451,0.0000901963,0.000029196368,0.00026809797,0.00021513307],"genre_scores_gemma":[0.19591045,0.00007597897,0.7945545,0.0038277614,0.00021314522,0.00001797717,0.00027731765,0.000022071288,0.0051008025],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99940866,0.000017721995,0.00010645445,0.00026241402,0.00009163368,0.00011310819],"domain_scores_gemma":[0.9992835,0.000096468866,0.000010442772,0.00054369937,0.000021043406,0.000044862718],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014508449,0.000050536582,0.000050917104,0.000048054437,0.00003385739,0.00052513025,0.0007985431,0.0000143956095,0.000057234432],"category_scores_gemma":[0.00002398643,0.00003904256,0.000016976686,0.00017430757,0.000006912885,0.0006736216,0.00026267805,0.000020625166,0.00014403243],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000013540018,0.00004549928,0.00021274305,0.0000522536,0.00003501531,0.000011649003,0.00029447072,0.00043068497,0.0002874524,0.47617838,0.30975118,0.21269931],"study_design_scores_gemma":[0.00004931716,0.000018184535,0.000011976345,0.000010042941,0.0000052250425,0.0000016674448,0.000016079599,0.9321113,0.00058141164,0.0020901344,0.06504502,0.000059595055],"about_ca_topic_score_codex":0.000014958142,"about_ca_topic_score_gemma":0.000018522504,"teacher_disagreement_score":0.9316807,"about_ca_system_score_codex":0.000006407297,"about_ca_system_score_gemma":0.000039555456,"threshold_uncertainty_score":0.5063843},"labels":[],"label_agreement":null},{"id":"W4396832691","doi":"10.1145/3613905.3636318","title":"Human-Notebook Interactions: The CHI of Computational Notebooks","year":2024,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Intersection (aeronautics); Computational thinking; Open research; Computational model; Metaphor; Human–computer interaction; Interface (matter); Data science; Artificial intelligence; World Wide Web; Engineering","score_opus":0.0383224153760659,"score_gpt":0.35586257254566445,"score_spread":0.31754015716959855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396832691","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00026493485,0.000039941722,0.9669922,0.0010758342,0.00021555947,0.000049125567,0.0000045401193,0.00013292533,0.031224953],"genre_scores_gemma":[0.9674446,0.0000029396303,0.016027959,0.0013606693,0.00007482034,0.0000045043175,0.000017579243,0.0000066526986,0.015060306],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994547,0.000024156805,0.00016698998,0.00012907892,0.00016254737,0.00006252747],"domain_scores_gemma":[0.9996169,0.000080211736,0.000027725378,0.00020228536,0.00005254447,0.000020329648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012605828,0.000050037364,0.000052515534,0.00007838091,0.00007806129,0.00019633466,0.00038547252,0.000011322416,0.00017525404],"category_scores_gemma":[0.0000107245005,0.000032019438,0.000045083783,0.00017538044,0.00004305679,0.00023692337,0.00012205751,0.000065201784,0.00012529508],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.3937837e-7,0.000014947069,0.0000053669855,0.000009244791,0.000015784559,0.0000012938508,0.0002755377,0.0007681213,0.000097250195,0.9796565,0.013375397,0.005780421],"study_design_scores_gemma":[0.000058063048,0.000016181031,0.00017013376,0.000033622993,0.000006142839,0.000009440251,0.00003705314,0.88457733,0.0006262757,0.035916414,0.07848366,0.00006569945],"about_ca_topic_score_codex":0.0000124904445,"about_ca_topic_score_gemma":0.000008308295,"teacher_disagreement_score":0.96717966,"about_ca_system_score_codex":0.000010432052,"about_ca_system_score_gemma":0.000046303485,"threshold_uncertainty_score":0.19189088},"labels":[],"label_agreement":null},{"id":"W4398427745","doi":"10.7910/dvn/itvlik/hcco5b","title":"pre-merge-commit.sample","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Commit; Merge (version control); Computer science; Database; Parallel computing","score_opus":0.024925237841148414,"score_gpt":0.2811614299723452,"score_spread":0.2562361921311968,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4398427745","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[6.78438e-8,6.7417517e-7,0.14774026,0.00004142519,0.0007333527,0.0001391329,0.85109794,0.00017611902,0.000071060174],"genre_scores_gemma":[8.868618e-7,0.0003511251,0.006762807,0.0032712172,0.00027151138,0.000010101126,0.98906976,0.000018006152,0.00024456152],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99763066,0.000115188195,0.00044498924,0.0008340063,0.00060202926,0.00037311733],"domain_scores_gemma":[0.9963517,0.00013119148,0.00027234037,0.0028321936,0.000086392596,0.0003261625],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00020312275,0.00036899597,0.00041381977,0.0001837765,0.00014932326,0.00057764584,0.0040832236,0.00019823408,0.007867024],"category_scores_gemma":[0.0006164779,0.0003721849,0.00013739798,0.00059843186,0.00006342988,0.0008702242,0.0024822222,0.0003985349,0.20134681],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004254681,0.000069269074,0.0000030533333,0.00008302768,0.00005149379,0.00006384481,0.000025734102,0.0000097763705,0.0000013764909,0.0019498452,0.9973487,0.00038960995],"study_design_scores_gemma":[0.00024536316,0.000042755262,0.0000057781995,0.000038859554,0.000057754107,0.000006472802,0.00000821641,0.0071033756,0.000011578633,0.00012087452,0.99193716,0.00042180426],"about_ca_topic_score_codex":0.00030103902,"about_ca_topic_score_gemma":0.00007894553,"teacher_disagreement_score":0.19347979,"about_ca_system_score_codex":0.00004754022,"about_ca_system_score_gemma":0.00021744303,"threshold_uncertainty_score":0.999873},"labels":[],"label_agreement":null},{"id":"W4398640897","doi":"10.7910/dvn/owgear/pnnrqx","title":"client_regimes.tab","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Business","score_opus":0.02441106733266293,"score_gpt":0.2748419053215183,"score_spread":0.2504308379888554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4398640897","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[3.439764e-8,6.8693515e-7,0.043614883,0.000045401834,0.0008671239,0.00012630656,0.95491993,0.00017014302,0.00025548218],"genre_scores_gemma":[4.2702882e-7,0.00043156193,0.0024643969,0.0035083182,0.0003657339,0.000005699646,0.9926822,0.000012853749,0.0005288165],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978904,0.00008334629,0.00036241926,0.0007778586,0.00056341995,0.00032251535],"domain_scores_gemma":[0.9969628,0.000045628287,0.00025197832,0.002377598,0.00007038962,0.00029159558],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00016827499,0.00032045945,0.00035775936,0.00018312663,0.0001099069,0.00056929054,0.0035043627,0.00018572363,0.0034091927],"category_scores_gemma":[0.00020573306,0.0003123138,0.00012568197,0.00055122783,0.00006388396,0.0007645511,0.002081718,0.00033859082,0.42716086],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000022351514,0.000052207964,7.4157106e-7,0.0000614687,0.00003572544,0.00013043689,0.000012059591,0.0000030606273,0.0000011485705,0.0029444296,0.99638695,0.00036954507],"study_design_scores_gemma":[0.00024097254,0.00003431391,0.000001779255,0.000039573853,0.000048659702,0.000010791251,0.000007632494,0.0029921357,0.0000081302605,0.00005093853,0.9962066,0.0003584659],"about_ca_topic_score_codex":0.000046051922,"about_ca_topic_score_gemma":0.000014029588,"teacher_disagreement_score":0.42375168,"about_ca_system_score_codex":0.000044693857,"about_ca_system_score_gemma":0.00021699471,"threshold_uncertainty_score":0.9999329},"labels":[],"label_agreement":null},{"id":"W4398910617","doi":"10.7910/dvn/q20fb7/pvwkjf","title":"unveiling_replication.Rproj","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Replication (statistics); Computer science; Biology; Virology","score_opus":0.024699788749320065,"score_gpt":0.2825623458019117,"score_spread":0.25786255705259165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4398910617","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[5.0207202e-8,5.625944e-7,0.06694969,0.00006509913,0.00041082696,0.00013789975,0.93209344,0.0002009445,0.00014150102],"genre_scores_gemma":[0.000001208945,0.0002750664,0.0043091197,0.0034587025,0.00020950017,0.00001122814,0.9914918,0.000012269047,0.00023111871],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980911,0.00006173265,0.00035902235,0.0007905049,0.0004563491,0.00024129545],"domain_scores_gemma":[0.9965547,0.00005251366,0.0002501761,0.0028171018,0.00010169607,0.00022386319],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00018529328,0.000262626,0.00028239514,0.0001531749,0.00011441346,0.00048371247,0.0031651978,0.00016454252,0.0022449875],"category_scores_gemma":[0.00034946072,0.0002617122,0.00009271665,0.0005582896,0.00005244738,0.00056807115,0.0013913978,0.0002895603,0.33509314],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002159877,0.000047003257,8.5305476e-7,0.00005971712,0.000027471764,0.00003629454,0.0000113686065,0.0000036540398,0.0000031510242,0.0021982673,0.9970156,0.0005944735],"study_design_scores_gemma":[0.00015239952,0.000033434106,0.000002564442,0.000029413972,0.00003549397,0.0000086934115,0.0000048351662,0.0051126797,0.00001607058,0.000097940676,0.9942117,0.00029480743],"about_ca_topic_score_codex":0.000041550767,"about_ca_topic_score_gemma":0.000010366685,"teacher_disagreement_score":0.33284816,"about_ca_system_score_codex":0.000045726963,"about_ca_system_score_gemma":0.00025052953,"threshold_uncertainty_score":0.9999835},"labels":[],"label_agreement":null},{"id":"W4398989438","doi":"10.7910/dvn/qbp1xw/sahubz","title":"Brennan_effect_sizes_from_model_params.xlsx","year":2011,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Psychology","score_opus":0.027371752686289632,"score_gpt":0.27035040481556033,"score_spread":0.2429786521292707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4398989438","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[3.1587228e-7,0.0000013513179,0.11743148,0.0000035531605,0.0010419526,0.00017092646,0.88058686,0.00017835235,0.0005852295],"genre_scores_gemma":[0.0000028835364,0.000298633,0.00391272,0.0009955417,0.00016341156,0.0000154902,0.9938595,0.000020859246,0.0007309356],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974896,0.00015223042,0.00044412934,0.00090921635,0.00051595614,0.00048888446],"domain_scores_gemma":[0.99531275,0.00006928882,0.00031118267,0.0039178776,0.000104248815,0.00028462592],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003663135,0.00045070954,0.00046000857,0.00031604234,0.00014207605,0.000422252,0.0042386497,0.00031012652,0.0104392115],"category_scores_gemma":[0.00014443722,0.000435718,0.00016446652,0.00045426172,0.00010310038,0.0010451077,0.0019415279,0.00039020367,0.28339797],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000044912153,0.000124661,7.711265e-7,0.00006912269,0.00005221015,0.00010390174,0.000022710308,0.000005148225,0.0000022341235,0.0031727904,0.99595034,0.00049159664],"study_design_scores_gemma":[0.00029883446,0.000054580836,0.000003827932,0.00006365819,0.000068261055,0.000025083105,0.0000032698463,0.0055931285,0.000020796262,0.00019666806,0.99315363,0.0005182874],"about_ca_topic_score_codex":0.00027824484,"about_ca_topic_score_gemma":0.000047223162,"teacher_disagreement_score":0.27295876,"about_ca_system_score_codex":0.000056481953,"about_ca_system_score_gemma":0.00019725792,"threshold_uncertainty_score":0.99980944},"labels":[],"label_agreement":null},{"id":"W4399199491","doi":"10.1145/3656650.3656683","title":"Flexible Visual Preference Inspection in Group Decision Making","year":2024,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Preference; Group decision-making; Visualization; Computer science; Stakeholder; Human–computer interaction; Group (periodic table); User group; Decision support system; Decision analysis; Decision model; R-CAST; Artificial intelligence; Management science; Business decision mapping; Machine learning; Engineering; Psychology; Multimedia; Statistics; Mathematics","score_opus":0.043849714954188726,"score_gpt":0.35736424309447157,"score_spread":0.31351452814028286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399199491","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0041264505,0.000069019625,0.98724884,0.00008517601,0.00036787218,0.000043363427,6.165846e-7,0.000564407,0.007494272],"genre_scores_gemma":[0.9779176,0.00003207274,0.021353267,0.00022201626,0.00003429111,0.0000026015462,0.000004204439,0.0000045569354,0.0004293485],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924225,0.000019086636,0.00015994246,0.00027420704,0.00018496916,0.00011953119],"domain_scores_gemma":[0.9997148,0.00006159567,0.000013632468,0.0001649838,0.000018205244,0.000026802463],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019550434,0.00006307441,0.000060125516,0.0002589268,0.000039062175,0.00046027193,0.00027906633,0.00003138673,0.000064338696],"category_scores_gemma":[0.000028966448,0.000053426153,0.000020395739,0.0010018991,0.000009990753,0.00082015025,0.00017197538,0.00007356862,0.00020809517],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021142923,0.000048577916,0.00061957166,0.000015758435,0.0000027281744,0.0000131408715,0.0001758848,0.00013456043,0.00014677548,0.76800907,0.0027393107,0.22809252],"study_design_scores_gemma":[0.00006992698,0.000036265592,0.0027903998,0.00014203652,0.0000011572714,0.0000054547086,0.000023904351,0.97539747,0.00029423556,0.012903247,0.008242419,0.000093464165],"about_ca_topic_score_codex":0.000014520354,"about_ca_topic_score_gemma":0.000070499766,"teacher_disagreement_score":0.97526294,"about_ca_system_score_codex":0.00004688674,"about_ca_system_score_gemma":0.000029449126,"threshold_uncertainty_score":0.44384128},"labels":[],"label_agreement":null},{"id":"W4399203219","doi":"10.1145/3656650.3656697","title":"Supporting Exploration of Women’s Print History Project Data via Interactively Constructing Networks of Interest","year":2024,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Universitas Brawijaya","keywords":"Computer science; Visualization; Domain (mathematical analysis); Focus (optics); Data visualization; World Wide Web; Information visualization; Data science; Data exploration; Multimedia; Data mining","score_opus":0.18181493032428858,"score_gpt":0.3805664437045152,"score_spread":0.19875151338022662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399203219","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0077079027,0.00004478318,0.9906861,0.000053775457,0.0004814174,0.000083976534,0.000006212521,0.00008728703,0.00084854604],"genre_scores_gemma":[0.9804358,0.00000949242,0.019230237,0.000054305932,0.0000335008,0.000003733918,0.000051847797,0.0000064559504,0.00017461913],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989595,0.00004991908,0.00044965182,0.0002838007,0.000107195556,0.00014997374],"domain_scores_gemma":[0.9990737,0.000093205206,0.00022574056,0.00048314309,0.0000909911,0.000033240838],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006583556,0.000074823045,0.00014467906,0.00016133886,0.000012742689,0.000060985738,0.00065870764,0.000025140444,0.00006607954],"category_scores_gemma":[0.00014954306,0.00006595233,0.000023566588,0.0002500821,0.00005190872,0.0020111308,0.0007019973,0.00009122841,0.0000032689084],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001852797,0.00021046304,0.00087940355,0.0006775868,0.00021355988,0.00001808311,0.025240172,0.00042291716,0.0061535765,0.5699528,0.010330142,0.38588277],"study_design_scores_gemma":[0.000058690926,0.0000427343,0.000012351547,0.00012265526,0.0000057433094,0.0000056142258,0.0016416744,0.98471814,0.0020920066,0.0003477943,0.010869319,0.00008328205],"about_ca_topic_score_codex":0.00004247477,"about_ca_topic_score_gemma":0.000020195524,"teacher_disagreement_score":0.9842952,"about_ca_system_score_codex":0.00018503338,"about_ca_system_score_gemma":0.00019501647,"threshold_uncertainty_score":0.26894578},"labels":[],"label_agreement":null},{"id":"W4399332714","doi":"10.1680/jgeot.23.00243","title":"Footprints on the beach: visualising dilation-induced air entry","year":2024,"lang":"en","type":"article","venue":"Géotechnique","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University; Royal Military College of Canada","funders":"","keywords":"Dilation (metric space); Geology; Mathematics; Geometry","score_opus":0.03863093687255568,"score_gpt":0.3211548431842524,"score_spread":0.2825239063116967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399332714","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0033417519,0.000021395905,0.98099726,0.0070074643,0.00028304785,0.0001838849,0.0000040640816,0.0009398649,0.0072212396],"genre_scores_gemma":[0.99356925,0.000012848422,0.0032380724,0.00242091,0.000104038736,0.000019628213,0.000013644457,0.00001383359,0.0006077475],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990636,0.000073050884,0.00016582017,0.0002921867,0.00024448178,0.00016087247],"domain_scores_gemma":[0.999207,0.00014364626,0.00003445216,0.00053465826,0.00003386192,0.00004638861],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043159118,0.000108034554,0.00007716,0.00013019571,0.00013578414,0.00031858092,0.00061582844,0.0000724091,0.000026537793],"category_scores_gemma":[0.00007597507,0.00007658956,0.000056025274,0.00059910037,0.000021302645,0.00024021158,0.00017952955,0.00020813354,0.00012855057],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.117122e-7,0.000026578211,0.000017275752,0.000010496991,0.00000980613,0.00001173914,0.0002297159,0.000019729121,0.0032553016,0.96443784,0.010364071,0.021616725],"study_design_scores_gemma":[0.00013283377,0.00015344101,0.00074780855,0.0005139885,0.00001734335,0.00003335384,0.000052313764,0.37008062,0.28109714,0.04870785,0.29788285,0.00058044115],"about_ca_topic_score_codex":0.000007849106,"about_ca_topic_score_gemma":0.0000015910497,"teacher_disagreement_score":0.9902275,"about_ca_system_score_codex":0.00004538025,"about_ca_system_score_gemma":0.0000574582,"threshold_uncertainty_score":0.31232315},"labels":[],"label_agreement":null},{"id":"W4399588815","doi":"10.32614/cran.package.shinystan","title":"shinystan: Interactive Visual and Numerical Diagnostics and Posterior Analysis for Bayesian Models","year":2015,"lang":"en","type":"dataset","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":71,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Stantec (Canada)","funders":"","keywords":"Bayesian probability; Interactive visual analysis; Computer science; Posterior probability; Visual analytics; Artificial intelligence; Visualization","score_opus":0.028924167382870954,"score_gpt":0.33997905592902816,"score_spread":0.3110548885461572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399588815","genre_codex":"methods","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000031438117,0.00007094753,0.5401245,0.0001352402,0.0000652336,0.00012561413,0.45943415,0.000024930036,0.000016262195],"genre_scores_gemma":[0.00090184965,0.00033799664,0.014138658,0.0012406809,0.0000861382,0.000022607344,0.9831049,0.0000147208075,0.00015245604],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983462,0.00007210511,0.00036306973,0.00066768064,0.0003073841,0.00024356217],"domain_scores_gemma":[0.9983406,0.00041472894,0.0002001471,0.0004982804,0.00024134063,0.00030487665],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00024796795,0.000293884,0.00057796505,0.00041173317,0.00008708232,0.00076398766,0.000561737,0.00016890287,0.00002672563],"category_scores_gemma":[0.00025657882,0.00025292308,0.000090362475,0.00057485246,0.000059945443,0.000695995,0.00075844553,0.00014791335,0.0000056424456],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011805056,0.00010143643,0.000022397568,0.000043256743,0.0003325763,0.000009874646,0.000091457354,0.00005317619,1.9366858e-7,0.0010548726,0.99712557,0.0011534137],"study_design_scores_gemma":[0.00025993286,0.00021638622,0.00001721003,0.00002023738,0.00048381073,0.000009823459,0.00005259891,0.7145009,0.0000019850902,0.00081749115,0.28329897,0.00032067252],"about_ca_topic_score_codex":0.00011609285,"about_ca_topic_score_gemma":0.00010988233,"teacher_disagreement_score":0.7144477,"about_ca_system_score_codex":0.000042179337,"about_ca_system_score_gemma":0.00010326753,"threshold_uncertainty_score":0.9999923},"labels":[],"label_agreement":null},{"id":"W4399800684","doi":"10.32628/ijsrset24113140","title":"Brushstrokes of Tomorrow: Exploring the Art of AI","year":2024,"lang":"en","type":"article","venue":"International Journal of Scientific Research in Science Engineering and Technology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Cognitive science; Art; Psychology","score_opus":0.0698952306295146,"score_gpt":0.39071769062015826,"score_spread":0.3208224599906437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399800684","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.83542234,0.0007943737,0.14436859,0.015227507,0.0038419585,0.000074557145,0.000006288285,0.000038916944,0.00022548417],"genre_scores_gemma":[0.9972777,0.00008673462,0.0025264227,0.0000037769303,0.00002432329,0.0000014477065,1.9485364e-7,0.0000020048074,0.000077388926],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99821836,0.00001700658,0.00032134852,0.00016664893,0.0011049404,0.00017169834],"domain_scores_gemma":[0.9986223,0.00015909446,0.000055909397,0.00019967013,0.0009232753,0.000039742827],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004572481,0.000042219865,0.00009005386,0.0034484374,0.00005225794,0.00037847433,0.0020310802,0.000020054857,0.0000028815068],"category_scores_gemma":[0.0006793966,0.000029233814,0.000023668328,0.0038895428,0.0010039269,0.0009208734,0.0004266821,0.00031631967,0.0000020920038],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000027973852,0.000047967438,0.0012341073,0.00003101661,0.000019864958,0.000060995906,0.0006023379,0.0023754672,0.12564087,0.8238664,0.00061411806,0.045504056],"study_design_scores_gemma":[0.00024138673,0.00017909665,0.0013715007,0.00096111966,0.000003287883,0.00030962395,0.0006178015,0.6881213,0.2534656,0.018950079,0.03565844,0.00012073929],"about_ca_topic_score_codex":0.0000032701744,"about_ca_topic_score_gemma":0.0000014698214,"teacher_disagreement_score":0.8049163,"about_ca_system_score_codex":0.000045354394,"about_ca_system_score_gemma":0.00030357283,"threshold_uncertainty_score":0.3774286},"labels":[],"label_agreement":null},{"id":"W4399803839","doi":"10.4204/eptcs.403.16","title":"Uniform Sampling and Visualization of 3D Reluctant Walks","year":2024,"lang":"en","type":"article","venue":"Electronic Proceedings in Theoretical Computer Science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Orthant; Random walk; Sampling (signal processing); Sample (material); Visualization; Mathematics; Statistical physics; Combinatorics; Computer science; Statistics; Data mining; Physics; Computer vision","score_opus":0.010211621795285286,"score_gpt":0.29270100765312157,"score_spread":0.2824893858578363,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399803839","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019357344,0.00026364683,0.97817916,0.0003301342,0.0001553836,0.000106671796,7.761658e-7,0.00016107706,0.0014458131],"genre_scores_gemma":[0.969103,0.00012994123,0.030567963,0.00013968181,0.00004071135,0.0000029141786,0.0000011728663,0.000008182403,0.000006424569],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980764,0.000010606435,0.00033201344,0.00060007896,0.0004778687,0.00050303934],"domain_scores_gemma":[0.9994418,0.00007856493,0.00005570037,0.00016596695,0.000161156,0.000096835625],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016401485,0.00013492454,0.00016505754,0.00046987634,0.00011522701,0.00057328556,0.0009671803,0.00004821986,0.000008176469],"category_scores_gemma":[0.00012886524,0.00011524415,0.000023007628,0.0027454386,0.0008060684,0.0011509679,0.000565419,0.00018822393,0.0000039623305],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000020623088,0.000021437087,0.00010957478,0.000049579623,0.000002770598,0.0000012788672,0.0005437524,0.000020390415,0.0009710598,0.97736853,0.000007734874,0.020901805],"study_design_scores_gemma":[0.000082213875,0.00014307258,0.0001518414,0.00012251745,0.0000033243286,0.000029530169,0.0000100111765,0.79465514,0.0026014678,0.20166703,0.00041035295,0.00012348316],"about_ca_topic_score_codex":0.0000017783447,"about_ca_topic_score_gemma":5.4340177e-7,"teacher_disagreement_score":0.94974566,"about_ca_system_score_codex":0.00012806528,"about_ca_system_score_gemma":0.00024245567,"threshold_uncertainty_score":0.5528206},"labels":[],"label_agreement":null},{"id":"W4400097509","doi":"10.2196/55182","title":"Use of Creative Frameworks in Health Care to Solve Data and Information Problems: Scoping Review","year":2024,"lang":"en","type":"review","venue":"JMIR Human Factors","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Preprint; Data science; Computer science; Health care; World Wide Web; Political science","score_opus":0.19010805070764278,"score_gpt":0.47368437844436073,"score_spread":0.2835763277367179,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400097509","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[6.0572086e-7,0.98325175,0.013909983,0.000053436976,0.00007088093,0.002191737,0.00043571368,0.000050793413,0.000035099245],"genre_scores_gemma":[0.0000021114165,0.99542034,0.0014532717,0.00046075697,0.000012891593,0.000046668974,0.0025752268,0.000012709602,0.000016031772],"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979505,0.00009901974,0.0010812383,0.00040181653,0.00028244974,0.00018497703],"domain_scores_gemma":[0.99817306,0.00007796502,0.00054366817,0.0010015523,0.000089756606,0.00011401468],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031652846,0.0002631776,0.0010825341,0.00052487885,0.000055600998,0.00039550182,0.0009866842,0.00016634463,0.000010102126],"category_scores_gemma":[0.00016576506,0.00020192486,0.00007222798,0.0010221365,0.00002649175,0.0020446677,0.0011901676,0.00041133308,0.000016428334],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.2628824e-7,0.00001837803,0.000007356245,0.56746054,0.00003379363,8.7780217e-7,0.004994625,0.0000024160804,3.97213e-9,0.0065223644,0.007095625,0.41386387],"study_design_scores_gemma":[0.000017219423,0.00003368728,0.000004578954,0.47168776,0.00003459781,5.449954e-7,0.000044481338,0.00009664509,2.458917e-8,0.000009692034,0.52792346,0.00014729876],"about_ca_topic_score_codex":0.000063528765,"about_ca_topic_score_gemma":0.00008426857,"teacher_disagreement_score":0.52082783,"about_ca_system_score_codex":0.000116196956,"about_ca_system_score_gemma":0.00042140728,"threshold_uncertainty_score":0.82342565},"labels":[],"label_agreement":null},{"id":"W4400153797","doi":"10.1007/978-3-031-60916-9_7","title":"The Role of Directed Edges","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in social networks","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science","score_opus":0.012308135807440139,"score_gpt":0.2636502139003343,"score_spread":0.25134207809289416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400153797","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[9.325186e-7,0.02017729,0.66337395,0.0012474457,0.001593176,0.00022747226,0.000028755954,0.0003156462,0.31303537],"genre_scores_gemma":[0.5915005,0.01770578,0.0090756165,0.005946261,0.026386153,0.000067272886,0.0010776035,0.0007247881,0.34751603],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99897486,0.000025858819,0.00028736828,0.00027805468,0.00023397268,0.00019989273],"domain_scores_gemma":[0.99910575,0.00034302953,0.0001498787,0.00029679647,0.00007718556,0.000027382308],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016230495,0.0001954904,0.00026192318,0.00007341574,0.00014214727,0.0001654648,0.0007474802,0.0003826015,0.000020519601],"category_scores_gemma":[0.00004538318,0.00014458087,0.0001327125,0.00021306566,0.00012918659,0.00004469801,0.00029291323,0.00052495487,0.00001370207],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000022727797,0.000005127261,0.000009323482,0.000010155313,0.00004616315,0.0000042193687,0.000309832,0.0008138625,0.0000013840664,0.80032986,0.001867103,0.19660069],"study_design_scores_gemma":[0.00004405572,0.000014119582,0.0000063636526,0.00009826943,0.000021938802,7.798429e-7,0.0000020222915,0.12956397,0.000017473829,0.5031723,0.36688817,0.00017052346],"about_ca_topic_score_codex":0.000006957715,"about_ca_topic_score_gemma":0.00013347813,"teacher_disagreement_score":0.6542983,"about_ca_system_score_codex":0.000040437393,"about_ca_system_score_gemma":0.00005657632,"threshold_uncertainty_score":0.5895837},"labels":[],"label_agreement":null},{"id":"W4400375525","doi":"10.48550/arxiv.2407.02611","title":"Co-Designing Unstructured Text Data Visualization Systems","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Unstructured data; Computer science; Visualization; Data visualization; Information visualization; Data science; Data mining; Big data","score_opus":0.12732811416337708,"score_gpt":0.26076424956592836,"score_spread":0.13343613540255128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400375525","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013707387,0.00019447679,0.9930134,0.000044265133,0.0014493294,0.0002563818,0.0002658803,0.00061967445,0.0027858482],"genre_scores_gemma":[0.99375826,0.0002065969,0.0010125116,0.00010346861,0.00017164717,4.191374e-7,0.0015686463,0.000034908284,0.0031435613],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99749684,0.00020084198,0.00029896433,0.0015375278,0.00017811745,0.00028769244],"domain_scores_gemma":[0.9967547,0.00006772119,0.0002722833,0.002585441,0.00015892103,0.00016090643],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00040287452,0.00032282138,0.00032881845,0.00043467694,0.00015459539,0.0009517257,0.0038597109,0.00027827546,0.000028314773],"category_scores_gemma":[0.000055949353,0.00035836568,0.00008488194,0.0010583814,0.0000761089,0.00060072966,0.0042219884,0.0004201261,0.00030002874],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000040191094,0.000034198558,0.00021292709,0.00033953146,0.00014151007,0.00021238446,0.00017780226,0.10425931,0.00005503243,0.87942034,0.014842668,0.00030030252],"study_design_scores_gemma":[0.00016531607,0.000013798238,0.000021009977,0.00022483035,0.00010431103,0.000007131504,0.00010034544,0.97832596,0.00007320575,0.013553971,0.007011627,0.00039847853],"about_ca_topic_score_codex":0.00008995603,"about_ca_topic_score_gemma":0.000010689324,"teacher_disagreement_score":0.9923875,"about_ca_system_score_codex":0.00015472675,"about_ca_system_score_gemma":0.00034138758,"threshold_uncertainty_score":0.9998868},"labels":[],"label_agreement":null},{"id":"W4400412785","doi":"10.1007/978-3-031-54650-1_15","title":"Multivariate Data Analysis","year":2024,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":96,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"","keywords":"Multivariate statistics; Multivariate analysis; Computer science; Statistics; Data mining; Mathematics","score_opus":0.08694553972968545,"score_gpt":0.3474566060413113,"score_spread":0.26051106631162585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400412785","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[2.6810554e-9,0.0001165884,0.5097752,0.000230193,0.00013978065,0.000024043853,0.00020871763,0.00017018017,0.4893353],"genre_scores_gemma":[0.000033729662,0.00008271491,0.018531704,0.00048875384,0.00008264422,3.34944e-7,0.0019735906,0.00001668916,0.97878987],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985297,0.0000049674195,0.00025834193,0.00079170393,0.00029907067,0.00011623744],"domain_scores_gemma":[0.9969468,0.000032612268,0.00007968068,0.0028079622,0.000053520598,0.00007939569],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00018367184,0.00018750914,0.000271182,0.00046183963,0.00003361084,0.00049187406,0.002651738,0.00011445407,0.0011635299],"category_scores_gemma":[0.000011773362,0.00015313258,0.00012723729,0.00027120576,0.000022011121,0.00032898318,0.0023276939,0.00014662925,0.0028000507],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.075577e-7,0.000003818166,6.123851e-7,0.000009288227,0.00068575214,0.000020969883,0.0000119224305,0.000014832281,3.1639874e-7,0.9582389,0.03825335,0.002760113],"study_design_scores_gemma":[0.000017745564,0.0000026869156,0.0000010840258,0.00001165009,0.00039480036,7.147932e-7,4.963266e-7,0.4319046,6.6124585e-7,0.0250381,0.54249334,0.0001341128],"about_ca_topic_score_codex":0.000025933658,"about_ca_topic_score_gemma":0.000060115934,"teacher_disagreement_score":0.93320084,"about_ca_system_score_codex":0.00001735991,"about_ca_system_score_gemma":0.00005593194,"threshold_uncertainty_score":0.99974954},"labels":[],"label_agreement":null},{"id":"W4400952056","doi":"10.2196/49865","title":"Introducing Attribute Association Graphs to Facilitate Medical Data Exploration: Development and Evaluation Using Epidemiological Study Data","year":2024,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Interpretability; Computer science; Data mining; Data science; Missing data; Data visualization; Visualization; Graph; Information retrieval; Machine learning; Theoretical computer science","score_opus":0.3586384535112016,"score_gpt":0.4528394844592802,"score_spread":0.09420103094807858,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400952056","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03448123,0.00008115685,0.9591409,0.0048606163,0.00052095804,0.0005957396,0.00007365797,0.00019304515,0.000052707062],"genre_scores_gemma":[0.5318998,0.0005242444,0.43418738,0.015376788,0.0013308139,0.00024097222,0.016090795,0.000056368393,0.0002928411],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99474174,0.00035618423,0.0011806589,0.0004805898,0.0029346687,0.00030616784],"domain_scores_gemma":[0.9973117,0.00059291057,0.00016329708,0.0012738662,0.00019864022,0.0004595599],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.016502803,0.00017527163,0.00030043916,0.00020332997,0.00018510871,0.0005036047,0.0021076615,0.00016632318,0.00009788526],"category_scores_gemma":[0.0076510874,0.00013501773,0.000016872644,0.00089519436,0.000039904397,0.0032157453,0.003686345,0.00033924312,0.000101008605],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008125517,0.0004835179,0.005301885,0.00035800174,0.00036092213,0.00005029713,0.045199886,0.0006373606,0.0000021086116,0.008512322,0.1469489,0.79213667],"study_design_scores_gemma":[0.00026721257,0.000048613918,0.000399821,0.00014336468,0.00002790508,0.00001077118,0.0013890864,0.9581957,0.0000021137987,0.00021831751,0.03913678,0.00016034229],"about_ca_topic_score_codex":0.0000100052675,"about_ca_topic_score_gemma":0.0000401345,"teacher_disagreement_score":0.95755833,"about_ca_system_score_codex":0.00017335998,"about_ca_system_score_gemma":0.0008435751,"threshold_uncertainty_score":0.91596186},"labels":[],"label_agreement":null},{"id":"W4401024374","doi":"10.24963/ijcai.2024/995","title":"Set-Based Retrograde Analysis: Precomputing the Solution to 28-card Bridge Double Dummy Deals","year":2024,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Science and Technology Council","keywords":"Computer science; Graphics; Visualization; Computer graphics (images); Image (mathematics); Data visualization; Computer vision; Human–computer interaction; Artificial intelligence; Information retrieval; Multimedia","score_opus":0.056932147436777845,"score_gpt":0.3483809186457991,"score_spread":0.2914487712090213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401024374","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002339635,0.00009010155,0.98764133,0.00757849,0.00029092238,0.00014580632,0.000008495527,0.0005343154,0.00137091],"genre_scores_gemma":[0.98147637,0.000004843792,0.015072223,0.0022781878,0.00011160516,0.000008254578,0.000055810862,0.000009196067,0.0009834992],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99858034,0.000074908,0.0002755192,0.00044531835,0.00034226454,0.00028163867],"domain_scores_gemma":[0.99907655,0.00009522049,0.00004319947,0.00060075556,0.00007172432,0.00011257581],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0007068408,0.00012418385,0.00015527762,0.00031201768,0.00018284163,0.0011304759,0.00078247604,0.000039030736,0.000040792984],"category_scores_gemma":[0.000022884893,0.00008609335,0.00017356689,0.0033711568,0.000020450772,0.00029142227,0.0002507216,0.00009878896,0.00022741676],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018199506,0.00015513902,0.006309289,0.00014940224,0.0015653862,0.00004494707,0.0035712812,0.0862532,0.0004995336,0.5146069,0.31118613,0.075640604],"study_design_scores_gemma":[0.00009963089,0.00002468274,0.0015733176,0.000021170417,0.00010632853,0.0000015910896,0.000023342453,0.9646441,0.00059156766,0.00014307682,0.032638285,0.0001329073],"about_ca_topic_score_codex":0.00014115017,"about_ca_topic_score_gemma":0.00009617977,"teacher_disagreement_score":0.97913677,"about_ca_system_score_codex":0.00005306379,"about_ca_system_score_gemma":0.00008535969,"threshold_uncertainty_score":0.9999064},"labels":[],"label_agreement":null},{"id":"W4401157363","doi":"10.1109/tvcg.2024.3456336","title":"DataGarden: Formalizing Personal Sketches into Structured Visualization Templates","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Centre National de la Recherche Scientifique; University of Toronto; Agence Nationale de la Recherche","keywords":"Computer science; Visualization; Template; Data visualization; Information visualization; Computer graphics (images); Human–computer interaction; Programming language; Artificial intelligence","score_opus":0.021462373659447673,"score_gpt":0.2978605084998114,"score_spread":0.2763981348403637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401157363","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027019407,0.00023195277,0.99450785,0.00012818557,0.001301882,0.00019907005,0.000041727377,0.00084379414,0.00004359044],"genre_scores_gemma":[0.9943946,0.00074315025,0.0026307749,0.0016580685,0.00015927698,0.000018549666,0.00018119847,0.000049825758,0.0001645642],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99786216,0.0001307524,0.0004720814,0.0007207921,0.0005170294,0.00029719804],"domain_scores_gemma":[0.99907583,0.00012595316,0.00008753126,0.00035579246,0.00016799275,0.0001868956],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00029167577,0.00033678662,0.00024716367,0.00081924815,0.0005549621,0.0013955559,0.00042046208,0.00016897557,0.00004440143],"category_scores_gemma":[0.000004970143,0.0003243359,0.00012704569,0.001579494,0.000110022265,0.0014990866,0.000018514658,0.00021417887,0.00002657347],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009464364,0.00011989962,0.00004032846,0.0002156886,0.00012162184,0.000012413957,0.004236137,0.00037861918,0.00008102488,0.9718357,0.0015474444,0.021401662],"study_design_scores_gemma":[0.0002944167,0.00016224536,0.000054270706,0.0001521875,0.0000440254,0.000045152545,0.00010300091,0.98276335,0.0023035952,0.0022349611,0.011457076,0.00038572293],"about_ca_topic_score_codex":0.000015808604,"about_ca_topic_score_gemma":0.000034540368,"teacher_disagreement_score":0.9918771,"about_ca_system_score_codex":0.000045460587,"about_ca_system_score_gemma":0.00009248669,"threshold_uncertainty_score":0.99992085},"labels":[],"label_agreement":null},{"id":"W4401169273","doi":"10.31219/osf.io/2t3sc","title":"The Effect of Visual Aids on Reading Numeric Data Tables","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Table (database); Computer science; Encoding (memory); Reading (process); Gaze; Value (mathematics); Representation (politics); Eye tracking; Row; Artificial intelligence; Arithmetic; Data mining; Machine learning; Mathematics; Database","score_opus":0.030632094868452236,"score_gpt":0.3608577129995143,"score_spread":0.33022561813106205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401169273","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020105431,0.0007695117,0.97017777,0.0008145999,0.003260874,0.0004274129,0.0002597554,0.00046211033,0.021817435],"genre_scores_gemma":[0.95616335,0.001296931,0.017279398,0.0007538229,0.00069136446,0.000038627237,0.0022591238,0.000099563695,0.021417836],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99845755,0.00014431855,0.00028354552,0.00058176374,0.00036802486,0.00016482483],"domain_scores_gemma":[0.99720955,0.0004808412,0.00012399134,0.0021049427,0.00003454848,0.0000461151],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0010320949,0.00018009289,0.00024237896,0.0001158768,0.00008126794,0.0006402993,0.0033351672,0.00007687736,0.000022167598],"category_scores_gemma":[0.00021728211,0.00010174904,0.00006332003,0.00039558785,0.000046935176,0.00011742364,0.0094092,0.0002874319,0.0001301625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015609403,0.000074168085,0.00034639562,0.0009802859,0.00034212912,0.000018266477,0.00016080466,0.0011152399,0.0001269226,0.5906127,0.13355242,0.27265504],"study_design_scores_gemma":[0.00007934857,0.0002399205,0.00001196301,0.00030541696,0.000047208858,0.0000018386141,0.000013280231,0.9610026,0.002454052,0.0026795438,0.032986183,0.0001786448],"about_ca_topic_score_codex":0.00006042361,"about_ca_topic_score_gemma":0.0000054105712,"teacher_disagreement_score":0.9598874,"about_ca_system_score_codex":0.000021408017,"about_ca_system_score_gemma":0.000090694964,"threshold_uncertainty_score":0.9986025},"labels":[],"label_agreement":null},{"id":"W4401172017","doi":"10.1145/3685266","title":"An Umbrella Review of Reporting Quality in CHI Systematic Reviews: Guiding Questions and Best Practices for HCI","year":2024,"lang":"en","type":"article","venue":"ACM Transactions on Computer-Human Interaction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Systematic review; Quality (philosophy); Medicine; Engineering ethics; Psychology; MEDLINE; Political science; Engineering; Epistemology","score_opus":0.3113466333537888,"score_gpt":0.5130249686148886,"score_spread":0.20167833526109974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401172017","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001063999,0.00428391,0.99221224,0.0005395587,0.0007463052,0.0009138304,0.000012273105,0.00014301258,0.00008484781],"genre_scores_gemma":[0.7309303,0.04634555,0.21902722,0.0016802631,0.0004455617,0.00072794163,0.00018059571,0.00008976927,0.00057276845],"study_design_codex":"systematic_review","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9963561,0.0005074487,0.0022120185,0.0005395662,0.00022617867,0.00015867231],"domain_scores_gemma":[0.9961092,0.000806227,0.0019383203,0.0008764608,0.00019553507,0.00007424095],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031800938,0.0001937392,0.0005805827,0.00039704124,0.00019272079,0.00037124174,0.00046940098,0.000060940136,0.000014842375],"category_scores_gemma":[0.0008787583,0.00017752078,0.00016398632,0.0005806333,0.000027183634,0.0017089711,0.000022637983,0.0001892405,0.000009726374],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025488669,0.0022535382,0.00011256216,0.6426995,0.0003211519,0.000031620748,0.00306275,0.0013635299,0.0034998432,0.06506547,0.0014448101,0.28011975],"study_design_scores_gemma":[0.00043022464,0.0010028773,0.00009550606,0.36581597,0.0003784203,0.0002773329,0.00029302842,0.6111827,0.0012580226,0.0012576642,0.017308287,0.00069999316],"about_ca_topic_score_codex":0.00020613102,"about_ca_topic_score_gemma":0.00014297584,"teacher_disagreement_score":0.773185,"about_ca_system_score_codex":0.00010030643,"about_ca_system_score_gemma":0.00005140638,"threshold_uncertainty_score":0.7239087},"labels":[],"label_agreement":null},{"id":"W4401416676","doi":"10.1109/icra57147.2024.10610324","title":"SceneControl: Diffusion for Controllable Traffic Scene Generation","year":2024,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Diffusion; Computer vision; Physics","score_opus":0.02922574277811324,"score_gpt":0.29823095434656066,"score_spread":0.2690052115684474,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401416676","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017465465,0.0003265346,0.9935448,0.002223941,0.00062026497,0.00018682507,0.000010140259,0.00037483897,0.0009660938],"genre_scores_gemma":[0.94606364,0.00008960591,0.038220264,0.002319224,0.00050490524,0.00003658562,0.00012659168,0.000017655342,0.012621524],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926466,0.000017450207,0.00016620065,0.0002709315,0.00012904817,0.00015173895],"domain_scores_gemma":[0.99958843,0.000055281133,0.000018743654,0.0002115282,0.00006925176,0.000056792862],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021879995,0.00007861129,0.00010067611,0.00009289611,0.00009445217,0.00065506063,0.00023939682,0.00003461133,0.00006413718],"category_scores_gemma":[0.000033622302,0.00006198069,0.000059853202,0.000236366,0.000008843005,0.00044624123,0.00003881505,0.000028006612,0.000085634754],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000080040245,0.000095033305,0.00000931724,0.000051360363,0.000038311504,0.0000039452716,0.00012405738,0.0030637765,0.020008702,0.6163899,0.13447413,0.22573349],"study_design_scores_gemma":[0.00039159614,0.000036465004,0.000005892755,0.000008530593,0.000007351394,0.0000015428067,0.0000036861702,0.8908495,0.0011256032,0.00035292504,0.10713713,0.00007982641],"about_ca_topic_score_codex":0.000003254031,"about_ca_topic_score_gemma":0.000021219039,"teacher_disagreement_score":0.95532453,"about_ca_system_score_codex":0.000021046128,"about_ca_system_score_gemma":0.000057105335,"threshold_uncertainty_score":0.6316765},"labels":[],"label_agreement":null},{"id":"W4402171355","doi":"10.1007/s10270-024-01204-x","title":"MUREQ: a multilayer framework for analyzing and operationalizing visualization requirements","year":2024,"lang":"en","type":"article","venue":"Software & Systems Modeling","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Beijing Municipal Natural Science Foundation; Beijing Municipal Commission of Education; National Natural Science Foundation of China","keywords":"Visualization; Operationalization; Computer science; Data visualization; Human–computer interaction; Information visualization; Interactive visualization; Data science; Data mining; Information retrieval","score_opus":0.06892788394374555,"score_gpt":0.36713497849621374,"score_spread":0.2982070945524682,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402171355","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012477274,0.0026038168,0.9943751,0.00009041332,0.0008111789,0.00031814052,0.00002171571,0.00052075594,0.00001114959],"genre_scores_gemma":[0.80651546,0.00007914673,0.19259392,0.00020059176,0.0002690218,0.00006144164,0.00009644208,0.000035781577,0.00014820698],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984569,0.00005312499,0.0004374117,0.00052556884,0.00029234603,0.00023467377],"domain_scores_gemma":[0.99920225,0.00016204765,0.0000632752,0.00028278385,0.00020165271,0.00008796136],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0005876991,0.00016315433,0.00018628122,0.00021231375,0.00027440122,0.0014777186,0.00026853246,0.00009547927,0.0000028593213],"category_scores_gemma":[0.00027505282,0.0001550824,0.00005812716,0.00042859773,0.000011717774,0.0011002222,0.00012883394,0.000081480575,0.000008792456],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000026670493,0.000022561604,0.00067851256,0.00060174044,0.000078964935,0.000004652061,0.001590601,0.15575998,0.00017239006,0.8355968,0.0003610075,0.005130114],"study_design_scores_gemma":[0.00011149696,0.000016454811,0.0000018985266,0.0007414845,0.000021381282,0.0000062169706,0.000095758434,0.9919196,0.000022709426,0.0048454767,0.002028177,0.0001893674],"about_ca_topic_score_codex":0.000028331187,"about_ca_topic_score_gemma":0.0000023611908,"teacher_disagreement_score":0.8361596,"about_ca_system_score_codex":0.00006617915,"about_ca_system_score_gemma":0.00008350594,"threshold_uncertainty_score":0.99955887},"labels":[],"label_agreement":null},{"id":"W4402211373","doi":"10.17742/image29710","title":"The Design in the Visualization of Uncertainty, Abstract Modelling and Virtual Photography","year":2024,"lang":"en","type":"article","venue":"Imaginations Journal of Cross-Cultural Image Studies","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Visualization; Photography; Computer science; Computer graphics (images); Human–computer interaction; Artificial intelligence; Visual arts; Art","score_opus":0.06026602396272844,"score_gpt":0.4235068413337827,"score_spread":0.36324081737105424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402211373","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017641392,0.00981099,0.9673327,0.0038541458,0.00036029806,0.00016881974,0.000010745534,0.000026719525,0.0007941559],"genre_scores_gemma":[0.9921119,0.0034136777,0.0042995787,0.00007861169,0.000044015385,0.0000034115671,0.0000019407619,0.000004529925,0.000042339165],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998809,0.000102500955,0.00048510815,0.000118956064,0.0003587167,0.00012574093],"domain_scores_gemma":[0.99614084,0.0006389615,0.00020927518,0.00012565528,0.0028630174,0.000022276403],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0013144232,0.00010685278,0.00014903433,0.00018534024,0.00032181593,0.0031323973,0.0004858386,0.000016619588,0.0000012509735],"category_scores_gemma":[0.0005135909,0.00005232998,0.00007915883,0.0007984268,0.0011839621,0.0057475157,0.000080608486,0.00014106427,0.0000010054337],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001842942,0.00011942879,0.00036607316,0.00008951647,0.00029329228,0.00004946271,0.019739611,0.046645112,0.0026681314,0.91064084,0.004775495,0.01459463],"study_design_scores_gemma":[0.000733171,0.00022945629,0.0025371339,0.00039730663,0.0000977557,0.00020049546,0.008339981,0.89145106,0.002031166,0.081753165,0.011932932,0.00029636134],"about_ca_topic_score_codex":0.0000075168537,"about_ca_topic_score_gemma":0.0000051472157,"teacher_disagreement_score":0.9744705,"about_ca_system_score_codex":0.000025776633,"about_ca_system_score_gemma":0.000050465624,"threshold_uncertainty_score":0.99790245},"labels":[],"label_agreement":null},{"id":"W4402401820","doi":"10.1109/tvcg.2024.3456361","title":"Quantifying Emotional Responses to Immutable Data Characteristics and Designer Choices in Data Visualizations","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Data visualization; Visualization; Data modeling; Human–computer interaction; Data science; Data mining; Software engineering","score_opus":0.12066754302721838,"score_gpt":0.37785527674805525,"score_spread":0.25718773372083686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402401820","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0033725493,0.00019123267,0.99431974,0.00033737815,0.000724756,0.000241757,0.0005066413,0.0002949472,0.000011022912],"genre_scores_gemma":[0.9823149,0.002083683,0.011023045,0.0028880218,0.00013898259,0.000021298309,0.0011867363,0.00006313003,0.00028021776],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99756855,0.00022083701,0.00051706075,0.0010499797,0.00037629303,0.00026729392],"domain_scores_gemma":[0.99815804,0.00034020847,0.00006781391,0.0011394296,0.00011388038,0.00018062994],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0007207437,0.0002539607,0.0002465207,0.0010798051,0.0003384648,0.001374473,0.0010462643,0.00010751995,0.00001831324],"category_scores_gemma":[0.0000305765,0.000258928,0.000025913396,0.0020573272,0.00008033603,0.0019938448,0.000119204924,0.00018825216,0.000016344133],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003107015,0.00044329828,0.0011245859,0.00026038705,0.00011030461,0.000031540843,0.0012879748,0.0004935903,0.000072545066,0.96691316,0.0021559137,0.02707561],"study_design_scores_gemma":[0.0002328019,0.00007455846,0.0018641257,0.0002392831,0.000030169484,0.000027676138,0.00003110737,0.9848839,0.000065095985,0.00021790032,0.012032111,0.00030128087],"about_ca_topic_score_codex":0.00003097641,"about_ca_topic_score_gemma":0.0001206182,"teacher_disagreement_score":0.9843903,"about_ca_system_score_codex":0.000023232918,"about_ca_system_score_gemma":0.00012169218,"threshold_uncertainty_score":0.9999863},"labels":[],"label_agreement":null},{"id":"W4402477877","doi":"10.7554/elife.94902.2.sa0","title":"Author response: Visual to default network pathways: A double dissociation between semantic and spatial cognition","year":2024,"lang":"en","type":"peer-review","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Dissociation (chemistry); Cognition; Cognitive psychology; Spatial cognition; Default mode network; Computer science; Cognitive science; Psychology; Neuroscience; Chemistry; Physical chemistry","score_opus":0.06734198341799244,"score_gpt":0.3779926817478865,"score_spread":0.3106506983298941,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402477877","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000056196182,0.002593324,0.8924095,0.09975798,0.0023084048,0.00092880445,0.00052638724,0.000500491,0.00091889704],"genre_scores_gemma":[0.029252518,0.0013333235,0.013886601,0.027179174,0.0062538986,0.00028208623,0.017432014,0.00022932628,0.9041511],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9971459,0.00025718653,0.0006240709,0.00082513713,0.0007548839,0.0003928248],"domain_scores_gemma":[0.9985034,0.0002804535,0.00022674946,0.00042715718,0.0003063781,0.0002558964],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0016376781,0.0003521449,0.0005948859,0.00024142514,0.00017269587,0.00080952555,0.0005347934,0.00026739694,0.000098192126],"category_scores_gemma":[0.00029460722,0.00031826415,0.00012407677,0.0010870511,0.000025472813,0.00025566496,0.00071585923,0.00030543128,0.00051737856],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016591872,0.000022754906,0.000022947857,0.00078359415,0.00007144605,0.0000113148735,0.00011229399,0.000004821885,0.0000030678227,0.0023488551,0.9764064,0.020195935],"study_design_scores_gemma":[0.00028645084,0.0001853917,0.00038452158,0.0038912504,0.00041172994,0.0000058886912,0.000009467889,0.03931631,0.000018593004,0.0018335647,0.95308864,0.00056818797],"about_ca_topic_score_codex":0.0001736501,"about_ca_topic_score_gemma":0.00028575992,"teacher_disagreement_score":0.90323216,"about_ca_system_score_codex":0.00009260867,"about_ca_system_score_gemma":0.00028076532,"threshold_uncertainty_score":0.9999269},"labels":[],"label_agreement":null},{"id":"W4402557614","doi":"10.1109/tpami.2024.3462291","title":"Quantifying and Learning Static vs. Dynamic Information in Deep Spatiotemporal Networks","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Pattern Analysis and Machine Intelligence","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Huawei Technologies (Canada); University of Guelph; Ontario Tech University; York University","funders":"","keywords":"Computer science; Artificial intelligence; Deep learning; Machine learning","score_opus":0.020188331944015658,"score_gpt":0.3023741369426208,"score_spread":0.2821858049986051,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402557614","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0035173057,0.00015326537,0.9956852,0.0003518382,0.00011883536,0.00006452477,0.000009560186,0.00008645526,0.000012985905],"genre_scores_gemma":[0.99736524,0.0010612202,0.0011583229,0.00032555792,0.0000043017003,0.000005645947,0.000032476768,0.0000058088162,0.00004144476],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99894357,0.000090192116,0.0003694656,0.0002747512,0.00016670485,0.0001553172],"domain_scores_gemma":[0.9995388,0.00013119706,0.000060426144,0.0001680978,0.000032512162,0.00006899639],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034178674,0.00013948268,0.00018893715,0.0008101754,0.00013154121,0.0005424028,0.00015897647,0.00004559681,0.000035129702],"category_scores_gemma":[0.00000714759,0.00012723402,0.00006869729,0.001336591,0.000033077045,0.00087500794,0.0000066214834,0.0003185564,0.000013750896],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000024337842,0.000019037907,0.0009918148,0.00003914302,0.00008457603,0.0000053186436,0.0007776649,0.30745322,0.000002894388,0.00021614706,0.0000016618055,0.6904061],"study_design_scores_gemma":[0.000042049083,0.000046620506,0.0011156994,0.00005043118,0.00009288954,0.000004603462,0.0001053579,0.99801797,0.00020704187,0.00006434638,0.000113731585,0.00013925436],"about_ca_topic_score_codex":0.0006302936,"about_ca_topic_score_gemma":0.0026214006,"teacher_disagreement_score":0.9945269,"about_ca_system_score_codex":0.000029359278,"about_ca_system_score_gemma":0.000014183865,"threshold_uncertainty_score":0.52304024},"labels":[],"label_agreement":null},{"id":"W4402580532","doi":"10.1109/tvcg.2024.3456192","title":"<i>Does This Have a Particular Meaning?</i> Interactive Pattern Explanation for Network Visualizations","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"Engineering and Physical Sciences Research Council","keywords":"Computer science; Visualization; Data visualization; Human–computer interaction; Terminology; Information visualization; Interactive visual analysis; Selection (genetic algorithm); Interactive visualization; Visual analytics; Artificial intelligence","score_opus":0.01970110976894902,"score_gpt":0.29932249539430056,"score_spread":0.27962138562535155,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402580532","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001257904,0.000056655364,0.9962996,0.00026217758,0.0020446538,0.00043812615,0.00007206891,0.0006389095,0.00006199365],"genre_scores_gemma":[0.99005765,0.00059297297,0.0033931646,0.0046610814,0.00038383962,0.0001936301,0.00021684481,0.00007395828,0.00042686303],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979988,0.0001541774,0.00048346972,0.0006879561,0.00035554374,0.00032005305],"domain_scores_gemma":[0.99878657,0.00032026917,0.00011052791,0.00034800943,0.00027978385,0.00015482707],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0003279875,0.00029390267,0.00024200408,0.00044739209,0.0005037053,0.0010663405,0.00030938504,0.00013156646,0.00003628458],"category_scores_gemma":[0.000008558048,0.00023348177,0.00016431749,0.0010267937,0.00006842015,0.0010091083,0.000011559975,0.0001700589,0.000016118642],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012139442,0.0002301538,0.000059804486,0.00014335569,0.00020063599,0.000008373131,0.002882652,0.0035562976,0.000009398451,0.96411294,0.0049936245,0.023790598],"study_design_scores_gemma":[0.0003525586,0.0001879184,0.000013660698,0.0001693625,0.00007531156,0.0000122496185,0.00005277861,0.9730139,0.00084361807,0.0037928913,0.021155126,0.00033067394],"about_ca_topic_score_codex":0.000011265641,"about_ca_topic_score_gemma":0.000049116352,"teacher_disagreement_score":0.99290645,"about_ca_system_score_codex":0.00004335368,"about_ca_system_score_gemma":0.000056288787,"threshold_uncertainty_score":0.9999707},"labels":[],"label_agreement":null},{"id":"W4402679133","doi":"10.7554/elife.95764.2.sa3","title":"eLife Assessment: Shortcutting from self-motion signals: quantifying trajectories and active sensing in an open maze","year":2024,"lang":"en","type":"peer-review","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Krembil Foundation","keywords":"Motion (physics); Computer science; Artificial intelligence","score_opus":0.12648070825541533,"score_gpt":0.4387571898833064,"score_spread":0.3122764816278911,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402679133","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005672973,0.007921968,0.9618354,0.016128164,0.0036609406,0.0016299769,0.0009035436,0.0008724826,0.006480254],"genre_scores_gemma":[0.059818435,0.02924134,0.8182003,0.027257934,0.0026068615,0.0000844573,0.02639356,0.00046076498,0.035936363],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99707663,0.00034684106,0.0006377253,0.0010986283,0.00055304304,0.00028713534],"domain_scores_gemma":[0.9985871,0.00021812957,0.0002545537,0.0005946841,0.0002164733,0.00012911254],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001116213,0.00036362992,0.00069719425,0.000272367,0.000108886365,0.0027874927,0.0010676761,0.0001802484,0.00008096855],"category_scores_gemma":[0.000095437164,0.00033253751,0.000056634013,0.0007875455,0.00002530987,0.0018636927,0.001280195,0.00048908143,0.000015629363],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011722633,0.0006716627,0.00090163026,0.008359115,0.0008676779,0.00048375528,0.009666367,0.000100654295,0.00072401937,0.051276114,0.31406856,0.6128687],"study_design_scores_gemma":[0.0002444573,0.000075002914,0.00042350832,0.007918921,0.0002276731,0.000012011109,0.00050694647,0.72311795,0.00009078737,0.0012359371,0.26527673,0.0008700987],"about_ca_topic_score_codex":0.0010686402,"about_ca_topic_score_gemma":0.0017330792,"teacher_disagreement_score":0.7230173,"about_ca_system_score_codex":0.00014983324,"about_ca_system_score_gemma":0.00034737194,"threshold_uncertainty_score":0.9999127},"labels":[],"label_agreement":null},{"id":"W4402721926","doi":"10.1145/3670947.3670977","title":"Investigating User Estimation of Missing Data in Visual Analysis","year":2024,"lang":"en","type":"article","venue":"Graphics Interface","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Universitas Brawijaya","keywords":"Computer science; Estimation; Missing data; Artificial intelligence; Data mining; Machine learning; Engineering","score_opus":0.060495921830692655,"score_gpt":0.3864893038071454,"score_spread":0.3259933819764528,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402721926","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02563033,0.00024772217,0.97331357,0.0004659231,0.00010717214,0.00003411692,0.000018461087,0.00008034885,0.00010237577],"genre_scores_gemma":[0.96549153,0.0000158666,0.034254603,0.00011183987,0.000008371158,6.0317416e-7,0.000082852406,0.000005714264,0.000028591825],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99891436,0.00006198413,0.0003322766,0.00034620098,0.00023061401,0.000114541144],"domain_scores_gemma":[0.99911463,0.00012011799,0.00007200217,0.00060866505,0.000041310977,0.000043279128],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006220104,0.00008322208,0.00015302854,0.0007014247,0.000029833942,0.0002895853,0.0008497279,0.00004091562,0.000009954754],"category_scores_gemma":[0.00021163607,0.00008103203,0.00004179237,0.003764493,0.000057021574,0.0008820691,0.0004619456,0.00012775128,0.0000071610407],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000031217612,0.0002491851,0.023098115,0.00066165574,0.00091390306,0.000037320868,0.0058103376,0.084817395,0.0022827676,0.7593393,0.0036389169,0.119148],"study_design_scores_gemma":[0.0000393266,0.000010814033,0.0007222139,0.0001391977,0.000049470236,0.0000014288136,0.00003360815,0.9927743,0.0012515925,0.0044401046,0.0004555327,0.00008239536],"about_ca_topic_score_codex":0.000084817,"about_ca_topic_score_gemma":0.00006297684,"teacher_disagreement_score":0.93986124,"about_ca_system_score_codex":0.000014370218,"about_ca_system_score_gemma":0.000058012873,"threshold_uncertainty_score":0.33043903},"labels":[],"label_agreement":null},{"id":"W4402815656","doi":"10.2352/j.percept.imaging.2024.7.000403","title":"Visualizing Uncertainty with Simulated Chromatic Aberration","year":2024,"lang":"en","type":"article","venue":"Journal of Perceptual Imaging","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Chromatic aberration; Computer science; Chromatic scale; Optics; Physics","score_opus":0.016930811782345668,"score_gpt":0.31118109277893163,"score_spread":0.29425028099658596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402815656","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.056145288,0.00033166187,0.94134563,0.0010525449,0.00039830082,0.000045429013,0.0000013625223,0.00011283193,0.0005669543],"genre_scores_gemma":[0.9910209,0.000019319907,0.008205687,0.00044416127,0.00015636701,1.7594402e-7,0.0000042418537,0.000012266455,0.0001368371],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99887127,0.000058954916,0.00037408058,0.00014851744,0.00039176436,0.0001554183],"domain_scores_gemma":[0.9993417,0.00007192181,0.00013713416,0.00015405049,0.00020629613,0.000088871435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040171738,0.0001088113,0.00015691978,0.00027077942,0.000079255,0.0007412137,0.00034750724,0.00001848274,0.00007463838],"category_scores_gemma":[0.000053404652,0.000077422046,0.00006542061,0.0005492666,0.000042942862,0.0017639904,0.00005570046,0.00016792194,0.000034288245],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000097892465,0.00087499415,0.0056943763,0.0010896951,0.0011043597,0.0042231726,0.099767536,0.21098804,0.09967156,0.22227621,0.068972014,0.28524014],"study_design_scores_gemma":[0.00021546776,0.00007277463,0.000241798,0.00033616557,0.000031393476,0.0003144686,0.0006896461,0.9917858,0.00014758242,0.0002595379,0.00578453,0.000120837525],"about_ca_topic_score_codex":0.0000067767423,"about_ca_topic_score_gemma":0.0000018257139,"teacher_disagreement_score":0.93487567,"about_ca_system_score_codex":0.000061170605,"about_ca_system_score_gemma":0.00015137489,"threshold_uncertainty_score":0.7147541},"labels":[],"label_agreement":null},{"id":"W4402904748","doi":"10.1167/jov.24.10.713","title":"Information transfer during goal-directed viewing of everyday scenes","year":2024,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Information transfer; Computer science; Psychology; Cognitive psychology; Human–computer interaction; Telecommunications","score_opus":0.01266413644592023,"score_gpt":0.2958396369162738,"score_spread":0.28317550047035356,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402904748","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21884115,0.0006705242,0.77884525,0.0005312358,0.00075724896,0.00004374726,0.0000044843705,0.00007181117,0.00023452507],"genre_scores_gemma":[0.9964019,0.00034193182,0.0030995384,0.000057423746,0.00005211836,1.0290348e-7,0.0000022484433,0.0000031194838,0.00004161507],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991085,0.00003061074,0.00043635804,0.000042363285,0.00031407984,0.00006809273],"domain_scores_gemma":[0.99956197,0.000032912038,0.00008228105,0.00009583502,0.00018493677,0.00004204267],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003436595,0.000052682884,0.0001155119,0.00027955795,0.000033100358,0.00017202899,0.00023881705,0.00002679114,0.00001718216],"category_scores_gemma":[0.000046017634,0.00003924782,0.00007767764,0.00044891235,0.000008919298,0.0024983557,0.00003398397,0.000081286205,0.000011685159],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013623055,0.00045788873,0.0014231437,0.0027251458,0.00036483273,0.00014243269,0.030525949,0.0069094463,0.2714858,0.032476,0.020266714,0.63308644],"study_design_scores_gemma":[0.0013714059,0.00049947324,0.035692584,0.0041568303,0.00007948506,0.00029650299,0.00025094565,0.8101225,0.061919328,0.0007946016,0.08445404,0.00036232738],"about_ca_topic_score_codex":0.0000011062649,"about_ca_topic_score_gemma":1.8474643e-7,"teacher_disagreement_score":0.80321306,"about_ca_system_score_codex":0.000023549424,"about_ca_system_score_gemma":0.00005399456,"threshold_uncertainty_score":0.18112475},"labels":[],"label_agreement":null},{"id":"W4402933813","doi":"10.1177/10711813241280938","title":"Public Health Decision-Making Using Uncertainty Displays","year":2024,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Public Health Ontario; University of Toronto","funders":"","keywords":"Public health; Computer science; Medicine; Nursing","score_opus":0.05108678732153848,"score_gpt":0.3121209008720534,"score_spread":0.2610341135505149,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402933813","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98272204,0.00031780207,0.01574658,0.00042776106,0.00029813458,0.00010708542,0.000038694146,0.00010815917,0.00023374667],"genre_scores_gemma":[0.9905823,0.00007569156,0.0089712925,0.0002519434,0.00007702229,9.1251565e-7,0.0000024133983,0.000013181681,0.000025263242],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987375,0.000008857593,0.00038265195,0.00036050344,0.00020248012,0.0003079796],"domain_scores_gemma":[0.99927694,0.00012710284,0.00024026682,0.00011992618,0.0001385384,0.00009723731],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008508333,0.00016435634,0.00021429962,0.000059594608,0.00069663953,0.0007685745,0.00067832135,0.000062145926,0.0000023763453],"category_scores_gemma":[0.00012584809,0.000117887525,0.0001813316,0.00040961168,0.0001083426,0.0009516148,0.0007471189,0.00017955813,4.893303e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007339282,0.00014658451,0.04711443,0.0012419076,0.00030627637,4.2745265e-7,0.08552645,0.0013499439,0.0025951683,0.8275479,0.013836114,0.020327467],"study_design_scores_gemma":[0.0002347849,0.00008057281,0.0059390035,0.0017905058,0.000036032794,0.000011362222,0.013048546,0.9546865,0.0003202709,0.013190076,0.010073508,0.0005888253],"about_ca_topic_score_codex":0.000044267763,"about_ca_topic_score_gemma":0.000004543373,"teacher_disagreement_score":0.9533366,"about_ca_system_score_codex":0.00014147136,"about_ca_system_score_gemma":0.00010554791,"threshold_uncertainty_score":0.7411381},"labels":[],"label_agreement":null},{"id":"W4403394530","doi":"10.2196/60128","title":"The Role of Visualization in Estimating Cardiovascular Disease Risk: Scoping Review","year":2024,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Javna Agencija za Raziskovalno Dejavnost RS","keywords":"CINAHL; Systematic review; MEDLINE; Medicine; Disease; Population; Framingham Risk Score; Data science; Computer science; Environmental health; Pathology; Psychological intervention; Nursing","score_opus":0.027496139326572074,"score_gpt":0.352298445779885,"score_spread":0.32480230645331293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403394530","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007175607,0.59571505,0.39910644,0.003347505,0.0001987901,0.000655742,0.0000139290005,0.00012046645,0.00012453701],"genre_scores_gemma":[0.6255202,0.36836058,0.0034033058,0.0021933552,0.0001598832,0.00016847938,0.000116958225,0.000029398734,0.000047803132],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984767,0.0003994446,0.00038387006,0.000254433,0.00026070204,0.0002248914],"domain_scores_gemma":[0.9990792,0.00018264535,0.00009510195,0.0003793981,0.000064241896,0.00019940214],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030034496,0.000073796495,0.00020689188,0.00007235547,0.0001428,0.00023658872,0.00023028153,0.000015464666,0.0000014502424],"category_scores_gemma":[0.00071490655,0.000054486063,0.000052924468,0.00078931823,0.00003079642,0.00029841668,0.00009208751,0.00006984722,0.000002328461],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012096854,0.000027001393,0.025247028,0.008441883,0.00002825911,0.0000031290188,0.00040038346,0.0001943186,2.0373533e-7,0.05342185,0.0005649681,0.9116698],"study_design_scores_gemma":[0.0000727336,0.000014945781,0.0019370969,0.0034340508,7.180169e-7,0.0000016848321,0.000022085225,0.9334435,1.5506578e-7,0.00038178317,0.060607407,0.00008382993],"about_ca_topic_score_codex":0.00003832859,"about_ca_topic_score_gemma":0.00002431051,"teacher_disagreement_score":0.9332492,"about_ca_system_score_codex":0.000022524478,"about_ca_system_score_gemma":0.000608801,"threshold_uncertainty_score":0.22814305},"labels":[],"label_agreement":null},{"id":"W4403423386","doi":"10.1145/3677077","title":"Hexed by Pressure: How Action-State Orientation Explains Propensity to Choke in Super Hexagon","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria; University of Saskatchewan","funders":"","keywords":"Choke; Action (physics); Orientation (vector space); Mechanics; Physics; Mathematics; Geometry; Quantum mechanics","score_opus":0.07581479060064612,"score_gpt":0.3529382036838795,"score_spread":0.2771234130832334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403423386","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9466933,0.000025092477,0.039659135,0.009236828,0.002791982,0.00075550063,0.000019453388,0.0003202776,0.00049842545],"genre_scores_gemma":[0.99527663,0.0000120868,0.0021551563,0.0006322242,0.00015509177,0.000028360817,0.000012017848,0.000019338428,0.0017090987],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9984865,0.00002501814,0.00031228107,0.00055402337,0.0004121477,0.00020998884],"domain_scores_gemma":[0.9990894,0.00005506283,0.00014757937,0.00042172094,0.00022006119,0.0000661749],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031309773,0.00018866014,0.00018849023,0.000327314,0.00013065794,0.00090142764,0.0013053396,0.00005254009,0.000012361934],"category_scores_gemma":[0.00012596742,0.00014799126,0.0000825551,0.00075479766,0.000024952986,0.0022194786,0.00069124927,0.00026503313,0.000031719697],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018654983,0.0010885576,0.0054533444,0.0010146993,0.00026945342,0.000006476331,0.020342683,0.0017407159,0.27836958,0.040533517,0.5606121,0.090382345],"study_design_scores_gemma":[0.0011459506,0.00084922125,0.017289314,0.0017962273,0.00007138454,0.000041871335,0.0005862191,0.35204986,0.45035353,0.0051437253,0.16966575,0.0010069321],"about_ca_topic_score_codex":0.000045320536,"about_ca_topic_score_gemma":0.000018786584,"teacher_disagreement_score":0.39094633,"about_ca_system_score_codex":0.00012987597,"about_ca_system_score_gemma":0.00002145995,"threshold_uncertainty_score":0.86924875},"labels":[],"label_agreement":null},{"id":"W4403494985","doi":"10.4236/jamp.2024.1210200","title":"Advancements in Time Modeling: Relationalism, Divisional Structures, and Geometry","year":2024,"lang":"en","type":"article","venue":"Journal of Applied Mathematics and Physics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Milton District Hospital","funders":"","keywords":"Geometry; Computer science; Mathematics","score_opus":0.019670415225147616,"score_gpt":0.28864666962206886,"score_spread":0.26897625439692124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403494985","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03630947,0.0002606239,0.9628488,0.0000987339,0.000055082644,0.000040456394,0.000006153825,0.000009079378,0.00037158947],"genre_scores_gemma":[0.67955184,0.00038399536,0.31962457,0.00019720942,0.00015208106,9.930023e-7,0.000011129183,0.000015393563,0.00006280946],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992753,0.00000309746,0.00027313095,0.00009372813,0.0002854879,0.00006924841],"domain_scores_gemma":[0.99967223,0.00007255256,0.00008929358,0.00008086286,0.000037408317,0.00004766103],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023933672,0.0000720707,0.00013754149,0.00007480708,0.000028530312,0.00019116048,0.00015525008,0.000025000167,0.000005760519],"category_scores_gemma":[0.000008430665,0.000056508074,0.00002089096,0.00021231026,0.0000149729785,0.0002631224,0.000102856946,0.00011249958,0.0000027020235],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000019778226,0.00004466339,0.000012086935,0.0000788183,0.000020409278,0.000004441649,0.0004947154,0.0037455484,0.0002035028,0.9846788,0.00015614757,0.01055888],"study_design_scores_gemma":[0.000106075655,0.0000093380395,0.0000141439805,0.00005135232,0.000006144435,0.000008071508,0.0000118860125,0.5927886,0.000025362255,0.40659824,0.0003390248,0.000041784846],"about_ca_topic_score_codex":1.6103098e-7,"about_ca_topic_score_gemma":4.2602892e-8,"teacher_disagreement_score":0.64324236,"about_ca_system_score_codex":0.000011256587,"about_ca_system_score_gemma":0.000031682393,"threshold_uncertainty_score":0.23043324},"labels":[],"label_agreement":null},{"id":"W4403511528","doi":"10.1109/iv64223.2024.00012","title":"Interactive Visual Analysis of COVID-19","year":2024,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Computer science; Coronavirus disease 2019 (COVID-19); Interactive visual analysis; Visual analytics; Human–computer interaction; Visualization; Computer graphics (images); Artificial intelligence; Medicine","score_opus":0.03070085404062247,"score_gpt":0.4028733601204708,"score_spread":0.37217250607984836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403511528","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005374981,0.000030044308,0.99393195,0.0008707511,0.000097736236,0.000017891192,0.0000101623555,0.00013264435,0.004371342],"genre_scores_gemma":[0.99192286,0.0000145304475,0.0036786662,0.001973827,0.00001306299,0.0000010244241,0.000036860078,0.0000026804692,0.0023565202],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994606,0.000026375401,0.00013581532,0.00017706251,0.00013780399,0.000062388055],"domain_scores_gemma":[0.9995657,0.00012409205,0.000024106073,0.00017368962,0.000036566133,0.00007579851],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013526496,0.00004419514,0.00010366551,0.00048033582,0.000017455248,0.00013986448,0.00027515597,0.0000148569,0.00046706136],"category_scores_gemma":[0.00007351948,0.000035013414,0.00008525575,0.0023624978,0.000018334706,0.00032639698,0.00012797723,0.000030294295,0.000052578358],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000017264164,0.00007153568,0.0005183416,0.00003434191,0.00090524973,0.000018027327,0.0015562439,0.0011190745,0.00018539118,0.9698869,0.017486041,0.008217121],"study_design_scores_gemma":[0.000026548516,0.000016159769,0.00012651096,0.0000031703685,0.00009545203,6.9393633e-7,0.000088733,0.96167725,0.0003872609,0.0005317907,0.03699972,0.000046721012],"about_ca_topic_score_codex":0.00006323268,"about_ca_topic_score_gemma":0.000025808371,"teacher_disagreement_score":0.99138534,"about_ca_system_score_codex":0.000026883703,"about_ca_system_score_gemma":0.000095241005,"threshold_uncertainty_score":0.51139945},"labels":[],"label_agreement":null},{"id":"W4403715389","doi":"10.1145/3696762.3698047","title":"Summary of the Workshop on Visual Methods and Analyzing Visual Data in Human Computer Interaction","year":2024,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Agence Nationale de la Recherche","keywords":"Computer science; Human–computer interaction; Interactive visual analysis; Visual analytics; Artificial intelligence; Computer graphics (images); Visualization","score_opus":0.0700970404012653,"score_gpt":0.4605869902428599,"score_spread":0.3904899498415946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403715389","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012456795,0.000072564195,0.98571473,0.00046593026,0.00040635778,0.00005896654,0.0000028739837,0.0000589545,0.00076284795],"genre_scores_gemma":[0.95514566,0.00005852338,0.043181587,0.0007463393,0.00013293751,0.000001369999,0.0000664858,0.000012348143,0.00065475993],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989767,0.00018894183,0.00024300547,0.00034735436,0.0001441282,0.00009989231],"domain_scores_gemma":[0.99917865,0.00026093505,0.000043757904,0.00046828977,0.000018972414,0.000029424273],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067034754,0.00008363961,0.000116487296,0.00019966795,0.000048691138,0.00028611734,0.0006397975,0.000033280532,0.00001673365],"category_scores_gemma":[0.000030220273,0.000056694902,0.000025881447,0.00068485003,0.000035552563,0.00065843033,0.0010923464,0.00014624708,0.0000030820627],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000073115643,0.00035053396,0.0042315335,0.00012663657,0.00009753581,0.000014787347,0.0011651025,0.00082167017,0.0032025448,0.2432112,0.011083067,0.7356881],"study_design_scores_gemma":[0.00007111008,0.000027102353,0.0021895051,0.0001887482,0.0000070945484,0.0000023869297,0.000055370427,0.9928313,0.00080127304,0.00024511098,0.003506676,0.000074320145],"about_ca_topic_score_codex":0.000025775431,"about_ca_topic_score_gemma":0.00004710478,"teacher_disagreement_score":0.99200964,"about_ca_system_score_codex":0.000018853396,"about_ca_system_score_gemma":0.000023344834,"threshold_uncertainty_score":0.2759036},"labels":[],"label_agreement":null},{"id":"W4403717131","doi":"10.1145/3698131","title":"VisConductor: Affect-Varying Widgets for Animated Data Storytelling in Gesture-Aware Augmented Video Presentation","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Presentation (obstetrics); Storytelling; Gesture; Computer science; Affect (linguistics); Multimedia; Animation; Computer graphics (images); Human–computer interaction; Artificial intelligence; Art; Communication; Psychology; Narrative; Medicine","score_opus":0.1347063429632634,"score_gpt":0.4070920585147327,"score_spread":0.2723857155514693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403717131","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.54200435,0.0002183796,0.4415164,0.0047926125,0.007209267,0.0023670462,0.000109173,0.00106505,0.0007177166],"genre_scores_gemma":[0.98992157,0.000014705496,0.0092518395,0.00024376663,0.00029224835,0.000023231114,0.0001093277,0.00002656239,0.00011674519],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99841875,0.00002129917,0.000413059,0.00063139235,0.00031153086,0.00020399193],"domain_scores_gemma":[0.99867743,0.00019428914,0.00023802415,0.00067535724,0.00017713361,0.000037765403],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044613358,0.00018596456,0.00019298945,0.00035544546,0.00014045715,0.00062653306,0.0026318773,0.00006329272,0.0000072398093],"category_scores_gemma":[0.00017501863,0.00015114197,0.000077055476,0.0004996594,0.000026449177,0.002578318,0.0012150886,0.00023247693,0.000008996403],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039361595,0.0017981814,0.003277664,0.0057163076,0.00085821777,0.000017679944,0.017614868,0.008382014,0.4016249,0.11443394,0.35544446,0.09043816],"study_design_scores_gemma":[0.0003633188,0.00014478939,0.00066833035,0.0010185996,0.000028531565,0.000009067052,0.00010262707,0.96087086,0.03147787,0.0016070764,0.0035176845,0.00019124895],"about_ca_topic_score_codex":0.000023436305,"about_ca_topic_score_gemma":0.0000069192106,"teacher_disagreement_score":0.95248884,"about_ca_system_score_codex":0.00014417646,"about_ca_system_score_gemma":0.000025910913,"threshold_uncertainty_score":0.616339},"labels":[],"label_agreement":null},{"id":"W4403717157","doi":"10.1145/3698139","title":"The Elephant in the Room: Expert Experiences Designing, Developing and Evaluating Data Visualizations on Large Displays","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Data science; Human–computer interaction; Visualization; Data visualization; World Wide Web; Data mining","score_opus":0.1698963727235606,"score_gpt":0.45288136913418936,"score_spread":0.2829849964106288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403717157","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6753342,0.00048103157,0.30418155,0.014316719,0.0031348248,0.0011321036,0.000013690051,0.00031837114,0.0010874674],"genre_scores_gemma":[0.99344254,0.00007499057,0.0048910626,0.0012246893,0.00022981397,0.00005030779,0.000011792784,0.000013852695,0.0000609662],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983964,0.00006450416,0.00037382604,0.00047189245,0.00048206068,0.000211309],"domain_scores_gemma":[0.9985181,0.0004841806,0.00019040376,0.00067498436,0.000108989836,0.000023330751],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0013892237,0.00015725811,0.00011872767,0.00014631588,0.0006314012,0.0014505248,0.0031932706,0.00003543725,0.0000035765884],"category_scores_gemma":[0.00046718973,0.00008273378,0.000038581173,0.0005629416,0.000049472434,0.0012405146,0.0015320242,0.00020931281,0.0000052352248],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035876514,0.00036749197,0.0007090022,0.00019298258,0.000116437484,0.000004831449,0.1266703,0.0002966875,0.0048616384,0.7481626,0.06826634,0.050315768],"study_design_scores_gemma":[0.00017455855,0.0001779421,0.00065731833,0.0008768401,0.000011793989,0.000022973853,0.005039232,0.9736378,0.0046254857,0.0030378534,0.011550329,0.00018787516],"about_ca_topic_score_codex":0.000010463433,"about_ca_topic_score_gemma":0.00001077262,"teacher_disagreement_score":0.9733411,"about_ca_system_score_codex":0.000055472065,"about_ca_system_score_gemma":0.00003407919,"threshold_uncertainty_score":0.99958605},"labels":[],"label_agreement":null},{"id":"W4403717207","doi":"10.1145/3698147","title":"Lights, Headset, Tablet, Action: Exploring the Use of Hybrid User Interfaces for Immersive Situated Analytics","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Headset; Situated; Human–computer interaction; Analytics; Action (physics); Computer science; Multimedia; Data science; Physics; Artificial intelligence","score_opus":0.2608486777574172,"score_gpt":0.375609770108066,"score_spread":0.1147610923506488,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403717207","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.69995314,0.000048651324,0.28712314,0.006638093,0.0050414144,0.0007929126,0.000045295656,0.00021062915,0.00014673882],"genre_scores_gemma":[0.992914,0.000041645453,0.005686627,0.00037681425,0.0003185319,0.000029157005,0.00001219065,0.000024530833,0.0005964675],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985495,0.000017604096,0.00048791256,0.00040812502,0.0003365773,0.0002002685],"domain_scores_gemma":[0.9982638,0.00030927904,0.00035737237,0.00055398035,0.00047597045,0.00003962867],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023611075,0.0002024622,0.00023263347,0.0002761216,0.00022668521,0.00067524123,0.0018804999,0.00003115835,0.000010354116],"category_scores_gemma":[0.00017146626,0.0001286731,0.00019739488,0.0005620995,0.00007206214,0.002492583,0.0008052356,0.00023625258,0.0000086622495],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002557041,0.0007489426,0.0005480302,0.0016763665,0.001489826,0.000004588519,0.009166536,0.009893338,0.14735806,0.15851443,0.63680893,0.033535223],"study_design_scores_gemma":[0.00020956507,0.00027901976,0.00022161103,0.00076225825,0.00009199412,0.000023688483,0.00022735859,0.3795742,0.55485207,0.0020106386,0.06153989,0.0002076666],"about_ca_topic_score_codex":0.000021320624,"about_ca_topic_score_gemma":0.0000037728848,"teacher_disagreement_score":0.57526904,"about_ca_system_score_codex":0.000092863775,"about_ca_system_score_gemma":0.00002433052,"threshold_uncertainty_score":0.65113664},"labels":[],"label_agreement":null},{"id":"W4403813921","doi":"10.48550/arxiv.2409.19747","title":"Natural Language Generation for Visualizations: State of the Art, Challenges and Future Directions","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Centre International de Recherche sur le Cancer","keywords":"Natural (archaeology); State (computer science); Computer science; Visualization; Human–computer interaction; Data science; Geology; Programming language; Artificial intelligence","score_opus":0.06189839220070732,"score_gpt":0.23837117424438845,"score_spread":0.1764727820436811,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403813921","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0684532,0.02553442,0.8918766,0.0037729922,0.005924773,0.0012950436,0.0005321389,0.0005206722,0.0020901714],"genre_scores_gemma":[0.9832214,0.010395511,0.00079724065,0.00011269428,0.00024703093,0.0000020821662,0.00011018459,0.000015011049,0.005098832],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926823,0.00006174729,0.00011630138,0.000407327,0.000053503714,0.00009289385],"domain_scores_gemma":[0.9992541,0.00003301613,0.00011623752,0.0004423544,0.00012069231,0.000033597655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011135679,0.00011876077,0.00012331265,0.00013235633,0.00009963615,0.00008501779,0.00041462557,0.00006650436,0.0000026221105],"category_scores_gemma":[0.000020703374,0.000101228245,0.00008667483,0.00029586282,0.000046972313,0.00013835158,0.00075026974,0.00014906404,0.0000035044602],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000036217798,0.000054873322,0.000018874542,0.00031226472,0.00011961278,0.0000060788084,0.002738011,0.006388719,0.00015058734,0.97414505,0.0019620971,0.014100206],"study_design_scores_gemma":[0.00011986471,0.000013203469,0.00013295554,0.00005454831,0.00006398684,0.0000014768319,0.00019044783,0.9677147,0.000203688,0.01482383,0.016537355,0.00014393528],"about_ca_topic_score_codex":0.000006951703,"about_ca_topic_score_gemma":0.00016071212,"teacher_disagreement_score":0.961326,"about_ca_system_score_codex":0.000032744712,"about_ca_system_score_gemma":0.000072809,"threshold_uncertainty_score":0.4127968},"labels":[],"label_agreement":null},{"id":"W4403886077","doi":"10.1007/978-981-97-8743-2_6","title":"SEBWatcher: Visual Analysis System for Subject, Environment and Behavior in Traffic Scenes","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute on Governance","funders":"","keywords":"Subject (documents); Computer science; Artificial intelligence; Information retrieval; Computer vision; World Wide Web","score_opus":0.035057437395595796,"score_gpt":0.31602534715595754,"score_spread":0.28096790976036173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403886077","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001951458,0.0015149588,0.9799173,0.0008661209,0.00037392558,0.0012636397,0.00013662215,0.00021862934,0.01375736],"genre_scores_gemma":[0.8503677,0.0084341755,0.13592818,0.00078007876,0.000073530784,0.00028344244,0.00076244934,0.000034560944,0.0033358636],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984689,0.000020815873,0.00067143614,0.00034102245,0.0003129717,0.00018488799],"domain_scores_gemma":[0.9984524,0.00013153169,0.00019282423,0.0010347491,0.00010102851,0.000087422326],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00095173926,0.00019342874,0.00029524078,0.0018829101,0.00032218566,0.00071679836,0.0014325368,0.00010033357,0.0000024191586],"category_scores_gemma":[0.000009635188,0.00019126447,0.00006320466,0.0007694465,0.00039825478,0.0027112197,0.0017933684,0.00019491838,0.000015507054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000027930619,0.000062285464,0.00036657677,0.00023449952,0.000044434888,0.000001485257,0.0037177585,0.0032419316,0.000002804841,0.8438189,0.00006156986,0.14844494],"study_design_scores_gemma":[0.00018354529,0.000039502735,0.0009949616,0.00011514612,0.00007355639,0.000007827853,0.00006561082,0.97125655,0.0000037206164,0.00031738478,0.026718514,0.00022366495],"about_ca_topic_score_codex":0.000009923879,"about_ca_topic_score_gemma":0.000027520739,"teacher_disagreement_score":0.96801466,"about_ca_system_score_codex":0.00017684561,"about_ca_system_score_gemma":0.00011243643,"threshold_uncertainty_score":0.77995384},"labels":[],"label_agreement":null},{"id":"W4403896196","doi":"10.1111/cgf.15266","title":"Natural Language Generation for Visualizations: State of the Art, Challenges and Future Directions","year":2024,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Centre International de Recherche sur le Cancer","keywords":"Computer science; State (computer science); Visualization; Natural (archaeology); Computer graphics (images); Natural language generation; Human–computer interaction; Natural language; Artificial intelligence; Programming language; Geology","score_opus":0.019661466829312323,"score_gpt":0.2910691527554301,"score_spread":0.2714076859261178,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403896196","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00087427394,0.021280622,0.9690277,0.0060162265,0.0023369116,0.00021358945,0.000040763043,0.00015492851,0.00005498337],"genre_scores_gemma":[0.88615197,0.046219125,0.055131868,0.0061648255,0.0032715378,0.00012769565,0.000561003,0.000110368426,0.0022615904],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99932545,0.00003820429,0.00015891119,0.00023037115,0.00012762465,0.00011946257],"domain_scores_gemma":[0.9995121,0.00005352263,0.000045583514,0.00027112605,0.0000884285,0.000029234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013704896,0.00008841912,0.00008739235,0.0001447673,0.00013903253,0.00017860167,0.000262708,0.000029907718,7.5819446e-7],"category_scores_gemma":[0.000007780935,0.00006375217,0.00007156399,0.00041417152,0.000043928252,0.00031006304,0.00015287597,0.00006884978,0.0000011329762],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.7353987e-7,0.000019678117,0.0000129843265,0.000061393526,0.000031932213,5.4063355e-7,0.0013776592,0.000017859007,0.00007873244,0.8501579,0.0072508636,0.14098997],"study_design_scores_gemma":[0.00007221217,0.000026208394,0.00024375587,0.000028022383,0.000009170366,0.0000058257083,0.0000322783,0.7926966,0.0001843273,0.0037690415,0.20285763,0.00007493605],"about_ca_topic_score_codex":0.0000012086356,"about_ca_topic_score_gemma":0.00006624505,"teacher_disagreement_score":0.91389585,"about_ca_system_score_codex":0.0000066930756,"about_ca_system_score_gemma":0.000028027878,"threshold_uncertainty_score":0.2599738},"labels":[],"label_agreement":null},{"id":"W4404036152","doi":"10.1109/tvcg.2024.3486613","title":"Iceberg Sensemaking: A Process Model for Critical Data Analysis","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Sensemaking; Iceberg; Data visualization; Process (computing); Data science; Visualization; Data mining; Human–computer interaction; Operating system; Geology","score_opus":0.06815865559870911,"score_gpt":0.3844994632814277,"score_spread":0.3163408076827186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404036152","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00007823919,0.000077057746,0.99822575,0.0002672306,0.00044120895,0.0001769765,0.00023506819,0.00048144598,0.000017022212],"genre_scores_gemma":[0.98112243,0.00017970717,0.01626938,0.0019018025,0.00008274743,0.000029573528,0.00022040585,0.00003187504,0.00016207663],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99818933,0.000065149135,0.0003497556,0.0008293429,0.00033330428,0.00023314271],"domain_scores_gemma":[0.9986212,0.0002710655,0.00004252551,0.0007080565,0.00021288187,0.00014425482],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003495672,0.00020806566,0.00023245944,0.0008347704,0.00031605203,0.0009170323,0.00058765686,0.00011594271,0.000007281194],"category_scores_gemma":[0.000011590284,0.00020248619,0.000129664,0.0024490436,0.000081327686,0.00097653473,0.0000143918205,0.00014360243,0.0000044790404],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000060950038,0.00016461818,0.0000049453106,0.00017211359,0.00027744207,0.000003833054,0.0008201486,0.018456018,0.0000023023488,0.97517383,0.00070583983,0.0042127883],"study_design_scores_gemma":[0.00016312483,0.00006601134,0.0000046028404,0.000049469778,0.00036172656,0.000008735823,0.00001949907,0.99322575,0.00007825173,0.0046947342,0.0010808229,0.0002472405],"about_ca_topic_score_codex":0.000003214649,"about_ca_topic_score_gemma":0.0000266263,"teacher_disagreement_score":0.98195636,"about_ca_system_score_codex":0.0000140822885,"about_ca_system_score_gemma":0.00009899997,"threshold_uncertainty_score":0.88429636},"labels":[],"label_agreement":null},{"id":"W4404136703","doi":"10.2139/ssrn.4970102","title":"Conformal Inverse Optimization for Adherence-aware Prescriptive Analytics","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal; University of Toronto","funders":"","keywords":"Analytics; Conformal map; Inverse; Computer science; Data science; Mathematics; Mathematical analysis","score_opus":0.030241048485253448,"score_gpt":0.30369308036080433,"score_spread":0.2734520318755509,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404136703","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00014152745,0.00079435005,0.9956668,0.0006488396,0.0014992633,0.00036758868,0.00009376246,0.00015523648,0.0006326326],"genre_scores_gemma":[0.6669061,0.05276017,0.19677807,0.004260371,0.0067731417,0.00034312927,0.0036386221,0.0005625916,0.06797777],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99669886,0.00007260913,0.00060512393,0.0005264824,0.0004466891,0.0016502413],"domain_scores_gemma":[0.9983059,0.000043241904,0.00045070946,0.0005065947,0.00053653907,0.00015702414],"candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0013103045,0.00034279868,0.00035815165,0.00039703678,0.00020721766,0.0011035113,0.001563087,0.0002702983,0.000030845324],"category_scores_gemma":[0.000108839246,0.00031775841,0.00030759364,0.00038684742,0.000051865794,0.0004830732,0.0011342949,0.0027667617,0.000038927843],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023257837,0.00006987922,0.000020624635,0.00017506022,0.0006086977,0.000007671589,0.00057312625,0.16766685,0.000002726534,0.8106311,0.008259456,0.011961571],"study_design_scores_gemma":[0.00031231044,0.00020556028,8.9881877e-7,0.00011762811,0.0001230187,0.000057125195,0.0004371085,0.7676926,0.000017487178,0.22835268,0.002400127,0.00028341342],"about_ca_topic_score_codex":0.000023125627,"about_ca_topic_score_gemma":0.00018512023,"teacher_disagreement_score":0.79888874,"about_ca_system_score_codex":0.000982452,"about_ca_system_score_gemma":0.0076000993,"threshold_uncertainty_score":0.9999334},"labels":[],"label_agreement":null},{"id":"W4404294301","doi":"10.1109/eduvis63909.2024.00006","title":"Challenges and Opportunities of Teaching Data Visualization Together with Data Science","year":2024,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bruyère; Carleton University","funders":"Carleton University","keywords":"Visualization; Computer science; Data visualization; Data science; Information visualization; Artificial intelligence","score_opus":0.27707162954960696,"score_gpt":0.40033328900105525,"score_spread":0.12326165945144829,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404294301","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00026598008,0.0020714507,0.97249967,0.0015670132,0.00007835709,0.000050145925,0.000045891196,0.00015643134,0.023265034],"genre_scores_gemma":[0.9372357,0.0079171145,0.052275706,0.0005901774,0.0000713647,0.0000012167849,0.0004345151,0.000020439807,0.001453735],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998967,0.000030307336,0.00012307755,0.0004779206,0.00030260655,0.00009912025],"domain_scores_gemma":[0.99838305,0.000044937424,0.000031874122,0.0014393388,0.000049561007,0.00005121511],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001182849,0.00006486318,0.00007556776,0.00015859111,0.000073680545,0.00034897655,0.0019251859,0.000013390335,0.00000876378],"category_scores_gemma":[0.00006267455,0.000045591976,0.0000029050957,0.00019004133,0.00017288359,0.004297845,0.0019695992,0.000040514245,0.000002113742],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.454171e-7,0.000013763908,0.0000137079005,0.000045787183,0.0000070945416,0.0000027857823,0.0005771776,0.0000015958324,0.00005517986,0.86785275,0.000548109,0.13088173],"study_design_scores_gemma":[0.000048450966,0.000035907928,0.000072143084,0.000099570534,0.000010033343,0.000014157302,0.0006464621,0.93674546,0.00012578511,0.00058508426,0.061521612,0.00009530072],"about_ca_topic_score_codex":0.0000128767515,"about_ca_topic_score_gemma":0.000019736814,"teacher_disagreement_score":0.93696976,"about_ca_system_score_codex":0.0000047698154,"about_ca_system_score_gemma":0.00016258119,"threshold_uncertainty_score":0.35775065},"labels":[],"label_agreement":null},{"id":"W4404317744","doi":"10.1109/visap64569.2024.00012","title":"What’s My Line? Exploring the Expressive Capacity of Lines in Scientific Visualization","year":2024,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Visualization; Computer science; Line (geometry); Data visualization; Data science; Human–computer interaction; Artificial intelligence; Mathematics","score_opus":0.11296807422059116,"score_gpt":0.3397716833403285,"score_spread":0.22680360911973732,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404317744","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10110811,0.00028405836,0.8942036,0.000850855,0.0029680708,0.000118236676,0.0000042957695,0.00015555516,0.00030723197],"genre_scores_gemma":[0.99648005,0.00015798306,0.0014420238,0.00014564588,0.0000696584,0.000012795453,0.00001405593,0.000006606666,0.0016711678],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990882,0.000052404623,0.00023903679,0.0002560252,0.0002500279,0.0001142948],"domain_scores_gemma":[0.9993908,0.000089596746,0.00003891886,0.00034394863,0.00010925957,0.000027523158],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0004385787,0.000069233676,0.00008089693,0.00021576043,0.00006884224,0.0011557438,0.000505319,0.000018724797,0.000021353866],"category_scores_gemma":[0.00008561653,0.000045575514,0.000032957545,0.0013606009,0.000077016266,0.0023920725,0.00018296493,0.000054716667,0.000023830946],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000011200686,0.00008220793,0.00025950483,0.00010550707,0.000012011451,0.0000053757503,0.010466356,0.0018135335,0.0053419843,0.9663236,0.0035989815,0.0119897835],"study_design_scores_gemma":[0.00006637155,0.000013886222,0.00017518635,0.00023989343,0.0000036755932,0.0000014571795,0.0007443084,0.9387798,0.044509653,0.0029000486,0.012472335,0.00009340737],"about_ca_topic_score_codex":0.000020656342,"about_ca_topic_score_gemma":0.000055589633,"teacher_disagreement_score":0.9634236,"about_ca_system_score_codex":0.000014704852,"about_ca_system_score_gemma":0.000054315566,"threshold_uncertainty_score":0.99988115},"labels":[],"label_agreement":null},{"id":"W4404396638","doi":"10.1016/j.ins.2024.121642","title":"Introducing fairness in network visualization","year":2024,"lang":"en","type":"article","venue":"Information Sciences","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"Ministero dell'Università e della Ricerca; Università degli Studi di Perugia; Ministero dell’Istruzione, dell’Università e della Ricerca","keywords":"Computer science; Visualization; Data mining","score_opus":0.02119981720258693,"score_gpt":0.3277941109098233,"score_spread":0.30659429370723634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404396638","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000807961,0.000065111184,0.99062604,0.00078688865,0.00071198016,0.00005792844,0.000001219575,0.0001985855,0.0067442637],"genre_scores_gemma":[0.98820496,0.000045558412,0.01017078,0.0013161622,0.00012909422,0.0000068700315,0.000026364072,0.000002400974,0.00009783235],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99903333,0.000030584994,0.00029476406,0.00014431887,0.0003296654,0.00016732483],"domain_scores_gemma":[0.99968034,0.000054772325,0.000048744052,0.0001345799,0.000051019106,0.00003053498],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0010961893,0.000059214883,0.00006136782,0.0003552204,0.00012196024,0.0015194458,0.000488661,0.00002449956,0.000025536398],"category_scores_gemma":[0.00009068862,0.000049597682,0.000016667866,0.0029713742,0.00004986589,0.0076595508,0.00010829368,0.00004564284,0.00022592247],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.2955162e-7,0.0000036717627,0.0005325037,0.00001799874,0.0000011197418,7.0349216e-7,0.0014319209,0.033937,0.000003818942,0.91971475,0.0044636894,0.0398926],"study_design_scores_gemma":[0.000036423375,0.000011845327,0.00049677235,0.00004708763,6.1814416e-7,0.0000032128382,0.00012014325,0.9410026,0.000048230133,0.0053142677,0.052846424,0.000072360126],"about_ca_topic_score_codex":0.000020744406,"about_ca_topic_score_gemma":0.000012602253,"teacher_disagreement_score":0.98739696,"about_ca_system_score_codex":0.00002984877,"about_ca_system_score_gemma":0.00011750283,"threshold_uncertainty_score":0.9995171},"labels":[],"label_agreement":null},{"id":"W4404586293","doi":"10.1145/3699730","title":"SynthCAT: Synthesizing Cellular Association Traces with Fusion of Model-Based and Data-Driven Approaches","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Data association; Association (psychology); Fusion; Computer science; Sensor fusion; Artificial intelligence; Psychology","score_opus":0.03872138332647597,"score_gpt":0.27986788631307813,"score_spread":0.24114650298660217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404586293","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97347975,0.0015322643,0.019064106,0.004030589,0.00008859127,0.00053524814,0.000064021944,0.00059547735,0.00060998043],"genre_scores_gemma":[0.99228555,0.00028822778,0.007289933,0.000019530635,0.000006872625,0.000030219539,0.0000020139137,0.00001008824,0.00006755986],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989622,0.000009568464,0.0001996622,0.00043389096,0.0002509304,0.00014372666],"domain_scores_gemma":[0.9988206,0.00027141877,0.00025155093,0.00052254135,0.00011554136,0.000018329101],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032645333,0.00014112561,0.0002180688,0.00019745354,0.0001039655,0.0002026659,0.0016429457,0.000095186544,8.057011e-7],"category_scores_gemma":[0.00078432733,0.00008939089,0.000029196663,0.00038557174,0.00014491065,0.0007658937,0.0013801127,0.0001983013,5.2589974e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037577908,0.0012241381,0.011638299,0.0051937196,0.0009607357,0.000008928354,0.0074261567,0.010912958,0.45158482,0.13055792,0.0047664666,0.3753501],"study_design_scores_gemma":[0.00007889967,0.00019620138,0.00003485257,0.0007295684,0.00004264739,0.0000028540203,0.001805678,0.5629233,0.42991248,0.003932063,0.00023290767,0.00010856101],"about_ca_topic_score_codex":0.000008740487,"about_ca_topic_score_gemma":0.0000020496602,"teacher_disagreement_score":0.55201036,"about_ca_system_score_codex":0.00004501559,"about_ca_system_score_gemma":0.000041596795,"threshold_uncertainty_score":0.36452547},"labels":[],"label_agreement":null},{"id":"W4404628253","doi":"10.1109/ciot63799.2024.10757021","title":"An Architectural Approach for Enhanced Data Interoperability Across Building Systems","year":2024,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Concordia University","funders":"","keywords":"Interoperability; Computer science; Software engineering; World Wide Web","score_opus":0.0828969629030021,"score_gpt":0.4080437267107684,"score_spread":0.3251467638077663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404628253","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011694712,0.000059254733,0.9867658,0.000081377046,0.0004103219,0.00018957103,0.00013013204,0.0003961295,0.00027269046],"genre_scores_gemma":[0.87124276,0.000001141018,0.12794147,0.00008510485,0.00009983026,0.0000119852475,0.00027076644,0.000007469392,0.00033947796],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987933,0.000046592675,0.00019767554,0.0006215323,0.00013366024,0.00020726293],"domain_scores_gemma":[0.99857485,0.00005572374,0.000019024668,0.0012270625,0.00004753015,0.00007577693],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0006213706,0.00009291778,0.000112425405,0.00003675864,0.0000890611,0.0014971616,0.0018377606,0.000026922173,0.0000043938676],"category_scores_gemma":[0.000047443074,0.00006718816,0.000027682776,0.0002503654,0.00003167381,0.0010548318,0.00054938445,0.00006408645,0.000006422918],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016921837,0.0003390966,0.00009611215,0.0013900328,0.00013619279,0.000004519759,0.0057799937,0.010377211,0.025487974,0.6566977,0.006025896,0.29364836],"study_design_scores_gemma":[0.00006510119,0.000033879343,0.000010280121,0.000018122686,0.0000029338837,0.000008634723,0.00016435239,0.99407935,0.0015442678,0.00015066355,0.0038185662,0.000103874554],"about_ca_topic_score_codex":0.000034267352,"about_ca_topic_score_gemma":0.000007142003,"teacher_disagreement_score":0.9837021,"about_ca_system_score_codex":0.000021364132,"about_ca_system_score_gemma":0.000033162185,"threshold_uncertainty_score":0.9995394},"labels":[],"label_agreement":null},{"id":"W4404708694","doi":"10.1109/tvcg.2024.3473148","title":"Preface","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Computer graphics (images)","score_opus":0.02132895336293722,"score_gpt":0.2957976141353369,"score_spread":0.2744686607723997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404708694","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0003879542,0.00012274885,0.99721897,0.00014895877,0.0010861617,0.000106137224,0.000013225371,0.00076464284,0.00015122656],"genre_scores_gemma":[0.9928221,0.0009034982,0.002475479,0.0028843628,0.000101930535,0.000015717504,0.000018659224,0.00003212475,0.0007461169],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99883336,0.0000673594,0.00023018596,0.00043619823,0.00026426738,0.00016865379],"domain_scores_gemma":[0.9994101,0.000074526906,0.000028498995,0.0002952769,0.000073060226,0.000118543954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015162645,0.00016647864,0.00012226816,0.00043478012,0.00020518995,0.0007254813,0.00027031,0.00007974822,0.000024989311],"category_scores_gemma":[0.0000012108991,0.000157242,0.00007457755,0.0011581298,0.0000536811,0.00061720907,0.000005605169,0.00014051367,0.000053117135],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001561641,0.00007592085,0.0000045076076,0.000043919146,0.00003295827,0.0000059967915,0.0004254425,0.00028807117,0.000007061993,0.97894967,0.0014007299,0.018764155],"study_design_scores_gemma":[0.00013795054,0.00010075528,0.000027431859,0.00006584389,0.000015584048,0.000019726236,0.000008862342,0.9717096,0.00073278754,0.0014893366,0.025505235,0.00018689495],"about_ca_topic_score_codex":0.000004299856,"about_ca_topic_score_gemma":0.0000046857313,"teacher_disagreement_score":0.99474347,"about_ca_system_score_codex":0.000015729975,"about_ca_system_score_gemma":0.00004561053,"threshold_uncertainty_score":0.6995833},"labels":[],"label_agreement":null},{"id":"W4405000865","doi":"10.1111/cgf.15271","title":"The State of the Art in User‐Adaptive Visualizations","year":2024,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of Toronto","funders":"","keywords":"Computer science; Computer graphics (images); State (computer science); Human–computer interaction; Programming language","score_opus":0.01663240177794631,"score_gpt":0.2825589619793363,"score_spread":0.26592656020138994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405000865","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006029982,0.00031683478,0.9952278,0.002493878,0.00093035155,0.00013759661,0.00001540357,0.00008290298,0.00019221794],"genre_scores_gemma":[0.98703665,0.0006695324,0.0059779654,0.0029710738,0.000106418505,0.000024160263,0.000028368035,0.000041605577,0.0031442372],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99890834,0.000095245225,0.00028636563,0.00022806438,0.00026466363,0.00021732642],"domain_scores_gemma":[0.99907506,0.00018815814,0.00006318226,0.0005475765,0.0000899787,0.000036076228],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031810853,0.00010134816,0.00009817859,0.00016582267,0.00017081162,0.00033731663,0.0011158338,0.000027112956,0.0000013620735],"category_scores_gemma":[0.000015052897,0.000060598886,0.000096163036,0.0019248977,0.00013420603,0.0003069451,0.00056170544,0.00014453371,0.000016212114],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.423003e-7,0.000023499615,0.00056314573,0.000008014366,0.00001826967,0.0000027470655,0.00028881495,0.00054098526,0.0000030154008,0.9777103,0.016086727,0.004753806],"study_design_scores_gemma":[0.000066937035,0.000027154527,0.0012056552,0.0000673378,0.000003599755,0.0000034030766,0.000012975135,0.84493273,0.000066975954,0.04381134,0.10972473,0.000077163575],"about_ca_topic_score_codex":0.000008952904,"about_ca_topic_score_gemma":0.00018802485,"teacher_disagreement_score":0.9892498,"about_ca_system_score_codex":0.000015597614,"about_ca_system_score_gemma":0.00009362692,"threshold_uncertainty_score":0.3252752},"labels":[],"label_agreement":null},{"id":"W4405093814","doi":"10.3138/cjc-2023-0022","title":"Searching for Digital Agency: Subject Possibilities in the Aesthetics of Computational Ambiguity","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Communication","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Athabasca University","funders":"","keywords":"Ambiguity; Agency (philosophy); Subject (documents); Aesthetics; Sociology; Epistemology; Computer science; Art; Philosophy; World Wide Web","score_opus":0.04399585197352474,"score_gpt":0.32743051020813524,"score_spread":0.2834346582346105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405093814","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.202318,0.0026516481,0.78285474,0.009709741,0.0002173615,0.00023862667,0.00009998875,0.000014581141,0.0018953251],"genre_scores_gemma":[0.99490654,0.000027610064,0.004880853,0.00011509225,0.000012127443,8.788095e-7,0.000023453666,0.0000032611008,0.000030152765],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99932843,0.00010477905,0.00028858433,0.000049208087,0.00014196652,0.000087019886],"domain_scores_gemma":[0.99906725,0.00032406353,0.000090577894,0.00027525032,0.00018343031,0.000059456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00093138975,0.000040917468,0.00007532479,0.00023197812,0.00007706762,0.00039206503,0.000993699,0.000018063218,0.000002633989],"category_scores_gemma":[0.00015886362,0.00003209195,0.000054674154,0.00030882616,0.000077534256,0.00050588814,0.00002515587,0.000121936435,0.000001019303],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000034593463,0.000039040355,0.00093205733,0.000065860266,0.000025084668,0.0000146411,0.02563981,0.0071236407,0.0000071181003,0.8807096,0.0020594457,0.08338024],"study_design_scores_gemma":[0.00029335165,0.00016626486,0.0077450485,0.00036988125,0.000014053147,0.00016371292,0.0012683262,0.42677745,0.000042588916,0.5436558,0.019366331,0.00013718265],"about_ca_topic_score_codex":0.00044041552,"about_ca_topic_score_gemma":0.0020809623,"teacher_disagreement_score":0.7925886,"about_ca_system_score_codex":0.00005481065,"about_ca_system_score_gemma":0.00091941276,"threshold_uncertainty_score":0.37806922},"labels":[],"label_agreement":null},{"id":"W4405248811","doi":"10.1177/20552076241300748","title":"RemoteHealthConnect: Innovating patient monitoring with wearable technology and custom visualization","year":2024,"lang":"en","type":"article","venue":"Digital Health","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph; Sheridan College","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wearable computer; Visualization; Computer science; Human–computer interaction; Wearable technology; Computer graphics (images); Engineering; Embedded system; Artificial intelligence","score_opus":0.017266376391650934,"score_gpt":0.31385302743059285,"score_spread":0.2965866510389419,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405248811","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08522966,0.0030949716,0.90350276,0.004807182,0.00037859555,0.00025609005,0.000014096096,0.0010528179,0.0016638391],"genre_scores_gemma":[0.99419725,0.00016616302,0.0051133786,0.00033966798,0.000037330923,0.0000033069741,0.000009978178,0.000014197915,0.00011870262],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99899095,0.000014198721,0.00024681637,0.0003195803,0.00018001898,0.0002484151],"domain_scores_gemma":[0.99952865,0.000032102384,0.00007071753,0.00019942517,0.000077926605,0.000091182694],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013435878,0.00009747863,0.000118961594,0.000389745,0.00014733203,0.0006123099,0.000141923,0.00003840454,8.143836e-7],"category_scores_gemma":[0.00003733941,0.000082988336,0.000008364822,0.0020742712,0.00003172018,0.00092428963,0.00011969622,0.000102599384,0.000014505486],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000014924832,0.0000234876,0.002803566,0.00018835672,0.0000061553587,0.000010374761,0.00056666817,0.000019349885,0.0000052451933,0.21679682,0.00013439449,0.7794441],"study_design_scores_gemma":[0.00071132527,0.0023631358,0.0013214656,0.0056821196,0.0000069813295,0.00034096435,0.0017538852,0.8734406,0.0010071021,0.017880028,0.09456249,0.0009298607],"about_ca_topic_score_codex":0.000016222757,"about_ca_topic_score_gemma":0.000002159674,"teacher_disagreement_score":0.9089676,"about_ca_system_score_codex":0.00007123432,"about_ca_system_score_gemma":0.00021656019,"threshold_uncertainty_score":0.59045184},"labels":[],"label_agreement":null},{"id":"W4405425135","doi":"10.1109/iccvw69036.2025.00176","title":"V-RoAst: Visual Road Assessment Can VLM be a Road Safety Assessor using the iRAP Standard?","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; China Scholarship Council; Chulalongkorn University; UK Research and Innovation; Canadian Thoracic Society","keywords":"Visual inspection; Computer science; Artificial intelligence; Transport engineering; Engineering","score_opus":0.050916854045783604,"score_gpt":0.40414706935615796,"score_spread":0.35323021531037435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405425135","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006961739,0.00006724559,0.9754675,0.005285507,0.0014289449,0.0005427402,0.00050391554,0.0003251867,0.01568281],"genre_scores_gemma":[0.5079927,0.00087843335,0.42232737,0.025193144,0.001380143,0.00017772391,0.0023813753,0.000174466,0.039494675],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.995981,0.00042125775,0.0009107446,0.001097267,0.0010651767,0.0005245919],"domain_scores_gemma":[0.99694836,0.000117536736,0.000477169,0.0018206537,0.00045541415,0.00018083568],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0013201324,0.0005127693,0.00066145003,0.00028530793,0.00051164,0.0018019838,0.0028735048,0.0002767904,0.00018804258],"category_scores_gemma":[0.00010226726,0.00037570237,0.00027806664,0.0008081064,0.00010929879,0.00031653463,0.0056747613,0.0008924447,0.0000048150146],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037681162,0.00079247396,0.0021111567,0.0005341466,0.0010910635,0.00006038809,0.0019896158,0.035987448,0.00011479287,0.6169376,0.023968559,0.3163751],"study_design_scores_gemma":[0.0004041165,0.000053434906,0.0012737749,0.00019785587,0.00009922993,0.000004757643,0.00031312593,0.96163404,0.00016275245,0.0011790872,0.03413498,0.0005428618],"about_ca_topic_score_codex":0.0015319106,"about_ca_topic_score_gemma":0.00076320494,"teacher_disagreement_score":0.9256466,"about_ca_system_score_codex":0.0005322579,"about_ca_system_score_gemma":0.0033181852,"threshold_uncertainty_score":0.99986947},"labels":[],"label_agreement":null},{"id":"W4405473276","doi":"10.2139/ssrn.5059947","title":"A Round-Up of Holiday Gifts from INFIDEOS","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Advertising; Art; Business","score_opus":0.012507591799974753,"score_gpt":0.2845945428031722,"score_spread":0.27208695100319746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405473276","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012119056,0.0035582625,0.98183644,0.0011140626,0.0006232218,0.000034707926,0.000009065536,0.00008127344,0.00062388787],"genre_scores_gemma":[0.9947148,0.0017864428,0.0007326511,0.0001768208,0.00021200473,7.443608e-7,0.000009104875,0.000011573713,0.0023558484],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99837595,0.00005478314,0.00027635513,0.000190979,0.00030297055,0.000798955],"domain_scores_gemma":[0.99947304,0.000055589506,0.000084246065,0.00025018977,0.000069099275,0.0000678392],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071571604,0.000098072924,0.00013461841,0.00016343126,0.00006486132,0.00033974354,0.0007077583,0.000042055075,0.00003826434],"category_scores_gemma":[0.000040420622,0.00008247751,0.00009493694,0.00046272768,0.000036923397,0.0006527124,0.000102327846,0.0006704748,0.00008740136],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002325688,0.00002166722,0.00011010865,0.0000054032553,0.00010195007,0.0000069235757,0.00034489715,0.000024451598,0.0003002783,0.96312565,0.00094311737,0.035013225],"study_design_scores_gemma":[0.00054110464,0.00024307634,0.00015921926,0.00013223593,0.000050588973,0.00028849937,0.00062376325,0.08750511,0.0012791055,0.8624136,0.04647412,0.000289584],"about_ca_topic_score_codex":0.00009640056,"about_ca_topic_score_gemma":0.0001810328,"teacher_disagreement_score":0.98259574,"about_ca_system_score_codex":0.00020604208,"about_ca_system_score_gemma":0.0017103403,"threshold_uncertainty_score":0.33633354},"labels":[],"label_agreement":null},{"id":"W4406071020","doi":"10.1016/j.softx.2025.102034","title":"GraphOptima: A graph layout optimization framework for visualizing large networks","year":2025,"lang":"en","type":"article","venue":"SoftwareX","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ted Rogers Centre for Heart Research","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Graph Layout; Graph drawing; Graph; Theoretical computer science; Visualization; Distributed computing; Artificial intelligence","score_opus":0.015078626115208842,"score_gpt":0.3222873554865336,"score_spread":0.30720872937132476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406071020","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00002157142,0.0002794183,0.9977077,0.00035537244,0.00064457586,0.00022824376,0.000021870748,0.00050880184,0.00023239545],"genre_scores_gemma":[0.04670514,0.00014033605,0.9467857,0.005420235,0.00011076069,0.000062849926,0.0002229119,0.000025081219,0.0005270206],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99875456,0.000043593984,0.00027725103,0.00040372772,0.00015802028,0.00036285073],"domain_scores_gemma":[0.99889183,0.00024988834,0.00010364629,0.0005072961,0.00017309157,0.0000742524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033064364,0.00015507516,0.00018491312,0.00026186908,0.00030065913,0.00032486487,0.0006742385,0.00013676543,0.00002088182],"category_scores_gemma":[0.00033680926,0.00015742228,0.00012764535,0.0014513101,0.000029664812,0.0003881581,0.00023081093,0.000120389435,0.00000592202],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000058580076,0.00009125648,0.0012288766,0.000034109707,0.000042480246,0.0000013419831,0.00014511989,0.08294389,9.0749387e-7,0.9020204,0.010512198,0.0029735754],"study_design_scores_gemma":[0.0003773157,0.000027012862,0.00008027373,0.000088961744,0.000021039996,6.4369897e-7,0.000034988316,0.94981515,0.000023411209,0.038388457,0.010962407,0.00018034976],"about_ca_topic_score_codex":0.0000032574087,"about_ca_topic_score_gemma":0.0000025444922,"teacher_disagreement_score":0.86687124,"about_ca_system_score_codex":0.000025009149,"about_ca_system_score_gemma":0.00006545518,"threshold_uncertainty_score":0.6419494},"labels":[],"label_agreement":null},{"id":"W4406400969","doi":"10.15198/seeci.2025.58.e909","title":"Assessing juicy elements in interactive infographics","year":2025,"lang":"en","type":"article","venue":"Revista de Comunicación de la SEECI","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MacEwan University","funders":"","keywords":"Infographic; Computer science; Psychology","score_opus":0.018920379090759748,"score_gpt":0.38157862409388743,"score_spread":0.3626582450031277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406400969","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029176842,0.0008361494,0.9408158,0.0014573885,0.00008200712,0.00020339056,0.000006128009,0.00017811202,0.027244184],"genre_scores_gemma":[0.96491146,0.0007950393,0.030938813,0.0030004445,0.000014449281,0.000009706615,0.000019512812,0.0000094950165,0.00030105424],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984255,0.00048502884,0.00040067657,0.0002601934,0.0001555932,0.0002730361],"domain_scores_gemma":[0.99847305,0.00047570758,0.00013232257,0.0007724115,0.0000732424,0.00007329244],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0011013171,0.00012913514,0.00021006809,0.00035474883,0.00008600412,0.0012119157,0.001270094,0.00008379529,0.000013551907],"category_scores_gemma":[0.000459325,0.00013603376,0.00007262925,0.001441483,0.00006759956,0.00077602,0.00061223155,0.00032462526,0.000008351587],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000057984576,0.00021590586,0.06018074,0.00007339442,0.0000545776,0.00003782309,0.00040324574,0.00008177486,0.00024848658,0.8913013,0.0032059296,0.044191036],"study_design_scores_gemma":[0.0011082251,0.000028044273,0.045084927,0.0009079412,0.00003168106,0.000016984499,0.00028885427,0.31560662,0.00019214957,0.010993542,0.6253528,0.0003882295],"about_ca_topic_score_codex":0.000020095047,"about_ca_topic_score_gemma":0.000014322686,"teacher_disagreement_score":0.9357346,"about_ca_system_score_codex":0.00018113635,"about_ca_system_score_gemma":0.0002681515,"threshold_uncertainty_score":0.99982494},"labels":[],"label_agreement":null},{"id":"W4406679308","doi":"10.29169/1927-5129.2025.21.02","title":"Review Article: Graph Colouring and Applications","year":2025,"lang":"en","type":"article","venue":"Journal of Basic & Applied Sciences","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Graph; Theoretical computer science","score_opus":0.022266516673836206,"score_gpt":0.32165851160756764,"score_spread":0.2993919949337314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406679308","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002291078,0.010776041,0.97032404,0.004947257,0.00012840716,0.00018690978,9.716462e-7,0.00002749456,0.011317817],"genre_scores_gemma":[0.8872492,0.021895235,0.06542394,0.024855154,0.00018832165,0.000029221137,9.027313e-7,0.0000071963236,0.0003508578],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99918884,0.000020671,0.0003112906,0.00014222499,0.00022390821,0.00011304344],"domain_scores_gemma":[0.9994181,0.00007911703,0.00020592341,0.00014670486,0.00008589476,0.00006428328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010311963,0.000057048463,0.00014536442,0.0001728966,0.00020169893,0.000177085,0.0006549746,0.000015097665,0.0000064913474],"category_scores_gemma":[0.000036399164,0.00004311029,0.000032418793,0.0013368368,0.00015448518,0.00030112683,0.00011691651,0.000077518846,0.0000044357107],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012472007,0.00006257875,0.00050990377,0.00016182402,0.000016193691,0.0000015673356,0.00006392506,0.00006475471,0.0010648846,0.88956535,0.011810183,0.096677594],"study_design_scores_gemma":[0.0017045668,0.00031097862,0.0063261134,0.0034988336,0.0002661951,0.000204661,0.00079112255,0.02353004,0.010581582,0.27623188,0.6757671,0.0007869003],"about_ca_topic_score_codex":5.895929e-7,"about_ca_topic_score_gemma":9.5173374e-7,"teacher_disagreement_score":0.9049001,"about_ca_system_score_codex":0.000010735407,"about_ca_system_score_gemma":0.00013514241,"threshold_uncertainty_score":0.17579865},"labels":[],"label_agreement":null},{"id":"W4406734073","doi":"10.1051/itmconf/20257003003","title":"Data Visualization and Prediction Model Analysis","year":2025,"lang":"en","type":"article","venue":"ITM Web of Conferences","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Saint Vincent University","funders":"","keywords":"Visualization; Computer science; Data science; Data mining","score_opus":0.05824450857557954,"score_gpt":0.35228130946626385,"score_spread":0.2940368008906843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406734073","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003086145,0.000074059666,0.9891803,0.00021716215,0.00005251686,0.000038600992,0.00011872212,0.00004832333,0.0071841194],"genre_scores_gemma":[0.996806,0.00020150236,0.0022767198,0.00011597477,0.000005668114,0.0000010500592,0.00024245905,0.0000010328035,0.00034956212],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99930006,0.000030512778,0.00020766642,0.0002444783,0.00015316484,0.00006412293],"domain_scores_gemma":[0.99925166,0.000036103007,0.000084034866,0.0004792648,0.0001232851,0.000025671196],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021272969,0.000057202167,0.00013508165,0.00030153376,0.000045297078,0.000126386,0.00062191376,0.00003205162,0.000012815333],"category_scores_gemma":[0.000060420865,0.000051331695,0.000017678218,0.0009479211,0.0000486473,0.00050694874,0.00030114435,0.000023234701,7.931462e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000013333321,0.000029943194,0.023248326,0.000016689553,0.000121648794,1.15410415e-7,0.00006180956,0.00094991626,0.0000685927,0.97023046,0.0015896723,0.003681486],"study_design_scores_gemma":[0.00009077429,0.000009737726,0.0028202948,0.000014143299,0.000111295,8.492506e-8,0.00003593632,0.98963994,0.00015581243,0.0037957479,0.0032835382,0.00004270394],"about_ca_topic_score_codex":0.000020193118,"about_ca_topic_score_gemma":0.00006855262,"teacher_disagreement_score":0.9937199,"about_ca_system_score_codex":0.0000035258477,"about_ca_system_score_gemma":0.00035937445,"threshold_uncertainty_score":0.20932458},"labels":[],"label_agreement":null},{"id":"W4406855759","doi":"10.1073/pnas.2401230121","title":"Is Ockham’s razor losing its edge? New perspectives on the principle of model parsimony","year":2025,"lang":"en","type":"review","venue":"Proceedings of the National Academy of Sciences","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Nokia Foundation; John Templeton Foundation; UK Research and Innovation; European Research Council; National Science Foundation; Schmidt Family Foundation; Canadian Institute for Advanced Research; Finnish Center for Artificial Intelligence; Bill and Ann Templeton Foundation","keywords":"Interpretability; Occam's razor; Computer science; Context (archaeology); Scientific modelling; Data science; Simple (philosophy); Management science; Artificial intelligence; Epistemology; Mathematics; Statistics; Paleontology; Biology","score_opus":0.17161533400200765,"score_gpt":0.4229019005456153,"score_spread":0.2512865665436076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406855759","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000116764764,0.97214425,0.0013796948,0.008586662,0.00009651682,0.001175435,0.00020219173,0.000050563187,0.01624793],"genre_scores_gemma":[0.004598103,0.9864844,0.0047890223,0.00079540204,0.00011099767,0.000013335345,6.2189235e-7,0.000009536889,0.003198569],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9971159,0.00001885796,0.0006299619,0.0004768425,0.0015867992,0.00017163961],"domain_scores_gemma":[0.99780345,0.0003664334,0.0012397091,0.0000423553,0.00050423923,0.00004379263],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001469048,0.00020690636,0.0005428675,0.0003876892,0.00023808381,0.00010363802,0.0043258634,0.0001318839,0.000009754325],"category_scores_gemma":[0.0013091422,0.000112069734,0.00029919884,0.0023659219,0.0004486746,0.00056646316,0.00076349865,0.0002688067,0.000002566581],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.786211e-7,0.000052129704,0.000004550288,0.001603524,0.00003814595,2.1960915e-9,0.00037982364,0.0001330773,0.000037368092,0.9832599,0.005632235,0.008858239],"study_design_scores_gemma":[0.0004335171,0.00017136178,0.00008591548,0.043525152,0.0005143818,0.000011728387,0.00066652434,0.36962226,0.013236059,0.15664876,0.41402185,0.0010624896],"about_ca_topic_score_codex":9.766169e-7,"about_ca_topic_score_gemma":1.163558e-8,"teacher_disagreement_score":0.82661116,"about_ca_system_score_codex":0.00006461992,"about_ca_system_score_gemma":0.000555264,"threshold_uncertainty_score":0.80386025},"labels":[],"label_agreement":null},{"id":"W4407050030","doi":"10.1093/iwc/iwaf001","title":"Introducing the INSPIRE Framework: Guidelines From Expert Librarians for Search and Selection in HCI Literature","year":2025,"lang":"en","type":"article","venue":"Interacting with Computers","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Transparency (behavior); Set (abstract data type); Field (mathematics); Selection (genetic algorithm); Data science; Systematic review; Quality (philosophy); Advice (programming); Management science; Artificial intelligence; MEDLINE; Engineering","score_opus":0.027325635350709067,"score_gpt":0.3516745835494605,"score_spread":0.32434894819875143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407050030","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0076637217,0.00020201776,0.977275,0.013790622,0.00075071026,0.0001654205,0.000003933042,0.000090745176,0.00005780284],"genre_scores_gemma":[0.35677737,0.00005380292,0.63273007,0.009675471,0.00047053903,0.00002191018,0.00002659495,0.000016553779,0.00022768449],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989698,0.00007642172,0.00025451434,0.00040102145,0.00011806842,0.0001801691],"domain_scores_gemma":[0.99825484,0.0012823781,0.00006135877,0.00021208999,0.00015749174,0.00003182672],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024976808,0.00012510706,0.00013875595,0.00019022753,0.00016360806,0.0010361783,0.00048601427,0.00005655775,0.0000019600557],"category_scores_gemma":[0.0004802741,0.00008654519,0.000026075786,0.00074303796,0.00002465533,0.0006290015,0.00024287663,0.00027018887,6.197944e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002548533,0.00024208656,0.015550728,0.00018125954,0.0003513529,0.00003413732,0.053577248,0.053184107,0.0011582554,0.15253341,0.093892425,0.6290401],"study_design_scores_gemma":[0.00027891103,0.000043843575,0.0005368439,0.0017629572,0.000004233582,0.0000067907754,0.00032491484,0.9821705,0.00042840294,0.0009734801,0.013354242,0.00011485271],"about_ca_topic_score_codex":0.00013448136,"about_ca_topic_score_gemma":0.00004983797,"teacher_disagreement_score":0.92898643,"about_ca_system_score_codex":0.0000344301,"about_ca_system_score_gemma":0.00006700873,"threshold_uncertainty_score":0.9991892},"labels":[],"label_agreement":null},{"id":"W4407264923","doi":"10.1007/s11606-025-09381-1","title":"The Impact of an Enhanced Data Visualization Tool for Hypertension in the Electronic Health Record on Physician Judgments About Hypertension Control","year":2025,"lang":"en","type":"article","venue":"Journal of General Internal Medicine","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Humber River Regional Hospital; University of Toronto","funders":"Agency for Healthcare Research and Quality","keywords":"Medicine; Blood pressure; Visualization; Vignette; Graph; Data visualization; Smoothing; Raw data; Medical record; Data mining; Internal medicine; Statistics; Computer science; Theoretical computer science; Mathematics","score_opus":0.03791385345786307,"score_gpt":0.3901555703219755,"score_spread":0.35224171686411243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407264923","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20832114,0.0005444947,0.782902,0.0070665865,0.00074815465,0.0003253194,0.000013211603,0.0000073975552,0.000071720606],"genre_scores_gemma":[0.99067426,0.0007439325,0.00033867676,0.007747602,0.0003447755,0.000002124023,0.000030003896,0.0000066795033,0.00011195751],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981785,0.00027383125,0.00075674005,0.00017917297,0.00038797525,0.00022380981],"domain_scores_gemma":[0.99813825,0.0002768702,0.0006736778,0.0005258593,0.0003354825,0.000049852402],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001829308,0.00012282614,0.0003542183,0.00018882818,0.00010490816,0.000058133333,0.0013544862,0.000029429344,0.0000017752378],"category_scores_gemma":[0.0003835798,0.000057045458,0.00007806537,0.00035844828,0.000043692395,0.00035842258,0.00006686604,0.00018076778,4.0831196e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025646193,0.0018511873,0.0012908255,0.00009845191,0.0006706864,0.00003186983,0.0010735804,0.0037420322,0.08201455,0.05101926,0.2013775,0.65426546],"study_design_scores_gemma":[0.004830616,0.0067082564,0.010897351,0.0010587147,0.00005423311,0.00003951714,0.00014573072,0.9671315,0.0015293219,0.0025688238,0.0049183774,0.00011756239],"about_ca_topic_score_codex":0.00022413106,"about_ca_topic_score_gemma":0.0000610127,"teacher_disagreement_score":0.96338946,"about_ca_system_score_codex":0.00012321952,"about_ca_system_score_gemma":0.00024427872,"threshold_uncertainty_score":0.25169948},"labels":[],"label_agreement":null},{"id":"W4407941953","doi":"10.1145/3689050.3704943","title":"Designing with Data: Supporting Design Processes in Physicalization Construction","year":2025,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria; Simon Fraser University","funders":"","keywords":"Computer science; Software engineering; Human–computer interaction","score_opus":0.04747030383320248,"score_gpt":0.3338864210195641,"score_spread":0.2864161171863616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407941953","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00014477143,0.000007333617,0.9980829,0.0002261696,0.000031215193,0.00009288109,9.61077e-7,0.00010676562,0.0013070338],"genre_scores_gemma":[0.30520725,0.000014548621,0.6938387,0.000520965,0.000015946172,0.0000062376334,0.000076977565,0.0000049537966,0.0003143953],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99930793,0.000041772568,0.00016257062,0.00026662537,0.000109430206,0.00011164589],"domain_scores_gemma":[0.9994338,0.00007328439,0.00006527171,0.00031723315,0.00009231728,0.000018059636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002487665,0.000060251245,0.00007796634,0.000120567194,0.000055878936,0.00019320894,0.00044389218,0.000017458926,0.000004932971],"category_scores_gemma":[0.00015776756,0.000049021564,0.0000036001518,0.0013614522,0.000025177267,0.0011426124,0.00013687361,0.000034585908,0.0000035434991],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023314898,0.00032156307,0.031696357,0.0003846218,0.000052091716,0.000020742184,0.0010345143,0.026751537,0.0014206859,0.8488334,0.0067568333,0.08270437],"study_design_scores_gemma":[0.0002701481,0.000021181691,0.0001667447,0.00009601665,0.000007023111,0.000003046233,0.00019758251,0.98614097,0.010054657,0.0021705138,0.0007633333,0.000108797314],"about_ca_topic_score_codex":0.000010089319,"about_ca_topic_score_gemma":0.0000200403,"teacher_disagreement_score":0.95938945,"about_ca_system_score_codex":0.000014109792,"about_ca_system_score_gemma":0.00024899593,"threshold_uncertainty_score":0.19990414},"labels":[],"label_agreement":null},{"id":"W4408357822","doi":"10.7554/elife.95802.3.sa0","title":"eLife Assessment: A statistical framework for analysis of trial-level temporal dynamics in fiber photometry experiments","year":2025,"lang":"en","type":"peer-review","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Photometry (optics); Statistical analysis; Dynamics (music); Computer science; Statistics; Mathematics; Physics; Computer vision; Acoustics","score_opus":0.11072849376052123,"score_gpt":0.4815278796861856,"score_spread":0.37079938592566436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408357822","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000017611177,0.00060207903,0.9858217,0.001855611,0.0007307756,0.00093148294,0.0068131355,0.000042125204,0.0032013196],"genre_scores_gemma":[0.00014549794,0.0012345365,0.85416526,0.004657753,0.00006128806,0.00022918108,0.023725932,0.000024861747,0.11575567],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99657804,0.00017040355,0.0013326616,0.00074935297,0.0008583742,0.0003111474],"domain_scores_gemma":[0.99693763,0.00092078856,0.00055388303,0.0010886024,0.00038524845,0.00011382751],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009903506,0.00033460182,0.001571581,0.0014968629,0.000041212552,0.00016136849,0.0013702678,0.00031863822,0.0010015577],"category_scores_gemma":[0.0009094198,0.00030556196,0.0004004288,0.0045966096,0.00004605366,0.0001508413,0.00048269585,0.00030658036,0.0000062231643],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000085729436,0.00074146513,0.00018832478,0.0018555721,0.0015450947,0.000005521302,0.00002142162,0.000033469823,1.1200001e-7,0.40601772,0.5799209,0.0095846895],"study_design_scores_gemma":[0.003660928,0.00013354258,0.000078610494,0.001598744,0.0013138244,1.7167267e-7,0.000027430047,0.7658222,0.0000049577206,0.0017852839,0.22508764,0.0004867027],"about_ca_topic_score_codex":0.00021113956,"about_ca_topic_score_gemma":0.00026670322,"teacher_disagreement_score":0.7657887,"about_ca_system_score_codex":0.0003163121,"about_ca_system_score_gemma":0.00075374445,"threshold_uncertainty_score":0.9999396},"labels":[],"label_agreement":null},{"id":"W4408859989","doi":"10.1109/tvcg.2025.3554969","title":"Human Performance and Perception of Uncertainty Visualizations in Geospatial Applications: A Scoping Review","year":2025,"lang":"en","type":"review","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Geospatial analysis; Computer science; Visualization; Data visualization; Perception; Data science; Geovisualization; Human–computer interaction; Information visualization; Data mining; Remote sensing; Geography","score_opus":0.03602168536880704,"score_gpt":0.37265012529577674,"score_spread":0.33662843992696967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408859989","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000014284396,0.3272013,0.67136693,0.000006454409,0.00009407275,0.0011884102,0.000040725103,0.00007994722,0.000020722318],"genre_scores_gemma":[0.0001584464,0.9983666,0.00042401653,0.0004451449,0.000027346296,0.00031414445,0.00017908087,0.000024072458,0.00006114386],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971641,0.00033306584,0.001226306,0.00072629424,0.00032924625,0.00022104254],"domain_scores_gemma":[0.9984841,0.00016701173,0.0004765761,0.0005541949,0.00021687044,0.00010128521],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00041915535,0.00042189079,0.0011332701,0.0012697276,0.00031197967,0.00015036635,0.0004640107,0.00025058357,0.000016624326],"category_scores_gemma":[0.000007088779,0.00042006565,0.00018111643,0.002688219,0.00013047161,0.0003945265,0.000027168482,0.00026797125,0.0000024953479],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000013521807,0.0003203565,0.0000057377447,0.12577033,0.00006029852,7.709448e-7,0.0001750822,0.00018770108,7.143365e-8,0.13998696,0.000080927945,0.7334104],"study_design_scores_gemma":[0.00067657075,0.00028016005,0.000018405366,0.41267174,0.000579863,0.000024113457,0.000021475742,0.5526664,0.0000013509581,0.00017616636,0.031917837,0.00096587936],"about_ca_topic_score_codex":0.000018483119,"about_ca_topic_score_gemma":0.000051132574,"teacher_disagreement_score":0.7324445,"about_ca_system_score_codex":0.00005113852,"about_ca_system_score_gemma":0.00027013972,"threshold_uncertainty_score":0.9998251},"labels":[],"label_agreement":null},{"id":"W4409157006","doi":"10.1007/s00236-025-00483-1","title":"Visualization of bipartite graphs in limited window size","year":2025,"lang":"en","type":"article","venue":"Acta Informatica","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Technische Universität München","keywords":"Bipartite graph; Theory of computation; Window (computing); Computer science; Visualization; Graph drawing; Theoretical computer science; Combinatorics; Mathematics; Algorithm; Graph; Artificial intelligence; World Wide Web","score_opus":0.012323274879951525,"score_gpt":0.28795044292069366,"score_spread":0.2756271680407421,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409157006","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09610902,0.0000462392,0.8291143,0.0021394547,0.00044968296,0.00054126343,0.000017240627,0.00031785152,0.07126493],"genre_scores_gemma":[0.99508965,0.000039066617,0.003270946,0.0013829125,0.0000026512641,0.000004401558,0.000020003172,0.0000024130302,0.00018795407],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99911165,0.000027400754,0.0004685648,0.000084374,0.00017101044,0.00013699895],"domain_scores_gemma":[0.9992657,0.00013383904,0.0001268772,0.00035294113,0.000087942186,0.000032725835],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021685059,0.00007524508,0.00014018928,0.00033637678,0.000031255207,0.000087051056,0.00047546506,0.000043570864,0.000022207216],"category_scores_gemma":[0.00038097578,0.00006995811,0.00003261839,0.0017571296,0.000031960495,0.0010235723,0.00016046221,0.000046373803,0.000017486449],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000616933,0.00012550465,0.009716414,0.00016732365,0.000024046018,8.6627506e-7,0.0017587997,0.00013733089,0.0004477908,0.9774454,0.004934125,0.0052362154],"study_design_scores_gemma":[0.0013664702,0.00008835125,0.045150124,0.00034463787,0.000019366624,0.0000019096917,0.00026196902,0.8977397,0.0073707304,0.01143755,0.03590746,0.00031171442],"about_ca_topic_score_codex":0.000008749196,"about_ca_topic_score_gemma":0.00000736356,"teacher_disagreement_score":0.9660079,"about_ca_system_score_codex":0.000015119785,"about_ca_system_score_gemma":0.00006817404,"threshold_uncertainty_score":0.28528088},"labels":[],"label_agreement":null},{"id":"W4409603789","doi":"10.61091/jcmcc127b-213","title":"Applying Principal Component Analysis to Optimize Visual Effects and Information Communication in Visualization Designs","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Principal component analysis; Visualization; Computer science; Component (thermodynamics); Information visualization; Human–computer interaction; Visual communication; Visual analytics; Artificial intelligence; Multimedia","score_opus":0.013512695836505767,"score_gpt":0.30289127395101295,"score_spread":0.2893785781145072,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409603789","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14031045,0.00011167123,0.8571903,0.00014902689,0.0014605324,0.00050235103,7.612244e-7,0.000036630794,0.00023827849],"genre_scores_gemma":[0.97063625,0.000067918896,0.029036993,0.00017274558,0.00006038309,0.000008857449,0.0000070791784,0.000007604137,0.0000021407882],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99768656,0.00022580051,0.0011879099,0.00018409258,0.00048958446,0.00022606656],"domain_scores_gemma":[0.9976117,0.0007415769,0.00073425955,0.00028694255,0.000474428,0.00015111615],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019221359,0.0002115863,0.00064425066,0.001232333,0.00023194276,0.0006674348,0.0005620005,0.00011198942,8.048623e-7],"category_scores_gemma":[0.0006113995,0.00020783578,0.00009203255,0.0020476375,0.000038618175,0.0011080817,0.0006026829,0.00023695754,9.960976e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029157474,0.00029475876,0.00089623395,0.00018507951,0.00017309331,0.0000028638292,0.0013874997,0.0016775301,0.000098502576,0.99191034,0.000044657816,0.0033002638],"study_design_scores_gemma":[0.0042924974,0.00037781094,0.002496784,0.0005893306,0.00030013255,0.000010827477,0.0003324672,0.87852216,0.00051465584,0.11130493,0.0009062545,0.00035215003],"about_ca_topic_score_codex":0.000012290714,"about_ca_topic_score_gemma":9.4795683e-7,"teacher_disagreement_score":0.8806054,"about_ca_system_score_codex":0.00011496105,"about_ca_system_score_gemma":0.00011063136,"threshold_uncertainty_score":0.8475297},"labels":[],"label_agreement":null},{"id":"W4409685445","doi":"10.3390/mti9050037","title":"VICTORIOUS: A Visual Analytics System for Scoping Review of Document Sets","year":2025,"lang":"en","type":"article","venue":"Multimodal Technologies and Interaction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Visual analytics; Analytics; Computer science; Data science; Information retrieval; Visualization; Data mining","score_opus":0.02290231419362321,"score_gpt":0.3757031390467271,"score_spread":0.3528008248531039,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409685445","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014998998,0.0036284425,0.99153155,0.0014165401,0.0004840438,0.00064885337,0.000007608247,0.00050842296,0.00027463122],"genre_scores_gemma":[0.9592048,0.011032845,0.029213328,0.0003162472,0.000013395182,0.000086341744,0.000027456615,0.000007336455,0.0000982501],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992577,0.000015345917,0.0003248002,0.00021016397,0.00008732022,0.00010468091],"domain_scores_gemma":[0.99937177,0.00007901236,0.00016384597,0.00023241724,0.00014070576,0.000012237228],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017291225,0.00008813672,0.00020740349,0.0001793682,0.00006578627,0.000071562754,0.00025051658,0.000062048166,0.0000014066483],"category_scores_gemma":[0.00023813598,0.00007536327,0.00004917944,0.0003377306,0.000028597664,0.0003036537,0.00021983766,0.000061724204,0.0000010975144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031776544,0.00017409006,0.0005901417,0.05862378,0.00016633904,0.000002640906,0.00011168822,0.0001057418,0.0014796141,0.16290401,0.0029776748,0.7728325],"study_design_scores_gemma":[0.00067390065,0.00027231462,0.000071452356,0.10801277,0.00007124358,0.000007910363,0.0013494315,0.85233605,0.029182432,0.00074901216,0.0070055407,0.00026794133],"about_ca_topic_score_codex":0.000015962996,"about_ca_topic_score_gemma":0.000005967693,"teacher_disagreement_score":0.96231824,"about_ca_system_score_codex":0.00006619104,"about_ca_system_score_gemma":0.000032704625,"threshold_uncertainty_score":0.3073225},"labels":[],"label_agreement":null},{"id":"W4410089755","doi":"10.2196/70073","title":"mindLAMPVis as a Co-Designed Clinician-Facing Data Visualization Portal to Integrate Clinical Observations From Digital Phenotyping in Schizophrenia: User-Centered Design Process and Pilot Implementation","year":2025,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Wellcome Trust","keywords":"Preprint; Process (computing); Visualization; Schizophrenia (object-oriented programming); Computer science; Human–computer interaction; Psychology; World Wide Web; Operating system; Data mining","score_opus":0.2910634454453821,"score_gpt":0.550344100102689,"score_spread":0.2592806546573069,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410089755","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2028027,0.000016079148,0.7951267,0.0005150173,0.00008803638,0.00095948187,0.00023324823,0.0000659982,0.00019273876],"genre_scores_gemma":[0.99266785,0.00003958258,0.004873265,0.00039780018,0.000039594914,0.00009195031,0.0018098725,0.0000133977655,0.00006667027],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.996643,0.00061004696,0.0010293428,0.0006814252,0.0006122576,0.00042389394],"domain_scores_gemma":[0.99763393,0.0008620997,0.00019725597,0.00065596687,0.00048715755,0.0001635669],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0026651826,0.000181829,0.0002959169,0.00071057386,0.00032160027,0.0012374814,0.0012633293,0.0000771476,0.000021020445],"category_scores_gemma":[0.00094593654,0.00017487422,0.000028751669,0.002254594,0.000102888436,0.0044109463,0.0009046197,0.00033523122,0.000049585142],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022664177,0.0041992306,0.18969013,0.00042201797,0.00056306494,0.000057610454,0.04460574,0.0003148927,0.0013159724,0.18268336,0.046621475,0.52726007],"study_design_scores_gemma":[0.0070211072,0.001543885,0.110129274,0.0010433806,0.00002452246,0.0000032397927,0.014333773,0.8487744,0.0020839768,0.011799401,0.0025013017,0.0007417759],"about_ca_topic_score_codex":0.00011826687,"about_ca_topic_score_gemma":0.00024982882,"teacher_disagreement_score":0.8484595,"about_ca_system_score_codex":0.00009722703,"about_ca_system_score_gemma":0.00064309215,"threshold_uncertainty_score":0.9997993},"labels":[],"label_agreement":null},{"id":"W4410465887","doi":"10.55041/ijsrem48103","title":"AI in Digital Entertainment: Exploring User-Centric Movie Prediction Systems","year":2025,"lang":"en","type":"article","venue":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Entertainment; Computer science; Multimedia; Human–computer interaction; Computer graphics (images); Art; Visual arts","score_opus":0.04852228849836137,"score_gpt":0.33076213255405107,"score_spread":0.2822398440556897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410465887","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13102956,0.00071408664,0.8627218,0.0013389782,0.0033401975,0.0003073193,0.000009241804,0.000028040386,0.0005107566],"genre_scores_gemma":[0.9985085,0.00039895167,0.0005159876,0.000017005143,0.000025195961,0.00001105501,0.0000043648038,0.0000031048467,0.00051583594],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99847746,0.00003287998,0.00043399184,0.00020255048,0.00062640937,0.00022669545],"domain_scores_gemma":[0.9995301,0.000060953706,0.000043332566,0.00014564134,0.00015933087,0.000060686612],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0019017431,0.00006870249,0.00011184079,0.002581516,0.00005739705,0.001126705,0.00045850145,0.000016778176,0.0000011550287],"category_scores_gemma":[0.000047570975,0.000063619074,0.000032073338,0.001360301,0.00003631101,0.0012202427,0.00028555744,0.00020763172,0.0000026048908],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057318844,0.0008132245,0.012609859,0.0015798028,0.00019916883,0.0005914865,0.0008150427,0.20303302,0.00051333423,0.7014483,0.008298514,0.070040904],"study_design_scores_gemma":[0.0011546604,0.000062816725,0.009724069,0.0031614273,0.0000046237424,0.000025813884,0.0004424948,0.8987424,0.00006541067,0.0010976196,0.085403904,0.00011479542],"about_ca_topic_score_codex":0.0000036292815,"about_ca_topic_score_gemma":7.4229285e-7,"teacher_disagreement_score":0.8674789,"about_ca_system_score_codex":0.00015760286,"about_ca_system_score_gemma":0.000028458546,"threshold_uncertainty_score":0.99991024},"labels":[],"label_agreement":null},{"id":"W4410478772","doi":"10.1155/ijcg/3609613","title":"Evolving Camouflages: A User‐Centric AI Approach for Game Aesthetics","year":2025,"lang":"en","type":"article","venue":"International Journal of Computer Games Technology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Thompson Rivers University","funders":"","keywords":"Aesthetics; Human–computer interaction; Computer science; Game design; Art","score_opus":0.009992992144242775,"score_gpt":0.3029945875627114,"score_spread":0.29300159541846865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410478772","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009553273,0.00035719,0.98728734,0.009654683,0.0013254237,0.00010546433,0.0000052014616,0.00010441769,0.00020493905],"genre_scores_gemma":[0.46103972,0.0001599309,0.53401303,0.0038831634,0.00030170623,0.000007895677,0.000013015554,0.000014506241,0.000567041],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985977,0.00003229067,0.00058556127,0.00023638294,0.00034016566,0.00020794375],"domain_scores_gemma":[0.9978366,0.00008764963,0.00037989003,0.00031843825,0.0013284782,0.000048948456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027368878,0.00014243649,0.00026618718,0.001515614,0.00004054959,0.00030777993,0.0027656576,0.00012948173,0.000004713582],"category_scores_gemma":[0.0001309186,0.0001300674,0.00015250518,0.0006947857,0.000082946804,0.00044942586,0.00050559646,0.00024184298,0.0000033600236],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002280787,0.00040713098,0.0022133116,0.000030726438,0.0003696067,0.000057660087,0.00018128313,0.0033416888,0.0001268578,0.7452135,0.04494057,0.20309485],"study_design_scores_gemma":[0.001319197,0.00018255165,0.00025468584,0.00012170123,0.000028828099,0.0003568212,0.000040860352,0.77978843,0.00094550464,0.0218876,0.1948975,0.00017629567],"about_ca_topic_score_codex":9.4245274e-7,"about_ca_topic_score_gemma":4.777125e-7,"teacher_disagreement_score":0.77644676,"about_ca_system_score_codex":0.00011332492,"about_ca_system_score_gemma":0.0001945626,"threshold_uncertainty_score":0.5303995},"labels":[],"label_agreement":null},{"id":"W4410898105","doi":"10.1007/978-3-031-93835-1_7","title":"Evaluating the Utility of Multiple Workspaces and Easy Chart Creation for Visual Analytics","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Workspace; Visual analytics; Chart; Analytics; Human–computer interaction; Data science; Software engineering; Computer graphics (images); Visualization; Artificial intelligence","score_opus":0.059221896171688715,"score_gpt":0.37305253101562336,"score_spread":0.31383063484393464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410898105","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009744434,0.00023201764,0.9976777,0.0005558046,0.00037979733,0.00041223303,0.00001822146,0.00003728785,0.00058948505],"genre_scores_gemma":[0.46614718,0.00013436985,0.5301078,0.0015966529,0.00030426006,0.00001719049,0.000049397793,0.000023559707,0.0016195972],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979267,0.000043605363,0.00043674588,0.00075007026,0.0005846181,0.00025821937],"domain_scores_gemma":[0.9970834,0.0014343489,0.00032312752,0.0006848146,0.0004148648,0.000059435824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015490967,0.00024334302,0.00034126264,0.0003628187,0.00025712783,0.00036136797,0.0012929459,0.00013907198,0.000006487366],"category_scores_gemma":[0.0007193513,0.00018335046,0.00007918137,0.00055740855,0.0005432217,0.00030194042,0.000765402,0.00022355931,8.2952243e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014516785,0.000041838488,0.00069019845,0.00014981732,0.00002725106,0.000001249002,0.000637897,0.010623578,0.00006927342,0.03538195,0.000094387535,0.95226806],"study_design_scores_gemma":[0.00019345502,0.00012324742,0.00029110818,0.00025124615,0.000019804667,0.0000019208858,6.7927476e-7,0.97518784,0.0003659288,0.022833113,0.00056005607,0.0001715754],"about_ca_topic_score_codex":0.000011780399,"about_ca_topic_score_gemma":0.000060133872,"teacher_disagreement_score":0.96456426,"about_ca_system_score_codex":0.00004421263,"about_ca_system_score_gemma":0.0003789238,"threshold_uncertainty_score":0.7476815},"labels":[],"label_agreement":null},{"id":"W4411450197","doi":"10.1145/3729363","title":"An Empirical Study of Bugs in Data Visualization Libraries","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ACM on software engineering.","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Hong Kong University of Science and Technology","keywords":"Computer science; Visualization; Data science; Information retrieval; Root cause; Empirical research; Software bug; Key (lock); Data mining; Software; Programming language; Computer security","score_opus":0.03286994685591208,"score_gpt":0.33228897766324655,"score_spread":0.29941903080733445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411450197","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8183854,0.000055846587,0.17984524,0.0005591118,0.00031128438,0.00041356718,0.000023346644,0.00034124037,0.00006496721],"genre_scores_gemma":[0.98011184,0.0000046311043,0.019638414,0.00015717288,0.000014918183,0.0000052307655,0.000009766314,0.000009870613,0.00004816744],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990647,0.0000070287706,0.00029086944,0.00027579156,0.00025378034,0.00010783826],"domain_scores_gemma":[0.9986694,0.00008002779,0.00010427282,0.0010078754,0.00011205229,0.000026373476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025638912,0.000100165285,0.00017029964,0.000243671,0.000027881946,0.00008793456,0.0044226204,0.000040344286,0.0000015433776],"category_scores_gemma":[0.0025807673,0.00007969215,0.000018428149,0.0013379258,0.000019318051,0.0008103819,0.0018387141,0.00008485994,5.090839e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033839067,0.002371673,0.8529526,0.0004913586,0.00008270719,9.085116e-7,0.004528481,0.0050868313,0.00078865286,0.11454258,0.016610213,0.0025101462],"study_design_scores_gemma":[0.0013542187,0.00047346577,0.23776095,0.00050686306,0.00004519745,0.000001386253,0.0007373658,0.74046314,0.011578283,0.0027467806,0.003931174,0.0004011638],"about_ca_topic_score_codex":0.0000076036467,"about_ca_topic_score_gemma":0.0000019434665,"teacher_disagreement_score":0.7353763,"about_ca_system_score_codex":0.000014777693,"about_ca_system_score_gemma":0.00003968494,"threshold_uncertainty_score":0.8218403},"labels":[],"label_agreement":null},{"id":"W4411673851","doi":"10.1145/3744750","title":"Data Has Entered the Chat: How Data Workers Conduct Exploratory Visual Analytic Conversations with GenAI Agents","year":2025,"lang":"en","type":"article","venue":"ACM Transactions on Interactive Intelligent Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Psychology","score_opus":0.2089093650588563,"score_gpt":0.3814249685980279,"score_spread":0.17251560353917159,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411673851","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007253944,0.00014595548,0.988745,0.0064181793,0.0021298307,0.0007046235,0.00073547964,0.00016647844,0.00022907257],"genre_scores_gemma":[0.9947889,0.0001437374,0.00080013333,0.00085085863,0.00006659433,0.00007996308,0.0006813632,0.00002655627,0.0025619324],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970089,0.00042769374,0.000528101,0.0011240675,0.00055820675,0.00035298322],"domain_scores_gemma":[0.9929675,0.00071116973,0.00031083645,0.005538641,0.0003361692,0.0001357062],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0005988305,0.00035517185,0.00036032556,0.00047384115,0.000595997,0.0014292352,0.006259971,0.00008415606,0.000096020995],"category_scores_gemma":[0.00018962422,0.00025489496,0.00008302169,0.001269429,0.00023818087,0.0027931214,0.00037451487,0.0004462091,0.00017393345],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019271206,0.012294352,0.007410557,0.0017924587,0.035128657,0.0004206331,0.03878103,0.050517187,0.00169631,0.026155375,0.6746446,0.14923175],"study_design_scores_gemma":[0.00070200075,0.00021175113,0.00014815918,0.0009532321,0.00034961276,0.000029907966,0.020829137,0.8089366,0.001906885,0.00007627611,0.16533908,0.00051736215],"about_ca_topic_score_codex":0.00020185093,"about_ca_topic_score_gemma":0.00029927847,"teacher_disagreement_score":0.99406344,"about_ca_system_score_codex":0.00022054354,"about_ca_system_score_gemma":0.00037996145,"threshold_uncertainty_score":0.99999034},"labels":[],"label_agreement":null},{"id":"W4411948814","doi":"10.1109/jiot.2025.3583477","title":"Exploring the Boundaries of On-Device Inference: When Tiny Falls Short, Go Hierarchical","year":2025,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Inference; Artificial intelligence","score_opus":0.07816842897662224,"score_gpt":0.3352194532792394,"score_spread":0.25705102430261717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411948814","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14933941,0.00006231208,0.8404853,0.0027216084,0.0019006047,0.00006573446,0.0000035295745,0.00003535359,0.005386183],"genre_scores_gemma":[0.9929359,0.00005873228,0.004386393,0.0013924045,0.000070947324,0.0000017160957,9.042762e-7,0.000005347986,0.0011476509],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99859434,0.000099483244,0.00053330726,0.0001576266,0.00044363292,0.00017159333],"domain_scores_gemma":[0.9989066,0.00026355882,0.00021565637,0.0003264045,0.0002259535,0.00006182307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007076194,0.00011507527,0.00021468966,0.00020917467,0.00012503225,0.0006405532,0.0017250126,0.000033447966,0.000026203641],"category_scores_gemma":[0.00031642106,0.00007804077,0.00011065916,0.00024494747,0.00022005558,0.0008828413,0.00028071564,0.0004543887,0.000008153763],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008916256,0.0003538019,0.003962283,0.00015210666,0.00045450244,0.000035008066,0.040723607,0.000411803,0.0024545374,0.79174924,0.04946452,0.110149406],"study_design_scores_gemma":[0.0017889865,0.0013201147,0.005519947,0.0057599507,0.00020099923,0.00022917072,0.0019844042,0.36245486,0.15647441,0.13907874,0.32413816,0.0010502494],"about_ca_topic_score_codex":0.000039784838,"about_ca_topic_score_gemma":0.000006262945,"teacher_disagreement_score":0.8435965,"about_ca_system_score_codex":0.000033351247,"about_ca_system_score_gemma":0.00020927757,"threshold_uncertainty_score":0.6176869},"labels":[],"label_agreement":null},{"id":"W4412106329","doi":"10.1145/3712256.3726331","title":"Emergent Braitenberg-style Behaviours for Navigating the ViZDoom 'My Way Home' Labyrinth","year":2025,"lang":"en","type":"article","venue":"Proceedings of the Genetic and Evolutionary Computation Conference","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Style (visual arts); Computer science; Telecommunications; Visual arts; Art","score_opus":0.01847430744442519,"score_gpt":0.2825160090607089,"score_spread":0.2640417016162837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412106329","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23954067,0.00039652188,0.7496964,0.008910631,0.00043264838,0.0005051995,0.000029661594,0.00013252582,0.0003557622],"genre_scores_gemma":[0.9753881,0.000053414376,0.023821604,0.0003863711,0.000027751179,0.000024301184,0.0000073493893,0.0000077923105,0.00028328542],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99902266,0.000014449224,0.00030743776,0.0002756318,0.00021788028,0.00016196437],"domain_scores_gemma":[0.9989517,0.000086262036,0.0002078843,0.00011915559,0.00059448555,0.00004051534],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020321379,0.00011814691,0.00012634306,0.000049102167,0.00040421676,0.00014262112,0.00068263034,0.000039489463,0.0000030554118],"category_scores_gemma":[0.000079826445,0.00008239484,0.000060178,0.00044754206,0.00014595452,0.00019266413,0.000390312,0.00010172562,0.000001413055],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002818466,0.00021896462,0.039184246,0.00031027943,0.0001194361,2.0778882e-7,0.0031493441,0.004011933,0.0016575286,0.82107115,0.028544206,0.10170452],"study_design_scores_gemma":[0.0003968759,0.00005526711,0.116749726,0.00017671284,0.000045892302,0.000006751103,0.00045867253,0.83238924,0.00057497877,0.047406085,0.0015770621,0.00016276004],"about_ca_topic_score_codex":0.000021322016,"about_ca_topic_score_gemma":0.0000025314914,"teacher_disagreement_score":0.8283773,"about_ca_system_score_codex":0.000023139834,"about_ca_system_score_gemma":0.0001019452,"threshold_uncertainty_score":0.33599642},"labels":[],"label_agreement":null},{"id":"W4412439465","doi":"10.1167/jov.25.9.2292","title":"Discrete vs. continuous timer bars: How visual segmentation shapes the perception of time \"running out\"","year":2025,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Timer; Segmentation; Perception; Computer science; Computer vision; Artificial intelligence; Psychology; Neuroscience; Computer hardware","score_opus":0.011134308457669927,"score_gpt":0.3286448291387521,"score_spread":0.31751052068108215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412439465","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.057325676,0.00010519615,0.9369744,0.0047452436,0.00031543468,0.00009741179,0.0000030682043,0.000018923687,0.0004146122],"genre_scores_gemma":[0.9886121,0.00011392342,0.008845472,0.0006297745,0.00010746132,5.0477075e-7,0.00000887768,0.000006386964,0.0016755046],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989777,0.00009259805,0.00035197652,0.00010658845,0.0003774085,0.000093697956],"domain_scores_gemma":[0.9991182,0.00007141802,0.0004130556,0.00012471869,0.00023693584,0.00003563421],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006057146,0.00008067152,0.000175912,0.00017123189,0.00009100056,0.00022239836,0.0004158733,0.000037068807,0.00004794604],"category_scores_gemma":[0.00007363564,0.000051266656,0.00009809297,0.00026453138,0.000038466558,0.0007704813,0.00012160265,0.0001070503,0.000016781692],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023859188,0.0006063366,0.005416856,0.00013494866,0.00034779802,0.000027079259,0.008736658,0.0026511506,0.4970538,0.006051141,0.12230345,0.3564322],"study_design_scores_gemma":[0.0016074562,0.001097135,0.047188938,0.0007874335,0.00014802473,0.000028770151,0.0016640746,0.9279634,0.00638166,0.0008199574,0.012063946,0.00024920888],"about_ca_topic_score_codex":0.0000020559692,"about_ca_topic_score_gemma":4.346203e-7,"teacher_disagreement_score":0.9312864,"about_ca_system_score_codex":0.000033432203,"about_ca_system_score_gemma":0.000046966223,"threshold_uncertainty_score":0.21445926},"labels":[],"label_agreement":null},{"id":"W4412591878","doi":"10.1111/cgf.70143","title":"Front Matter","year":2025,"lang":"en","type":"paratext","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Lawrence Berkeley National Laboratory; School of Medicine, Stanford University; Stony Brook University; Sorbonne Université; Helmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum GFZ; Universität Stuttgart; Universität Duisburg-Essen; Newcastle University; Rheinische Friedrich-Wilhelms-Universität Bonn; Syddansk Universitet; Linköpings Universitet; Universitetet i Bergen; Zhejiang University; Centre National de la Recherche Scientifique; Université de Toulouse; Tianjin University; Simon Fraser University; Universität Zürich; Universität Rostock; Technische Universität München; Tsinghua University; Renmin University of China; Gottfried Wilhelm Leibniz Universität Hannover; Linnéuniversitetet; North Carolina State University; Carnegie Mellon University; Advanced Micro Devices; Khalifa University of Science, Technology and Research; École Centrale de Lyon; Fudan University; Université Paris-Saclay; Universita degli Studi di Bari Aldo Moro; Universiteit Utrecht; Nanyang Technological University; University of Leeds; Augusta University; Indian Institute of Technology Kanpur; King Abdullah University of Science and Technology; York University; Technische Universität Kaiserslautern; Technische Universität Wien; Leibniz-Gemeinschaft; Sapienza Università di Roma; Universität Wien; Emory University; University of Oklahoma; Purdue University; Medizinischen Hochschule Hannover; Universität Passau; University of Notre Dame; Brown University","keywords":"Computer science; Computer graphics (images); Front (military); Geology","score_opus":0.015227993820295924,"score_gpt":0.280637806926757,"score_spread":0.26540981310646106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412591878","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[7.5160415e-7,0.0006732359,0.90253836,0.0020987948,0.008353493,0.00018797992,0.00014943666,0.0001365287,0.08586143],"genre_scores_gemma":[0.00018649988,0.0011877286,0.038672257,0.058652826,0.0010433459,0.00003870993,0.0023235662,0.00007646281,0.8978186],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974782,0.00009449033,0.0005249366,0.0009075354,0.0004213633,0.00057350897],"domain_scores_gemma":[0.9976317,0.00007671437,0.00024123992,0.0016832437,0.0002108831,0.00015617411],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00015736486,0.0004652124,0.00053577725,0.0007628921,0.0002127265,0.0008353801,0.0030662918,0.00039066508,0.001984929],"category_scores_gemma":[0.000004625084,0.0004518041,0.00031800862,0.0007304286,0.000080379206,0.000362805,0.0019436707,0.0005082894,0.043179724],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.690666e-7,0.000047078498,0.00006529428,0.00009469201,0.000074991185,0.000006421749,0.000030124034,0.000035502424,1.7235801e-7,0.08315535,0.9141006,0.0023889942],"study_design_scores_gemma":[0.0001727061,0.0000319027,0.000045193377,0.00019207159,0.000017930357,0.0000054470356,0.0000017556025,0.12609708,0.000011264186,0.0017214082,0.8712699,0.0004333551],"about_ca_topic_score_codex":0.000020264502,"about_ca_topic_score_gemma":0.000007582811,"teacher_disagreement_score":0.8638661,"about_ca_system_score_codex":0.00004261063,"about_ca_system_score_gemma":0.00023167196,"threshold_uncertainty_score":0.99979335},"labels":[],"label_agreement":null},{"id":"W4412636227","doi":"10.1002/spe.70010","title":"Leveraging the Power of Images: Image Recommendation to Enhance Issue Reports","year":2025,"lang":"en","type":"article","venue":"Software Practice and Experience","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Image (mathematics); Data science; Power (physics); Computer vision; Information retrieval; Artificial intelligence","score_opus":0.012337132147721657,"score_gpt":0.3599018589456765,"score_spread":0.34756472679795486,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412636227","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0031228038,0.00010664787,0.9809515,0.013143787,0.00030461463,0.00011096895,0.0000015375305,0.00006289386,0.0021952502],"genre_scores_gemma":[0.7855543,0.00023758154,0.1945313,0.017969893,0.000032309697,0.0000402486,0.000008459595,0.000008586322,0.0016173235],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990769,0.00007189292,0.00025761614,0.00031131477,0.00015130022,0.00013097629],"domain_scores_gemma":[0.9987488,0.0003311336,0.00017337217,0.00048363602,0.00021905634,0.00004400834],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047656198,0.000082330494,0.00009971423,0.00006666297,0.00017619172,0.00023833239,0.00031727858,0.00002140135,0.00004675409],"category_scores_gemma":[0.002617861,0.00006513277,0.000018845867,0.0005627035,0.000060275084,0.0016206455,0.0003268835,0.000077728495,0.000011725694],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007630426,0.00054569554,0.0031072267,0.00017877234,0.00010694362,0.00012292656,0.23747654,0.000063768006,0.013375201,0.016630644,0.16257651,0.56573945],"study_design_scores_gemma":[0.00010522931,0.000077989826,0.0007442517,0.00012629303,0.00002048894,0.00007028791,0.019688029,0.0012401695,0.059849944,0.0012024235,0.91659486,0.0002800449],"about_ca_topic_score_codex":0.000056489935,"about_ca_topic_score_gemma":0.0000011496426,"teacher_disagreement_score":0.78642017,"about_ca_system_score_codex":0.000014857962,"about_ca_system_score_gemma":0.000059259954,"threshold_uncertainty_score":0.3134013},"labels":[],"label_agreement":null},{"id":"W4412819563","doi":"10.1007/978-3-031-89033-8_29","title":"VTK","year":2025,"lang":"en","type":"book-chapter","venue":"CMS/CAIMS books in mathematics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science","score_opus":0.03360202583895656,"score_gpt":0.29255482102496505,"score_spread":0.2589527951860085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412819563","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[4.508768e-7,0.00017417505,0.27234793,0.00015433959,0.00029985016,0.00019989688,0.000025307894,0.00016275642,0.7266353],"genre_scores_gemma":[0.000029920275,0.00020786673,0.05220741,0.0007261665,0.00007354681,0.000008563481,0.00004483491,0.000041270647,0.9466604],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9979421,0.000015655467,0.0007628372,0.000516337,0.0004708143,0.00029224824],"domain_scores_gemma":[0.99779886,0.0001874265,0.000321726,0.0014778916,0.000118719785,0.0000953524],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003622276,0.00040100084,0.0005828671,0.00047007846,0.00007049827,0.0002803578,0.0017144002,0.00032391842,0.0001641874],"category_scores_gemma":[0.0001067898,0.00039703245,0.0001659356,0.00011312556,0.00009012562,0.00019203911,0.00074517453,0.00040882605,0.0004434571],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.9856243e-7,0.000035486642,0.0000014638583,0.00025670658,0.000027121201,0.00003411631,0.00028564772,0.0000074776963,0.0000018443229,0.96176517,0.034159664,0.0034249297],"study_design_scores_gemma":[0.00018234176,0.000018548324,7.5549644e-7,0.00092369295,0.000029516394,0.000008353332,0.0000134339,0.04199232,0.000029905004,0.5721204,0.38427383,0.00040686582],"about_ca_topic_score_codex":0.0000019047156,"about_ca_topic_score_gemma":0.000012523266,"teacher_disagreement_score":0.3896447,"about_ca_system_score_codex":0.00011235342,"about_ca_system_score_gemma":0.00022983077,"threshold_uncertainty_score":0.9998481},"labels":[],"label_agreement":null},{"id":"W4412969072","doi":"10.1117/12.3066019","title":"Exact simulation of photonic continuous-variable cluster states","year":2025,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; Xanadu Quantum Technologies (Canada); National Research Council Canada","funders":"","keywords":"Cluster (spacecraft); Photonics; Variable (mathematics); Cluster state; Computer science; Physics; Mathematics; Optics; Quantum entanglement; Quantum mechanics; Computer network; Mathematical analysis","score_opus":0.012037419112605252,"score_gpt":0.3017769808909319,"score_spread":0.28973956177832666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412969072","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011420142,0.000015976188,0.97972006,0.00018446562,0.00008599532,0.000059630253,0.0000032305732,0.000059715938,0.018728893],"genre_scores_gemma":[0.9605927,0.000014337401,0.021804424,0.0019547893,0.000006848601,0.0000016089559,0.000026774565,0.000003113145,0.015595431],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99950063,0.000023662098,0.00017304203,0.00012700402,0.000091810325,0.00008385884],"domain_scores_gemma":[0.9994618,0.00010821561,0.000048661244,0.00026108164,0.000101927326,0.000018283414],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015133628,0.000046998644,0.00009200218,0.000081052574,0.00002642326,0.000070460184,0.0002606629,0.00002234234,0.00011207579],"category_scores_gemma":[0.000043178912,0.000039949453,0.00001975467,0.00039800126,0.000013819931,0.00025681077,0.00011864703,0.000023376933,0.000014437704],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000074113104,0.00015315742,0.0018262716,0.00007147005,0.000046625246,6.079644e-7,0.00024482762,0.21236232,0.00079178176,0.75984925,0.018313175,0.0063331346],"study_design_scores_gemma":[0.00019760687,0.000012398439,0.00009202164,0.000015048925,0.0000040186865,7.9040944e-8,0.000020337915,0.96332234,0.0026573685,0.0035157017,0.030120783,0.000042321786],"about_ca_topic_score_codex":0.000027145077,"about_ca_topic_score_gemma":0.0000040269756,"teacher_disagreement_score":0.95945066,"about_ca_system_score_codex":0.000010520146,"about_ca_system_score_gemma":0.000050394905,"threshold_uncertainty_score":0.16290915},"labels":[],"label_agreement":null},{"id":"W4413052386","doi":"10.1109/tvcg.2025.3596541","title":"More Like Vis, Less Like Vis: Comparing Interactions for Integrating User Preferences Into Partial Specification Recommenders","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Visualization; Computer science; Data visualization; Process (computing); Human–computer interaction; Interactive visualization; Comprehension; Creative visualization; Data mining; Information retrieval; Machine learning; Programming language","score_opus":0.05653016292367945,"score_gpt":0.3423513509854848,"score_spread":0.28582118806180534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413052386","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0025862616,0.000029866322,0.994159,0.00045445262,0.0019014552,0.00041009398,0.000014903867,0.00034868636,0.000095292155],"genre_scores_gemma":[0.9815886,0.00037453312,0.013848524,0.0035646993,0.000095050105,0.00012368984,0.00012385783,0.000028064731,0.00025300577],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99801314,0.00015484824,0.00061077904,0.00066192145,0.00029552687,0.0002637922],"domain_scores_gemma":[0.9986696,0.0002084911,0.00020474783,0.00045224308,0.00034067323,0.00012421422],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00026549931,0.0002986938,0.00030099892,0.00073994143,0.0007794212,0.0007051075,0.00050774554,0.00012161176,0.000009439099],"category_scores_gemma":[0.000008343601,0.00030333013,0.0001362567,0.0012899879,0.00010367295,0.0008865378,0.000019969078,0.0002479797,0.0000030191966],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056130415,0.0007571147,0.0004960531,0.00017187903,0.00019263945,7.510019e-7,0.0041155913,0.0020937377,0.000049543934,0.9416284,0.0053800293,0.045058124],"study_design_scores_gemma":[0.0006426722,0.00011561203,0.00016509413,0.00020467519,0.000056539677,0.0000027692777,0.00068891706,0.9729823,0.0009964892,0.0009517646,0.022889797,0.00030335732],"about_ca_topic_score_codex":0.000036837493,"about_ca_topic_score_gemma":0.00018414043,"teacher_disagreement_score":0.98031044,"about_ca_system_score_codex":0.00006432461,"about_ca_system_score_gemma":0.00008941928,"threshold_uncertainty_score":0.9999419},"labels":[],"label_agreement":null},{"id":"W4413054268","doi":"10.1109/mcg.2025.3566453","title":"What Can Visualization Research Do for Climate? A Workshop Report","year":2025,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Visualization; Stewardship (theology); Computer science; Data science; Sustainability; Data visualization; Narrative; Field (mathematics); Human–computer interaction; Political science; Ecology; Artificial intelligence","score_opus":0.06348461584062814,"score_gpt":0.4140966688542162,"score_spread":0.35061205301358805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413054268","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004372281,0.00023883332,0.9959484,0.002129027,0.00036561216,0.00060656073,0.000015893385,0.00012098264,0.00013751064],"genre_scores_gemma":[0.76751757,0.022123108,0.18090814,0.016243182,0.0018797038,0.00516856,0.0018338284,0.00013856456,0.0041873553],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985722,0.000052714524,0.0003274756,0.0005491808,0.00022347657,0.00027497718],"domain_scores_gemma":[0.9982888,0.00027259617,0.00008687548,0.00071804906,0.0005399318,0.000093726456],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0008026783,0.00011451782,0.00014122842,0.00043650612,0.0006123118,0.0013771129,0.0005705635,0.00008207074,0.0000010481831],"category_scores_gemma":[0.000017020748,0.000115366434,0.000054100467,0.0016852944,0.00011091531,0.00038932098,0.00025012073,0.000115033356,0.0000029981895],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010737017,0.00007206278,0.00020577322,0.000050719394,0.000015353931,0.0000012843888,0.00012282895,0.000042268606,0.000012254801,0.9757868,0.008836365,0.014853225],"study_design_scores_gemma":[0.0003233778,0.000031557047,0.00039451255,0.00011932906,0.000016934331,0.0000143546,0.00010548261,0.5747924,0.00013112345,0.086516395,0.33733672,0.0002178333],"about_ca_topic_score_codex":0.0000048858774,"about_ca_topic_score_gemma":0.000016065394,"teacher_disagreement_score":0.88927037,"about_ca_system_score_codex":0.00001922048,"about_ca_system_score_gemma":0.00009073005,"threshold_uncertainty_score":0.99965954},"labels":[],"label_agreement":null},{"id":"W4413096328","doi":"10.1109/iccsp64183.2025.11088600","title":"Advanced Visualization Tools, Algorithms, and Techniques: Advancements and Applications Across Domains","year":2025,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Visualization; Data science; Data mining","score_opus":0.015034314870000351,"score_gpt":0.36357181951858586,"score_spread":0.3485375046485855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413096328","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00019168705,0.00014954359,0.99611646,0.00030523972,0.00003229416,0.00027681602,0.000017208888,0.0002395783,0.00267117],"genre_scores_gemma":[0.12527606,0.0059810644,0.8409748,0.011733897,0.00011009439,0.0005979224,0.00043940428,0.00003873319,0.014847991],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.999238,0.000017423241,0.00018152274,0.0003161333,0.00010533334,0.0001415893],"domain_scores_gemma":[0.99949515,0.000035291316,0.00004960826,0.00028757672,0.000080798345,0.0000515758],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012947408,0.00009215948,0.00009744791,0.00007351667,0.00020314816,0.0002886387,0.00022922308,0.000037198934,0.0000037956972],"category_scores_gemma":[0.00002501635,0.00008782612,0.000010709516,0.00052672485,0.000050590195,0.00075122865,0.0003115893,0.00003391859,0.0000030464666],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.300393e-7,0.000034072706,0.0003286728,0.00002041184,0.0000062779586,2.7124784e-7,0.000057278987,0.0000029309174,0.00026734904,0.53425056,0.0003352832,0.46469608],"study_design_scores_gemma":[0.0008504391,0.0000651747,0.0016241138,0.00006621782,0.000013998528,0.0000051412153,0.00033150386,0.079795785,0.00878074,0.016581556,0.89151895,0.0003663536],"about_ca_topic_score_codex":0.000003511796,"about_ca_topic_score_gemma":0.0000072706744,"teacher_disagreement_score":0.8911837,"about_ca_system_score_codex":0.00001933895,"about_ca_system_score_gemma":0.000023519875,"threshold_uncertainty_score":0.35814452},"labels":[],"label_agreement":null},{"id":"W4413144822","doi":"10.1109/cvpr52734.2025.02234","title":"Mind the Time: Temporally-Controlled Multi-Event Video Generation","year":2025,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Event (particle physics)","score_opus":0.024033723472757916,"score_gpt":0.3138316349936845,"score_spread":0.2897979115209266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413144822","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00040931802,0.000043966582,0.98868465,0.0065558506,0.00017685324,0.00018080996,0.0000013163367,0.000046553174,0.0039006914],"genre_scores_gemma":[0.44006902,0.00003338591,0.085335985,0.019826887,0.000197077,0.000050118004,0.00008534551,0.0000107689,0.45439142],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993144,0.00006947496,0.00020583098,0.00018154895,0.00013230939,0.00009641185],"domain_scores_gemma":[0.9994235,0.00005027775,0.000049741182,0.00037898473,0.00007117781,0.000026309497],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033990623,0.000068710135,0.000104345025,0.00006013194,0.00012447413,0.0002696164,0.0004945525,0.000025868549,0.00013364415],"category_scores_gemma":[0.00007910019,0.000040265237,0.0000542742,0.0003091676,0.000016786604,0.00020059403,0.0001358951,0.00003729403,0.00023579627],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015869547,0.00042956645,0.00046708848,0.000009697078,0.00016298621,0.0000056014874,0.0003935232,0.002339887,0.00762446,0.4689229,0.42839003,0.09123838],"study_design_scores_gemma":[0.0009872004,0.0000075262474,0.000091130314,0.0000035761288,0.000007711455,3.4729837e-7,0.000007443023,0.94427866,0.0014784548,0.00013586831,0.052950148,0.000051936408],"about_ca_topic_score_codex":0.000009353091,"about_ca_topic_score_gemma":0.000024523764,"teacher_disagreement_score":0.94193876,"about_ca_system_score_codex":0.000015378522,"about_ca_system_score_gemma":0.00007222521,"threshold_uncertainty_score":0.30307627},"labels":[],"label_agreement":null},{"id":"W4413146116","doi":"10.1109/cvpr52734.2025.00797","title":"Enhancing Video-LLM Reasoning via Agent-of-Thoughts Distillation","year":2025,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Distillation; Chemistry; Chromatography","score_opus":0.01280561128987202,"score_gpt":0.29789379645179387,"score_spread":0.28508818516192186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413146116","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010178447,0.00002942018,0.986801,0.00017895047,0.00024775547,0.00004259526,7.6450027e-7,0.00009313614,0.011588502],"genre_scores_gemma":[0.9132712,0.000011332344,0.08143347,0.0004168008,0.000035557325,0.0000013978574,0.00001280976,0.0000033290296,0.0048141014],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993537,0.000027635833,0.0002097584,0.0001779962,0.00013060725,0.0001002956],"domain_scores_gemma":[0.99948454,0.00005190813,0.00006794554,0.00029359313,0.00007189285,0.000030127867],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016922095,0.00005980426,0.00009163389,0.000101817095,0.00006588374,0.000077406155,0.0002880009,0.000025699059,0.000020161264],"category_scores_gemma":[0.00009072794,0.000053569667,0.000032359087,0.0005567744,0.000013328787,0.0002947816,0.00015104398,0.000030064362,0.000019488083],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000020451357,0.00006169658,0.0023070246,0.000051521296,0.000024573626,0.000002238742,0.0003223174,0.00026818,0.0046607116,0.94499665,0.00311954,0.04418352],"study_design_scores_gemma":[0.00019977694,0.000021519565,0.0027153718,0.00011721982,0.000012469705,0.0000012078245,0.000033770535,0.90154374,0.06849971,0.006727832,0.019985495,0.00014188833],"about_ca_topic_score_codex":0.000018568897,"about_ca_topic_score_gemma":0.000028514114,"teacher_disagreement_score":0.9382688,"about_ca_system_score_codex":0.000019579302,"about_ca_system_score_gemma":0.000037895068,"threshold_uncertainty_score":0.21845077},"labels":[],"label_agreement":null},{"id":"W4413182692","doi":"10.1784/insi.2025.67.8.459","title":"Visualising fault conditions with Omniverse","year":2025,"lang":"en","type":"article","venue":"Insight - Non-Destructive Testing and Condition Monitoring","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Fault (geology); Geology; Seismology","score_opus":0.02349313504798206,"score_gpt":0.31274514897308553,"score_spread":0.28925201392510347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413182692","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6775829,0.000043675187,0.30843794,0.00012481947,0.0005642982,0.00018225683,0.000023823322,0.0004091474,0.012631139],"genre_scores_gemma":[0.9784961,0.000009164375,0.021060457,0.00010634024,0.0001084164,0.000013621708,0.00002016578,0.000010492669,0.00017525414],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9988665,0.000052865435,0.00022289006,0.00042714318,0.00020391589,0.00022666567],"domain_scores_gemma":[0.9988718,0.00030506606,0.0001372775,0.00026847678,0.0003197003,0.00009768221],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010202162,0.00018734833,0.00017744963,0.00030641185,0.00062799576,0.0004074016,0.0002418595,0.000060686725,0.0000050471026],"category_scores_gemma":[0.00014919075,0.00017887609,0.0000255486,0.0009885856,0.00014319707,0.0010818944,0.00013077454,0.00016831468,0.000007971888],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004786933,0.0003413073,0.27474168,0.0003147782,0.00044740713,0.00032287385,0.00439683,0.001810055,0.061485004,0.61253005,0.0008240894,0.042738054],"study_design_scores_gemma":[0.005691022,0.0007477807,0.66777104,0.004429342,0.00035901726,0.0003770688,0.005390736,0.13860255,0.08265421,0.089193635,0.0023626727,0.0024209202],"about_ca_topic_score_codex":0.00006351455,"about_ca_topic_score_gemma":0.0000020901543,"teacher_disagreement_score":0.5233364,"about_ca_system_score_codex":0.00007348885,"about_ca_system_score_gemma":0.0001215021,"threshold_uncertainty_score":0.7294355},"labels":[],"label_agreement":null},{"id":"W4413195869","doi":"10.1016/j.socnet.2026.06.004","title":"Relationships between Node Degrees and Hyperedge Sizes in Empirical Hypergraphs","year":2025,"lang":"en","type":"article","venue":"Social Networks","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Szkoła Główna Handlowa w Warszawie","keywords":"Node (physics); Empirical research; Mathematics; Computer science; Statistics; Engineering","score_opus":0.058281503066105744,"score_gpt":0.3382205507031642,"score_spread":0.27993904763705846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413195869","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0353336,0.0004862605,0.9534667,0.0052255606,0.00022989618,0.00010895163,0.00000617223,0.00014125911,0.005001601],"genre_scores_gemma":[0.9964705,0.000045021905,0.0026199617,0.00052565365,0.00012600592,0.0000032116677,0.0000189744,0.000004154464,0.00018648808],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99922305,0.00011624784,0.00018685525,0.00021018964,0.00009223575,0.00017142198],"domain_scores_gemma":[0.99953705,0.0002197368,0.000036115885,0.00013251699,0.000029601484,0.00004499024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028922802,0.00007904111,0.00014569957,0.00011090769,0.00024558703,0.00012230779,0.0002660765,0.00013304464,0.0000019401623],"category_scores_gemma":[0.00007931605,0.000079647136,0.000032746997,0.000909407,0.000068776055,0.000175393,0.00017215278,0.00022994624,0.000003327158],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000019517415,0.000029119468,0.763334,0.0000075838243,0.000018696797,0.0000024224946,0.0006658398,0.00034258916,7.601115e-7,0.20786922,0.008402803,0.019325037],"study_design_scores_gemma":[0.00040362496,0.000009731193,0.75406694,0.000031982167,0.000016856435,4.1425133e-7,0.00016588868,0.21530059,0.0000015001942,0.022946306,0.0068822326,0.00017395223],"about_ca_topic_score_codex":0.000014558456,"about_ca_topic_score_gemma":0.00009418139,"teacher_disagreement_score":0.96113694,"about_ca_system_score_codex":0.000020561993,"about_ca_system_score_gemma":0.00004230676,"threshold_uncertainty_score":0.3247916},"labels":[],"label_agreement":null},{"id":"W4413258532","doi":"10.1109/tvcg.2025.3599458","title":"VIVA: Virtual Healthcare Interactions Using Visual Analytics, With Controllability Through Configuration","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Controllability; Computer science; Visual analytics; Human–computer interaction; Visualization; Data visualization; Analytics; Interactive visual analysis; Computer graphics (images); Artificial intelligence; Data mining; Mathematics","score_opus":0.027503810517595425,"score_gpt":0.33203624735162235,"score_spread":0.3045324368340269,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413258532","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0045759506,0.000026379565,0.993478,0.00039565467,0.000776894,0.00033696325,0.000026080661,0.0002904784,0.000093571194],"genre_scores_gemma":[0.99291444,0.00011690677,0.002678114,0.0040456234,0.000046768917,0.0000151691975,0.000035621655,0.000017860879,0.0001294829],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979427,0.00024910088,0.0005391519,0.00063717423,0.00036322788,0.00026865696],"domain_scores_gemma":[0.9985455,0.00017688845,0.00017402884,0.00044137312,0.0005357159,0.0001264674],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00021139141,0.00029746722,0.0003368773,0.00053465646,0.0006612232,0.00048921944,0.0002869809,0.00012109655,0.000014215545],"category_scores_gemma":[0.0000072525495,0.0002791103,0.00009732197,0.0018646646,0.00016765192,0.0009963166,0.000010316757,0.00025152168,0.0000052210094],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006140207,0.0004507504,0.00026467227,0.00005554031,0.00015745952,0.0000030508604,0.0006621958,0.00592008,0.000042088235,0.9876907,0.00015459368,0.0045374944],"study_design_scores_gemma":[0.0010391659,0.00034414927,0.00027081437,0.00012252614,0.000074490286,0.000011595734,0.00014264377,0.9936956,0.0016407082,0.0009406848,0.0014352078,0.0002823833],"about_ca_topic_score_codex":0.000101154255,"about_ca_topic_score_gemma":0.00022325253,"teacher_disagreement_score":0.9907999,"about_ca_system_score_codex":0.00008497249,"about_ca_system_score_gemma":0.00020234233,"threshold_uncertainty_score":0.9999661},"labels":[],"label_agreement":null},{"id":"W4413263825","doi":"10.2139/ssrn.5371575","title":"Guided Creativity: AI Intermediation for Enhancing Originality and Quality in Visual Design","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Originality; Creativity; Quality (philosophy); Intermediation; Psychology; Computer science; Business; Social psychology; Epistemology; Philosophy","score_opus":0.047371671558409385,"score_gpt":0.40080733453522166,"score_spread":0.3534356629768123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413263825","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0056050913,0.0004468295,0.99200773,0.0010938033,0.00036899198,0.00035263813,0.00001396874,0.000048558646,0.000062363055],"genre_scores_gemma":[0.9724673,0.004893097,0.01902605,0.0011511805,0.00045338072,0.000069184476,0.00011089666,0.000025593446,0.0018033431],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9966734,0.0005788588,0.0007703394,0.00053442566,0.000309088,0.0011338716],"domain_scores_gemma":[0.9984942,0.00034641582,0.00048307388,0.00032849348,0.00026488205,0.00008294871],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.008100478,0.00024969844,0.00044505516,0.00037277985,0.00014571194,0.0004760099,0.0007189174,0.00019212245,0.0000026675818],"category_scores_gemma":[0.0007374668,0.00024785748,0.000112642854,0.00029807584,0.00003724772,0.00046416497,0.00050854497,0.0017337031,0.0000012772142],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007211311,0.00023749007,0.0042431606,0.00031050772,0.00022137952,0.0000027377127,0.00090822956,0.0014105967,0.00017263509,0.9406906,0.00036731127,0.051363274],"study_design_scores_gemma":[0.0012850643,0.00022986294,0.00086640095,0.00036178282,0.000059907507,0.000029190973,0.0002533687,0.2810103,0.00081763323,0.7136162,0.0009650077,0.00050529087],"about_ca_topic_score_codex":0.0001512591,"about_ca_topic_score_gemma":0.0020165518,"teacher_disagreement_score":0.9729817,"about_ca_system_score_codex":0.0012762846,"about_ca_system_score_gemma":0.0059338403,"threshold_uncertainty_score":0.9999974},"labels":[],"label_agreement":null},{"id":"W4413324908","doi":"10.1016/j.infsof.2025.107871","title":"Community Tapestry: An actionable tool to track turnover and diversity in OSS","year":2025,"lang":"en","type":"article","venue":"Information and Software Technology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Google; Australian Speleological Federation; Children's Neuroblastoma Cancer Foundation; National Science Foundation","keywords":"Diversity (politics); Track (disk drive); Data science; Geography; Computer science; Sociology; Anthropology","score_opus":0.01589763545276102,"score_gpt":0.27921690278046113,"score_spread":0.2633192673277001,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413324908","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5445603,0.000009427948,0.45278683,0.001778367,0.000058779347,0.00010145898,0.000010063398,0.0003395577,0.00035518873],"genre_scores_gemma":[0.9871939,0.000018169185,0.010187991,0.0024573554,0.0000018784078,0.0000044245003,0.000025569912,0.0000010889185,0.00010966014],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9996158,0.00001995009,0.00014126647,0.00006923371,0.00006087882,0.00009285601],"domain_scores_gemma":[0.99962103,0.000022566872,0.000034777953,0.00023408525,0.000058674796,0.00002888194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017506481,0.000055539702,0.000079134916,0.0004089969,0.00024660907,0.000109344524,0.0003059548,0.00009296857,0.0000047663602],"category_scores_gemma":[0.00016144528,0.00005721983,0.000005816362,0.00061607535,0.000044237026,0.0015180592,0.0007048372,0.00015337559,0.00000793059],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010907892,0.000090349604,0.13686714,0.00006674061,0.000011011388,0.0000014527744,0.0031048045,0.00012187165,0.000012415016,0.31916222,0.0029467917,0.5376043],"study_design_scores_gemma":[0.0025946172,0.00032463425,0.55360746,0.00011258097,0.000015471103,0.00004037295,0.0040483857,0.05857722,0.0005754303,0.07763732,0.30177924,0.0006872323],"about_ca_topic_score_codex":0.000089229645,"about_ca_topic_score_gemma":0.00013929664,"teacher_disagreement_score":0.53691703,"about_ca_system_score_codex":0.000026253387,"about_ca_system_score_gemma":0.000028050907,"threshold_uncertainty_score":0.23333569},"labels":[],"label_agreement":null},{"id":"W4413367005","doi":"10.1016/j.eng.2025.08.014","title":"Visualization of Industrial Big Data: State-of-the-Art and Future Perspectives","year":2025,"lang":"en","type":"article","venue":"Engineering","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"National Key Research and Development Program of China","keywords":"Visualization; State (computer science); Data science; The arts; Big data; Computer science; Engineering; Visual arts; Data mining; Art; Programming language","score_opus":0.02778992851155839,"score_gpt":0.279439209780753,"score_spread":0.2516492812691946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413367005","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005174881,0.00022155409,0.99343204,0.00020890866,0.0007528404,0.000049782306,0.000014211572,0.0000292785,0.000116476345],"genre_scores_gemma":[0.9944092,0.00021069704,0.0045420695,0.000047973404,0.00034424177,0.0000014549095,0.000030915988,0.000008891115,0.0004045508],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99964446,0.00001034082,0.00010836636,0.00010777674,0.000081,0.000048071524],"domain_scores_gemma":[0.9995996,0.000019741266,0.000036174384,0.00029188974,0.000040434683,0.000012170662],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000096612144,0.000041521365,0.000067644585,0.000077101045,0.0000167206,0.000025660405,0.00032555268,0.000019066001,9.201614e-7],"category_scores_gemma":[0.00008859269,0.000034688615,0.000010016745,0.0004755415,0.0000128206975,0.00016850719,0.00025892496,0.00003755585,2.1759918e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007375921,0.00013302409,0.006982052,0.00023696634,0.00015578032,0.0000012028889,0.0045140325,0.01115404,0.0035088214,0.8126003,0.013334111,0.14737229],"study_design_scores_gemma":[0.0005035668,0.000022399225,0.0036557936,0.00014106056,0.000018821338,8.716853e-7,0.00024727226,0.88591444,0.0084168445,0.00022603935,0.100711964,0.00014094665],"about_ca_topic_score_codex":0.0000021075941,"about_ca_topic_score_gemma":0.000001228181,"teacher_disagreement_score":0.9892343,"about_ca_system_score_codex":0.000006978474,"about_ca_system_score_gemma":0.00003392206,"threshold_uncertainty_score":0.14145607},"labels":[],"label_agreement":null},{"id":"W4413575367","doi":"10.1007/978-981-96-5761-2_19","title":"Visualisation Patterns in Visual Reasoning Tasks with Different Complexity Levels: Insights from Human and Machine Approach","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in educational technology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Future Earth","funders":"","keywords":"Computer science; Human–computer interaction; Visualization; Visual reasoning; Visual analytics; Interactive visual analysis; Cognitive science; Artificial intelligence; Psychology","score_opus":0.03891792327206388,"score_gpt":0.3106667513915943,"score_spread":0.2717488281195304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413575367","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0109829,0.0007902156,0.9800994,0.0034847734,0.00017070126,0.00039660968,0.00014590811,0.00015164277,0.0037778718],"genre_scores_gemma":[0.97922176,0.000048169353,0.016964529,0.0004654332,0.00009364971,0.000037025267,0.0022533527,0.00002677275,0.00088932976],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982595,0.000048140348,0.0004299291,0.0007972477,0.0002643435,0.00020086512],"domain_scores_gemma":[0.99893117,0.00021369947,0.00024621666,0.0004754303,0.00008873858,0.000044719643],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007023877,0.00036762762,0.00045221034,0.0012037089,0.00010940571,0.00010185982,0.00060884113,0.00049646985,0.000053651438],"category_scores_gemma":[0.000105283005,0.0003227545,0.000030842944,0.0003130369,0.00020938936,0.00013194907,0.0003495547,0.00070890423,0.0000019178824],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000049642895,0.00018726921,0.012348992,0.00005082234,0.000040819843,0.000004346337,0.00037647766,0.000059534203,0.000029138386,0.9783674,0.000018131926,0.008512139],"study_design_scores_gemma":[0.0007296776,0.000118289645,0.029694906,0.0007214956,0.00003225005,0.000016033033,0.000024294643,0.041591395,0.00025130517,0.9251036,0.0010602017,0.0006565481],"about_ca_topic_score_codex":0.00019591085,"about_ca_topic_score_gemma":0.0025081325,"teacher_disagreement_score":0.96823883,"about_ca_system_score_codex":0.00021222177,"about_ca_system_score_gemma":0.00017516836,"threshold_uncertainty_score":0.99992245},"labels":[],"label_agreement":null},{"id":"W4413868413","doi":"10.1002/sam.70042","title":"Recursive Random Binning to Detect and Display Pairwise Dependence","year":2025,"lang":"en","type":"article","venue":"Statistical Analysis and Data Mining The ASA Data Science Journal","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Pairwise comparison; Computer science; Mathematics; Statistics; Algorithm; Artificial intelligence","score_opus":0.04648949380676017,"score_gpt":0.3791487152178348,"score_spread":0.3326592214110746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413868413","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0029547212,0.00019328036,0.9932385,0.0024217395,0.00011908504,0.00006803388,0.0009124978,0.000016657039,0.0000754581],"genre_scores_gemma":[0.30995727,0.00066616293,0.68683106,0.0019815257,0.00007216722,0.0000021605667,0.00039577883,0.0000061055275,0.00008779773],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972861,0.00016938438,0.0004524258,0.0009880076,0.0007067956,0.00039733245],"domain_scores_gemma":[0.9959993,0.00097555574,0.00017129474,0.0023101617,0.00017471414,0.00036897874],"candidate_categories":["sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0062863394,0.00015627957,0.00031411782,0.0006007738,0.0013308467,0.0029940447,0.0062353816,0.000026441057,0.000021179732],"category_scores_gemma":[0.0050900863,0.00009822986,0.000022880296,0.0041172868,0.000591613,0.002804536,0.007018029,0.00022678432,0.0000050626027],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010313763,0.00007526356,0.019544749,0.000032132994,0.0008339642,0.00012407312,0.0014606661,0.00027482666,0.00039918226,0.13777213,0.046008028,0.79337186],"study_design_scores_gemma":[0.0004174699,0.000056367033,0.019360388,0.00007451593,0.0006364189,0.00006855779,0.0006055891,0.96991086,0.000029190362,0.00407003,0.004545508,0.00022510023],"about_ca_topic_score_codex":0.000072193245,"about_ca_topic_score_gemma":0.00014673808,"teacher_disagreement_score":0.969636,"about_ca_system_score_codex":0.000022925593,"about_ca_system_score_gemma":0.00030509284,"threshold_uncertainty_score":0.9999693},"labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"low"},{"model":"gpt","categories":[],"domain":null,"study_design":"design_other","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"medium"}],"label_agreement":"split"},{"id":"W4414073095","doi":"10.1007/978-3-032-05005-2_11","title":"Improving Visual Comparison Across Multiple Views with Shadow Marks","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Autodesk (Canada); University of Saskatchewan","funders":"","keywords":"Shadow (psychology); Frame (networking); Overlay; Grid; Reference frame; Spatial analysis; Frame of reference","score_opus":0.023054856342315844,"score_gpt":0.3164895371532244,"score_spread":0.29343468081090857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414073095","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00003459318,0.00024310383,0.9959596,0.00028149685,0.00094561506,0.0003844729,0.000022660104,0.0002097743,0.0019186925],"genre_scores_gemma":[0.17304736,0.000059209033,0.8166482,0.0059085977,0.00058203156,0.000020427535,0.00010989446,0.00007968802,0.003544626],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99562013,0.000043925087,0.00070781953,0.0017659448,0.001053895,0.0008082629],"domain_scores_gemma":[0.99715024,0.00043875448,0.00046002123,0.0014077364,0.00033821608,0.00020501147],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0008598524,0.00061883155,0.00074294605,0.00058125396,0.00043412443,0.0014496443,0.00364855,0.00029753827,0.000018573433],"category_scores_gemma":[0.00014781371,0.0005156518,0.00012051141,0.0010583267,0.0006190406,0.000808111,0.002346686,0.0008191861,0.000034603076],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013458287,0.000087372304,0.00089581474,0.00012791915,0.00002194498,0.000060420876,0.0008646198,0.016942883,0.00006150296,0.009081889,0.00020059013,0.9716416],"study_design_scores_gemma":[0.00042502256,0.00017307785,0.00011193098,0.00048534077,0.000010686769,0.0000186045,8.499641e-7,0.9895553,0.00057708635,0.0022563075,0.0057277726,0.00065804116],"about_ca_topic_score_codex":0.000058308025,"about_ca_topic_score_gemma":0.00081352156,"teacher_disagreement_score":0.9726124,"about_ca_system_score_codex":0.0002509678,"about_ca_system_score_gemma":0.00068697054,"threshold_uncertainty_score":0.9997295},"labels":[],"label_agreement":null},{"id":"W4414131122","doi":"10.1177/14738716251365892","title":"Interactive data driven exploration of COVID-19","year":2025,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Defence Research and Development Canada","funders":"","keywords":"Visualization; Data visualization; Raw data; Interactive visualization; Big data; Set (abstract data type); Data-driven; Information visualization; Visual analytics","score_opus":0.07122618163928575,"score_gpt":0.4035709611656654,"score_spread":0.33234477952637964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414131122","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000086527536,0.000008448412,0.9947265,0.0009777275,0.00027219125,0.0001919974,0.000057118326,0.00016430345,0.0035152293],"genre_scores_gemma":[0.95687467,0.0002106423,0.0194344,0.010847953,0.00005203294,0.00003275276,0.012054543,0.000010964417,0.00048205344],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99883646,0.000083805644,0.00055502076,0.00015977016,0.00027063052,0.00009432202],"domain_scores_gemma":[0.9984101,0.00008240537,0.00037317534,0.00072373525,0.00034850786,0.00006208227],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00036220177,0.00009099686,0.00012134532,0.00051182025,0.00010676445,0.00023504953,0.00091365364,0.0000547501,0.000031896267],"category_scores_gemma":[0.00096449174,0.00009336575,0.000021935117,0.001248266,0.000031373056,0.014741432,0.00044084183,0.000043178487,0.00004805725],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009310817,0.00005381091,0.00029171203,0.00011594911,0.000024541705,1.7281023e-7,0.0034102825,0.005818328,0.0000363136,0.95745045,0.023220917,0.009568204],"study_design_scores_gemma":[0.00035875075,0.000019491605,0.0001089489,0.000030099098,0.000009534737,6.0750324e-7,0.0005288817,0.8834903,0.00061052357,0.0036063287,0.111148275,0.00008823366],"about_ca_topic_score_codex":0.000025885187,"about_ca_topic_score_gemma":0.00001041505,"teacher_disagreement_score":0.9752921,"about_ca_system_score_codex":0.000078844736,"about_ca_system_score_gemma":0.00032798407,"threshold_uncertainty_score":0.9990389},"labels":[],"label_agreement":null},{"id":"W4414145443","doi":"10.1093/mnras/staf1487","title":"Emulating dark matter halo merger trees with graph generative models","year":2025,"lang":"en","type":"article","venue":"Monthly Notices of the Royal Astronomical Society","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Particle Physics","funders":"Leibniz-Rechenzentrum; Gauss Centre for Supercomputing; Leibniz-Institut für Astrophysik Potsdam; Flatiron Health; Leibniz-Gemeinschaft; National Aeronautics and Space Administration; Partnership for Advanced Computing in Europe AISBL; Space Telescope Science Institute; National Science Foundation","keywords":"Halo; Dark matter; Tree (set theory); Galaxy; Scaling; Branching (polymer chemistry); Generative model; Graph","score_opus":0.011387465954599675,"score_gpt":0.23482659419779595,"score_spread":0.22343912824319628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414145443","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5899493,0.000060534192,0.40406486,0.002668648,0.00018386412,0.00017918942,0.000036041998,0.000051249972,0.0028063082],"genre_scores_gemma":[0.9375673,8.0792795e-8,0.06116751,0.0004817332,0.00002494448,0.00000498407,0.0000069918788,0.0000064932847,0.0007399578],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989955,0.00006402933,0.00026225,0.00029205513,0.00017872523,0.00020742817],"domain_scores_gemma":[0.99922585,0.00006879677,0.00015608373,0.00044151917,0.000060797807,0.00004697056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013829418,0.00014462828,0.00020171177,0.000019390383,0.00018269519,0.00012818565,0.0008758544,0.00004835028,0.0000138448295],"category_scores_gemma":[0.0000072798975,0.000091992,0.00020949227,0.00022850883,0.00013824039,0.00027072817,0.0004382129,0.00012042293,0.00000412707],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000047756566,0.00005291496,0.011478625,0.000009028938,0.00009930313,3.695588e-8,0.00033262122,0.9784425,0.00002185769,0.0027510046,0.0065356367,0.00027171365],"study_design_scores_gemma":[0.0002366413,0.00001662472,0.020991674,0.000034254994,0.000034095832,3.3725636e-9,0.00010712791,0.9777013,0.00031046776,0.00035073634,0.00011603043,0.0001010611],"about_ca_topic_score_codex":0.00010798963,"about_ca_topic_score_gemma":0.000035034944,"teacher_disagreement_score":0.347618,"about_ca_system_score_codex":0.00003722782,"about_ca_system_score_gemma":0.000049102982,"threshold_uncertainty_score":0.3751325},"labels":[],"label_agreement":null},{"id":"W4414192480","doi":"10.1007/978-3-032-04630-7_1","title":"Evaluating Compliance with Visualization Guidelines in Diagrams for Scientific Publications Using Large Vision Language Models","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Visualization; Set (abstract data type); Misinformation; Data visualization; Field (mathematics); Creative visualization; Data set; Quality (philosophy)","score_opus":0.14537905230043033,"score_gpt":0.43875689070741575,"score_spread":0.2933778384069854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414192480","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009851834,0.00029007334,0.997254,0.0005189062,0.00057323946,0.00074509706,0.000047856105,0.00013248713,0.0003398029],"genre_scores_gemma":[0.024508923,0.000019418741,0.9721396,0.0013819841,0.00016679808,0.000030006711,0.00024264681,0.000037159847,0.0014734596],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99614793,0.00004796072,0.00074052886,0.0015261149,0.0009827312,0.0005547566],"domain_scores_gemma":[0.9966179,0.000318075,0.00039520467,0.0012273566,0.0013404398,0.00010103699],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0022421398,0.0003699491,0.0004113035,0.0015503188,0.0005149848,0.0017340287,0.0021752862,0.00017023816,0.000006366783],"category_scores_gemma":[0.0004055427,0.00033143035,0.000072618255,0.0024517528,0.0003159968,0.0014971123,0.00084099197,0.00024768853,0.0000031515103],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006287856,0.00008517827,0.00008523371,0.0001467537,0.000009073253,0.0000048985075,0.001042543,0.510316,0.00022904786,0.2529428,0.00011675727,0.23501542],"study_design_scores_gemma":[0.00040796364,0.00007119528,0.000012950501,0.0011630808,0.000010012501,0.0000049696723,0.0000013385693,0.9652693,0.0001698842,0.031800535,0.00071952713,0.00036921413],"about_ca_topic_score_codex":0.000023705066,"about_ca_topic_score_gemma":0.0004194507,"teacher_disagreement_score":0.4549533,"about_ca_system_score_codex":0.00029237554,"about_ca_system_score_gemma":0.0010340282,"threshold_uncertainty_score":0.99991375},"labels":[],"label_agreement":null},{"id":"W4414680536","doi":"10.33767/osf.io/tyfbm_v1","title":"Flirting Charts: Expressive Motion Design in Information Visualization Inspired by Animal Courtship Performances","year":2025,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Flirting; Motion (physics); Visualization; Courtship; Code (set theory); Choreography","score_opus":0.01875751148281971,"score_gpt":0.29349408415333983,"score_spread":0.2747365726705201,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414680536","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0052384473,0.000034838635,0.9916727,0.00034450073,0.00010123019,0.00016638084,0.0000033133172,0.00014696272,0.0022916545],"genre_scores_gemma":[0.99183136,0.00007120079,0.006505064,0.0013030274,0.000012747477,0.000015430673,0.00010346986,0.0000032007608,0.00015448229],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990048,0.00008084287,0.0003827085,0.00016177598,0.00020503454,0.0001648756],"domain_scores_gemma":[0.9994697,0.000044440665,0.00014115748,0.00017349736,0.00013852955,0.000032681255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042400038,0.00009932869,0.00010261297,0.0003041623,0.0001124573,0.0003555961,0.00032963455,0.000056003846,0.000023636418],"category_scores_gemma":[0.00011086904,0.00009493684,0.000017712631,0.00080588,0.00001796845,0.0038008878,0.00010154581,0.00005573102,0.00003496418],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046217836,0.0002534976,0.009255282,0.00013231163,0.000022857466,0.0000018070899,0.004418741,0.007084625,0.0058617815,0.8377904,0.040916987,0.09421549],"study_design_scores_gemma":[0.00039366557,0.000037775444,0.0014006039,0.0000539647,0.000002078992,3.891058e-7,0.00021399943,0.97621304,0.017574808,0.0005012276,0.0034876682,0.00012075493],"about_ca_topic_score_codex":0.000018074983,"about_ca_topic_score_gemma":0.0000017713637,"teacher_disagreement_score":0.98659295,"about_ca_system_score_codex":0.000055316654,"about_ca_system_score_gemma":0.000060043654,"threshold_uncertainty_score":0.3871412},"labels":[],"label_agreement":null},{"id":"W4414738120","doi":"10.1177/23733799251370365","title":"An Online Interactive Tool for Exploring Water Justice with Undergraduate Students","year":2025,"lang":"en","type":"article","venue":"Pedagogy in Health Promotion","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute on Governance; University of Guelph","funders":"National Science Foundation","keywords":"Environmental justice; Public health; Set (abstract data type); Water quality; Safe Drinking Water Act; Exploratory research; Public engagement; Meaning (existential)","score_opus":0.1492992023701516,"score_gpt":0.4881486840466953,"score_spread":0.3388494816765437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414738120","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15347217,0.0000070586234,0.837108,0.008484647,0.00034200953,0.00047979332,0.000008482199,0.00007789998,0.000019927407],"genre_scores_gemma":[0.9833827,0.00007399968,0.014586339,0.0012015204,0.000060569106,0.00012812308,0.00021144665,0.0000096019185,0.0003457266],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99876374,0.00015312346,0.00031950822,0.0003283557,0.00016793945,0.0002673133],"domain_scores_gemma":[0.99941725,0.000053821434,0.000081218095,0.00027458795,0.00011935934,0.000053761214],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052324357,0.00009749735,0.00014429314,0.0002132916,0.0001341807,0.00011117517,0.000378545,0.000026373935,0.00000285304],"category_scores_gemma":[0.00004104289,0.00007566785,0.000014782884,0.00024899663,0.000013330885,0.0009488767,0.00009224861,0.00010617153,0.0000051693864],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005728344,0.01788269,0.09079328,0.008493222,0.00026043496,0.00004487446,0.05134339,0.016044745,0.0010120317,0.39535502,0.001256141,0.41694134],"study_design_scores_gemma":[0.005272627,0.0041161976,0.038651913,0.0015740307,0.00006891701,0.000011377661,0.003045224,0.92139435,0.0028314167,0.0146503365,0.0076935785,0.00069004466],"about_ca_topic_score_codex":0.00005775988,"about_ca_topic_score_gemma":0.0002773732,"teacher_disagreement_score":0.9053496,"about_ca_system_score_codex":0.00013867635,"about_ca_system_score_gemma":0.00015877427,"threshold_uncertainty_score":0.30856454},"labels":[],"label_agreement":null},{"id":"W4415159644","doi":"10.1108/s0733-558x20250000095003","title":"Assembling Frankensteins: How Data Scientists Stitch Together Provisional Artifacts to Generate Novel Insights","year":2025,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; University of Alberta","funders":"","keywords":"Perspective (graphical); Conversation; Image stitching; Range (aeronautics); Agency (philosophy); Key (lock)","score_opus":0.09333093751975764,"score_gpt":0.32246491612634387,"score_spread":0.22913397860658624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415159644","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000077640125,0.00011324189,0.8219192,0.0014462433,0.00099332,0.00031090528,0.00024314452,0.0001828038,0.17478335],"genre_scores_gemma":[0.0005252254,0.0000467517,0.10246687,0.004588251,0.0002446127,0.000003832274,0.0010296268,0.00003428471,0.89106053],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966981,0.00001899198,0.0004190834,0.0015158762,0.0010103522,0.0003376151],"domain_scores_gemma":[0.9963485,0.00007810903,0.00019244387,0.0026688494,0.00043575527,0.0002763171],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0003643759,0.00041915796,0.0004003517,0.0006341635,0.00023691435,0.0017184302,0.003628068,0.00023270615,0.00018318927],"category_scores_gemma":[0.00014958969,0.00035847246,0.00007851092,0.0003602159,0.000053584226,0.001099976,0.0036101043,0.00025559668,0.0004567794],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000018526266,0.000048348236,0.0000017075664,0.000038368995,0.00006032547,0.000020974481,0.000052405143,0.00009198554,0.00042211745,0.87859297,0.10646135,0.014207606],"study_design_scores_gemma":[0.00018735627,0.000025960304,0.0000049318282,0.0002524655,0.000023063252,0.000003893037,0.0000030083636,0.19192553,0.00029830475,0.0016077528,0.8052119,0.0004558636],"about_ca_topic_score_codex":0.000012910879,"about_ca_topic_score_gemma":0.00012525091,"teacher_disagreement_score":0.8769852,"about_ca_system_score_codex":0.00006325219,"about_ca_system_score_gemma":0.0006490595,"threshold_uncertainty_score":0.99988675},"labels":[],"label_agreement":null},{"id":"W4415512746","doi":"10.21105/joss.08334","title":"E2P Simulator: An Interactive Tool for Estimating Real-World Predictive Utility of Research Findings","year":2025,"lang":"","type":"article","venue":"The Journal of Open Source Software","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"Canadian Institutes of Health Research; Krembil Foundation","keywords":"Open source; Predictive modelling; R package; Predictive value; Clinical decision making","score_opus":0.09271475147312076,"score_gpt":0.4616549664918029,"score_spread":0.3689402150186821,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415512746","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034693886,0.000078690995,0.96224535,0.00068342674,0.0005931116,0.0010624361,0.00016505407,0.00002480664,0.0004532491],"genre_scores_gemma":[0.9430189,0.000048769907,0.053741973,0.0002774968,0.00020617535,0.000006822202,0.000012021257,0.000030640254,0.0026572086],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9947074,0.0015548064,0.001660741,0.00042609856,0.0011160072,0.0005349177],"domain_scores_gemma":[0.98764074,0.005750047,0.0014035129,0.001136308,0.003870389,0.00019902669],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.013886828,0.00028254188,0.00077888346,0.00068026036,0.0010187433,0.0011869072,0.006075972,0.00011208943,0.00012121452],"category_scores_gemma":[0.006542965,0.0002146112,0.00023640384,0.0021850143,0.0005524869,0.0029420166,0.0030162258,0.0010423452,0.0000041394296],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.012670938,0.004880976,0.07596376,0.0025614623,0.0035766836,0.0000416177,0.16022636,0.20381321,0.00031443159,0.016191823,0.09824596,0.42151275],"study_design_scores_gemma":[0.0015067951,0.001001824,0.004454576,0.00236274,0.00023751163,0.000012636902,0.004547993,0.9738659,0.0010098403,0.006858088,0.003928762,0.00021331047],"about_ca_topic_score_codex":0.0002407716,"about_ca_topic_score_gemma":0.000043379827,"teacher_disagreement_score":0.90850335,"about_ca_system_score_codex":0.00023671324,"about_ca_system_score_gemma":0.0014417429,"threshold_uncertainty_score":0.99985},"labels":[],"label_agreement":null},{"id":"W4415719548","doi":"10.18280/ts.420522","title":"Multimodal Image Processing and Learning Behavior Pattern Visualization for Educational Management","year":2025,"lang":"","type":"article","venue":"Traitement du signal","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Visualization; Image processing; Learning Management; Image (mathematics); Data visualization","score_opus":0.01843494516402935,"score_gpt":0.33068488653291034,"score_spread":0.312249941368881,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415719548","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0055864872,0.00023094333,0.99078697,0.0012389147,0.00031898194,0.0011264776,0.000043986456,0.00007480089,0.00059242285],"genre_scores_gemma":[0.97348124,0.000109844135,0.020164214,0.0011392038,0.00020916927,0.0003151751,0.00048763017,0.000030338939,0.004063158],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975008,0.00014312657,0.0006976089,0.00078981085,0.00044205342,0.00042660563],"domain_scores_gemma":[0.998941,0.00010312825,0.00028056453,0.00019977968,0.00034391967,0.00013162242],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0006566979,0.00032509433,0.00025920125,0.00040273787,0.0008523842,0.0012610271,0.00045659905,0.00008382449,0.00028295355],"category_scores_gemma":[0.00003541553,0.00036434043,0.00009085585,0.0005922155,0.00011793566,0.0008757646,0.0003063476,0.00015061423,0.0000125098],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036766054,0.0014577864,0.009695542,0.0015787184,0.00015121259,0.00000647635,0.0020679184,0.00061693345,0.0007568356,0.05682844,0.0023962294,0.9244071],"study_design_scores_gemma":[0.0019778134,0.00015221836,0.020332986,0.0004198034,0.00030661267,0.0000028536933,0.00046298103,0.96702737,0.00030384504,0.00037256838,0.008239393,0.00040156697],"about_ca_topic_score_codex":0.000012246427,"about_ca_topic_score_gemma":0.000004766868,"teacher_disagreement_score":0.9706228,"about_ca_system_score_codex":0.00011237664,"about_ca_system_score_gemma":0.0001908928,"threshold_uncertainty_score":0.99988085},"labels":[],"label_agreement":null},{"id":"W4415743675","doi":"10.1109/iv68685.2025.00049","title":"An Environmental Analytics Solution for Visualizing Clusters of Wildfires","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Visual analytics; Visualization; Analytics; Globe; Cluster analysis; Data visualization; Generalization; Visibility","score_opus":0.026211640638289443,"score_gpt":0.335866236404604,"score_spread":0.30965459576631454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415743675","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0058561093,0.00016464968,0.99180216,0.0005365806,0.0005179248,0.00032883216,0.00009806605,0.000047353948,0.0006483333],"genre_scores_gemma":[0.9730189,0.00018830324,0.024113817,0.0012374897,0.00005073881,0.000004826534,0.00013734047,0.000012127844,0.0012364875],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978775,0.0001010038,0.00075680786,0.0005714781,0.0003259737,0.0003672428],"domain_scores_gemma":[0.99868876,0.00010886933,0.00027658461,0.000736748,0.000059180315,0.0001298635],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005039837,0.00023349417,0.00033547822,0.00036247366,0.00026099104,0.0002594488,0.0009048854,0.00012811126,0.00006586497],"category_scores_gemma":[0.000052107043,0.00024752755,0.00017645706,0.00060874736,0.00021185695,0.00088272546,0.00032787424,0.00007312325,0.00000770839],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011891217,0.002760011,0.01244942,0.0006521718,0.0005500288,0.0000026201506,0.002064712,0.005749875,0.016209884,0.7265904,0.010741939,0.22211],"study_design_scores_gemma":[0.0007162435,0.00028623364,0.0010865229,0.00009377288,0.00013400777,7.077138e-7,0.00040141263,0.984503,0.005343379,0.000789475,0.0064093545,0.00023592603],"about_ca_topic_score_codex":0.000072842035,"about_ca_topic_score_gemma":0.000024012472,"teacher_disagreement_score":0.9787531,"about_ca_system_score_codex":0.00016486977,"about_ca_system_score_gemma":0.00017148242,"threshold_uncertainty_score":0.9999977},"labels":[],"label_agreement":null},{"id":"W4415743872","doi":"10.1109/iv68685.2025.00031","title":"Visualization of Node-Centric Hierarchical Structures in Directed Graphs","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Visualization; Hierarchy; Plug-in; Directed graph; Enhanced Data Rates for GSM Evolution; Limiting; Graph Layout; Graph drawing; CLARITY","score_opus":0.014301013865296221,"score_gpt":0.31176608107908504,"score_spread":0.29746506721378885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415743872","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0066825096,0.0003789827,0.98284346,0.00057333364,0.0007410525,0.00032432046,0.000022372142,0.00013736916,0.008296628],"genre_scores_gemma":[0.9905029,0.00046566414,0.006220652,0.0010636944,0.000016962931,0.0000034600148,0.00007302213,0.000010531044,0.0016431211],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997308,0.0003211242,0.0009646474,0.0005807744,0.00046419143,0.00036126096],"domain_scores_gemma":[0.99864846,0.00016244756,0.00020980714,0.0005895545,0.00028771418,0.000102019854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032981441,0.00023609026,0.0004167548,0.0015227746,0.00009133835,0.0002118935,0.00091677596,0.00017215477,0.00033018526],"category_scores_gemma":[0.00036787856,0.00022769772,0.000105986415,0.008090969,0.00016292493,0.00038034553,0.00046734023,0.00016741168,0.0000074554778],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017742548,0.0003714227,0.021893904,0.0001451965,0.000038148148,0.0000043200644,0.00032845995,0.0005569867,0.0001572848,0.95512474,0.0023430106,0.019018812],"study_design_scores_gemma":[0.0010599005,0.000048400278,0.046954148,0.00016913287,0.00003147983,9.637537e-7,0.00003933918,0.91823125,0.002099219,0.028498378,0.0026239734,0.0002437949],"about_ca_topic_score_codex":0.0001224785,"about_ca_topic_score_gemma":0.00008181352,"teacher_disagreement_score":0.9838204,"about_ca_system_score_codex":0.0000582249,"about_ca_system_score_gemma":0.00037245356,"threshold_uncertainty_score":0.9285243},"labels":[],"label_agreement":null},{"id":"W4415743915","doi":"10.1109/iv68685.2025.00036","title":"Ocean Science Visualization Via the World Ocean Assessment","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Canada First Research Excellence Fund","keywords":"Visualization; Point (geometry); Ocean science; Data visualization; Indian ocean","score_opus":0.02025038036090948,"score_gpt":0.369804016169135,"score_spread":0.3495536358082255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415743915","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00032524785,0.00008156724,0.90457755,0.0077254265,0.0019891893,0.00039766595,0.000006744896,0.00018694214,0.084709674],"genre_scores_gemma":[0.9175622,0.00009530454,0.0032958512,0.012552464,0.000114977105,9.670505e-7,0.000024256755,0.000015577967,0.06633844],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99567056,0.00024758533,0.0008510809,0.001109756,0.0013840339,0.00073696754],"domain_scores_gemma":[0.9967109,0.00019532393,0.00029689493,0.0017636956,0.000804582,0.00022862953],"candidate_categories":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002721972,0.0003608485,0.00029502957,0.00104383,0.001973665,0.0036436657,0.0040728203,0.00006430947,0.00048007045],"category_scores_gemma":[0.00017540135,0.00026264277,0.00012319293,0.013575034,0.001085728,0.0019000887,0.002020738,0.00026982487,0.0001024025],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000018766972,0.00023116254,0.0030695077,0.000032114673,0.000029885048,0.0000022299912,0.00022857646,0.0006905827,0.00008147462,0.93968374,0.04450651,0.01144232],"study_design_scores_gemma":[0.0003018652,0.00004653211,0.0029945457,0.00010459085,0.000052236093,0.0000022188956,0.00016362913,0.9254576,0.0015089663,0.004495073,0.0645704,0.00030233266],"about_ca_topic_score_codex":0.000040835977,"about_ca_topic_score_gemma":0.000055135,"teacher_disagreement_score":0.9351887,"about_ca_system_score_codex":0.00032736358,"about_ca_system_score_gemma":0.0019062844,"threshold_uncertainty_score":0.9999826},"labels":[],"label_agreement":null},{"id":"W4415743927","doi":"10.1109/iv68685.2025.00046","title":"Information Visualization for Transportation Analytics","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Visual analytics; Visualization; Analytics; Public transport; Data visualization; Transit (satellite); Information visualization; Information system; Transportation industry","score_opus":0.01984329256737681,"score_gpt":0.3280165750014089,"score_spread":0.3081732824340321,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415743927","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00007577856,0.00004910312,0.99090564,0.0014990463,0.0010544044,0.00062321435,0.00021996035,0.0001559594,0.005416871],"genre_scores_gemma":[0.8859558,0.0009147347,0.05024075,0.02286809,0.0002307572,0.00011370348,0.010805302,0.000037309568,0.02883352],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980963,0.000041674735,0.0009861029,0.00025492196,0.0003199412,0.00030108014],"domain_scores_gemma":[0.99811506,0.00009745649,0.00029726216,0.00045732633,0.0009422648,0.00009063273],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043523198,0.00022660212,0.00025036852,0.0006315208,0.0002972816,0.0009290082,0.000562143,0.00016979115,0.000098097036],"category_scores_gemma":[0.00018884496,0.00024220953,0.00015119575,0.0021877417,0.00004970009,0.0033715349,0.0000345207,0.0000654702,0.000061517036],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014936912,0.00008541368,0.0002878046,0.00027678141,0.000059241862,1.0383403e-7,0.00072642916,0.0018808545,0.000009525676,0.91878617,0.03362253,0.044250224],"study_design_scores_gemma":[0.0007708344,0.00006426305,0.0007120127,0.000074489035,0.00011349567,1.3324441e-7,0.00026653084,0.77825767,0.0006920487,0.0047393464,0.21410409,0.00020511266],"about_ca_topic_score_codex":0.000019190156,"about_ca_topic_score_gemma":0.00003954292,"teacher_disagreement_score":0.9406649,"about_ca_system_score_codex":0.00008623095,"about_ca_system_score_gemma":0.00040896263,"threshold_uncertainty_score":0.9877018},"labels":[],"label_agreement":null},{"id":"W4415744052","doi":"10.1109/iv68685.2025.00019","title":"Dynamic Conflict Surges Flagging and Visualization","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Flagging; Exploit; Dashboard; Visualization; Data visualization; Earth observation satellite","score_opus":0.017671754519394206,"score_gpt":0.33369721876333286,"score_spread":0.3160254642439386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415744052","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016403002,0.0011298552,0.98319876,0.0018645964,0.0006866302,0.00015413815,0.000008930667,0.00017159704,0.011145196],"genre_scores_gemma":[0.9376331,0.0044540283,0.0030424427,0.005336403,0.000023582004,0.0000038853873,0.000075672404,0.000017611857,0.04941331],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982895,0.00011783736,0.00047118092,0.0005793421,0.00023715242,0.00030496658],"domain_scores_gemma":[0.9989808,0.00012713223,0.000121120174,0.0004610735,0.00019451173,0.0001153421],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00044226387,0.0002184182,0.0002608897,0.00043051122,0.00030570469,0.0010767888,0.00042661346,0.00010420865,0.000210972],"category_scores_gemma":[0.00013977721,0.00022272317,0.00005032849,0.0013582271,0.00012635157,0.0007017748,0.00053480023,0.0000854475,0.00003004217],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000031799393,0.00007788749,0.0021115905,0.00014643719,0.000056560682,0.0000045097736,0.00046052705,0.00013360241,0.00017194566,0.9306146,0.005875441,0.060343698],"study_design_scores_gemma":[0.00032048047,0.000021983224,0.0015165958,0.00015508854,0.000034744116,0.0000020671175,0.00013308917,0.9360572,0.00033149222,0.00074016384,0.060466833,0.00022025495],"about_ca_topic_score_codex":0.0000361146,"about_ca_topic_score_gemma":0.000032954606,"teacher_disagreement_score":0.9801563,"about_ca_system_score_codex":0.000043656437,"about_ca_system_score_gemma":0.00018326638,"threshold_uncertainty_score":0.9999602},"labels":[],"label_agreement":null},{"id":"W4415870720","doi":"10.1145/3757232.3757234","title":"“It looks like someone just threw random dots on a dot plot”: User Response to Sketchy Rendering Styles for Data-Driven Algorithmic Systems","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Science Foundation","keywords":"Rendering (computer graphics); User experience design; User interface; Systems design; Outlier; 3D rendering; Non-photorealistic rendering","score_opus":0.07522241032032567,"score_gpt":0.35862622235562003,"score_spread":0.28340381203529436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415870720","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00071397156,0.0004570341,0.98284996,0.00854897,0.0025742913,0.0025064668,0.0008514871,0.00035738602,0.0011404606],"genre_scores_gemma":[0.36848733,0.0017184232,0.14147185,0.044104934,0.0026881471,0.0009968297,0.0018282947,0.0004674514,0.43823674],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9934913,0.00068051234,0.0015621345,0.0022344699,0.0009766001,0.0010549718],"domain_scores_gemma":[0.9929593,0.0015534504,0.00036749698,0.004119799,0.00049332925,0.00050659577],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.003099009,0.00072320504,0.0010966591,0.0010544789,0.00071942265,0.0026612754,0.004401922,0.00026930214,0.00012222015],"category_scores_gemma":[0.0008313776,0.0006720146,0.00022637198,0.0017936245,0.00013613584,0.0012882352,0.0029623641,0.00035648185,0.00042818132],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.01065445,0.0016461335,0.000121857236,0.0024182824,0.0019475139,0.00016060866,0.005877291,0.036864355,0.002402403,0.1496097,0.7253022,0.062995166],"study_design_scores_gemma":[0.004968464,0.00036615934,0.00004008712,0.0010669724,0.00016683896,0.0000072430225,0.0008909997,0.69344234,0.00027327068,0.0000610882,0.29811233,0.00060419645],"about_ca_topic_score_codex":0.000119057564,"about_ca_topic_score_gemma":0.00022575763,"teacher_disagreement_score":0.8413781,"about_ca_system_score_codex":0.00025915765,"about_ca_system_score_gemma":0.0011017356,"threshold_uncertainty_score":0.9995731},"labels":[],"label_agreement":null},{"id":"W4416039489","doi":"10.1007/978-3-032-06161-4_24","title":"A Spatial Data Stream Ensemble for Prediction of Emergency Service Priorities","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes on data engineering and communications technologies","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Context (archaeology); Cluster analysis; Spatial contextual awareness; Service (business); Class (philosophy); Spatial analysis; Ensemble forecasting; Big data","score_opus":0.07016433396691418,"score_gpt":0.30252129899926117,"score_spread":0.23235696503234698,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416039489","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000013587871,0.0034595164,0.9806356,0.0028396517,0.0001525369,0.0002700955,0.010802381,0.0008174894,0.001021384],"genre_scores_gemma":[0.046630073,0.08410164,0.7768211,0.00032428667,0.00017007363,0.00013399565,0.08696505,0.0001421501,0.0047116657],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99892706,0.0000075133003,0.0003391126,0.00046593352,0.00013521075,0.00012516545],"domain_scores_gemma":[0.99034667,0.0003489081,0.00016430185,0.008977577,0.00014602536,0.000016496027],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.00014226155,0.00023166618,0.00026969347,0.00029682138,0.00012449015,0.00006962237,0.006751847,0.00027879578,0.0000018990096],"category_scores_gemma":[0.0006327398,0.00022273642,0.000026686668,0.00017279123,0.00004984485,0.000267467,0.0056184274,0.00030983504,0.0000010839282],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000058511678,0.000060868737,0.00001567934,0.000782881,0.00021369764,3.8847747e-7,0.000072956405,0.00063466385,0.00013282614,0.60453266,0.0063410574,0.38720644],"study_design_scores_gemma":[0.00013436096,0.00007445644,0.0000085643,0.00044779014,0.00010335459,0.0000016781887,0.000013013109,0.71984065,0.00029135493,0.011895658,0.26695052,0.0002386128],"about_ca_topic_score_codex":0.000027282294,"about_ca_topic_score_gemma":0.00014295655,"teacher_disagreement_score":0.719206,"about_ca_system_score_codex":0.000017375896,"about_ca_system_score_gemma":0.00007078784,"threshold_uncertainty_score":0.9986221},"labels":[],"label_agreement":null},{"id":"W4416072333","doi":"10.2312/eved.20251004","title":"From Reality to Recognition: Evaluating Visualization Analogies for Novice Chart Comprehension","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Visualization; Chart; Comprehension; Data visualization; Pie chart; Information visualization; Creative visualization","score_opus":0.2597139608255297,"score_gpt":0.44235934638684976,"score_spread":0.18264538556132004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416072333","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06323676,0.000057124053,0.9311573,0.0019896103,0.0012320906,0.0007328046,0.0007468732,0.0004069719,0.00044046977],"genre_scores_gemma":[0.65366006,0.0004095113,0.28200006,0.023015104,0.002801081,0.0007360981,0.034968924,0.000113348244,0.0022958321],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99740595,0.00021988255,0.00063775404,0.0010607078,0.00040317836,0.0002725144],"domain_scores_gemma":[0.997165,0.00036001968,0.0003580501,0.0011200537,0.000879892,0.00011693444],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006612902,0.0002975161,0.000418385,0.00024157592,0.00023346214,0.00032104802,0.0010681642,0.00022634988,0.000039372753],"category_scores_gemma":[0.0007614837,0.000318241,0.00014025209,0.0006034361,0.000034134246,0.00030518277,0.0017875233,0.00020099318,0.00011144283],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047091802,0.00246626,0.09325841,0.0055258055,0.001817423,0.00003786123,0.021293644,0.04566286,0.011755016,0.06327002,0.2627676,0.49167418],"study_design_scores_gemma":[0.00089628744,0.00018051144,0.02666051,0.0014302257,0.00020071052,9.3469953e-7,0.00026575118,0.9269083,0.004044393,0.016713673,0.021662414,0.0010362503],"about_ca_topic_score_codex":0.0002609432,"about_ca_topic_score_gemma":0.000060224076,"teacher_disagreement_score":0.8812455,"about_ca_system_score_codex":0.0001058977,"about_ca_system_score_gemma":0.0002498748,"threshold_uncertainty_score":0.999927},"labels":[],"label_agreement":null},{"id":"W4416125918","doi":"10.48550/arxiv.2504.04221","title":"Evaluating Graphical Perception with Multimodal LLMs","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Task (project management); Perception; Task analysis; Multimodality; Graphical display","score_opus":0.09317410924726038,"score_gpt":0.3894718387441124,"score_spread":0.296297729496852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416125918","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41551706,0.000022562952,0.58191186,0.00075529225,0.00043590428,0.00021582442,0.00002098078,0.00027137273,0.0008491505],"genre_scores_gemma":[0.9465704,0.000050136405,0.05074279,0.0010310488,0.00015437148,0.00003124016,0.00021114731,0.000013925001,0.0011949331],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980523,0.00014252806,0.00031832905,0.0007733599,0.00046664345,0.0002468259],"domain_scores_gemma":[0.9984318,0.000062481784,0.0001723552,0.0009968752,0.00023895653,0.000097516975],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043493067,0.00024600644,0.00026122862,0.0002070703,0.00015061715,0.00022662657,0.0011083272,0.00019667041,0.000053708223],"category_scores_gemma":[0.000115146926,0.00021105305,0.00010434917,0.0004532975,0.00006968335,0.00023175095,0.0013121419,0.00049901597,0.00008958327],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044853467,0.0006870592,0.87399423,0.00065463246,0.00036329922,0.000054819633,0.0034666501,0.020322498,0.0013874391,0.031850576,0.0031154647,0.064058475],"study_design_scores_gemma":[0.00040818183,0.000086265725,0.17086183,0.0002914474,0.000055192897,0.0000037413597,0.000057777255,0.82647073,0.00007544902,0.0006794123,0.0006304887,0.00037949596],"about_ca_topic_score_codex":0.00007228154,"about_ca_topic_score_gemma":0.000021639857,"teacher_disagreement_score":0.80614823,"about_ca_system_score_codex":0.00005905144,"about_ca_system_score_gemma":0.0002631111,"threshold_uncertainty_score":0.86064935},"labels":[],"label_agreement":null},{"id":"W4416152875","doi":"10.2196/79407","title":"Designing a Substance Misuse Data Dashboard for Overdose Fatality Review Teams: User-Centered Design Approach","year":2025,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Dashboard; Workload; Process (computing); Psychological intervention; Work (physics); Data collection; Data visualization","score_opus":0.1803517906600137,"score_gpt":0.40616007694485246,"score_spread":0.22580828628483876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416152875","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010704481,0.0007833263,0.9958376,0.000121603,0.00013629094,0.0012756066,0.0001872335,0.00027535367,0.0003125151],"genre_scores_gemma":[0.41959795,0.003260142,0.53051037,0.017258605,0.0003406252,0.00087940076,0.014425714,0.00022852307,0.013498696],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976541,0.00020948384,0.00052333996,0.00088797894,0.00034290343,0.00038223068],"domain_scores_gemma":[0.9970177,0.000169273,0.00023152902,0.0023182328,0.00013855266,0.00012472438],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008166673,0.00027476906,0.00040624684,0.0001555266,0.00030849132,0.0004120935,0.0031966877,0.000077396806,0.000016325781],"category_scores_gemma":[0.00021046078,0.0002481255,0.00010233994,0.0007484421,0.00006468114,0.0011821175,0.0005689849,0.00013805882,0.000008491498],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048577116,0.001971677,0.016626885,0.0077755568,0.0004531348,0.000012913079,0.0021504199,0.000096117,0.0021061266,0.16310143,0.80045867,0.0051985006],"study_design_scores_gemma":[0.006555142,0.00040258604,0.009717758,0.008620201,0.0005234471,0.0000068553204,0.00074474415,0.2198177,0.010243626,0.004670071,0.73517025,0.0035276273],"about_ca_topic_score_codex":0.0000138996065,"about_ca_topic_score_gemma":0.000010942293,"teacher_disagreement_score":0.4653273,"about_ca_system_score_codex":0.000101874226,"about_ca_system_score_gemma":0.0001403268,"threshold_uncertainty_score":0.9999971},"labels":[],"label_agreement":null},{"id":"W4416162028","doi":"10.1145/3773068","title":"Studying Visual Evidence from Using Physical Space to Think","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Energy; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Set (abstract data type); Space (punctuation); Visualization; Physical space; Data visualization; Key (lock)","score_opus":0.11895573304276924,"score_gpt":0.41363942507563023,"score_spread":0.294683692032861,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416162028","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8615673,0.0000068336103,0.13441764,0.0024120796,0.00093895546,0.00022395582,0.0000015237915,0.000115349765,0.0003163534],"genre_scores_gemma":[0.9745536,0.0000019092515,0.023846356,0.0011262923,0.0002942372,0.0000041589506,9.635057e-7,0.000009574318,0.00016290837],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99863523,0.000021061769,0.00029253692,0.0004817438,0.0003918878,0.00017756684],"domain_scores_gemma":[0.99869436,0.00018957448,0.00024999786,0.0005339176,0.00028223445,0.00004991279],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021538643,0.00017432083,0.00022073547,0.000233568,0.000238656,0.0004878908,0.0026300696,0.00003971273,0.0000048244724],"category_scores_gemma":[0.0003375085,0.0001378323,0.000112862646,0.0006927076,0.00002836588,0.0012112367,0.0024045517,0.00021283906,0.000019635545],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019503398,0.0020332586,0.009633107,0.00034435058,0.0005123977,0.0000032525083,0.030236688,0.0066646114,0.64071023,0.18809986,0.06568291,0.05588427],"study_design_scores_gemma":[0.00029657502,0.00024297003,0.0050998786,0.002052608,0.000056643126,0.0000024551744,0.00038998836,0.81320536,0.1679055,0.009494167,0.0009680633,0.0002858294],"about_ca_topic_score_codex":0.000074077856,"about_ca_topic_score_gemma":0.0000023552686,"teacher_disagreement_score":0.8065407,"about_ca_system_score_codex":0.00013627185,"about_ca_system_score_gemma":0.00002576508,"threshold_uncertainty_score":0.5620639},"labels":[],"label_agreement":null},{"id":"W4416331727","doi":"10.1080/29979676.2025.2569894","title":"Statistics, Data Science, and the Connectome","year":2025,"lang":"en","type":"article","venue":"Statistics and data science in imaging.","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Connectome; Human Connectome Project; Neuroimaging; Functional connectivity; Connectomics; Cognition; Power graph analysis; Causal model; Functional neuroimaging; Graph theory","score_opus":0.03236640182886594,"score_gpt":0.37298327065499887,"score_spread":0.34061686882613296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416331727","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000073943476,0.00022533261,0.9889584,0.0034206398,0.00045466298,0.0001543581,0.004604042,0.00002771416,0.002080877],"genre_scores_gemma":[0.35413668,0.002075493,0.63344353,0.008854917,0.00005472849,0.000007299588,0.0010869115,0.000013159433,0.00032729947],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974415,0.000050311544,0.00031300294,0.001084036,0.00071807916,0.0003931228],"domain_scores_gemma":[0.99619746,0.00056615024,0.00009392774,0.002656047,0.0003590478,0.0001273393],"candidate_categories":["sts","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.005896952,0.00012368824,0.00017008332,0.00045392066,0.0006976963,0.0024250865,0.0067477827,0.0000110002875,0.000006480149],"category_scores_gemma":[0.005677944,0.00008982224,0.000002579423,0.0025870227,0.0065369303,0.0037862386,0.009043125,0.00012895126,0.0000047779813],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000023882228,0.000015726386,0.0019045379,0.000013116347,0.0000015412576,0.000007470994,0.0001088408,0.0000015455519,0.000017193131,0.9339763,0.022568254,0.041383114],"study_design_scores_gemma":[0.0005554679,0.0000053430704,0.0052896943,0.000023632203,0.000009376932,0.00000818474,0.00012297778,0.9305886,0.0000067327214,0.02689914,0.036369115,0.00012171868],"about_ca_topic_score_codex":0.00026753437,"about_ca_topic_score_gemma":0.00012756637,"teacher_disagreement_score":0.93058705,"about_ca_system_score_codex":0.000026278663,"about_ca_system_score_gemma":0.0012603559,"threshold_uncertainty_score":0.9989715},"labels":[],"label_agreement":null},{"id":"W4416366455","doi":"10.1109/tvcg.2025.3634830","title":"Deconstructing Implicit Beliefs in Visual Data Journalism: Unstable Meanings Behind Data as Truth &amp; Design for Insight","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Deconstruction (building); Storytelling; Sociotechnical system; Data visualization; Visual research; Meaning (existential); Visualization; Cognitive reframing; Sensemaking; Strict constructionism","score_opus":0.0701763343402511,"score_gpt":0.3575251183793133,"score_spread":0.28734878403906217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416366455","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008621338,0.000087332395,0.9972562,0.0001845886,0.0008682604,0.00040405686,0.000116058975,0.00016549803,0.000055874763],"genre_scores_gemma":[0.8645997,0.0024065503,0.11915718,0.0107520465,0.00032343052,0.000073978554,0.0019980255,0.0001337913,0.0005553206],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99727863,0.0002250593,0.00072980765,0.0010497641,0.00034542414,0.00037128644],"domain_scores_gemma":[0.9975117,0.00054314017,0.00021683746,0.0013534868,0.00022463997,0.00015018844],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010110536,0.00030518847,0.0003594073,0.001035093,0.00058280665,0.0008846972,0.0017952356,0.00016642435,0.000012596235],"category_scores_gemma":[0.0000525554,0.00032087576,0.000054812208,0.0015768089,0.000094242176,0.0018988944,0.000107791915,0.00026628515,0.0000047002313],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006055483,0.00063774333,0.00024534905,0.00014788483,0.00020721862,0.000006047979,0.0015320941,0.0037006084,0.00004186236,0.9548858,0.003065795,0.035469078],"study_design_scores_gemma":[0.0012438063,0.00010875764,0.000056173023,0.00018295243,0.00005417995,0.000027786658,0.000060333008,0.9855806,0.0004262361,0.0033003946,0.008632491,0.0003262453],"about_ca_topic_score_codex":0.00006056694,"about_ca_topic_score_gemma":0.00019568265,"teacher_disagreement_score":0.98188,"about_ca_system_score_codex":0.00004073302,"about_ca_system_score_gemma":0.0002748156,"threshold_uncertainty_score":0.9999243},"labels":[],"label_agreement":null},{"id":"W4416524826","doi":"10.1016/b978-0-323-90509-1.00051-5","title":"Principles of persuasive data presentation","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Presentation (obstetrics); Cognition; Cognitive load; Data visualization; Data presentation; Persuasive communication; Visualization","score_opus":0.06463392772313398,"score_gpt":0.3265104742471766,"score_spread":0.26187654652404263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416524826","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[2.1247867e-7,0.00024787744,0.016485205,0.000094150884,0.00023557473,0.0002217653,0.00026297377,0.00005513019,0.98239714],"genre_scores_gemma":[0.000027551596,0.00013008369,0.0059876065,0.00021357389,0.00006718546,0.000002750698,0.0005267546,0.000013399613,0.9930311],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985699,0.000023356088,0.0004269847,0.0005016235,0.00035818067,0.00011997212],"domain_scores_gemma":[0.99744654,0.00006936749,0.00034881,0.0019029134,0.00017940374,0.000052973108],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020018916,0.00019185692,0.00029332435,0.00019160577,0.000050534098,0.000088107314,0.0021443113,0.000121107776,0.000047611993],"category_scores_gemma":[0.00006370147,0.00018599507,0.000074626405,0.00002991487,0.00007692511,0.00019128955,0.001652826,0.00013864641,0.000035059962],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.201319e-7,0.000004907906,0.0000021609496,0.000078877056,0.000047673653,0.0000033706958,0.00010017443,0.0000015060613,0.0000026530736,0.46676174,0.001036495,0.53195953],"study_design_scores_gemma":[0.0001159376,0.000017276094,0.000005913419,0.00028471142,0.000057604702,0.0000016728043,0.0000069129424,0.007617943,0.000053809636,0.003420345,0.98824924,0.0001686267],"about_ca_topic_score_codex":5.767386e-7,"about_ca_topic_score_gemma":0.000011667057,"teacher_disagreement_score":0.9872128,"about_ca_system_score_codex":0.000024358129,"about_ca_system_score_gemma":0.0002798095,"threshold_uncertainty_score":0.7584659},"labels":[],"label_agreement":null},{"id":"W4416621715","doi":"10.1145/3756884.3765974","title":"Animated Transitions for Abstract and Concrete Immersive Visualizations: A Design Space and Experiment","year":2025,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada; Agence Nationale de la Recherche","keywords":"Space (punctuation); Transition (genetics); Complement (music); Virtual reality; Animation; Visualization; Virtual space; Variety (cybernetics)","score_opus":0.03293086159609325,"score_gpt":0.3424402106147067,"score_spread":0.30950934901861343,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416621715","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004196446,0.00019864285,0.9964376,0.0016790244,0.00003139033,0.00026540385,0.000014499986,0.000055541226,0.00089824555],"genre_scores_gemma":[0.74730563,0.0003430018,0.24716221,0.003180278,0.000015762345,0.000084725645,0.000076875214,0.000012444529,0.0018190956],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99949694,0.000018918578,0.00012515594,0.00020382229,0.000054756896,0.00010038261],"domain_scores_gemma":[0.99962634,0.00009989515,0.000027999042,0.000118257194,0.00007809875,0.000049406648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010523548,0.000073939984,0.00008956823,0.00009098402,0.00016219512,0.00018219132,0.00009759785,0.000028171837,0.000014948273],"category_scores_gemma":[0.00002745423,0.00006930721,0.0000154897,0.00022280088,0.000039481652,0.0002598919,0.00003875841,0.000018034034,0.0000013973712],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000059829777,0.000012264767,0.0000114407385,0.000024157634,0.000028120485,7.9617564e-7,0.0008824458,0.000022886692,0.010300658,0.98307234,0.0052726357,0.0003662426],"study_design_scores_gemma":[0.0013640921,0.00014788927,0.0002541651,0.00006898342,0.0000422099,0.000005127915,0.0015936081,0.9246724,0.05618254,0.0055516674,0.009852691,0.0002646068],"about_ca_topic_score_codex":0.000007851617,"about_ca_topic_score_gemma":0.0000012085989,"teacher_disagreement_score":0.9775207,"about_ca_system_score_codex":0.000010290836,"about_ca_system_score_gemma":0.000044205637,"threshold_uncertainty_score":0.2826266},"labels":[],"label_agreement":null},{"id":"W4416690870","doi":"10.1109/tvcg.2025.3634790","title":"A Design Space for Multiscale Visualization","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Visualization; Dimension (graph theory); Space (punctuation); Data visualization; Code (set theory); Scale (ratio); Power (physics); Generative Design; Generative grammar","score_opus":0.027971482482008553,"score_gpt":0.31382832604057764,"score_spread":0.2858568435585691,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416690870","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00010070905,0.00003994726,0.9978301,0.00019799628,0.00080387184,0.0005610951,0.00001649146,0.00039938773,0.000050402858],"genre_scores_gemma":[0.880746,0.0012832016,0.099054635,0.015034983,0.00017821156,0.00036647034,0.0001542319,0.00010803765,0.003074224],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984232,0.0001566106,0.0003819321,0.00055090705,0.0002378901,0.00024944445],"domain_scores_gemma":[0.9988513,0.00025184112,0.000109855406,0.0003884653,0.00029035952,0.00010820805],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00031271478,0.00024152924,0.00023015085,0.0006907296,0.00049479544,0.0004154085,0.00036166268,0.00014255905,0.0000067510896],"category_scores_gemma":[0.000009526469,0.00025106527,0.00009802864,0.0015116099,0.00007328575,0.00048819152,0.000008792043,0.00009503003,0.0000056891895],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021219626,0.00026684764,0.000016546826,0.00006126074,0.000054605942,6.715055e-7,0.00034943558,0.0029636794,0.000031535965,0.9858088,0.0022301313,0.00819528],"study_design_scores_gemma":[0.0009775409,0.0001946973,0.000041441403,0.00007401223,0.000039508035,0.0000030358196,0.000020726631,0.98362887,0.0045027,0.003125806,0.007138718,0.0002529161],"about_ca_topic_score_codex":0.0000061360142,"about_ca_topic_score_gemma":0.0000081978915,"teacher_disagreement_score":0.982683,"about_ca_system_score_codex":0.000031030926,"about_ca_system_score_gemma":0.00008443199,"threshold_uncertainty_score":0.99999416},"labels":[],"label_agreement":null},{"id":"W4416798313","doi":"10.1109/tvcg.2025.3634631","title":"Running with Data: A Survey of the Current Research and a Design Exploration of Future Immersive Visualisations","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Visualization; Augmented reality; Set (abstract data type); Space (punctuation); Smartwatch; Data visualization; Phone; Data exploration","score_opus":0.17340110688938687,"score_gpt":0.3975103900507273,"score_spread":0.22410928316134043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416798313","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017016287,0.00012457397,0.9973149,0.0001458872,0.00030954997,0.00031100193,0.000063551655,0.000022173248,0.0000067582596],"genre_scores_gemma":[0.9969037,0.0009752001,0.0018189609,0.00016641499,0.00001948459,0.000014003411,0.00006777115,0.000010142473,0.000024279221],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983047,0.00046650486,0.0003348775,0.00036923235,0.0003947122,0.00012995925],"domain_scores_gemma":[0.99815273,0.00030535532,0.00015192476,0.00060644693,0.0007358931,0.0000476542],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091033435,0.00012659463,0.00017838537,0.00052362157,0.00036779532,0.0001328528,0.0005140859,0.000054802902,0.0000012310833],"category_scores_gemma":[0.000012609766,0.000096479496,0.000022261818,0.0029392284,0.00025216784,0.0007362755,0.000036540718,0.00018869525,2.1322735e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006264818,0.00058892387,0.0011967509,0.00017197173,0.00012151033,3.6018338e-7,0.0028302602,0.0023126402,0.000028643239,0.9754485,0.0007855962,0.01645219],"study_design_scores_gemma":[0.0004992525,0.00022910237,0.0040515764,0.00022255059,0.000031460757,0.0000014234153,0.0001757014,0.991709,0.0015230868,0.0009484435,0.00049127196,0.00011711414],"about_ca_topic_score_codex":0.00006152381,"about_ca_topic_score_gemma":0.00014919558,"teacher_disagreement_score":0.9954959,"about_ca_system_score_codex":0.000012194271,"about_ca_system_score_gemma":0.00019048453,"threshold_uncertainty_score":0.39343196},"labels":[],"label_agreement":null},{"id":"W4417002795","doi":"10.1109/tvcg.2025.3633883","title":"“It Looks Sexy but it's Wrong.” Tensions in Creativity and Accuracy using genAI for Biomedical Visualization","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Trond Mohn stiftelse","keywords":"Visualization; Workflow; Creativity; Pipeline (software); Scientific visualization; Data visualization; Information visualization; Creative visualization; Embodied cognition","score_opus":0.04428523211648161,"score_gpt":0.3552425932021934,"score_spread":0.3109573610857118,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417002795","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007881455,0.000042808224,0.9903583,0.0005275217,0.00049796986,0.00045580597,0.000047428573,0.00015506397,0.00003363631],"genre_scores_gemma":[0.97983265,0.00097058504,0.008799964,0.009835439,0.000079418794,0.00004824697,0.00012009386,0.000040760195,0.0002728515],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99799544,0.00018245316,0.00056992914,0.0006534202,0.0003010609,0.000297729],"domain_scores_gemma":[0.9986933,0.00040099333,0.00014186684,0.0003521916,0.00025241944,0.00015924353],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004052998,0.0002776793,0.00031741412,0.0010960826,0.00049390737,0.000398634,0.0002765878,0.0002076932,0.000010944506],"category_scores_gemma":[0.000037781672,0.00028408025,0.000083563486,0.0016495079,0.00017497681,0.00064992247,0.00002359511,0.00016387695,0.0000017851345],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000068831316,0.001533176,0.0009653221,0.00047706746,0.00017759569,0.000010166401,0.002962893,0.0020510813,0.00030929223,0.9658017,0.0035411096,0.02210173],"study_design_scores_gemma":[0.001171757,0.00014287773,0.00034638192,0.00022043516,0.00005396204,0.000010924966,0.00013080411,0.991949,0.000616993,0.0012417863,0.0038300562,0.0002850126],"about_ca_topic_score_codex":0.0000372779,"about_ca_topic_score_gemma":0.00009233327,"teacher_disagreement_score":0.9898979,"about_ca_system_score_codex":0.000049300736,"about_ca_system_score_gemma":0.00015952848,"threshold_uncertainty_score":0.99996114},"labels":[],"label_agreement":null},{"id":"W4417248863","doi":"10.1109/tvcg.2025.3634777","title":"Correcting Misperceptions at a Glance: Using Data Visualizations to Reduce Political Sectarianism","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"National Science Foundation","keywords":"Sectarianism; Politics; Psychological intervention; Motivated reasoning; Survey data collection; Control (management); Political violence; Range (aeronautics)","score_opus":0.05880523301195154,"score_gpt":0.3684059441336142,"score_spread":0.30960071112166265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417248863","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006253882,0.000017628314,0.99107623,0.00036148058,0.0013248139,0.00031843092,0.00010855603,0.0003836202,0.00015534768],"genre_scores_gemma":[0.9727169,0.00007280993,0.015143018,0.011013904,0.00014277668,0.000022052616,0.00019845674,0.0000415972,0.00064842874],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975808,0.0001937659,0.0005246697,0.00090629415,0.00036102012,0.00043340723],"domain_scores_gemma":[0.9981193,0.00013671668,0.00009416112,0.0010813393,0.00026787337,0.00030059146],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002928201,0.00028799855,0.0002781145,0.00086559734,0.001061327,0.00051645446,0.00087679655,0.00015181299,0.00003360185],"category_scores_gemma":[0.000024907267,0.00031873753,0.00007385618,0.0026331432,0.00010104684,0.0006373737,0.00009332369,0.00019061196,0.000020427731],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000133047515,0.000319206,0.00012655012,0.000044768953,0.00007400537,0.000003247271,0.0006114518,0.0022442976,0.00013652159,0.99032193,0.0018589932,0.0042457194],"study_design_scores_gemma":[0.00046881175,0.000076867975,0.00023157647,0.00013046277,0.00006250478,0.00004472169,0.00009017635,0.9936743,0.0010024152,0.0007089725,0.0031828696,0.0003263462],"about_ca_topic_score_codex":0.000084859224,"about_ca_topic_score_gemma":0.00012231161,"teacher_disagreement_score":0.99143,"about_ca_system_score_codex":0.00013075028,"about_ca_system_score_gemma":0.00017686846,"threshold_uncertainty_score":0.99992645},"labels":[],"label_agreement":null},{"id":"W4417317278","doi":"10.5194/ica-abs-10-192-2025","title":"Creating Geospatial Data Visualization and Exploration Tools for Simulated and Modeled Datasets","year":2025,"lang":"en","type":"article","venue":"Abstracts of the ICA","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; Kelowna General Hospital","funders":"","keywords":"Geospatial analysis; Visualization; Data visualization; Geovisualization; Geographic information system; Data exploration","score_opus":0.06386447566676638,"score_gpt":0.3555502358206232,"score_spread":0.2916857601538568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417317278","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03172078,0.000045709257,0.96648204,0.0007189342,0.000089599576,0.00029516505,0.00046091792,0.000035466754,0.00015140139],"genre_scores_gemma":[0.9941155,0.00003571329,0.004469812,0.000224442,0.000012516497,0.0000015706361,0.0010947295,0.0000032955843,0.00004242358],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993731,0.000024669918,0.00022233724,0.00020665328,0.00010010543,0.00007313323],"domain_scores_gemma":[0.9989989,0.0002206113,0.00013481958,0.0005594662,0.000064366846,0.000021860433],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002441753,0.000060496568,0.000088424706,0.000038925562,0.00012425269,0.00022715636,0.00048869697,0.0000317328,8.808361e-7],"category_scores_gemma":[0.00067715935,0.000047386653,0.000008961658,0.00015586561,0.000027745153,0.0014968795,0.0004866846,0.000027227497,2.7463565e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013873223,0.00063376484,0.0012099941,0.00081182725,0.00030727236,0.0000024338574,0.0026665987,0.09500614,0.008745796,0.63864267,0.02875748,0.22307727],"study_design_scores_gemma":[0.00029761664,0.000014144497,0.0010889393,0.000047214526,0.000021557167,3.2571717e-7,0.000032995806,0.9920187,0.0018715872,0.0024974782,0.0020569388,0.000052511186],"about_ca_topic_score_codex":0.000040387076,"about_ca_topic_score_gemma":0.00002780103,"teacher_disagreement_score":0.9623947,"about_ca_system_score_codex":0.0000046303962,"about_ca_system_score_gemma":0.000039237177,"threshold_uncertainty_score":0.2190474},"labels":[],"label_agreement":null},{"id":"W44614705","doi":"10.1007/978-3-642-59789-3_24","title":"Estimating Trees From Incomplete Distance Matrices: A Comparison of Two Methods","year":2000,"lang":"en","type":"book-chapter","venue":"Studies in classification, data analysis, and knowledge organization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Path (computing); Distance matrices in phylogeny; Algorithm; Mathematics; Tree (set theory); Combinatorics; Computer science; Topology (electrical circuits)","score_opus":0.17093780995420788,"score_gpt":0.45570590503897723,"score_spread":0.28476809508476936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W44614705","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00002203099,0.009795281,0.9816335,0.000079880236,0.00020660936,0.00015941498,0.00073592016,0.000085891224,0.007281514],"genre_scores_gemma":[0.09074197,0.035532754,0.81637895,0.000101246296,0.0006657182,0.00001617289,0.042886723,0.00015362613,0.013522839],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9968378,0.00020322212,0.0013532332,0.0011209667,0.0003098483,0.00017491738],"domain_scores_gemma":[0.9956508,0.00053890754,0.0010643022,0.0019439133,0.0007330839,0.000068963505],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007162126,0.00037108533,0.0011348813,0.0008112105,0.0002493154,0.00017115909,0.001486184,0.0001485973,0.00008292391],"category_scores_gemma":[0.0005150516,0.00036364608,0.000060618524,0.0023492977,0.00030733144,0.0005974586,0.0009664741,0.00018993493,0.000020431824],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010607321,0.00041185273,0.061788004,0.00053939223,0.004948125,0.0000032607174,0.012957416,0.0007217086,0.000087281915,0.75636786,0.008026379,0.1541381],"study_design_scores_gemma":[0.00038766966,0.000020077916,0.003875439,0.00038153742,0.0021065057,6.9643545e-7,0.00029382843,0.93853325,0.000034548586,0.021453263,0.03232191,0.0005912768],"about_ca_topic_score_codex":0.00009641857,"about_ca_topic_score_gemma":0.0029285776,"teacher_disagreement_score":0.93781155,"about_ca_system_score_codex":0.00011065722,"about_ca_system_score_gemma":0.00014347036,"threshold_uncertainty_score":0.99988157},"labels":[],"label_agreement":null},{"id":"W46738011","doi":"10.1007/978-94-6091-924-4_7","title":"Visualizations and Visualization in Science Education","year":2012,"lang":"en","type":"book-chapter","venue":"SensePublishers eBooks","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Visualization; Science education; Computer science; Data science; Information visualization; Engineering ethics; Human–computer interaction; Mathematics education; Psychology; Engineering; Artificial intelligence","score_opus":0.021988214043860452,"score_gpt":0.2959055282114957,"score_spread":0.2739173141676352,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W46738011","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00004696473,0.0003881526,0.045351617,0.00016326379,0.0009109682,0.00038643295,0.000011410985,0.0002341177,0.9525071],"genre_scores_gemma":[0.02883152,0.00022721743,0.0057554445,0.0031702893,0.00046562633,0.000020363079,0.00040106068,0.00014615903,0.9609823],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977836,0.00003486901,0.00047925106,0.00069394644,0.0006275474,0.00038077048],"domain_scores_gemma":[0.9982214,0.000043621134,0.00029310794,0.00072577293,0.0004384656,0.00027764475],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0006635677,0.000313789,0.000276639,0.0014698853,0.00022801915,0.0013676406,0.0007389607,0.00023629518,0.000043700762],"category_scores_gemma":[0.00012711008,0.00034158668,0.00004757491,0.000305474,0.0003949274,0.0018692459,0.00044787585,0.00021975682,0.00003634182],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.630884e-7,0.0000253131,0.000052283118,0.000027033926,0.0000062853933,0.0000014429828,0.00064302824,0.0000016592903,0.000035259396,0.9605369,0.002856493,0.035813563],"study_design_scores_gemma":[0.000415002,0.00005643799,0.00028564653,0.00036029148,0.00004958618,0.00004924012,0.00013661546,0.015908116,0.0001706177,0.060001902,0.92144346,0.0011230696],"about_ca_topic_score_codex":0.000025152085,"about_ca_topic_score_gemma":0.000052085536,"teacher_disagreement_score":0.91858697,"about_ca_system_score_codex":0.00019646484,"about_ca_system_score_gemma":0.001517083,"threshold_uncertainty_score":0.9999036},"labels":[],"label_agreement":null},{"id":"W47667084","doi":"10.3233/978-1-61499-101-4-544","title":"Ophiucus: RDF-based Visualization Tool for Health Simulation Models","year":2012,"lang":"en","type":"article","venue":"Studies in health technology and informatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"RDF; Computer science; Visualization; Data mining; Information retrieval; Semantic Web","score_opus":0.10085178589726547,"score_gpt":0.4455976848960257,"score_spread":0.34474589899876024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W47667084","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014803674,0.0018097137,0.9920094,0.0037427898,0.00024019138,0.00047639132,0.000011751166,0.0001940385,0.0000353402],"genre_scores_gemma":[0.8975762,0.0017117024,0.09226514,0.008282793,0.000030220539,0.000065391076,0.00004234333,0.0000086036935,0.000017613389],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985424,0.000038398786,0.0007910563,0.000102605656,0.00012287998,0.00040262518],"domain_scores_gemma":[0.99904233,0.0001559018,0.0003611556,0.00025925678,0.00012360026,0.000057735368],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011145588,0.00011917012,0.00027959837,0.00054866716,0.00031187176,0.000025090152,0.00020752162,0.00009641585,5.055057e-7],"category_scores_gemma":[0.00029482914,0.00010967272,0.000018142207,0.00085151714,0.00011039215,0.0010233335,0.00015281502,0.000094893556,0.0000022195834],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000057068332,0.00007919053,0.0025706626,0.0012627005,0.000015580228,5.9663655e-8,0.006307108,0.02779025,1.07723e-7,0.9302332,0.0012948354,0.030440593],"study_design_scores_gemma":[0.00044284906,0.000167031,0.0001098366,0.000114773284,0.0000017341134,0.0000012132249,0.0010040269,0.97609967,0.000008213403,0.011455687,0.010485913,0.00010906259],"about_ca_topic_score_codex":0.0000022599736,"about_ca_topic_score_gemma":0.0000038218395,"teacher_disagreement_score":0.9483094,"about_ca_system_score_codex":0.00012487294,"about_ca_system_score_gemma":0.00012459724,"threshold_uncertainty_score":0.44723237},"labels":[],"label_agreement":null},{"id":"W50490165","doi":"10.1007/978-3-642-21669-5_6","title":"A Classification Scheme for Characterizing Visual Mining","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Scheme (mathematics); Coding (social sciences); Visualization; Process (computing); Representation (politics); Data mining; Data visualization; Classification scheme; Artificial intelligence; Information retrieval; Machine learning","score_opus":0.06090087405889728,"score_gpt":0.31257347746646036,"score_spread":0.2516726034075631,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W50490165","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006315532,0.000063519554,0.9964395,0.0003929811,0.0010169935,0.00031552123,0.00001030954,0.00015370028,0.0015442831],"genre_scores_gemma":[0.055290315,0.00005545284,0.93910444,0.0035743744,0.0007584765,0.00002703863,0.00009275018,0.00006243908,0.0010347045],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99725175,0.000017028642,0.000502954,0.001213238,0.0005307947,0.0004842272],"domain_scores_gemma":[0.9980929,0.0002213919,0.00038865578,0.0008562919,0.0002978769,0.00014291324],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007177134,0.00036746947,0.0003735095,0.00070663326,0.00024427762,0.0006053395,0.0022399337,0.0002377531,0.000019527874],"category_scores_gemma":[0.00012567315,0.0003593077,0.0001111487,0.00044833095,0.0002892985,0.0008282791,0.00069844146,0.0002759942,0.000034684497],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008553985,0.00006433939,0.00013388465,0.00009012702,0.000019393281,0.000013915557,0.0012960973,0.00012866515,0.0018289759,0.20922911,0.00010657495,0.78708035],"study_design_scores_gemma":[0.00023052425,0.0001421389,0.0001880634,0.00029520117,0.0000083321465,0.000015429265,3.0510597e-7,0.9593158,0.0012727308,0.027809901,0.010152689,0.0005688878],"about_ca_topic_score_codex":0.0000028773275,"about_ca_topic_score_gemma":0.000008902023,"teacher_disagreement_score":0.95918715,"about_ca_system_score_codex":0.00014541355,"about_ca_system_score_gemma":0.0003970661,"threshold_uncertainty_score":0.9998859},"labels":[],"label_agreement":null},{"id":"W52376542","doi":"10.1007/978-3-642-19641-6_4","title":"The Personal Equation of Complex Individual Cognition during Visual Interface Interaction","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Cognition; Human–computer interaction; Interface (matter); Cognitive science; User interface; Psychology; Programming language","score_opus":0.06616030832857735,"score_gpt":0.3167468442517306,"score_spread":0.2505865359231533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W52376542","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00039256795,0.00008007145,0.99669063,0.00018125921,0.0010202364,0.00020003437,0.000014057593,0.0000633396,0.0013577892],"genre_scores_gemma":[0.9783801,0.00007010605,0.020690057,0.0002884454,0.00024418216,0.0000035041633,0.00005585082,0.000022689206,0.0002451042],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99748015,0.00005421145,0.0005544563,0.00069269387,0.00088933774,0.0003291397],"domain_scores_gemma":[0.9982282,0.00033943664,0.000527435,0.00046791017,0.00035588088,0.00008113671],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072846207,0.00029533906,0.0002767679,0.00049980124,0.00031893258,0.00049089704,0.0017591945,0.00014775057,0.000054784727],"category_scores_gemma":[0.00011256612,0.00023995657,0.00009665269,0.00042690925,0.00049409055,0.00078359345,0.0009937529,0.00043864507,0.000036386544],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054483855,0.0001553972,0.00008818965,0.00013240305,0.00009482895,0.000018146446,0.006904719,0.005294956,0.0018505853,0.0518689,0.00009654139,0.93344086],"study_design_scores_gemma":[0.00036725926,0.0002442479,0.00056162913,0.00044680727,0.000027064432,0.000038234022,0.0000038343615,0.95504445,0.007203248,0.03451038,0.0010705492,0.0004823112],"about_ca_topic_score_codex":0.000012179949,"about_ca_topic_score_gemma":0.00005293669,"teacher_disagreement_score":0.97798747,"about_ca_system_score_codex":0.00013102141,"about_ca_system_score_gemma":0.00021146411,"threshold_uncertainty_score":0.9785145},"labels":[],"label_agreement":null},{"id":"W5315797","doi":"10.1007/978-1-4614-7485-2_27","title":"Common Visualizations: Their Cognitive Utility","year":2013,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Cognition; Visualization; Visual analytics; Computer science; Perception; Diagrammatic reasoning; Information visualization; Data visualization; Data science; Human–computer interaction; Informatics; Cognitive science; Psychology; Artificial intelligence; Engineering","score_opus":0.05450103897936317,"score_gpt":0.3147408310737675,"score_spread":0.26023979209440434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W5315797","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[6.368232e-7,0.00007829461,0.44522247,0.00010125031,0.000108387954,0.00016228044,0.00006994539,0.00020760133,0.55404913],"genre_scores_gemma":[0.004786145,0.00030705135,0.0016316341,0.0032622563,0.00009154727,0.000009975961,0.00085077697,0.000039340463,0.9890213],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986063,0.00003224894,0.00038779096,0.0004973161,0.0002917195,0.00018460979],"domain_scores_gemma":[0.99848384,0.00014601252,0.000206494,0.0006851847,0.00034991463,0.00012852815],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00014386681,0.00030215384,0.0003282768,0.000159004,0.00012559505,0.00035650577,0.00083222275,0.00020941797,0.0046342732],"category_scores_gemma":[0.000034642257,0.00024880332,0.00011924282,0.000087022105,0.000102732,0.0004609947,0.0004936125,0.00017896645,0.0025602197],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.804978e-7,0.000024780724,0.000010518506,0.000013237678,0.000039418483,0.000002104983,0.00007028149,2.7461425e-7,3.0526144e-7,0.94878834,0.02854178,0.022508465],"study_design_scores_gemma":[0.0002314999,0.000053770764,0.000052737007,0.00019267637,0.00003631962,0.000006941349,0.00003485372,0.10548602,0.00007557299,0.1451193,0.7480858,0.00062450906],"about_ca_topic_score_codex":0.000015920938,"about_ca_topic_score_gemma":0.00002332564,"teacher_disagreement_score":0.80366904,"about_ca_system_score_codex":0.00002431933,"about_ca_system_score_gemma":0.00009262325,"threshold_uncertainty_score":0.9999964},"labels":[],"label_agreement":null},{"id":"W63994157","doi":"10.4018/978-1-60566-010-3.ch316","title":"Visualization Techniques for Confidence Based Data","year":2009,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of Guelph; Mount Allison University","funders":"","keywords":"Computer science; Visualization; Decision support system; Context (archaeology); Data visualization; Certainty; Data mining; Interfacing; Visual analytics; Artificial intelligence; Data science; Human–computer interaction; Machine learning; Mathematics","score_opus":0.05643472030203352,"score_gpt":0.3444561206472951,"score_spread":0.2880214003452616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W63994157","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[1.469005e-8,0.000049898088,0.61024106,0.00009337142,0.00010695667,0.00030479088,0.00053271966,0.000340213,0.388331],"genre_scores_gemma":[0.006170468,0.000102180165,0.5449669,0.041694883,0.001779541,0.00009051943,0.005474568,0.0002567575,0.3994642],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99807173,0.000018002811,0.0004277353,0.00080722204,0.0004304799,0.00024484246],"domain_scores_gemma":[0.9973204,0.00004861043,0.00031961835,0.0019034311,0.00028588923,0.00012205626],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00027170454,0.00032585292,0.00033291406,0.00010279053,0.000110117064,0.00040843547,0.002546448,0.00028007347,0.000013133225],"category_scores_gemma":[0.00006995447,0.0003376847,0.00009438525,0.000044702447,0.000060315084,0.00027625618,0.00043332754,0.00009199238,0.00003831855],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000039651645,0.000009490055,5.5135433e-7,0.000027831024,0.000013248601,0.0000059464105,0.0000039761903,0.0000015828823,0.0000053964395,0.942219,0.02442962,0.033279363],"study_design_scores_gemma":[0.00017384307,0.000106274085,8.014088e-7,0.00021946199,0.000042564756,0.000006428406,6.529971e-7,0.06763446,0.00023206326,0.38644007,0.54473823,0.0004051778],"about_ca_topic_score_codex":0.000010500203,"about_ca_topic_score_gemma":0.000023658753,"teacher_disagreement_score":0.555779,"about_ca_system_score_codex":0.000096410404,"about_ca_system_score_gemma":0.0003875044,"threshold_uncertainty_score":0.9999075},"labels":[],"label_agreement":null},{"id":"W645846989","doi":"","title":"A Review of Colour and Cartography in Avalanche Danger Visualization","year":2004,"lang":"en","type":"review","venue":"Proceedings of the 2004 International Snow Science Workshop, Jackson Hole, Wyoming","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visualization; Scale (ratio); Hazard; Representation (politics); Cartography; Set (abstract data type); Natural hazard; Information visualization; Geographic information system; Computer science; Data science; Geography; Data mining; Meteorology; Political science","score_opus":0.029962071943813978,"score_gpt":0.3532013886669687,"score_spread":0.32323931672315476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W645846989","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00004702163,0.99393994,0.003107226,0.00038083544,0.0005585192,0.0007230947,0.000024190951,0.000036444777,0.0011827518],"genre_scores_gemma":[0.00045178732,0.9964026,0.0026196851,0.00025977514,0.000053058477,0.000032559856,0.000012595352,0.000019936233,0.00014796658],"study_design_codex":"design_other","study_design_gemma":"systematic_review","domain_scores_codex":[0.99670905,0.000026875234,0.0011029609,0.0007148286,0.0011151384,0.00033117444],"domain_scores_gemma":[0.9971511,0.00011389984,0.0014971487,0.00030871676,0.000827492,0.00010163869],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0020004555,0.00033177563,0.0008881595,0.00097421097,0.00012953645,0.00027054612,0.003511672,0.00013997604,0.00001162411],"category_scores_gemma":[0.0011592973,0.0002490406,0.0002815598,0.004900856,0.0005110772,0.0011990804,0.0010811151,0.00030241354,0.0000030084545],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000085005595,0.00047896878,0.0008403874,0.08660858,0.00019746814,0.000003100829,0.001548748,0.00008632307,0.00011667369,0.22079323,0.0036057725,0.6857123],"study_design_scores_gemma":[0.00055645197,0.000055096676,0.0001098573,0.60023874,0.00030493314,0.00006674889,0.00017866404,0.006760192,0.00028777748,0.0013063219,0.38928708,0.0008481234],"about_ca_topic_score_codex":0.000021841934,"about_ca_topic_score_gemma":0.0000044225785,"teacher_disagreement_score":0.6848641,"about_ca_system_score_codex":0.0002857768,"about_ca_system_score_gemma":0.00049432536,"threshold_uncertainty_score":0.9999962},"labels":[],"label_agreement":null},{"id":"W6884889869","doi":"10.13140/2.1.3980.0962","title":"Visualization Studio: Two Years of Experience at the University of Calgary","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Visualization; Data visualization; Information visualization","score_opus":0.018494502919329484,"score_gpt":0.28854805067330747,"score_spread":0.270053547753978,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6884889869","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.077142686,0.000007854525,0.92010194,0.000039647864,0.00003957983,0.00003116246,9.220784e-7,0.000019146953,0.0026170516],"genre_scores_gemma":[0.996721,0.000015566775,0.0017946877,0.00012778,0.0000042041515,7.310441e-8,0.0000042044485,0.0000015400108,0.0013309246],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99957615,0.00004984322,0.000081100094,0.00009543314,0.00014760233,0.000049850154],"domain_scores_gemma":[0.99954563,0.000042714186,0.00006606149,0.00026875077,0.000057358586,0.000019455536],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013342137,0.000028865798,0.000060795766,0.000024038223,0.000044879063,0.000007530383,0.00040402779,0.000010334017,0.00007715635],"category_scores_gemma":[0.000028607139,0.000023554629,0.000020092884,0.00024920198,0.00007993068,0.00012602683,0.0002598045,0.0000119089045,0.000014190183],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000055706496,0.00010230617,0.012675523,0.000014255501,0.00001772262,0.0000012613672,0.010192986,0.00027491478,0.002229941,0.9450504,0.005512288,0.023922794],"study_design_scores_gemma":[0.0005601104,0.000078471974,0.02138732,0.00001737583,0.000011146853,0.0000016528882,0.00067698077,0.91908354,0.009845666,0.00042080853,0.04778076,0.00013615473],"about_ca_topic_score_codex":0.000091972535,"about_ca_topic_score_gemma":0.000060375576,"teacher_disagreement_score":0.9446296,"about_ca_system_score_codex":0.000009020283,"about_ca_system_score_gemma":0.000012993862,"threshold_uncertainty_score":0.09605299},"labels":[],"label_agreement":null},{"id":"W6887707991","doi":"10.17605/osf.io/a3gtd","title":"Visualizing demographic evolution using geographically inconsistent census data","year":2018,"lang":"en","type":"article","venue":"Open Science Framework","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Census; Demographic analysis; Consistency (knowledge bases); Analytics; Population statistics; Visualization; American Community Survey","score_opus":0.10951430580210458,"score_gpt":0.4156047375414365,"score_spread":0.3060904317393319,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6887707991","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015566256,0.000058121987,0.9809741,0.0007114698,0.00092248316,0.00024754708,0.000028280368,0.000121500394,0.0013702457],"genre_scores_gemma":[0.65630484,0.000012531217,0.3423509,0.001156193,0.00012964869,0.0000021591077,0.000015636662,0.000008418456,0.00001966079],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9966754,0.00011130011,0.00039953762,0.0012421802,0.00096040644,0.0006111986],"domain_scores_gemma":[0.9953845,0.00010937495,0.00022521055,0.0034451184,0.0005177241,0.00031804317],"candidate_categories":["sts","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0031088903,0.00017899647,0.0002095808,0.00049755146,0.0014349611,0.0032262837,0.01486924,0.00010641143,0.00003149989],"category_scores_gemma":[0.001238991,0.0001643155,0.000042268013,0.007775451,0.0014587392,0.0043701148,0.010191075,0.0002216242,0.000058032736],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000057914717,0.00014409603,0.019969031,0.0000072831585,0.000017295151,0.00000877314,0.00021973262,0.000037863723,0.001545218,0.9659579,0.0008648202,0.011222207],"study_design_scores_gemma":[0.00022037573,0.00012230975,0.0102370335,0.00026067096,0.000025536216,0.000037325386,0.00017634328,0.92485774,0.00025528218,0.04650337,0.016774302,0.0005297052],"about_ca_topic_score_codex":0.00019626596,"about_ca_topic_score_gemma":0.00004411378,"teacher_disagreement_score":0.9248199,"about_ca_system_score_codex":0.00008200647,"about_ca_system_score_gemma":0.00057157036,"threshold_uncertainty_score":0.99986506},"labels":[],"label_agreement":null},{"id":"W6888442983","doi":"10.20380/gi2022.24","title":"A Design Framework for Contextual and Embedded Information Visualizations in Spatial Augmented Reality","year":2022,"lang":"en","type":"article","venue":"Canada Human-Computer Communications Society","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Augmented reality; Visualization; Context (archaeology); Process (computing); Spatial contextual awareness; Data visualization; Information visualization; Design process","score_opus":0.061790052315139746,"score_gpt":0.3341619149715408,"score_spread":0.27237186265640106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6888442983","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00020877074,0.000058692433,0.9956436,0.0031669277,0.00013551027,0.00053510244,0.00011040062,0.00008636024,0.000054607382],"genre_scores_gemma":[0.46080452,0.00005489313,0.5288164,0.008217518,0.000043337062,0.00039995796,0.0015843965,0.000017483144,0.000061456085],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99843985,0.0003111604,0.00049057533,0.00022956419,0.0002992286,0.00022963031],"domain_scores_gemma":[0.9978852,0.00042288675,0.00022288812,0.0012041989,0.00017690896,0.000087914836],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0005917945,0.00014078204,0.00018457758,0.00008455351,0.0013284402,0.00023975704,0.0015418632,0.000049089766,0.000016842674],"category_scores_gemma":[0.000047990718,0.00017158748,0.000056681412,0.0005842505,0.00008689514,0.00054288574,0.0012345074,0.00025480072,5.0900917e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006038932,0.00021751958,0.00022574251,0.00004777536,0.0000637963,6.7399736e-7,0.011656494,0.007983924,0.0000152123575,0.886265,0.08349438,0.010023446],"study_design_scores_gemma":[0.00062551076,0.000048810456,0.00056789775,0.00001419792,0.000010151703,0.0000030921242,0.00075296074,0.9462858,0.000010412197,0.004993037,0.04647918,0.00020893688],"about_ca_topic_score_codex":0.025912132,"about_ca_topic_score_gemma":0.03303241,"teacher_disagreement_score":0.93830186,"about_ca_system_score_codex":0.00042120012,"about_ca_system_score_gemma":0.0006523194,"threshold_uncertainty_score":0.9999717},"labels":[],"label_agreement":null},{"id":"W6888444211","doi":"10.20380/gi2021.02","title":"A Conversation with CHCCS 2021 Achievement Award Winner Tamara Munzner","year":2021,"lang":"en","type":"article","venue":"Canada Human-Computer Communications Society","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Conversation; Casual; Field (mathematics); Conversation analysis; Visualization","score_opus":0.024722538237302256,"score_gpt":0.2676569345187913,"score_spread":0.24293439628148905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6888444211","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0022808982,0.00027606057,0.9593812,0.036428258,0.0002851378,0.0002077145,0.000034750006,0.00012667887,0.000979277],"genre_scores_gemma":[0.3975789,0.00046479324,0.56863856,0.026401289,0.00030122334,0.00007737032,0.002274932,0.0000619151,0.004200988],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982166,0.00017820792,0.00036759823,0.00044250666,0.0004926135,0.00030245373],"domain_scores_gemma":[0.99599,0.00009946479,0.0001771254,0.0030593635,0.00051640027,0.00015764992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022225337,0.00021154161,0.00022574373,0.000036173937,0.00079041196,0.00038111364,0.0020339256,0.0000661992,0.000059485934],"category_scores_gemma":[0.000008598207,0.00020836292,0.00011087717,0.0007482276,0.0001520861,0.00045078123,0.0012065407,0.0002726242,0.0000121900885],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000031703657,0.0008786486,0.004818675,0.000108618915,0.00087399554,0.000052132506,0.009998923,0.002494724,0.00053723925,0.36913866,0.59595346,0.01514176],"study_design_scores_gemma":[0.00091229856,0.000038725768,0.0034541145,0.000065457316,0.000048179594,0.00001939072,0.00065386057,0.33317676,0.00037215807,0.00026514515,0.6604616,0.00053231453],"about_ca_topic_score_codex":0.014930672,"about_ca_topic_score_gemma":0.095004745,"teacher_disagreement_score":0.395298,"about_ca_system_score_codex":0.0003897981,"about_ca_system_score_gemma":0.0013389671,"threshold_uncertainty_score":0.991629},"labels":[],"label_agreement":null},{"id":"W6888589361","doi":"10.20380/gi2022.25","title":"Accidental Landmarks: How Showing (and Removing) Emphasis in a 2D Visualization Affected Retrieval and Revisitation","year":2022,"lang":"en","type":"article","venue":"Canada Human-Computer Communications Society","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; University of Saskatchewan","funders":"","keywords":"Visualization; Emphasis (telecommunications); Set (abstract data type); Point (geometry); Data visualization; Key (lock); Information visualization","score_opus":0.0261557990929378,"score_gpt":0.2895163424916254,"score_spread":0.2633605433986876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6888589361","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38207355,0.0025543077,0.5993042,0.013985991,0.00044165057,0.00096067,0.00007655872,0.00035566482,0.00024743463],"genre_scores_gemma":[0.976488,0.00023838335,0.02094243,0.0017600378,0.000032305936,0.00001556588,0.00039378775,0.000015747224,0.000113737304],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984518,0.00036966638,0.00027750677,0.00035424068,0.0003492169,0.0001975408],"domain_scores_gemma":[0.998597,0.0001691479,0.00015985276,0.00089608395,0.000091017326,0.00008684622],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005413325,0.00014529111,0.00018910403,0.00010626162,0.0010798642,0.00040516944,0.0010248161,0.000040539995,0.000009154463],"category_scores_gemma":[0.000040563074,0.000175808,0.00004689911,0.0008416443,0.000069217924,0.0005534518,0.0017411864,0.00024041285,1.9861864e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006451304,0.0016359822,0.10176188,0.0009031466,0.0008966074,0.0001086113,0.09028635,0.0038160942,0.0073491726,0.35813403,0.34064212,0.094401486],"study_design_scores_gemma":[0.0009409798,0.000048277278,0.035286393,0.000058725556,0.000025479987,0.000032480693,0.0013917254,0.93945545,0.000037191214,0.0002990108,0.022022175,0.000402094],"about_ca_topic_score_codex":0.00709713,"about_ca_topic_score_gemma":0.031701338,"teacher_disagreement_score":0.9356394,"about_ca_system_score_codex":0.00040685025,"about_ca_system_score_gemma":0.0002421218,"threshold_uncertainty_score":0.9995147},"labels":[],"label_agreement":null},{"id":"W6888829327","doi":"10.2312/eurova.20231090","title":"ChatKG: Visualizing Temporal Patterns as Knowledge Graph","year":2023,"lang":"en","type":"article","venue":"TU/e Research Portal","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Visualization; Knowledge graph; Graph; Temporal database; Data visualization; Oracle; Knowledge extraction; Information visualization","score_opus":0.15299819189036828,"score_gpt":0.47584660245752186,"score_spread":0.3228484105671536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6888829327","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.56573486,0.0008210878,0.2088672,0.008115625,0.0029694466,0.0020021815,0.00027859793,0.0059620696,0.20524894],"genre_scores_gemma":[0.99015146,0.0001853375,0.00021521072,0.000124041,0.00021156813,0.000025145342,0.0002265072,0.000026918917,0.008833815],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9970612,0.00024422436,0.00030467284,0.0005261757,0.0010647844,0.0007989651],"domain_scores_gemma":[0.9984704,0.00015429028,0.000055321045,0.00070162525,0.00028509198,0.00033323155],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0021450813,0.000145436,0.00017560052,0.0008565246,0.00034169064,0.00046692815,0.0012794432,0.000072166025,0.00033417746],"category_scores_gemma":[0.00024159311,0.00013698192,0.00009394257,0.0030028704,0.00011013807,0.0006076983,0.0010197766,0.0003155807,0.0036635876],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009099966,0.0004532881,0.038632575,0.00019150246,0.000096399,0.0015444122,0.0033812232,0.000017332502,0.00079633563,0.63958645,0.29046375,0.024827648],"study_design_scores_gemma":[0.002481762,0.0011992066,0.041428868,0.00052392407,0.000019737052,0.0001971545,0.005955872,0.382449,0.006788734,0.03445279,0.5223868,0.0021161363],"about_ca_topic_score_codex":0.00015724683,"about_ca_topic_score_gemma":0.00009701801,"teacher_disagreement_score":0.60513365,"about_ca_system_score_codex":0.00002432562,"about_ca_system_score_gemma":0.00028263492,"threshold_uncertainty_score":0.99711215},"labels":[],"label_agreement":null},{"id":"W6889414790","doi":"10.25549/wpacards-m36731","title":"WPA block face card for household census of Veteran, Rose, Greenfield Streets, in Los Angeles County","year":2012,"lang":"en","type":"dataset","venue":"University of Southern California Digital Library","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Census; Block (permutation group theory); Face (sociological concept); Quarter (Canadian coin); Metropolitan area","score_opus":0.019084099861993765,"score_gpt":0.20145776543233052,"score_spread":0.18237366557033674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6889414790","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00041556227,0.00010442971,0.0014769817,0.000038132985,0.00004358785,0.00017212617,0.99757373,0.000051857824,0.00012359089],"genre_scores_gemma":[0.0021590337,0.000046818393,0.0004343681,0.000073002564,0.00004596732,1.850679e-7,0.9970859,0.000018535693,0.00013617691],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99883693,0.00002997798,0.00028643108,0.00031608957,0.00027778902,0.00025277818],"domain_scores_gemma":[0.998869,0.000098533375,0.00032298893,0.0005395645,0.00004380534,0.00012610582],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006387683,0.00023072999,0.00039564946,0.00023234371,0.00004697537,0.00009507154,0.001238149,0.00022329798,0.000011357863],"category_scores_gemma":[0.000018160503,0.00024385039,0.00017158451,0.00027819406,0.00012429406,0.00054200593,0.000559496,0.00015123843,0.000029039578],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040027146,0.00017018945,0.0015267865,0.0002713035,0.000037695296,0.00001465028,0.00001959726,0.000026936932,0.000001295398,0.000040120187,0.9972582,0.0005931831],"study_design_scores_gemma":[0.00042673797,0.00003476234,0.000018112041,0.0001368197,0.000035640005,0.000002015016,0.00031406098,0.0005659837,0.000028840628,0.000050833776,0.99813145,0.00025474824],"about_ca_topic_score_codex":0.00009482762,"about_ca_topic_score_gemma":0.000036068806,"teacher_disagreement_score":0.0017434712,"about_ca_system_score_codex":0.000021328973,"about_ca_system_score_gemma":0.00011111079,"threshold_uncertainty_score":0.99439305},"labels":[],"label_agreement":null},{"id":"W6893238064","doi":"10.5281/zenodo.15314329","title":"Keçeci Layout","year":2025,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Association of Physicists","funders":"","keywords":"Zigzag; Visualization; Graph; Graph drawing; Graph Layout; Offset (computer science); Python (programming language); Identifier","score_opus":0.03546159851422611,"score_gpt":0.2865200474942355,"score_spread":0.2510584489800094,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6893238064","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00036490717,0.00004213404,0.6829337,0.0021603121,0.000150544,0.00013856757,0.000044541033,0.0011217209,0.3130436],"genre_scores_gemma":[0.9445283,0.00022603723,0.009804557,0.0062027727,0.000263316,5.7131984e-8,0.0028398538,0.0014160913,0.034719024],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99888223,0.00015221718,0.00017716333,0.00032647743,0.00023570468,0.0002261895],"domain_scores_gemma":[0.9988915,0.000015618845,0.000049509847,0.00059401867,0.00035623895,0.000093136725],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00040832625,0.0000854693,0.00008946507,0.00025525468,0.0012529056,0.0013654254,0.0019011459,0.000035946294,0.0021689897],"category_scores_gemma":[0.00036840176,0.00008927812,0.000034756868,0.0010422262,0.000065929176,0.00038721075,0.0017639926,0.00012076745,0.005684675],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000037763698,0.00007452304,0.0000036488161,0.00002144913,0.000019413937,0.0000051568286,0.00029112908,0.00004426647,0.00035777423,0.43945742,0.45287013,0.106851324],"study_design_scores_gemma":[0.0002205899,0.000034879627,0.00017968946,0.000017264134,0.0000042303045,0.000011381044,0.00005477799,0.013924181,0.00026126546,0.0012260256,0.98397315,0.00009259767],"about_ca_topic_score_codex":0.000003848805,"about_ca_topic_score_gemma":1.072238e-7,"teacher_disagreement_score":0.9441634,"about_ca_system_score_codex":0.00006215049,"about_ca_system_score_gemma":0.000005190069,"threshold_uncertainty_score":0.9996713},"labels":[],"label_agreement":null},{"id":"W6893744409","doi":"10.5281/zenodo.4058837","title":"Silent Noise: Channel Noise in Visual Communications","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Visual communication; Noise (video); Communication design; Graphics; Channel (broadcasting); Fidelity; Communications system; Terminology","score_opus":0.07334605655952856,"score_gpt":0.3039716357720551,"score_spread":0.23062557921252655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6893744409","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036702123,0.0002266836,0.8644061,0.035356596,0.00017168334,0.00085373677,0.00026160033,0.002651378,0.092402],"genre_scores_gemma":[0.99353415,0.00022879943,0.0017171568,0.0023795003,0.00008858177,6.300273e-8,0.0013422676,0.00046916804,0.00024032197],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99851155,0.00029088143,0.00026744377,0.00036364485,0.00030617282,0.0002602917],"domain_scores_gemma":[0.99868554,0.000022858105,0.00008164064,0.00071292056,0.00027372077,0.00022333543],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00037796004,0.0001088475,0.0001231393,0.00018057524,0.0008473431,0.00083864026,0.002950192,0.000039793387,0.0009906637],"category_scores_gemma":[0.0004488474,0.00012111438,0.00003604727,0.0012447393,0.00009513932,0.0005076313,0.0033264863,0.00021726766,0.0051441737],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000068879344,0.0016385224,0.00005514413,0.00021480257,0.00008713947,0.00006534145,0.021266721,0.0017768199,0.010150883,0.28493586,0.46053705,0.21920285],"study_design_scores_gemma":[0.00039239263,0.0001185584,0.00035466428,0.000017162996,0.0000034968389,0.00001076007,0.00022364156,0.23202531,0.00020139279,0.00014273965,0.766356,0.00015390183],"about_ca_topic_score_codex":0.00001060365,"about_ca_topic_score_gemma":4.976571e-7,"teacher_disagreement_score":0.98986393,"about_ca_system_score_codex":0.00007519326,"about_ca_system_score_gemma":0.00000632523,"threshold_uncertainty_score":0.9999226},"labels":[],"label_agreement":null},{"id":"W6901982381","doi":"10.6084/m9.figshare.15079514","title":"Additional file 1 of ABrainVis: an android brain image visualization tool","year":2021,"lang":"en","type":"article","venue":"Open MIND","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Visualization; Data visualization; Android (operating system); Information visualization; Image manipulation; Table (database); File format","score_opus":0.031023288901768763,"score_gpt":0.336298801322036,"score_spread":0.30527551242026724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6901982381","genre_codex":"dataset","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007085548,0.000010133625,0.34642974,0.00072021334,0.0001151139,0.00027621782,0.60610473,0.000016901653,0.045618355],"genre_scores_gemma":[0.0010318669,0.0000042115976,0.4905036,0.002297596,0.00012127556,0.000046861434,0.47846234,0.000021629325,0.027510619],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99910086,0.00008633895,0.0002121533,0.00028893855,0.00020653213,0.00010514664],"domain_scores_gemma":[0.99897575,0.0002676587,0.00011076759,0.00038601196,0.00020058153,0.00005921576],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00012945598,0.00007091647,0.00011235711,0.000049722636,0.0000661435,0.0004458781,0.0006312336,0.000032607837,0.783995],"category_scores_gemma":[0.00069188705,0.000075050746,0.00002914892,0.0004497355,0.00003232035,0.0013655254,0.0003600832,0.000032582924,0.0004819584],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010740541,0.000112339876,0.000001938918,0.000002922732,0.0000065590248,0.000012208537,0.0001466555,0.000005111505,0.0003481571,0.00336819,0.9708052,0.02518962],"study_design_scores_gemma":[0.0001665415,0.000037880855,0.00016652106,0.000047291953,0.0000026141342,0.000012479861,0.00008302658,0.06009126,0.0037059907,0.00045610114,0.93511224,0.00011802256],"about_ca_topic_score_codex":0.00000211051,"about_ca_topic_score_gemma":0.000018277357,"teacher_disagreement_score":0.783513,"about_ca_system_score_codex":0.000011084859,"about_ca_system_score_gemma":0.00025110107,"threshold_uncertainty_score":0.61947614},"labels":[],"label_agreement":null},{"id":"W6902111824","doi":"10.6084/m9.figshare.17073468","title":"Additional file 3 of Improving 3D convolutional neural network comprehensibility via interactive visualization of relevance maps: evaluation in Alzheimer’s disease","year":2021,"lang":"en","type":"article","venue":"Figshare","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Visualization; Relevance (law); Interactive visualization; Convolutional neural network; Data visualization; Information visualization","score_opus":0.05986277659263135,"score_gpt":0.3244017688958645,"score_spread":0.26453899230323313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6902111824","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00002140071,0.0001673359,0.0034822463,0.000021455322,0.000056678397,0.00016635365,0.9958759,0.000025335323,0.00018331013],"genre_scores_gemma":[0.041363496,7.8640915e-7,0.003438579,0.00014599013,0.000055522945,0.00011687969,0.9548492,0.000006552396,0.000023006294],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985197,0.00020705536,0.00037955615,0.0003160928,0.00044490272,0.00013268368],"domain_scores_gemma":[0.9972006,0.0010627173,0.00033889047,0.00029926124,0.0010371164,0.00006141624],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000078213874,0.000097230164,0.00015318632,0.0000642954,0.000042034208,0.00003165841,0.00023255392,0.000038247825,0.7078885],"category_scores_gemma":[0.0042136186,0.00011060671,0.000059129965,0.0006099159,0.000016315445,0.00059035624,0.00023536559,0.00007278223,0.00006810937],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011571108,0.00012947136,0.00005363792,0.00006597494,0.00001595891,0.000003965084,0.000043157877,0.009478283,0.000014308415,0.00029543805,0.9818894,0.007998812],"study_design_scores_gemma":[0.00018938478,0.000016860236,0.01703609,0.0008528106,0.000010271081,0.0000017991202,0.000009751555,0.95752025,0.00006985667,0.0005110951,0.023676524,0.00010531737],"about_ca_topic_score_codex":0.0000037929958,"about_ca_topic_score_gemma":0.000024688426,"teacher_disagreement_score":0.9582129,"about_ca_system_score_codex":0.000055806635,"about_ca_system_score_gemma":0.00044659394,"threshold_uncertainty_score":0.50443995},"labels":[],"label_agreement":null},{"id":"W6902399852","doi":"10.6084/m9.figshare.9205838","title":"The 13th International conference “Science and society” (Canada, Hamilton, 19th July 2019)","year":2019,"lang":"en","type":"article","venue":"Figshare","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Stress (linguistics); Focus (optics); Graphics; Exposition (narrative)","score_opus":0.0258475906148321,"score_gpt":0.270938504665639,"score_spread":0.2450909140508069,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6902399852","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027014434,0.0016532,0.017471567,0.03652673,0.0088775195,0.0028754636,0.4241083,0.001257333,0.50452846],"genre_scores_gemma":[0.87962115,0.00029893895,0.0042444863,0.02369355,0.0004110481,0.000070214424,0.02884853,0.000045495435,0.06276658],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99892986,0.000009791761,0.000104302686,0.00024796458,0.0005342974,0.0001738088],"domain_scores_gemma":[0.9990569,0.00006795341,0.00006861657,0.00033355528,0.000396256,0.00007674113],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001187448,0.00007121122,0.000055440327,0.000018958703,0.00020713604,0.0006378735,0.0013897674,0.00001884468,0.0032256413],"category_scores_gemma":[0.00020668098,0.00005208566,0.000017053491,0.00025842944,0.000027066439,0.0004919687,0.00042938234,0.00007515501,0.00050249905],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.8389573e-7,0.0000040680447,0.00002949841,0.0000066629323,0.000004814987,8.410871e-7,0.00012654133,0.0000048560705,0.000032206557,0.010819126,0.9862682,0.0027028862],"study_design_scores_gemma":[0.00008049955,0.0000071312943,0.0016200646,0.000061951345,6.002659e-7,0.0000032956755,0.000036484926,0.17571914,0.00013185936,0.0000786699,0.8221766,0.00008372196],"about_ca_topic_score_codex":0.0005824375,"about_ca_topic_score_gemma":0.0014334593,"teacher_disagreement_score":0.8769197,"about_ca_system_score_codex":0.000056585475,"about_ca_system_score_gemma":0.0007602588,"threshold_uncertainty_score":0.99768555},"labels":[],"label_agreement":null},{"id":"W6902404854","doi":"10.6084/m9.figshare.9205838.v1","title":"The 13th International conference “Science and society” (Canada, Hamilton, 19th July 2019)","year":2019,"lang":"en","type":"article","venue":"Figshare","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Stress (linguistics); Focus (optics); Graphics; Exposition (narrative)","score_opus":0.0258475906148321,"score_gpt":0.270938504665639,"score_spread":0.2450909140508069,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6902404854","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027014434,0.0016532,0.017471567,0.03652673,0.0088775195,0.0028754636,0.4241083,0.001257333,0.50452846],"genre_scores_gemma":[0.87962115,0.00029893895,0.0042444863,0.02369355,0.0004110481,0.000070214424,0.02884853,0.000045495435,0.06276658],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99892986,0.000009791761,0.000104302686,0.00024796458,0.0005342974,0.0001738088],"domain_scores_gemma":[0.9990569,0.00006795341,0.00006861657,0.00033355528,0.000396256,0.00007674113],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001187448,0.00007121122,0.000055440327,0.000018958703,0.00020713604,0.0006378735,0.0013897674,0.00001884468,0.0032256413],"category_scores_gemma":[0.00020668098,0.00005208566,0.000017053491,0.00025842944,0.000027066439,0.0004919687,0.00042938234,0.00007515501,0.00050249905],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.8389573e-7,0.0000040680447,0.00002949841,0.0000066629323,0.000004814987,8.410871e-7,0.00012654133,0.0000048560705,0.000032206557,0.010819126,0.9862682,0.0027028862],"study_design_scores_gemma":[0.00008049955,0.0000071312943,0.0016200646,0.000061951345,6.002659e-7,0.0000032956755,0.000036484926,0.17571914,0.00013185936,0.0000786699,0.8221766,0.00008372196],"about_ca_topic_score_codex":0.0005824375,"about_ca_topic_score_gemma":0.0014334593,"teacher_disagreement_score":0.8769197,"about_ca_system_score_codex":0.000056585475,"about_ca_system_score_gemma":0.0007602588,"threshold_uncertainty_score":0.99768555},"labels":[],"label_agreement":null},{"id":"W6906244360","doi":"10.17613/g68br-51f33","title":"Beyond the Textual: Visual Information Systems that Help and Hinder","year":2022,"lang":"en","type":"article","venue":"Knowledge Commons (Lakehead University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Seekers; Focus (optics); Information system; Set (abstract data type); Information seeking; Information visualization; Information needs; The arts","score_opus":0.02629553068710905,"score_gpt":0.2509297221794139,"score_spread":0.22463419149230485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6906244360","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.050733194,0.0013698249,0.53488714,0.0042712414,0.002234875,0.0009775957,0.00022732993,0.00084463955,0.40445417],"genre_scores_gemma":[0.99547523,0.00000257832,0.000021647676,0.000050784125,0.00002449929,0.0000018227579,0.000064255466,0.000005084105,0.004354125],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.999014,0.00024994186,0.0001318901,0.00017586986,0.00023796878,0.00019031354],"domain_scores_gemma":[0.9991997,0.00012102148,0.000098500714,0.0003926619,0.0000943182,0.00009380767],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027599136,0.000117856245,0.00012600161,0.00035476268,0.0009885,0.0002994119,0.00096994714,0.000033894506,0.000022317952],"category_scores_gemma":[0.000014535388,0.00010722424,0.000042159252,0.0010519947,0.00008529495,0.0011731831,0.0014009582,0.0001988824,0.00005047736],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000060035486,0.00009042989,0.0059091416,0.000019867752,0.000027075943,0.000009257594,0.002260119,0.00019457824,0.0000038844155,0.9593137,0.027147517,0.005018407],"study_design_scores_gemma":[0.00042722758,0.00006467896,0.0021299368,0.0000072929934,0.00001845128,0.000025756404,0.0031780968,0.050238464,0.000011657534,0.0001331833,0.9435927,0.00017249947],"about_ca_topic_score_codex":0.000025342099,"about_ca_topic_score_gemma":0.0009518663,"teacher_disagreement_score":0.95918053,"about_ca_system_score_codex":0.0001171678,"about_ca_system_score_gemma":0.0001078511,"threshold_uncertainty_score":0.76028425},"labels":[],"label_agreement":null},{"id":"W6906791343","doi":"10.17895/ices.pub.19280369","title":"REPORT OF THE WORKING GROUP FOR REGIONAL ECOSYSTEM DESCRIPTION (WGRED)","year":2008,"lang":"en","type":"report","venue":"International Council for the Exploration of the Sea (ICES)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Work (physics); Group (periodic table); Working group; Ecosystem","score_opus":0.3647405869969031,"score_gpt":0.33742944327701857,"score_spread":0.027311143719884523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6906791343","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00023834425,0.0005211346,0.9686038,0.0082258815,0.01538384,0.0018175397,0.0007058349,0.00006925692,0.004434356],"genre_scores_gemma":[0.9110582,0.0041909,0.011845709,0.0017218104,0.0070346575,0.0014377818,0.0026239657,0.00022420054,0.05986282],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99414986,0.000119792,0.0012106175,0.00045819284,0.0038715191,0.00019000233],"domain_scores_gemma":[0.9892401,0.00047793792,0.0029325117,0.001229812,0.006083817,0.00003579841],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036145896,0.00026274147,0.00034589655,0.00010676642,0.00043141647,0.00018890463,0.0032474615,0.00017397944,0.0000079181245],"category_scores_gemma":[0.0019188038,0.00015289515,0.0006545701,0.00040654643,0.00012396419,0.00085407,0.00042080585,0.00019614129,0.0000027744204],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020489542,0.00039251373,0.00092643796,0.0006565487,0.0014567146,0.00000565463,0.0021427795,0.012899049,0.00040690633,0.13590066,0.8383044,0.006703421],"study_design_scores_gemma":[0.000395113,0.000041689047,0.00017058782,0.00053134206,0.00010526395,0.00011279153,0.00009747218,0.1011712,0.00037094246,0.005252423,0.89155734,0.00019383941],"about_ca_topic_score_codex":0.00012742869,"about_ca_topic_score_gemma":0.00066363445,"teacher_disagreement_score":0.9567581,"about_ca_system_score_codex":0.001038344,"about_ca_system_score_gemma":0.0023622075,"threshold_uncertainty_score":0.62348837},"labels":[],"label_agreement":null},{"id":"W6907140032","doi":"10.20380/gi2021.28","title":"Perspective Charts","year":2021,"lang":"en","type":"article","venue":"Open MIND","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Bar chart; Perspective (graphical); Pie chart; Chart; Bar (unit); Representation (politics); Variation (astronomy)","score_opus":0.0645800746095508,"score_gpt":0.3745219813835605,"score_spread":0.30994190677400973,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6907140032","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00368791,0.00011380126,0.37036774,0.0072170547,0.00033349707,0.00012131149,0.000019604968,0.0000065089603,0.6181326],"genre_scores_gemma":[0.48937216,0.00005761423,0.3214487,0.0036014498,0.00020668354,0.0000070143337,0.00008015887,0.000016894697,0.18520929],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99957544,0.000021073305,0.000056059118,0.00019695371,0.00008027779,0.000070210845],"domain_scores_gemma":[0.9995527,0.000009800743,0.000019605906,0.00027452412,0.00010332468,0.000040014926],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00007626813,0.000033498414,0.000051309402,0.000015675596,0.000046064415,0.00049446226,0.0005308205,0.000011886443,0.0015205452],"category_scores_gemma":[0.000040700663,0.000032334778,0.000014196931,0.00022164057,0.000009054093,0.0003983079,0.00046849958,0.000025315676,0.0009979204],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000022622237,0.00031859428,0.0003169781,0.0000026672521,0.000049264563,0.0003218164,0.008803565,0.000025267194,0.0015236054,0.69252115,0.0289302,0.26718464],"study_design_scores_gemma":[0.00033118943,0.00002313183,0.00034739703,0.000016218466,0.0000061679857,0.00003146858,0.0012788582,0.026683562,0.026031889,0.0029744883,0.9420857,0.00018992105],"about_ca_topic_score_codex":0.0000064129013,"about_ca_topic_score_gemma":0.000013650102,"teacher_disagreement_score":0.9131555,"about_ca_system_score_codex":0.00001718832,"about_ca_system_score_gemma":0.000102272475,"threshold_uncertainty_score":0.99977994},"labels":[],"label_agreement":null},{"id":"W6907160317","doi":"10.20380/gi2022.13","title":"I'm Not Sure: Designing for Ambiguity in Visual Analytics","year":2022,"lang":"en","type":"article","venue":"Canada Human-Computer Communications Society","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Sensemaking; Visual analytics; Ambiguity; Relevance (law); Visualization; Cultural analytics; Analytics; Meaning (existential)","score_opus":0.07209690797647186,"score_gpt":0.3328927987694109,"score_spread":0.2607958907929391,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6907160317","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013302744,0.00013739648,0.99377257,0.00383788,0.00024247731,0.00032421385,0.00007315213,0.00011159221,0.00017043413],"genre_scores_gemma":[0.70554376,0.000047939924,0.2839264,0.0092310095,0.00007552638,0.00014932756,0.00055399403,0.000029389812,0.00044266737],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981335,0.00024027037,0.00047191975,0.0003795987,0.00042487236,0.0003498493],"domain_scores_gemma":[0.99748665,0.00031532894,0.00018727386,0.0017435383,0.00016227803,0.000104938925],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0008229536,0.00016686785,0.0002386582,0.0000880749,0.0015051896,0.00015049553,0.003558824,0.000040117153,0.000017228087],"category_scores_gemma":[0.000021495853,0.00020858673,0.00014747764,0.00093318475,0.00007974567,0.0002539475,0.002203755,0.00036106483,8.8079713e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006418287,0.0009812216,0.003308175,0.000102453196,0.00026782294,0.000011558001,0.0057779043,0.024300065,0.00044352745,0.34503442,0.60381126,0.015955187],"study_design_scores_gemma":[0.0004788342,0.000038940758,0.0010596255,0.000008061258,0.000011923161,0.0000034474376,0.000263465,0.8842062,0.000063887615,0.00056514895,0.113035135,0.0002653682],"about_ca_topic_score_codex":0.02594684,"about_ca_topic_score_gemma":0.09220745,"teacher_disagreement_score":0.8599061,"about_ca_system_score_codex":0.000773484,"about_ca_system_score_gemma":0.001020937,"threshold_uncertainty_score":0.9997947},"labels":[],"label_agreement":null},{"id":"W6907517467","doi":"10.2312/evs.20221088","title":"SSCA: Situated Space-time Cube Analytics","year":2022,"lang":"en","type":"article","venue":"Eurographics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; Kelowna General Hospital; University of British Columbia; University of Manitoba","funders":"","keywords":"Situated; Visualization; Cube (algebra); Data visualization; Domain (mathematical analysis); Analytics; Visual analytics","score_opus":0.019051847391045273,"score_gpt":0.2591364248455776,"score_spread":0.24008457745453232,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6907517467","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021923894,0.00047715244,0.93729985,0.010707464,0.0017671316,0.0005065229,0.00020002008,0.002494081,0.024623897],"genre_scores_gemma":[0.9587714,0.0002336941,0.022663532,0.008380082,0.00019588243,0.00002416067,0.00046464696,0.000082975756,0.009183588],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99839807,0.0001551209,0.00022917891,0.0003637401,0.0005677006,0.00028621685],"domain_scores_gemma":[0.99890155,0.000058716887,0.000110636916,0.0007068922,0.00009292848,0.00012926022],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040736183,0.0001381048,0.00015100706,0.0003641699,0.0003976348,0.00021524976,0.0011570287,0.000026963884,0.00022374948],"category_scores_gemma":[0.000053119944,0.00014980201,0.000114002665,0.0033105875,0.000058564303,0.00025174514,0.0007998543,0.0002467852,0.0001318048],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008337811,0.00064184266,0.0060542384,0.000018441404,0.00015792083,0.00021230972,0.0008783507,0.004714442,0.0005809083,0.8462307,0.1351993,0.0053032157],"study_design_scores_gemma":[0.000305736,0.00014584418,0.00076967623,0.0000031203633,0.0000249147,0.000026766154,0.000057483878,0.5512118,0.0000729057,0.0021132848,0.44498783,0.00028068674],"about_ca_topic_score_codex":0.000005871499,"about_ca_topic_score_gemma":0.0000021866986,"teacher_disagreement_score":0.93684757,"about_ca_system_score_codex":0.000022523562,"about_ca_system_score_gemma":0.00006597406,"threshold_uncertainty_score":0.61087483},"labels":[],"label_agreement":null},{"id":"W6911390515","doi":"10.5281/zenodo.1184221","title":"Flower Space: Exploring The Feature Space Manifold Of A Gan","year":2018,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Feature (linguistics); Space (punctuation); Manifold (fluid mechanics); Pattern recognition (psychology); Feature vector","score_opus":0.057249720534938854,"score_gpt":0.27086140208489334,"score_spread":0.2136116815499545,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6911390515","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015998835,0.00010748222,0.695251,0.0144954175,0.00081482047,0.00070119736,0.00016113755,0.0018500723,0.27062005],"genre_scores_gemma":[0.99149925,0.0000930509,0.0026255986,0.00044001598,0.0003271145,3.854579e-8,0.00019298431,0.0005562195,0.004265741],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987255,0.00017669001,0.00015292918,0.00030337344,0.0003907074,0.00025080284],"domain_scores_gemma":[0.99844956,0.000020029096,0.00009485976,0.00077194255,0.0005607035,0.00010288804],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005406558,0.000103865554,0.00010166091,0.00014647415,0.0011817706,0.0007443132,0.0019147685,0.000030738956,0.0015707726],"category_scores_gemma":[0.00033440586,0.00008391431,0.000041656334,0.0009577392,0.00013931896,0.00050096714,0.0012699047,0.00015298233,0.0026098879],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019732426,0.000121420984,0.0000074565883,0.000043965163,0.000047586334,0.000010612862,0.0047229705,0.00003486232,0.004542675,0.38454798,0.5768067,0.029094039],"study_design_scores_gemma":[0.00018444234,0.000121022895,0.00032452453,0.000026476202,0.0000066146554,0.000033729873,0.00026260738,0.0063115093,0.003932162,0.00020828478,0.9884781,0.000110473586],"about_ca_topic_score_codex":0.0000066303273,"about_ca_topic_score_gemma":7.5975436e-7,"teacher_disagreement_score":0.9755004,"about_ca_system_score_codex":0.000038621434,"about_ca_system_score_gemma":0.000004484833,"threshold_uncertainty_score":0.9993419},"labels":[],"label_agreement":null},{"id":"W6911754595","doi":"10.5281/zenodo.14176549","title":"CoMRAT: Commit Message Rationale Analysis Tool","year":2024,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Université de Montréal","funders":"","keywords":"Commit; Identification (biology); Key (lock); Information system; Data analysis","score_opus":0.04032913863773703,"score_gpt":0.2824120865856222,"score_spread":0.2420829479478852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6911754595","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006222888,0.00014037879,0.9255041,0.0023073987,0.00013238215,0.00018802055,0.00023935927,0.0017201374,0.06914592],"genre_scores_gemma":[0.97212917,0.00020351108,0.005048271,0.0013617205,0.0002537461,9.596539e-8,0.008444859,0.0009841389,0.011574511],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99843484,0.00022733763,0.00024597006,0.00043019248,0.0004327815,0.00022886881],"domain_scores_gemma":[0.99888045,0.000041126277,0.000047905014,0.000606331,0.00031130033,0.0001128781],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00067606993,0.00011171613,0.00013371388,0.0004908696,0.0011676097,0.0035491504,0.0015219545,0.000039557188,0.008060086],"category_scores_gemma":[0.000205431,0.00011267094,0.000093000046,0.0026892514,0.000073136995,0.00075838313,0.0011153412,0.00016127956,0.008197789],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000038219177,0.0000940181,0.000005974855,0.00004957631,0.00027453888,0.000031053976,0.0008907653,0.0004823362,0.00044838866,0.5385644,0.40676403,0.052391097],"study_design_scores_gemma":[0.00009610838,0.000033947945,0.0001565905,0.000011355113,0.000042198797,0.000017202743,0.00004493823,0.18340643,0.00010415484,0.0005168127,0.8154485,0.00012175464],"about_ca_topic_score_codex":0.000004400054,"about_ca_topic_score_gemma":4.0225623e-7,"teacher_disagreement_score":0.97150683,"about_ca_system_score_codex":0.000076590084,"about_ca_system_score_gemma":0.000006839989,"threshold_uncertainty_score":0.9974853},"labels":[],"label_agreement":null},{"id":"W6912362456","doi":"10.5281/zenodo.3780992","title":"Visualizing survey data: disseminating results from a population health survey on HIV and AIDS in Canada","year":2014,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Dissemination; Session (web analytics); Population; Visualization; Data visualization; Public health; Information Dissemination; Human immunodeficiency virus (HIV)","score_opus":0.0832508723616967,"score_gpt":0.31748009507910024,"score_spread":0.23422922271740354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6912362456","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.51986206,0.0001272652,0.4435232,0.003019183,0.00057224114,0.0011500033,0.023061939,0.0012890126,0.0073950854],"genre_scores_gemma":[0.9555576,0.000029317887,0.0006174928,0.00037354423,0.000031695534,6.2403203e-9,0.043141995,0.00019138573,0.00005699155],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99681276,0.0015369499,0.00038781372,0.00059494306,0.00039792035,0.0002695929],"domain_scores_gemma":[0.9983903,0.00029970167,0.00018283585,0.0007855473,0.00017895199,0.00016264335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036598374,0.00011278499,0.00016732783,0.00016552016,0.0007385656,0.0007827733,0.0013242053,0.000025831154,0.00007385278],"category_scores_gemma":[0.00402985,0.00012068649,0.000007302025,0.0007493733,0.000024527022,0.00046838884,0.0014133919,0.00015400763,0.00010388318],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016480937,0.00028961318,0.021224938,0.00007375036,0.00004714456,0.000013804989,0.0032618667,0.0010230152,0.000114260525,0.016218074,0.44444805,0.51312065],"study_design_scores_gemma":[0.0007866359,0.00012503171,0.7045449,0.00010231138,0.0000018706853,0.0000035669866,0.00012943792,0.23295459,0.000019395073,0.000077696975,0.06101237,0.00024221888],"about_ca_topic_score_codex":0.5027552,"about_ca_topic_score_gemma":0.13265923,"teacher_disagreement_score":0.6833199,"about_ca_system_score_codex":0.00024645074,"about_ca_system_score_gemma":0.000024587376,"threshold_uncertainty_score":0.8831675},"labels":[],"label_agreement":null},{"id":"W6912370028","doi":"10.5281/zenodo.3780991","title":"Visualizing survey data: disseminating results from a population health survey on HIV and AIDS in Canada","year":2014,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Dissemination; Session (web analytics); Population; Visualization; Data visualization; Public health; Information Dissemination; Human immunodeficiency virus (HIV)","score_opus":0.0832508723616967,"score_gpt":0.31748009507910024,"score_spread":0.23422922271740354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6912370028","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.51986206,0.0001272652,0.4435232,0.003019183,0.00057224114,0.0011500033,0.023061939,0.0012890126,0.0073950854],"genre_scores_gemma":[0.9555576,0.000029317887,0.0006174928,0.00037354423,0.000031695534,6.2403203e-9,0.043141995,0.00019138573,0.00005699155],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99681276,0.0015369499,0.00038781372,0.00059494306,0.00039792035,0.0002695929],"domain_scores_gemma":[0.9983903,0.00029970167,0.00018283585,0.0007855473,0.00017895199,0.00016264335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036598374,0.00011278499,0.00016732783,0.00016552016,0.0007385656,0.0007827733,0.0013242053,0.000025831154,0.00007385278],"category_scores_gemma":[0.00402985,0.00012068649,0.000007302025,0.0007493733,0.000024527022,0.00046838884,0.0014133919,0.00015400763,0.00010388318],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016480937,0.00028961318,0.021224938,0.00007375036,0.00004714456,0.000013804989,0.0032618667,0.0010230152,0.000114260525,0.016218074,0.44444805,0.51312065],"study_design_scores_gemma":[0.0007866359,0.00012503171,0.7045449,0.00010231138,0.0000018706853,0.0000035669866,0.00012943792,0.23295459,0.000019395073,0.000077696975,0.06101237,0.00024221888],"about_ca_topic_score_codex":0.5027552,"about_ca_topic_score_gemma":0.13265923,"teacher_disagreement_score":0.6833199,"about_ca_system_score_codex":0.00024645074,"about_ca_system_score_gemma":0.000024587376,"threshold_uncertainty_score":0.8831675},"labels":[],"label_agreement":null},{"id":"W6912657897","doi":"10.5281/zenodo.3357823","title":"The 13th International conference \"Science and society\" (Canada, Hamilton, 19th July 2019)","year":2019,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Stress (linguistics); Focus (optics); Graphics; Exposition (narrative)","score_opus":0.024280374930589762,"score_gpt":0.2525598070128623,"score_spread":0.22827943208227253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6912657897","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011901675,0.00021343662,0.24649923,0.020557914,0.0022133216,0.0012435449,0.0005716958,0.0015312455,0.71526796],"genre_scores_gemma":[0.97877425,0.0007760584,0.0018839216,0.002576917,0.00013865635,4.8098276e-8,0.0004889873,0.00041610992,0.014945024],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983694,0.00007264778,0.00016416318,0.00037173694,0.0007528478,0.0002692324],"domain_scores_gemma":[0.9981988,0.000027913153,0.00008694034,0.00049365294,0.0010557697,0.00013691236],"candidate_categories":["sts","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008853633,0.00008780935,0.00007141938,0.00006518954,0.0019096361,0.002513003,0.0026921388,0.000021119624,0.00067465554],"category_scores_gemma":[0.000264053,0.00007299981,0.000018909806,0.000584267,0.000268889,0.000621635,0.0016974977,0.00014140934,0.0012788294],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000054042857,0.000032668373,0.0000092723185,0.000012498863,0.000024294986,0.0000024105912,0.0010476079,0.000021644624,0.001551951,0.26004016,0.6804021,0.056849945],"study_design_scores_gemma":[0.00017429545,0.000034068937,0.0005168092,0.000008813212,0.0000017718261,0.000022533117,0.00018053847,0.0544368,0.00014746902,0.00018927953,0.9441914,0.00009624743],"about_ca_topic_score_codex":0.0004635959,"about_ca_topic_score_gemma":0.000030502535,"teacher_disagreement_score":0.96687263,"about_ca_system_score_codex":0.00014837587,"about_ca_system_score_gemma":0.000055691264,"threshold_uncertainty_score":0.9994988},"labels":[],"label_agreement":null},{"id":"W6912669858","doi":"10.5281/zenodo.3775611","title":"Census program data viewer, 2016 Census","year":2018,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Census; Geospatial analysis; Data visualization; Visualization; Product (mathematics); Presentation (obstetrics); Process (computing); Casual","score_opus":0.10622560777195553,"score_gpt":0.33977004938295574,"score_spread":0.23354444161100021,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6912669858","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00084078027,0.00031724063,0.61252874,0.005422356,0.0012402231,0.001540317,0.003625221,0.008954565,0.36553055],"genre_scores_gemma":[0.5510293,0.0030073903,0.21282719,0.011037346,0.0075256554,5.4060274e-7,0.16426842,0.012041184,0.03826295],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979857,0.00024366255,0.000266396,0.0006524502,0.00044077655,0.0004109891],"domain_scores_gemma":[0.9969846,0.000016520624,0.00011307997,0.0018472825,0.00081229606,0.00022623628],"candidate_categories":["sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007741439,0.00013903147,0.00012817934,0.00017438461,0.0016454136,0.0017663466,0.0047282223,0.00005047765,0.0018419483],"category_scores_gemma":[0.000645592,0.00013419859,0.000029296916,0.0010086425,0.00022841303,0.0007704906,0.005455066,0.00013183818,0.008920782],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000054406996,0.00013698917,6.361528e-7,0.000013699793,0.0000150718315,0.0000068204877,0.0001396336,0.0000010976063,0.00012656146,0.018753214,0.65636253,0.3244383],"study_design_scores_gemma":[0.00028002472,0.0002057876,0.00006257917,0.000022249653,0.0000072269463,0.000048384845,0.00004046306,0.029708186,0.00011054229,0.00021248497,0.96913576,0.0001663005],"about_ca_topic_score_codex":0.000008068694,"about_ca_topic_score_gemma":3.4844564e-7,"teacher_disagreement_score":0.55018854,"about_ca_system_score_codex":0.000055132186,"about_ca_system_score_gemma":0.000007427513,"threshold_uncertainty_score":0.9996543},"labels":[],"label_agreement":null},{"id":"W6920363873","doi":"10.60692/w7d6m-pvy80","title":"A Multi-facetted Visual Analytics Tool for Exploratory Analysis of Human Brain and Function Datasets","year":2016,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre hospitalier de l'Université Laval","funders":"","keywords":"Visual analytics; Exploratory data analysis; Visualization; Exploratory analysis; Software; Function (biology); Process (computing); Limiting","score_opus":0.056522176943477775,"score_gpt":0.28805895330326087,"score_spread":0.2315367763597831,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6920363873","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10089082,9.410263e-7,0.897621,0.000054579745,0.0000727915,0.00018848776,0.0010610991,0.00009961726,0.000010689527],"genre_scores_gemma":[0.9973528,1.3344331e-7,0.0018951045,0.00024366194,0.00001567153,0.000020878288,0.0004117813,0.00000465888,0.00005535959],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987224,0.000060411618,0.0006349126,0.00018824286,0.00024059105,0.00015348002],"domain_scores_gemma":[0.9988033,0.000027041118,0.000418116,0.0004525631,0.00022965936,0.00006930201],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053710386,0.00013067068,0.000270511,0.00072394864,0.00011282605,0.00018567892,0.0002473359,0.0000643883,0.000006445775],"category_scores_gemma":[0.000057438247,0.00009334347,0.000080442725,0.0007923054,0.0000327101,0.0017855077,0.00011783136,0.0000227846,0.000026419333],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003562461,0.00015061525,0.7346024,0.0033885934,0.008344021,0.0000071840573,0.12684254,0.0018883873,0.0036518802,0.07551464,0.019606711,0.025646774],"study_design_scores_gemma":[0.0029193063,0.00018514114,0.07651477,0.00012523378,0.000549633,0.0000025637157,0.0025204516,0.9141099,0.0010386673,0.0000038840876,0.0016373702,0.0003930975],"about_ca_topic_score_codex":0.0000016231764,"about_ca_topic_score_gemma":9.010967e-7,"teacher_disagreement_score":0.9122215,"about_ca_system_score_codex":0.000042165942,"about_ca_system_score_gemma":0.00002557081,"threshold_uncertainty_score":0.3806436},"labels":[],"label_agreement":null},{"id":"W6920738683","doi":"10.6084/m9.figshare.15079514.v1","title":"Additional file 1 of ABrainVis: an android brain image visualization tool","year":2021,"lang":"en","type":"article","venue":"Figshare","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Visualization; Data visualization; Android (operating system); Information visualization; Image manipulation; Table (database); File format","score_opus":0.027371175299561252,"score_gpt":0.29569630291931176,"score_spread":0.2683251276197505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6920738683","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000014969779,0.0000064545416,0.0039478275,0.00006952168,0.000013006158,0.000037520986,0.9936921,0.0000797748,0.0021523081],"genre_scores_gemma":[0.0000617696,3.8778865e-7,0.0075008906,0.0014697508,0.000058167032,0.00005440597,0.98925763,0.000008268319,0.0015887248],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99915063,0.00006183527,0.00018090296,0.0002466996,0.00024360963,0.00011631701],"domain_scores_gemma":[0.9986828,0.00044533142,0.00010922928,0.00035749903,0.00034331187,0.0000618534],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000026072572,0.00007879839,0.000095669646,0.000058766134,0.00005844627,0.00016828679,0.00034760506,0.000042175063,0.98912495],"category_scores_gemma":[0.0042279796,0.00008591385,0.00004540356,0.0004967471,0.0000062373233,0.0008527082,0.00018330102,0.00004042307,0.0013971794],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.0137574e-7,0.00005333678,2.4019832e-7,0.000028837658,0.0000042318543,0.0000121368985,0.000042249023,0.0000049688147,0.000041980584,0.0017081499,0.99661976,0.0014838083],"study_design_scores_gemma":[0.00008392361,0.000022907405,0.00023622182,0.00037048906,9.591432e-7,0.000010499525,0.000017990553,0.07027469,0.0008774192,0.0002762121,0.92771435,0.000114342765],"about_ca_topic_score_codex":3.372801e-7,"about_ca_topic_score_gemma":0.0000036970525,"teacher_disagreement_score":0.98772776,"about_ca_system_score_codex":0.000011961049,"about_ca_system_score_gemma":0.00019551313,"threshold_uncertainty_score":0.99938035},"labels":[],"label_agreement":null},{"id":"W6920911314","doi":"10.6084/m9.figshare.17073474.v1","title":"Additional file 5 of Improving 3D convolutional neural network comprehensibility via interactive visualization of relevance maps: evaluation in Alzheimer’s disease","year":2021,"lang":"en","type":"article","venue":"Figshare","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Relevance (law); Convolutional neural network; Visualization; Artificial neural network; Data visualization; Interactive visualization","score_opus":0.05985795858445674,"score_gpt":0.3245238747791893,"score_spread":0.26466591619473256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6920911314","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000021440532,0.00016799754,0.0034984206,0.000021561667,0.000056314708,0.00016673763,0.9958592,0.000025411919,0.00018289796],"genre_scores_gemma":[0.041915033,7.8624134e-7,0.0034412546,0.00014619612,0.000055011165,0.00011686268,0.9542959,0.0000065507293,0.000022426337],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99851936,0.00020719014,0.0003796693,0.00031615878,0.0004449013,0.00013269445],"domain_scores_gemma":[0.99721,0.0010632875,0.00033890727,0.0002993377,0.0010269961,0.000061421015],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000078307385,0.00009724515,0.00015324348,0.00006432039,0.00004205512,0.00003166102,0.00023263034,0.00003825248,0.70463383],"category_scores_gemma":[0.004175167,0.000110627814,0.000059141457,0.00061002455,0.000016318201,0.0005904343,0.00023545857,0.000072787996,0.00006642504],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000115302955,0.00012971234,0.000053649128,0.0000656059,0.000015980488,0.000003982814,0.00004323401,0.009476089,0.000014223277,0.00030582168,0.9818651,0.008015092],"study_design_scores_gemma":[0.00018875724,0.000016928587,0.017378477,0.0008559738,0.000010354048,0.00000181792,0.000009791559,0.9582109,0.00006908713,0.00051377167,0.022638716,0.000105441635],"about_ca_topic_score_codex":0.0000037934346,"about_ca_topic_score_gemma":0.000024862517,"teacher_disagreement_score":0.95922637,"about_ca_system_score_codex":0.0000556213,"about_ca_system_score_gemma":0.00044552074,"threshold_uncertainty_score":0.49983662},"labels":[],"label_agreement":null},{"id":"W6924758658","doi":"10.15468/dl.w4mqm5","title":"Occurrence Download","year":2022,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); Alien; The Internet","score_opus":0.02001907944244022,"score_gpt":0.24722695263138136,"score_spread":0.22720787318894115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6924758658","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000003963346,0.000010432091,0.001351383,0.00022177548,0.00072992156,0.0001597851,0.99725646,0.00016206955,0.00010421534],"genre_scores_gemma":[8.982557e-7,0.000066217224,0.00000854896,0.0016176866,7.2139215e-7,0.0000027424767,0.99830294,7.3414452e-9,2.471494e-7],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99824107,0.00009364764,0.00037759688,0.00028493776,0.00074471364,0.00025802932],"domain_scores_gemma":[0.9983836,0.000017183103,0.0003297876,0.0009270566,0.00018513521,0.00015727853],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00032035343,0.00023021405,0.00021980416,0.00013297144,0.00044393307,0.00045432732,0.0020740612,0.00014758609,0.019581625],"category_scores_gemma":[0.000117880154,0.00025123986,0.0001256302,0.0007686452,0.00007825476,0.0021648752,0.0017654526,0.00026367116,0.07176742],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000042156566,0.00003813698,0.00009849676,0.000055475546,0.000016247424,0.000002788425,0.000034067212,0.000024576984,4.0399915e-9,0.000006600334,0.9983674,0.0013519913],"study_design_scores_gemma":[0.00019372068,0.000028901932,0.000009995538,6.9447e-7,0.000017431585,0.0000050551407,0.000051668765,0.000009617061,4.869324e-7,0.000002350257,0.99941623,0.00026387168],"about_ca_topic_score_codex":0.00017149045,"about_ca_topic_score_gemma":0.0000046175546,"teacher_disagreement_score":0.052185792,"about_ca_system_score_codex":0.0003043273,"about_ca_system_score_gemma":0.0002283184,"threshold_uncertainty_score":0.999994},"labels":[],"label_agreement":null},{"id":"W6926408855","doi":"10.25316/ir-11180","title":"The Nanaimo Free Press [Saturday, July 29, 1876]","year":2019,"lang":"en","type":"other","venue":"VIUSpace (Vancouver Island University Library)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"","score_opus":0.008360355994042888,"score_gpt":0.19969319990664047,"score_spread":0.19133284391259758,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6926408855","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[2.1645809e-7,0.00043923064,0.028567784,0.0010975561,0.0018034402,0.00028155776,0.00034300424,0.00061176025,0.96685547],"genre_scores_gemma":[0.000020264146,0.0017864832,0.0017898199,0.00035748997,0.00020877075,4.3311303e-7,0.000019303758,0.00014082363,0.99567664],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99820966,0.00013481993,0.0001451484,0.0006287459,0.0004610824,0.00042052928],"domain_scores_gemma":[0.9974063,0.000110520465,0.00029506686,0.001996183,0.000033008335,0.00015891116],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00005799386,0.0003657486,0.00033118261,0.00025498652,0.00026657197,0.00047086665,0.0040475293,0.00030523207,0.00016917082],"category_scores_gemma":[0.000021162714,0.00028821224,0.00016304417,0.0005779678,0.00012377638,0.0011064565,0.0018233693,0.00036258285,0.00033718554],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008477394,0.000029651352,0.000005945876,0.000035718356,0.000088813955,0.00004199313,0.00010311663,0.000011299987,3.0997106e-7,0.031157576,0.9680524,0.0004646896],"study_design_scores_gemma":[0.00066738937,0.000035105997,0.0000048763163,0.00009500767,0.00003686662,9.906514e-7,0.000076460434,0.001712124,0.000017936842,0.00021397247,0.9967235,0.00041576795],"about_ca_topic_score_codex":0.00024463746,"about_ca_topic_score_gemma":0.053625636,"teacher_disagreement_score":0.053381,"about_ca_system_score_codex":0.000038577917,"about_ca_system_score_gemma":0.0002341807,"threshold_uncertainty_score":0.999957},"labels":[],"label_agreement":null},{"id":"W6929220506","doi":"10.47670/wuwijar201821mnha","title":"The influence of training courses, customer relationship, and human resource management on customer focus among construction companies","year":2018,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wycliffe College","funders":"","keywords":"Customer relationship management; Customer intelligence; Enterprise relationship management; Human resource management; Customer advocacy; Focus (optics); Human resources; Voice of the customer","score_opus":0.1811701358245901,"score_gpt":0.5058071835063889,"score_spread":0.3246370476817988,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6929220506","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96516067,0.00067287224,0.007241181,0.00023152212,0.00026136564,0.00040201578,0.0000180298,0.00006216296,0.025950197],"genre_scores_gemma":[0.99834317,0.0005021668,0.00065603247,0.0001287156,0.000055453427,0.000007723012,0.000004030527,0.000014635523,0.00028808427],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99790734,0.0002387239,0.0006605806,0.00033088788,0.0006236575,0.0002388311],"domain_scores_gemma":[0.9978545,0.00032501278,0.00082847785,0.00055984757,0.0003016366,0.00013054785],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0012419946,0.00018330234,0.00032617158,0.0005601629,0.0007801636,0.0012724096,0.0021986205,0.00005500225,0.00014610418],"category_scores_gemma":[0.00012153464,0.00014534836,0.000058943035,0.0010420848,0.000776425,0.0019071134,0.000801379,0.00021680117,0.00001059619],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006704031,0.00017476473,0.57775354,0.00008008208,0.00028972383,0.00001340812,0.0018927462,0.0018753533,0.0013790557,0.3508748,0.025401618,0.040197894],"study_design_scores_gemma":[0.0004312535,0.000021659795,0.9634056,0.00043772435,0.00006058318,0.0000103238135,0.0007330771,0.0012672275,0.0010021188,0.0077571706,0.024596058,0.00027721425],"about_ca_topic_score_codex":0.0001300749,"about_ca_topic_score_gemma":0.000046050103,"teacher_disagreement_score":0.38565207,"about_ca_system_score_codex":0.00003890354,"about_ca_system_score_gemma":0.00004062869,"threshold_uncertainty_score":0.9997644},"labels":[],"label_agreement":null},{"id":"W6929702660","doi":"10.48550/arxiv.0811.1994","title":"Optical Images of an Exosolar Planet 25 Light Years from Earth","year":2008,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Herzberg Institute of Astrophysics","funders":"","keywords":"Planet; Exoplanet; Starlight; Jupiter (rocket family); Brightness; Galilean moons; Orbit (dynamics); Spitzer Space Telescope; Telescope; Flux (metallurgy)","score_opus":0.05149097148767367,"score_gpt":0.19984013334953682,"score_spread":0.14834916186186314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6929702660","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38431147,0.00006369054,0.60831314,0.00006653785,0.000489812,0.00017927849,0.00057080574,0.00027847633,0.0057267803],"genre_scores_gemma":[0.99171335,0.00041079108,0.006482767,0.00008466345,0.00005518943,9.6290925e-8,0.00048872974,0.00001266996,0.0007517306],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99874425,0.00008660602,0.00018064272,0.00067863974,0.000120001765,0.00018985869],"domain_scores_gemma":[0.9984695,0.000043028744,0.00016678788,0.0010741454,0.00007304397,0.00017354265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000081481776,0.00018062508,0.0002780668,0.00017401761,0.000050952967,0.00008296079,0.0015647827,0.00018692172,0.00006744014],"category_scores_gemma":[0.000017029026,0.00021343137,0.00007949856,0.0002742034,0.00012424708,0.00039413007,0.0011491181,0.00026819226,0.00012196679],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011155601,0.0017870268,0.0061902823,0.00021253023,0.00069956575,0.0073267426,0.0018794058,0.16963224,0.0015309587,0.7884499,0.018078668,0.004101133],"study_design_scores_gemma":[0.0009487361,0.00016359653,0.012657271,0.00012600834,0.00012446548,0.000012463708,0.00009137176,0.95429844,0.0025496746,0.012823988,0.015292847,0.00091112056],"about_ca_topic_score_codex":0.00018432757,"about_ca_topic_score_gemma":0.000026267664,"teacher_disagreement_score":0.78466624,"about_ca_system_score_codex":0.000022053055,"about_ca_system_score_gemma":0.00013117926,"threshold_uncertainty_score":0.87034786},"labels":[],"label_agreement":null},{"id":"W6930423125","doi":"10.5281/zenodo.12066412","title":"Iso 2758 pdf","year":2024,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Limiting; Nucleofection; Subpoena; Work (physics)","score_opus":0.03542749468484255,"score_gpt":0.2788053372452136,"score_spread":0.24337784256037107,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6930423125","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[2.1749591e-7,0.0002641795,0.12806371,0.0005502104,0.00030873276,0.00017757433,0.00017694864,0.002332814,0.8681256],"genre_scores_gemma":[0.000117419804,0.00026898188,0.0013317391,0.00040097485,0.00033988312,1.6115573e-8,0.0019746153,0.0056702024,0.9898962],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982348,0.00016494798,0.00021610135,0.0006295647,0.00044283364,0.00031176154],"domain_scores_gemma":[0.9986302,0.00000700805,0.00011577148,0.00089878397,0.00017416516,0.00017407448],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003434365,0.00020036536,0.0001798539,0.00053943665,0.00045177786,0.0023699065,0.0025576907,0.00012659744,0.081966795],"category_scores_gemma":[0.00017527114,0.0002055988,0.00006982823,0.00088591815,0.00009457088,0.00019096196,0.002514278,0.00028202208,0.3322742],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.201003e-7,0.00003776896,3.498372e-8,0.000095964155,0.00003908585,0.000020951284,0.00014067043,0.0000014974424,0.00002190178,0.06703121,0.9116458,0.020964162],"study_design_scores_gemma":[0.00012626094,0.000054537453,0.0000012159709,0.000114713264,0.000014263194,0.000044506767,0.000025013387,0.0020702141,0.000015341622,0.0005289151,0.99677664,0.00022837611],"about_ca_topic_score_codex":0.000009333107,"about_ca_topic_score_gemma":3.9220845e-7,"teacher_disagreement_score":0.2503074,"about_ca_system_score_codex":0.0000721696,"about_ca_system_score_gemma":0.000005594685,"threshold_uncertainty_score":0.99866575},"labels":[],"label_agreement":null},{"id":"W6931018691","doi":"10.5281/zenodo.15836687","title":"Fig. 3 in New and little-known Canadian LasIOGLOssum (DIaLICTus) (Hymenoptera: Halictidae) and an emended key to species","year":2021,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Key (lock); Taxonomy (biology); Scale (ratio); Habitus","score_opus":0.04116046821609008,"score_gpt":0.2746834689890475,"score_spread":0.2335230007729574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931018691","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00017932488,0.0004111214,0.01234971,0.002813334,0.00020447368,0.00051701354,0.0005157272,0.0005586599,0.98245066],"genre_scores_gemma":[0.007391324,0.0015484444,0.0064981766,0.0029290356,0.0008645624,1.11948765e-7,0.0060089203,0.0044199913,0.9703394],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982258,0.00021955359,0.00022067453,0.0006673617,0.00028376607,0.00038281],"domain_scores_gemma":[0.99845403,0.000008499586,0.00007476274,0.0006202177,0.00014066981,0.000701829],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00028333112,0.00020918265,0.00022711123,0.00078826526,0.00046998827,0.002142231,0.0010422108,0.00011385676,0.013107129],"category_scores_gemma":[0.00022014917,0.0002343314,0.00001942667,0.00081675104,0.00006811592,0.00023501141,0.0012744823,0.00018479297,0.00071976875],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000032376945,0.000038726183,0.000017609063,0.000052042345,0.000024057543,0.000042385484,0.0018196986,0.0000034512013,0.00008031102,0.03269229,0.93592316,0.029303007],"study_design_scores_gemma":[0.0002841382,0.000090622096,0.0005253052,0.00010529495,0.000005539725,0.000025807023,0.000111300986,0.0006370728,0.000017379414,0.00006823632,0.9978786,0.0002507086],"about_ca_topic_score_codex":0.006179297,"about_ca_topic_score_gemma":0.004899513,"teacher_disagreement_score":0.06195541,"about_ca_system_score_codex":0.00011854997,"about_ca_system_score_gemma":0.000040331473,"threshold_uncertainty_score":0.9988936},"labels":[],"label_agreement":null},{"id":"W6931242359","doi":"10.5281/zenodo.6277593","title":"Geostiba","year":2002,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Aedeagus; Spermatheca; Arthropod mouthparts; Appendage; Seta","score_opus":0.05659568807957787,"score_gpt":0.2611329920433998,"score_spread":0.20453730396382191,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931242359","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00058234547,0.00009912874,0.6308461,0.0027995103,0.00015996145,0.00019593928,0.00008007761,0.0020777122,0.36315924],"genre_scores_gemma":[0.96744007,0.00045915332,0.008932537,0.0030685093,0.00038400877,2.906937e-8,0.0016939184,0.001860924,0.016160833],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99883926,0.00013509339,0.00016188742,0.00031351158,0.00029849296,0.00025172628],"domain_scores_gemma":[0.998945,0.000012440527,0.000057507852,0.0005584269,0.00027911656,0.00014750217],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00029295468,0.000086043285,0.00007948836,0.00016534355,0.0012636012,0.0012693722,0.0017089356,0.000032056778,0.012616687],"category_scores_gemma":[0.00030594392,0.0000899345,0.00003181917,0.0007003153,0.0000636832,0.0005094657,0.001211535,0.000115771654,0.024191242],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000015723614,0.000119578144,0.0000016210163,0.000013901352,0.00001372658,0.000012868344,0.00067441096,0.00003656019,0.0003754222,0.13870315,0.6491708,0.21087639],"study_design_scores_gemma":[0.00018336538,0.00006237722,0.000066733584,0.0000072056177,0.0000026466776,0.00005286504,0.000029885114,0.047051594,0.00011623069,0.00029759968,0.95201945,0.00011004536],"about_ca_topic_score_codex":0.0000025779807,"about_ca_topic_score_gemma":4.561998e-8,"teacher_disagreement_score":0.96685773,"about_ca_system_score_codex":0.00004462301,"about_ca_system_score_gemma":8.4205584e-7,"threshold_uncertainty_score":0.9997674},"labels":[],"label_agreement":null},{"id":"W6931288534","doi":"10.5281/zenodo.4493322","title":"[FILMS VOIR] The Ice Road (2021) FILMS STREAMING VF EN GRATUIT ET VOSTFR zot","year":2021,"lang":"fr","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Dry ice; Ice stream; Iceberg; Video recording","score_opus":0.04635197044517007,"score_gpt":0.29042141373782965,"score_spread":0.2440694432926596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931288534","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0034114607,0.0049135415,0.51660794,0.0705142,0.003356099,0.0012300167,0.0028032702,0.0018235123,0.39533994],"genre_scores_gemma":[0.3660371,0.0147264805,0.021895966,0.017911278,0.0029341301,5.4105e-7,0.028149381,0.008842993,0.53950214],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9951928,0.0018819078,0.00050262833,0.0008721182,0.00084534206,0.0007051979],"domain_scores_gemma":[0.9964933,0.00013945907,0.00021976986,0.0013852275,0.0014341866,0.0003280594],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0017393386,0.0002997521,0.00025690658,0.00018382551,0.0028044716,0.0055314237,0.0028124305,0.00014229528,0.03365098],"category_scores_gemma":[0.0023107147,0.0002903264,0.00012890341,0.0022026913,0.0003142725,0.0011650812,0.0046291687,0.00067095784,0.016032808],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009923882,0.00032096292,0.0000045159713,0.000091919035,0.00009955706,0.00014607146,0.0047605657,0.00051828055,0.0012925634,0.17505173,0.5661944,0.25150952],"study_design_scores_gemma":[0.00040448166,0.00013204342,0.00033845607,0.00013551516,0.00004099201,0.00028717585,0.0019197623,0.05565043,0.0007290332,0.00029269635,0.9397493,0.000320118],"about_ca_topic_score_codex":0.000105474464,"about_ca_topic_score_gemma":0.0000080938225,"teacher_disagreement_score":0.494712,"about_ca_system_score_codex":0.00012786678,"about_ca_system_score_gemma":0.000058407422,"threshold_uncertainty_score":0.9999549},"labels":[],"label_agreement":null},{"id":"W6931293110","doi":"10.5281/zenodo.4213609","title":"globalbioticinteractions/globalbioticinteractions v0.19.4","year":2020,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Search engine indexing; Extension (predicate logic); Interface (matter); Prefix; Identification (biology)","score_opus":0.042520086963539275,"score_gpt":0.2966773307757311,"score_spread":0.25415724381219185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931293110","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[4.989865e-7,0.00012762968,0.2506106,0.0025767263,0.00048219768,0.00028866844,0.00060774287,0.0027645717,0.7425414],"genre_scores_gemma":[0.004798997,0.0018326394,0.019129695,0.0069036693,0.0022935546,1.2229202e-7,0.018793207,0.017211957,0.92903614],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977074,0.00028596108,0.00034617377,0.000775881,0.0004934311,0.0003911049],"domain_scores_gemma":[0.9980168,0.000024058618,0.0002875505,0.0009853345,0.00028194286,0.00040435037],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00020966264,0.00028938535,0.00027755357,0.0004648242,0.0011233418,0.0021274441,0.0028090838,0.00014871599,0.03661357],"category_scores_gemma":[0.00066513184,0.00031305425,0.0001162399,0.0011867577,0.000117382566,0.00038262727,0.002160828,0.00040220076,0.038809836],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004438453,0.00010571032,4.1122252e-7,0.000056426386,0.000082466126,0.000020418984,0.00013362146,0.000012858056,0.00006064829,0.050875384,0.934921,0.013726562],"study_design_scores_gemma":[0.00026649833,0.00009916938,0.000011953534,0.00009304813,0.000030990217,0.00013144291,0.00009437836,0.0047810497,0.000023934466,0.00013465996,0.9940294,0.00030346334],"about_ca_topic_score_codex":0.00007968565,"about_ca_topic_score_gemma":0.0000025221143,"teacher_disagreement_score":0.23148091,"about_ca_system_score_codex":0.00025522386,"about_ca_system_score_gemma":0.000015669535,"threshold_uncertainty_score":0.99993217},"labels":[],"label_agreement":null},{"id":"W6931466964","doi":"10.5281/zenodo.6132502","title":"Cliona lobata Hancock 1849","year":2014,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Shore; Lobata; Sieve (category theory); Smooth surface","score_opus":0.03815771310741739,"score_gpt":0.2706009940228726,"score_spread":0.23244328091545519,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931466964","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00045759615,0.00002052101,0.836323,0.0013196088,0.00015772777,0.00013250619,0.00005197738,0.0011888064,0.16034822],"genre_scores_gemma":[0.9693434,0.00016591138,0.012280883,0.003754552,0.0006353344,4.4562338e-8,0.003598718,0.0018498916,0.008371221],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984418,0.00026404043,0.0002133693,0.00040980632,0.0003794509,0.00029154593],"domain_scores_gemma":[0.9985445,0.000023282892,0.00008625395,0.00077780074,0.00038466626,0.00018346604],"candidate_categories":["sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00070117885,0.0001089933,0.00011060205,0.00019043805,0.0013215491,0.0014106948,0.0021982102,0.00004203017,0.0027522973],"category_scores_gemma":[0.0005985934,0.00011248976,0.000040285104,0.0007637717,0.00007980505,0.0005500337,0.0018135536,0.00013607256,0.015191596],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005042452,0.0001034947,0.000004150461,0.000024007135,0.00001534841,0.0000040708765,0.0003256991,0.00006927181,0.0005105781,0.3681983,0.4614692,0.16927083],"study_design_scores_gemma":[0.0002570156,0.00008987153,0.00017092265,0.000012836288,0.0000035615265,0.000032992128,0.000026139236,0.036497377,0.00021975348,0.0011354971,0.9614161,0.00013791854],"about_ca_topic_score_codex":0.0000041920925,"about_ca_topic_score_gemma":1.6598328e-7,"teacher_disagreement_score":0.96888584,"about_ca_system_score_codex":0.00005174241,"about_ca_system_score_gemma":0.0000032595049,"threshold_uncertainty_score":0.9999786},"labels":[],"label_agreement":null},{"id":"W6931601928","doi":"10.5281/zenodo.8189971","title":"Callinectes marginatus","year":2023,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Callinectes; Cape verde; Nova scotia; Clearance","score_opus":0.04883792224026125,"score_gpt":0.2849317317372655,"score_spread":0.23609380949700426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931601928","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00585188,0.000089888956,0.72553754,0.008189078,0.0005114702,0.0005332795,0.00032279443,0.012422917,0.24654114],"genre_scores_gemma":[0.95516133,0.00068544707,0.0072290557,0.002183831,0.00054387405,8.341218e-8,0.010060247,0.0029744206,0.021161713],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987624,0.00014119936,0.00015687494,0.00032604186,0.00031619793,0.00029723055],"domain_scores_gemma":[0.99896145,0.000022527285,0.000050437156,0.00050047605,0.0003281033,0.00013702689],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000498305,0.000086301334,0.00008392635,0.00028250884,0.0011889054,0.0011602056,0.0016418371,0.00003453843,0.002246146],"category_scores_gemma":[0.00047810454,0.0000894215,0.00003334874,0.0016356508,0.000057772126,0.00040133757,0.0016607344,0.000118304844,0.025212053],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000036585882,0.00006016222,0.000004647821,0.000027105161,0.000018065617,0.00002370335,0.000522851,0.00012612065,0.0011097039,0.20627685,0.67492217,0.11690496],"study_design_scores_gemma":[0.00017367867,0.00005041861,0.0004959468,0.000008877969,0.0000024163464,0.000023211185,0.000051211482,0.041455917,0.00021397829,0.00080062967,0.9566127,0.0001110184],"about_ca_topic_score_codex":0.0000035648877,"about_ca_topic_score_gemma":8.807825e-8,"teacher_disagreement_score":0.94930947,"about_ca_system_score_codex":0.000043274922,"about_ca_system_score_gemma":0.0000029642756,"threshold_uncertainty_score":0.9998767},"labels":[],"label_agreement":null},{"id":"W6931780212","doi":"10.5683/sp3/axpfzj","title":"Enquête sur la population active, décembre 2018 [Canada] [Remanié 2025]","year":2018,"lang":"fr","type":"dataset","venue":"Borealis","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Population; Research methodology; Publics; Social interest","score_opus":0.02946098449411472,"score_gpt":0.29321449507377234,"score_spread":0.2637535105796576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931780212","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000013285759,0.00015323306,0.006321276,0.0010871426,0.0014265976,0.0002862127,0.98779136,0.00007631213,0.0028445914],"genre_scores_gemma":[0.00005943881,0.00055404817,0.00071102247,0.0020003342,0.0010161684,0.000013281847,0.9874757,0.000043385415,0.00812661],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99612796,0.00041407422,0.00075332326,0.0010270417,0.0010324391,0.00064515753],"domain_scores_gemma":[0.99628484,0.00026486485,0.0006546608,0.0019222068,0.00048708767,0.00038635056],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004274602,0.0005961705,0.00060370105,0.00022702441,0.0003544204,0.00076094107,0.0019711128,0.00047376272,0.00036893628],"category_scores_gemma":[0.00044182857,0.0006282712,0.00015111866,0.00069166464,0.00019593495,0.0010682445,0.00075274706,0.00039080295,0.00015213457],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012390769,0.0001260909,0.000058278292,0.00014703596,0.00009723634,0.00009801406,0.000046389297,0.000024466188,0.0000015162896,0.00592569,0.989577,0.0038858713],"study_design_scores_gemma":[0.00033264514,0.00007541634,0.0038606126,0.0002616795,0.00012862997,0.00003524692,0.000013399062,0.015753608,0.000027567243,0.00023904003,0.9786027,0.0006694491],"about_ca_topic_score_codex":0.9346605,"about_ca_topic_score_gemma":0.95382553,"teacher_disagreement_score":0.019165086,"about_ca_system_score_codex":0.00037489744,"about_ca_system_score_gemma":0.0019499727,"threshold_uncertainty_score":0.99961686},"labels":[],"label_agreement":null},{"id":"W6931876535","doi":"10.5284/1126447","title":"Historic building recording at the Coach House, Wakes Colne Mills, Colchester Road, Wakes Colne, Colchester, Essex, CO6 2BY","year":2021,"lang":"en","type":"article","venue":"Archaeology Data Service","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Plan (archaeology); Period (music); Shot (pellet); Photography; Excavation; Roof; Quarter (Canadian coin); Plank","score_opus":0.054537151943566245,"score_gpt":0.3017980291435222,"score_spread":0.247260877199956,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931876535","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3228655,0.008077143,0.53704333,0.117306605,0.0073695825,0.0018065072,0.0023703552,0.0019133172,0.0012476876],"genre_scores_gemma":[0.75582856,0.0040096072,0.103924476,0.106361754,0.0012461402,0.00022919333,0.014165545,0.00043051474,0.013804235],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9959725,0.00062676735,0.0006785925,0.0014156519,0.0005223567,0.0007841313],"domain_scores_gemma":[0.9941125,0.0009704322,0.00036237456,0.0038795099,0.00043193187,0.00024326198],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0010164272,0.00040852313,0.00056051335,0.00015384078,0.00072102103,0.00021427842,0.004974671,0.00021426284,0.0001475818],"category_scores_gemma":[0.00034984286,0.00035267507,0.000077596786,0.0017274293,0.0003481681,0.0015197804,0.008762274,0.0003941094,0.00020289759],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002463406,0.0020291742,0.11346922,0.0015824427,0.0016569085,0.001718036,0.035103388,0.0013035409,0.024004927,0.21712105,0.5763889,0.025376085],"study_design_scores_gemma":[0.0012361319,0.00009888424,0.004559489,0.00011883739,0.00015816449,0.00042216128,0.0011783962,0.0956474,0.0036802304,0.0014455381,0.89061904,0.00083569734],"about_ca_topic_score_codex":0.001156152,"about_ca_topic_score_gemma":0.011197639,"teacher_disagreement_score":0.43311885,"about_ca_system_score_codex":0.0002255103,"about_ca_system_score_gemma":0.00039093476,"threshold_uncertainty_score":0.99989253},"labels":[],"label_agreement":null},{"id":"W6931884870","doi":"10.5683/sp3/7pwn0w","title":"MVSMMP Map 04 Landslide Susceptibility","year":2024,"lang":"en","type":"dataset","venue":"Borealis","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Western University","funders":"","keywords":"Landslide; Hazard; Hazard map; Yield (engineering); Landslide classification","score_opus":0.022369902281421765,"score_gpt":0.3074548530563111,"score_spread":0.2850849507748893,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931884870","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[9.0529866e-8,0.00014616737,0.009683628,0.0007852975,0.00060184335,0.000104072635,0.987877,0.00022302399,0.00057886716],"genre_scores_gemma":[0.0000013098235,0.00019004566,0.0008553234,0.0010693837,0.0003207485,0.000008118377,0.99694085,0.000013533981,0.0006006919],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99815774,0.00007397596,0.0003490156,0.00068278075,0.00045028195,0.0002861925],"domain_scores_gemma":[0.9976239,0.00005604012,0.00011168649,0.0019634317,0.00008857448,0.00015633716],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00036182057,0.0002677384,0.0003072292,0.00018992735,0.00006851546,0.00063834415,0.0018381655,0.00020991913,0.00015874043],"category_scores_gemma":[0.00009766666,0.00022950764,0.00013470813,0.00035602998,0.000051398216,0.00022283399,0.0007702365,0.00029482343,0.002128806],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.8486627e-7,0.000041282536,0.000005930453,0.00017714604,0.000028154163,0.000066996916,0.000020823183,0.0000015957364,3.185322e-7,0.0025783707,0.99645853,0.0006199931],"study_design_scores_gemma":[0.000077889665,0.000026366182,0.000018029694,0.0000707049,0.00004265065,0.0000062951526,0.000006051538,0.0011292419,0.0000060845696,0.0012755005,0.99707085,0.0002703382],"about_ca_topic_score_codex":0.004685188,"about_ca_topic_score_gemma":0.010567299,"teacher_disagreement_score":0.009063835,"about_ca_system_score_codex":0.00006324151,"about_ca_system_score_gemma":0.00018851687,"threshold_uncertainty_score":0.99864817},"labels":[],"label_agreement":null},{"id":"W6939025411","doi":"10.6084/m9.figshare.17073468.v1","title":"Additional file 3 of Improving 3D convolutional neural network comprehensibility via interactive visualization of relevance maps: evaluation in Alzheimer’s disease","year":2021,"lang":"en","type":"article","venue":"Figshare","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Visualization; Relevance (law); Interactive visualization; Convolutional neural network; Data visualization; Information visualization","score_opus":0.05986277659263135,"score_gpt":0.3244017688958645,"score_spread":0.26453899230323313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6939025411","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00002140071,0.0001673359,0.0034822463,0.000021455322,0.000056678397,0.00016635365,0.9958759,0.000025335323,0.00018331013],"genre_scores_gemma":[0.041363496,7.8640915e-7,0.003438579,0.00014599013,0.000055522945,0.00011687969,0.9548492,0.000006552396,0.000023006294],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985197,0.00020705536,0.00037955615,0.0003160928,0.00044490272,0.00013268368],"domain_scores_gemma":[0.9972006,0.0010627173,0.00033889047,0.00029926124,0.0010371164,0.00006141624],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000078213874,0.000097230164,0.00015318632,0.0000642954,0.000042034208,0.00003165841,0.00023255392,0.000038247825,0.7078885],"category_scores_gemma":[0.0042136186,0.00011060671,0.000059129965,0.0006099159,0.000016315445,0.00059035624,0.00023536559,0.00007278223,0.00006810937],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011571108,0.00012947136,0.00005363792,0.00006597494,0.00001595891,0.000003965084,0.000043157877,0.009478283,0.000014308415,0.00029543805,0.9818894,0.007998812],"study_design_scores_gemma":[0.00018938478,0.000016860236,0.01703609,0.0008528106,0.000010271081,0.0000017991202,0.000009751555,0.95752025,0.00006985667,0.0005110951,0.023676524,0.00010531737],"about_ca_topic_score_codex":0.0000037929958,"about_ca_topic_score_gemma":0.000024688426,"teacher_disagreement_score":0.9582129,"about_ca_system_score_codex":0.000055806635,"about_ca_system_score_gemma":0.00044659394,"threshold_uncertainty_score":0.50443995},"labels":[],"label_agreement":null},{"id":"W6939165614","doi":"10.60692/zvj1a-m9697","title":"Interactive visual analytics of moving passenger flocks using massive smart card data","year":2022,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network","funders":"","keywords":"Visual analytics; Visualization; Analytics; Data visualization; Flock; Metropolitan area; Bridge (graph theory); Transit (satellite)","score_opus":0.07044165868658721,"score_gpt":0.29040858098449257,"score_spread":0.21996692229790538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6939165614","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.058282975,0.0000019996787,0.9392774,0.000037363,0.0006227643,0.00018966453,0.00058494165,0.00012751606,0.0008753805],"genre_scores_gemma":[0.9967834,7.1548506e-8,0.0027529506,0.00015356822,0.000035063797,0.000006689976,0.00021102761,0.0000073434862,0.000049884864],"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99812466,0.00014908801,0.0007032487,0.00023151298,0.0005928835,0.00019863129],"domain_scores_gemma":[0.99807763,0.000018531147,0.0006443131,0.0009333977,0.0002528192,0.0000733065],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005512781,0.00014715364,0.00025387673,0.0004306582,0.0002390543,0.00027601724,0.0011151278,0.000036863454,0.000026238966],"category_scores_gemma":[0.000041965002,0.00014198662,0.000058464557,0.0007150067,0.00002136182,0.002429873,0.0017470042,0.00013421003,0.00005115334],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000228132,0.00011628451,0.25586116,0.0022015788,0.001736877,0.00011079543,0.48092508,0.22172208,0.00013075178,0.022426512,0.007618833,0.0069219167],"study_design_scores_gemma":[0.00031318577,0.00003253718,0.0009645103,0.000043636486,0.000032010037,0.000025920272,0.017568884,0.9797614,0.00019905632,0.0000010858106,0.0008981787,0.00015958899],"about_ca_topic_score_codex":0.000020755004,"about_ca_topic_score_gemma":2.0969738e-7,"teacher_disagreement_score":0.9385004,"about_ca_system_score_codex":0.00019521167,"about_ca_system_score_gemma":0.00012978668,"threshold_uncertainty_score":0.57900465},"labels":[],"label_agreement":null},{"id":"W6949424820","doi":"10.5281/zenodo.1478895","title":"Digital Elevation Models (Experimental Bed)","year":2018,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Flume; Digital elevation model; Elevation (ballistics); Sediment; Hydrology (agriculture)","score_opus":0.05284887825358298,"score_gpt":0.28411474113810053,"score_spread":0.23126586288451756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6949424820","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003412137,0.000021168275,0.78942794,0.00046587354,0.00012141448,0.00016895158,0.00008668561,0.0010772009,0.20521861],"genre_scores_gemma":[0.99504966,0.000009578096,0.0016222425,0.00037933566,0.00017475108,1.513837e-8,0.0010774237,0.00037509832,0.001311892],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988216,0.00007537884,0.00018191546,0.00034474453,0.00034239359,0.00023394596],"domain_scores_gemma":[0.9988719,0.00000792125,0.00006888778,0.00045737752,0.00046680903,0.00012709192],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00024171096,0.000096481715,0.00007723162,0.00016215252,0.001128917,0.0022380475,0.0012994686,0.000033804594,0.0019289154],"category_scores_gemma":[0.00013320055,0.000102079604,0.000030356583,0.0005952185,0.00012079021,0.0016141805,0.0012523519,0.00008155084,0.006962896],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020625155,0.00036484996,0.0000030959245,0.000015413012,0.000036135858,0.000007264926,0.0025360123,0.0000938179,0.0059159957,0.5393794,0.26552537,0.18610202],"study_design_scores_gemma":[0.00030033384,0.00023493063,0.00002437364,0.000010134174,0.0000024181145,0.000035690446,0.00012377655,0.12326905,0.0032754655,0.0014173518,0.87114453,0.00016194298],"about_ca_topic_score_codex":0.0000017216169,"about_ca_topic_score_gemma":4.016639e-8,"teacher_disagreement_score":0.9916375,"about_ca_system_score_codex":0.000073050964,"about_ca_system_score_gemma":0.000003519299,"threshold_uncertainty_score":0.99898344},"labels":[],"label_agreement":null},{"id":"W6949960900","doi":"10.5281/zenodo.3775610","title":"Census program data viewer, 2016 Census","year":2018,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Census; Geospatial analysis; Data visualization; Visualization; Product (mathematics); Presentation (obstetrics); Process (computing); Casual","score_opus":0.10622560777195553,"score_gpt":0.33977004938295574,"score_spread":0.23354444161100021,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6949960900","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00084078027,0.00031724063,0.61252874,0.005422356,0.0012402231,0.001540317,0.003625221,0.008954565,0.36553055],"genre_scores_gemma":[0.5510293,0.0030073903,0.21282719,0.011037346,0.0075256554,5.4060274e-7,0.16426842,0.012041184,0.03826295],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979857,0.00024366255,0.000266396,0.0006524502,0.00044077655,0.0004109891],"domain_scores_gemma":[0.9969846,0.000016520624,0.00011307997,0.0018472825,0.00081229606,0.00022623628],"candidate_categories":["sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007741439,0.00013903147,0.00012817934,0.00017438461,0.0016454136,0.0017663466,0.0047282223,0.00005047765,0.0018419483],"category_scores_gemma":[0.000645592,0.00013419859,0.000029296916,0.0010086425,0.00022841303,0.0007704906,0.005455066,0.00013183818,0.008920782],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000054406996,0.00013698917,6.361528e-7,0.000013699793,0.0000150718315,0.0000068204877,0.0001396336,0.0000010976063,0.00012656146,0.018753214,0.65636253,0.3244383],"study_design_scores_gemma":[0.00028002472,0.0002057876,0.00006257917,0.000022249653,0.0000072269463,0.000048384845,0.00004046306,0.029708186,0.00011054229,0.00021248497,0.96913576,0.0001663005],"about_ca_topic_score_codex":0.000008068694,"about_ca_topic_score_gemma":3.4844564e-7,"teacher_disagreement_score":0.55018854,"about_ca_system_score_codex":0.000055132186,"about_ca_system_score_gemma":0.000007427513,"threshold_uncertainty_score":0.9996543},"labels":[],"label_agreement":null},{"id":"W6957822053","doi":"10.6084/m9.figshare.19704006","title":"Additional file 2 of Sex differences in the aging murine urinary bladder and influence on the tumor immune microenvironment of a carcinogen-induced model of bladder cancer","year":2022,"lang":"en","type":"article","venue":"Figshare","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Bladder cancer; Multiplex; Immunofluorescence; Tumor microenvironment; Immune system; Antibody; Urinary Bladder Cancer","score_opus":0.043327740164504434,"score_gpt":0.2492710704475936,"score_spread":0.20594333028308917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6957822053","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0568565,0.000060643775,0.0000055912456,0.0001569876,0.000004141766,0.00012266438,0.942683,0.0000042830025,0.00010620725],"genre_scores_gemma":[0.95656306,0.000003968672,0.00009524827,0.00044879498,0.0000070211368,0.0003355326,0.042431705,0.000004556967,0.00011012357],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99918264,0.00007454568,0.00019747787,0.00015142775,0.00030134426,0.0000925523],"domain_scores_gemma":[0.9991011,0.00039850298,0.00018044133,0.0002770103,0.000028360166,0.000014560386],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00005042611,0.000075866235,0.00011462044,0.00005443388,0.000072967894,0.0000139813255,0.0005967733,0.000009772285,0.44690603],"category_scores_gemma":[0.000112048765,0.000050882136,0.00003077592,0.00019910731,0.000021692538,0.00008234042,0.00046592293,0.000099827026,0.0000049277915],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008220984,0.0004087505,0.00024331493,0.00012330768,0.000049395952,0.000009872336,0.0031829178,0.007408043,0.001920855,0.0002644596,0.9857567,0.0006241864],"study_design_scores_gemma":[0.00057940837,0.0004402925,0.1683655,0.0016947014,0.000018845076,0.000024247343,0.002089934,0.79497045,0.007612917,0.00031798187,0.023474049,0.00041166908],"about_ca_topic_score_codex":0.000024773275,"about_ca_topic_score_gemma":0.0000038890657,"teacher_disagreement_score":0.9622826,"about_ca_system_score_codex":0.000014919415,"about_ca_system_score_gemma":0.000071552895,"threshold_uncertainty_score":0.5535996},"labels":[],"label_agreement":null},{"id":"W6958114226","doi":"10.60692/ss3me-0ks67","title":"Awake Craniotomy in Africa: A Scoping Review of Literature and Proposed Solutions to Tackle Challenges","year":2023,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University Health Network; McGill University; University of British Columbia","funders":"","keywords":"Awake craniotomy; Craniotomy; Protocol (science); Systematic review; MEDLINE; Medical literature; Review article","score_opus":0.08357979944508691,"score_gpt":0.2833700268279988,"score_spread":0.19979022738291186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6958114226","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021410255,0.006794053,0.93687814,0.00831965,0.0012267475,0.0081392275,0.000569487,0.0022058156,0.014456623],"genre_scores_gemma":[0.99755424,0.0003332157,0.0015702463,0.0003568181,0.000020407651,0.000045787016,0.000032067812,0.0000056174595,0.000081584214],"study_design_codex":"qualitative","study_design_gemma":"systematic_review","domain_scores_codex":[0.99894166,0.00005825656,0.00048135995,0.00012919743,0.00021768139,0.00017185554],"domain_scores_gemma":[0.9993075,0.000008133041,0.00014728821,0.00030899848,0.00016455683,0.000063537125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062052644,0.0000893164,0.00020094798,0.00041944647,0.00005530987,0.00014466298,0.000230015,0.00004102106,0.0000017931034],"category_scores_gemma":[0.00005547964,0.00007410483,0.000026354997,0.0012478518,0.000010088713,0.0008502457,0.00017838956,0.000042483312,0.00012198304],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001120999,0.0000170218,0.00693081,0.20687161,0.000057848327,0.000023608358,0.6853701,0.0002792493,0.000008132692,0.08931938,0.0032382603,0.007872765],"study_design_scores_gemma":[0.0030868219,0.00024075761,0.03174987,0.71438986,0.000050605686,0.000104601815,0.01707534,0.22639446,0.0003704101,0.00006549214,0.0051001026,0.0013716937],"about_ca_topic_score_codex":7.15422e-7,"about_ca_topic_score_gemma":3.377317e-7,"teacher_disagreement_score":0.976144,"about_ca_system_score_codex":0.000023074199,"about_ca_system_score_gemma":0.00004382464,"threshold_uncertainty_score":0.30219072},"labels":[],"label_agreement":null},{"id":"W6958226083","doi":"10.6084/m9.figshare.17073474","title":"Additional file 5 of Improving 3D convolutional neural network comprehensibility via interactive visualization of relevance maps: evaluation in Alzheimer’s disease","year":2021,"lang":"en","type":"article","venue":"Figshare","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Relevance (law); Convolutional neural network; Visualization; Artificial neural network; Data visualization; Interactive visualization","score_opus":0.05985795858445674,"score_gpt":0.3245238747791893,"score_spread":0.26466591619473256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6958226083","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000021440532,0.00016799754,0.0034984206,0.000021561667,0.000056314708,0.00016673763,0.9958592,0.000025411919,0.00018289796],"genre_scores_gemma":[0.041915033,7.8624134e-7,0.0034412546,0.00014619612,0.000055011165,0.00011686268,0.9542959,0.0000065507293,0.000022426337],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99851936,0.00020719014,0.0003796693,0.00031615878,0.0004449013,0.00013269445],"domain_scores_gemma":[0.99721,0.0010632875,0.00033890727,0.0002993377,0.0010269961,0.000061421015],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000078307385,0.00009724515,0.00015324348,0.00006432039,0.00004205512,0.00003166102,0.00023263034,0.00003825248,0.70463383],"category_scores_gemma":[0.004175167,0.000110627814,0.000059141457,0.00061002455,0.000016318201,0.0005904343,0.00023545857,0.000072787996,0.00006642504],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000115302955,0.00012971234,0.000053649128,0.0000656059,0.000015980488,0.000003982814,0.00004323401,0.009476089,0.000014223277,0.00030582168,0.9818651,0.008015092],"study_design_scores_gemma":[0.00018875724,0.000016928587,0.017378477,0.0008559738,0.000010354048,0.00000181792,0.000009791559,0.9582109,0.00006908713,0.00051377167,0.022638716,0.000105441635],"about_ca_topic_score_codex":0.0000037934346,"about_ca_topic_score_gemma":0.000024862517,"teacher_disagreement_score":0.95922637,"about_ca_system_score_codex":0.0000556213,"about_ca_system_score_gemma":0.00044552074,"threshold_uncertainty_score":0.49983662},"labels":[],"label_agreement":null},{"id":"W6958265587","doi":"10.60692/v29rs-kwz75","title":"A randomised clinical trial of methotrexate points to possible efficacy and adaptive immune dysfunction in psychosis","year":2020,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Methotrexate; Placebo; Clinical trial; Psychosis; Immune system; Schizophrenia (object-oriented programming); Autoantibody; Randomized controlled trial","score_opus":0.10245571869634727,"score_gpt":0.32408222774880113,"score_spread":0.22162650905245385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6958265587","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20652863,0.0000016866128,0.79141355,0.00033824655,0.0003117481,0.00080282055,0.00002134994,0.00008377148,0.0004982051],"genre_scores_gemma":[0.9930652,5.9758946e-7,0.0063498323,0.0004991322,0.00003831274,0.000023054132,0.0000073280235,0.000003883695,0.000012659624],"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980474,0.00024303165,0.0011561813,0.00018801782,0.00023955833,0.00012577206],"domain_scores_gemma":[0.9990192,0.000041146253,0.00040206802,0.00027530242,0.00012448202,0.00013781353],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010918735,0.00011382747,0.00036431593,0.00022952251,0.00003697848,0.00014567103,0.00026695797,0.000067554975,0.0000045633938],"category_scores_gemma":[0.00020776577,0.00009502718,0.000069510934,0.0006632936,0.000017368999,0.0007724292,0.00012098932,0.00007355079,0.00011657873],"study_design_candidate":"randomized_trial","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.2798622,0.00021720777,0.054833047,0.0015302824,0.0007060442,0.000020725174,0.56693286,0.0022149994,0.000045784036,0.022157146,0.0021453432,0.06933439],"study_design_scores_gemma":[0.3921024,0.0016579145,0.049220048,0.00037145233,0.00005773782,0.0000063696166,0.0044049374,0.55083644,0.00043848305,0.0000072130447,0.00045595862,0.0004410539],"about_ca_topic_score_codex":0.0000055710593,"about_ca_topic_score_gemma":1.1910385e-7,"teacher_disagreement_score":0.7865366,"about_ca_system_score_codex":0.000020730206,"about_ca_system_score_gemma":0.00002945396,"threshold_uncertainty_score":0.38750958},"labels":[],"label_agreement":null},{"id":"W6958469702","doi":"10.6084/m9.figshare.21080580","title":"Additional file 2 of Single nucleotide polymorphism genes and mitochondrial DNA haplogroups as biomarkers for early prediction of knee osteoarthritis structural progressors: use of supervised machine learning classifiers","year":2022,"lang":"en","type":"article","venue":"Figshare","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"Haplogroup; Mitochondrial DNA; Human mitochondrial DNA haplogroup; Haplotype; Single-nucleotide polymorphism; Population; Gene; DNA sequencing","score_opus":0.036209172270510306,"score_gpt":0.23631111964314835,"score_spread":0.20010194737263803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6958469702","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005396003,0.0000794846,0.00005872053,0.000017629962,0.0000722198,0.00025016462,0.9940648,0.00003939753,0.000021555696],"genre_scores_gemma":[0.037119284,0.0000011552199,0.006747488,0.00003020294,0.00006985124,0.0002707005,0.9555607,0.000019653375,0.0001809672],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989712,0.00007401565,0.00029339956,0.00022844758,0.00030083928,0.0001320537],"domain_scores_gemma":[0.99889237,0.00043277748,0.00030212328,0.00016259318,0.00015417417,0.00005595484],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000023589542,0.00010116094,0.0001666448,0.00014752975,0.00013938824,0.00005695069,0.00022573896,0.000039873124,0.32857832],"category_scores_gemma":[0.0007608763,0.00010966559,0.00008180678,0.00028172103,0.000036903184,0.00044202316,0.00024699382,0.000067047455,0.0000030515714],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000119569544,0.00009592758,0.0002453088,0.000201471,0.00010362046,0.0000046785185,0.00042914806,0.00010831166,0.0053557255,0.00009781378,0.96456915,0.028669298],"study_design_scores_gemma":[0.0033623092,0.0048296577,0.007062803,0.0018088855,0.00005055213,0.000047112695,0.0003269355,0.32913366,0.005553023,0.00018011361,0.64712566,0.00051926717],"about_ca_topic_score_codex":0.000015733385,"about_ca_topic_score_gemma":0.000005047648,"teacher_disagreement_score":0.32902536,"about_ca_system_score_codex":0.000017934672,"about_ca_system_score_gemma":0.0000692242,"threshold_uncertainty_score":0.67203546},"labels":[],"label_agreement":null},{"id":"W6958964833","doi":"10.6084/m9.figshare.c.7591090","title":"Medical education videos – comparative analysis of sonography vs. clinical examination videos: user perception and educational value","year":2024,"lang":"en","type":"other","venue":"Figshare","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Quality (philosophy); Perception; Medical history; Physical examination; Resource (disambiguation); Video recording; Educational measurement","score_opus":0.060648365733233726,"score_gpt":0.41577289782579696,"score_spread":0.3551245320925632,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6958964833","genre_codex":"other","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00021476137,0.010077773,0.035684545,0.0068060895,0.0045369407,0.0031428346,0.3405949,0.0016131524,0.597329],"genre_scores_gemma":[0.01599591,0.000679341,0.010725484,0.0036135893,0.0018728012,0.00036366488,0.69484067,0.0002684477,0.27164006],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.997916,0.00023575075,0.0005160299,0.00059460994,0.00061160367,0.00012600928],"domain_scores_gemma":[0.9985751,0.00018655747,0.00039666795,0.00044747358,0.00021923262,0.00017499828],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00027525602,0.0002113399,0.00046307774,0.0012859658,0.000033781733,0.000179403,0.0005505945,0.00032170245,0.09694408],"category_scores_gemma":[0.00061149726,0.00020112252,0.00021698793,0.0016030817,0.000041509455,0.00023229173,0.00022534849,0.00021260986,0.00081371446],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.984033e-7,0.00016866165,0.00022785197,0.00020885126,0.00038951467,4.5540173e-7,0.00026238163,0.000002935406,2.1233502e-7,0.00575062,0.9872606,0.0057271332],"study_design_scores_gemma":[0.00014734086,0.000053474938,0.033687677,0.002975368,0.00050442404,0.0000028250317,0.000099454875,0.08643565,0.0000013185908,0.00023942426,0.87550116,0.00035188344],"about_ca_topic_score_codex":0.000031845586,"about_ca_topic_score_gemma":0.000087580316,"teacher_disagreement_score":0.3542458,"about_ca_system_score_codex":0.000032729826,"about_ca_system_score_gemma":0.0006028535,"threshold_uncertainty_score":0.9999643},"labels":[],"label_agreement":null},{"id":"W6958971095","doi":"10.6084/m9.figshare.c.4364690.v1","title":"Modeling gene-environment interactions in longitudinal family studies: a comparison of methods and their application to the association between the IGF pathway and childhood obesity","year":2019,"lang":"en","type":"other","venue":"Figshare","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Association (psychology); Genetic association; Longitudinal study; Gene–environment interaction; Longitudinal data; Random effects model; Twin study; Statistic; Attendance; Monozygotic twin","score_opus":0.11173223817561731,"score_gpt":0.38869279339101054,"score_spread":0.2769605552153932,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6958971095","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00070945505,0.008239469,0.9140872,0.0010892951,0.00017329182,0.0027550966,0.06857699,0.00013528047,0.0042339237],"genre_scores_gemma":[0.87611383,0.0020616397,0.040939678,0.0020991985,0.001372768,0.0014910997,0.054482862,0.0005166803,0.02092224],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99910593,0.00015236213,0.00022424897,0.00028579438,0.00013073705,0.00010092306],"domain_scores_gemma":[0.999022,0.0002723982,0.00025382335,0.00039042195,0.000034612163,0.000026757396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002680034,0.00013404348,0.00025831966,0.000087220236,0.00007268763,0.00006909906,0.00038265667,0.000060176088,0.000078304525],"category_scores_gemma":[0.00016870134,0.00008317188,0.000030521915,0.00016865558,0.0000051636234,0.000073130526,0.00046292588,0.00015581444,0.000044124074],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004815689,0.0006682013,0.029501839,0.0007830126,0.0014735854,5.5323693e-7,0.027932908,0.022254266,0.00008759778,0.0011362196,0.7223369,0.19382009],"study_design_scores_gemma":[0.0002573473,0.00004756338,0.033880796,0.0012422419,0.000052206306,8.6158826e-7,0.0011282695,0.6148621,0.000098989425,0.00012528778,0.34794825,0.0003561162],"about_ca_topic_score_codex":0.000034812558,"about_ca_topic_score_gemma":0.00008606339,"teacher_disagreement_score":0.87540436,"about_ca_system_score_codex":0.0000704291,"about_ca_system_score_gemma":0.00002384148,"threshold_uncertainty_score":0.3391651},"labels":[],"label_agreement":null},{"id":"W6959210818","doi":"10.1021/acs.est.4c12263.s001","title":"DiminishingMercuryBioaccumulation in Zooplanktonalong an Estuarine Salinity Gradient","year":2025,"lang":"en","type":"article","venue":"Figshare","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Bioaccumulation; Methylmercury; Estuary; Trophic level; Mercury (programming language); Zooplankton; Organic matter; Food web; Salinity","score_opus":0.05822701390219679,"score_gpt":0.3437889703168112,"score_spread":0.2855619564146144,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6959210818","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.106686674,0.0016244183,0.4184938,0.014079745,0.005041153,0.0057364893,0.2833907,0.0075240717,0.15742293],"genre_scores_gemma":[0.91786945,0.000002033603,0.0018227956,0.0012885594,0.000039182996,0.000027927043,0.07862315,0.0000064525475,0.00032042133],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992674,0.000045271827,0.00017864845,0.00024618537,0.00012806077,0.00013441639],"domain_scores_gemma":[0.9994182,0.000065550186,0.000048034446,0.00035514554,0.00006237561,0.00005067224],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008578737,0.00007824223,0.000088890476,0.0001554626,0.000058045604,0.00020741258,0.00053626235,0.000042968306,0.0024944944],"category_scores_gemma":[0.00040375537,0.000079694684,0.000022662858,0.0006232132,0.0000030779265,0.00064030825,0.00022933788,0.000083764266,0.00017377026],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018573346,0.0012600127,0.02956224,0.0004908104,0.00005024516,0.00014205117,0.0024691238,0.003922224,0.000058319045,0.2775962,0.54830766,0.13612255],"study_design_scores_gemma":[0.00046405641,0.00004452103,0.13860133,0.0006946037,0.0000038964863,0.0000027068468,0.000040345873,0.7790096,0.00024811932,0.0025972938,0.07802429,0.00026923252],"about_ca_topic_score_codex":0.000026637532,"about_ca_topic_score_gemma":0.00014526649,"teacher_disagreement_score":0.8111828,"about_ca_system_score_codex":0.00003293218,"about_ca_system_score_gemma":0.00006877761,"threshold_uncertainty_score":0.9984174},"labels":[],"label_agreement":null},{"id":"W6961425060","doi":"10.14288/1.0371413","title":"C.P.R. S.S. Princess Adelaide","year":2018,"lang":"en","type":"other","venue":"cIRcle (University of British Columbia)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"DOCK; Face (sociological concept); Period (music); Work (physics)","score_opus":0.010582456145934857,"score_gpt":0.20501622616960297,"score_spread":0.1944337700236681,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6961425060","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00045738468,0.00022870458,0.32112068,0.00010536787,0.00061056664,0.00024674562,0.00039833796,0.0006434066,0.6761888],"genre_scores_gemma":[0.0032340495,0.00039540723,0.010411518,0.00010655672,0.00010535499,1.4036817e-7,0.00007552943,0.00008059273,0.9855909],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99893486,0.000038100472,0.00009384122,0.0004613197,0.00028643204,0.00018547087],"domain_scores_gemma":[0.9989474,0.000010751431,0.00022866235,0.0006063418,0.00009669328,0.00011016319],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000093150775,0.000050449315,0.00025674616,0.000091688,0.00008913713,0.00020370068,0.001505939,0.0001773799,0.0014535257],"category_scores_gemma":[0.000013154011,0.00020445164,0.00009061246,0.00037736088,0.00023019795,0.0002428546,0.0004922355,0.00007565715,0.00046705222],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.4507867e-7,0.000044823475,0.0002639324,0.00006401563,0.000034069413,0.00006782014,0.00002339761,2.2209048e-7,8.7709736e-7,0.000064498425,0.86699224,0.13244385],"study_design_scores_gemma":[0.00043724861,0.00003725833,0.04703013,0.0004915481,0.000030395942,0.000025262461,0.00007015064,0.0015897156,1.4264506e-7,0.00026059174,0.94967854,0.00034904465],"about_ca_topic_score_codex":0.034038033,"about_ca_topic_score_gemma":0.25257778,"teacher_disagreement_score":0.31070918,"about_ca_system_score_codex":0.000027415406,"about_ca_system_score_gemma":0.0001092492,"threshold_uncertainty_score":0.99945927},"labels":[],"label_agreement":null},{"id":"W6963356793","doi":"10.20380/gi2021.31","title":"Contour Line Stylization to Visualize Multivariate Information","year":2021,"lang":"en","type":"article","venue":"Canada Human-Computer Communications Society","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Interpretability; Contour line; Geospatial analysis; Visualization; Clutter; Margin (machine learning); Pattern recognition (psychology); Data visualization; Spatial analysis","score_opus":0.037122818941651085,"score_gpt":0.3217405188139579,"score_spread":0.2846176998723068,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6963356793","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00035013826,0.000085286956,0.9908635,0.0071438323,0.00026991908,0.00017859256,0.00004672695,0.00018236884,0.0008796419],"genre_scores_gemma":[0.26885417,0.0001941131,0.6813549,0.04529692,0.00020265709,0.0000566917,0.0028110137,0.00003205356,0.0011974602],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983699,0.00016329723,0.0005279152,0.00027146577,0.00040342382,0.00026400815],"domain_scores_gemma":[0.99638337,0.00011744916,0.0001846023,0.0022704096,0.0008372956,0.00020688801],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025235838,0.00017826764,0.00020569767,0.0000636948,0.0006976887,0.00054542423,0.00195827,0.000071822746,0.00003908165],"category_scores_gemma":[0.00006060723,0.000203676,0.00009967159,0.0010136329,0.000042747815,0.0010018602,0.0014259818,0.00017953383,0.00002974576],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012045278,0.00022666687,0.00024455116,0.000057349975,0.00015875474,0.000004394705,0.0056057395,0.0031778298,0.00067507697,0.57734436,0.3897144,0.0227897],"study_design_scores_gemma":[0.00037327158,0.00001340506,0.0010071147,0.000030851552,0.000011824043,0.0000047449435,0.0001760611,0.5186798,0.0003711822,0.00033368636,0.47872868,0.0002693585],"about_ca_topic_score_codex":0.021250363,"about_ca_topic_score_gemma":0.04226896,"teacher_disagreement_score":0.57701063,"about_ca_system_score_codex":0.00032239282,"about_ca_system_score_gemma":0.00093642756,"threshold_uncertainty_score":0.9852672},"labels":[],"label_agreement":null},{"id":"W6968597373","doi":"10.5281/zenodo.3626744","title":"Interactive plots and the spectrum of data visualization","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Visualization; Data visualization; Scatter plot; Information visualization; Data point; Point (geometry); Interactive visualization","score_opus":0.07989669546639341,"score_gpt":0.30958038781046343,"score_spread":0.22968369234407002,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6968597373","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006510182,0.00005880379,0.97719765,0.007895318,0.000044067325,0.00026127035,0.00017561606,0.00039775795,0.013318473],"genre_scores_gemma":[0.9957223,0.00017729182,0.0011100412,0.0011625323,0.00008778582,1.0391964e-8,0.001361533,0.00028577013,0.00009272102],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988535,0.00027843265,0.00019166362,0.00031398764,0.00024292589,0.000119493336],"domain_scores_gemma":[0.9990182,0.00004138953,0.00012122152,0.0005415849,0.00019038816,0.00008724017],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048534566,0.00007008202,0.00010709506,0.00006920645,0.00053029653,0.0006283077,0.0020581086,0.000018861101,0.00056345307],"category_scores_gemma":[0.00072854833,0.00005648201,0.000015978405,0.00060721586,0.00016201386,0.00079702307,0.0035421762,0.000092751136,0.00038909575],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011863796,0.00011745495,0.0000069161015,0.00008725504,0.00008533563,0.000005329956,0.008616865,0.00006393012,0.000807381,0.7864517,0.12660384,0.07703537],"study_design_scores_gemma":[0.0008192107,0.000110396104,0.00011340144,0.000016623926,0.000012528078,0.000019005529,0.0002999918,0.31525624,0.00043655356,0.0007698114,0.6820478,0.00009847166],"about_ca_topic_score_codex":0.0000062138706,"about_ca_topic_score_gemma":1.3611417e-7,"teacher_disagreement_score":0.9950713,"about_ca_system_score_codex":0.000013816204,"about_ca_system_score_gemma":0.0000032502521,"threshold_uncertainty_score":0.6169416},"labels":[],"label_agreement":null},{"id":"W6968863970","doi":"10.5281/zenodo.4058838","title":"Silent Noise: Channel Noise in Visual Communications","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Visual communication; Noise (video); Communication design; Graphics; Channel (broadcasting); Fidelity; Communications system; Terminology","score_opus":0.07334605655952856,"score_gpt":0.3039716357720551,"score_spread":0.23062557921252655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6968863970","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036702123,0.0002266836,0.8644061,0.035356596,0.00017168334,0.00085373677,0.00026160033,0.002651378,0.092402],"genre_scores_gemma":[0.99353415,0.00022879943,0.0017171568,0.0023795003,0.00008858177,6.300273e-8,0.0013422676,0.00046916804,0.00024032197],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99851155,0.00029088143,0.00026744377,0.00036364485,0.00030617282,0.0002602917],"domain_scores_gemma":[0.99868554,0.000022858105,0.00008164064,0.00071292056,0.00027372077,0.00022333543],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00037796004,0.0001088475,0.0001231393,0.00018057524,0.0008473431,0.00083864026,0.002950192,0.000039793387,0.0009906637],"category_scores_gemma":[0.0004488474,0.00012111438,0.00003604727,0.0012447393,0.00009513932,0.0005076313,0.0033264863,0.00021726766,0.0051441737],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000068879344,0.0016385224,0.00005514413,0.00021480257,0.00008713947,0.00006534145,0.021266721,0.0017768199,0.010150883,0.28493586,0.46053705,0.21920285],"study_design_scores_gemma":[0.00039239263,0.0001185584,0.00035466428,0.000017162996,0.0000034968389,0.00001076007,0.00022364156,0.23202531,0.00020139279,0.00014273965,0.766356,0.00015390183],"about_ca_topic_score_codex":0.00001060365,"about_ca_topic_score_gemma":4.976571e-7,"teacher_disagreement_score":0.98986393,"about_ca_system_score_codex":0.00007519326,"about_ca_system_score_gemma":0.00000632523,"threshold_uncertainty_score":0.9999226},"labels":[],"label_agreement":null},{"id":"W6977314135","doi":"10.60692/cf5hs-0dy06","title":"Interactive visual analytics of moving passenger flocks using massive smart card data","year":2022,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network","funders":"","keywords":"Visual analytics; Visualization; Analytics; Data visualization; Flock; Metropolitan area; Bridge (graph theory); Transit (satellite)","score_opus":0.07044165868658721,"score_gpt":0.29040858098449257,"score_spread":0.21996692229790538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6977314135","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.058282975,0.0000019996787,0.9392774,0.000037363,0.0006227643,0.00018966453,0.00058494165,0.00012751606,0.0008753805],"genre_scores_gemma":[0.9967834,7.1548506e-8,0.0027529506,0.00015356822,0.000035063797,0.000006689976,0.00021102761,0.0000073434862,0.000049884864],"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99812466,0.00014908801,0.0007032487,0.00023151298,0.0005928835,0.00019863129],"domain_scores_gemma":[0.99807763,0.000018531147,0.0006443131,0.0009333977,0.0002528192,0.0000733065],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005512781,0.00014715364,0.00025387673,0.0004306582,0.0002390543,0.00027601724,0.0011151278,0.000036863454,0.000026238966],"category_scores_gemma":[0.000041965002,0.00014198662,0.000058464557,0.0007150067,0.00002136182,0.002429873,0.0017470042,0.00013421003,0.00005115334],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000228132,0.00011628451,0.25586116,0.0022015788,0.001736877,0.00011079543,0.48092508,0.22172208,0.00013075178,0.022426512,0.007618833,0.0069219167],"study_design_scores_gemma":[0.00031318577,0.00003253718,0.0009645103,0.000043636486,0.000032010037,0.000025920272,0.017568884,0.9797614,0.00019905632,0.0000010858106,0.0008981787,0.00015958899],"about_ca_topic_score_codex":0.000020755004,"about_ca_topic_score_gemma":2.0969738e-7,"teacher_disagreement_score":0.9385004,"about_ca_system_score_codex":0.00019521167,"about_ca_system_score_gemma":0.00012978668,"threshold_uncertainty_score":0.57900465},"labels":[],"label_agreement":null},{"id":"W6977433874","doi":"10.6084/m9.figshare.c.5058358","title":"Incidence, risk factors, and outcomes of early postoperative hyperglycemia in surgical patients: a protocol for a systematic review and meta-analysis","year":2020,"lang":"en","type":"other","venue":"Figshare","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Observational study; Incidence (geometry); Protocol (science); Randomized controlled trial; Cohort study; Meta-analysis; MEDLINE; Cohort","score_opus":0.0733675150401843,"score_gpt":0.3598377016094833,"score_spread":0.286470186569299,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6977433874","genre_codex":"dataset","genre_gemma":"protocol","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"protocol","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000013985343,0.0028628695,0.0005520926,0.00017762728,0.00000774607,0.27703586,0.7171044,0.00013381962,0.0021242276],"genre_scores_gemma":[0.00048807755,0.00018722775,0.005441296,0.0031776698,0.000032226253,0.838739,0.09766752,0.00043225312,0.053834777],"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","domain_scores_codex":[0.99859285,0.00018413045,0.000493805,0.00038636627,0.0002385322,0.000104302795],"domain_scores_gemma":[0.9986171,0.00021632716,0.00064842793,0.0003425686,0.0000997402,0.00007584995],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008242388,0.00024594166,0.001970249,0.00022026346,0.000021418193,0.00009113469,0.00038138358,0.000095565316,0.0071243197],"category_scores_gemma":[0.0011355334,0.00014855473,0.00029318934,0.00059031276,0.000008431563,0.00013930813,0.00023820471,0.00008742748,0.000011783308],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008838105,0.00020198138,0.007058485,0.48880106,0.041920338,0.000015285432,0.0006944193,0.0000020756759,2.1120941e-8,0.0004750101,0.460802,0.000020492873],"study_design_scores_gemma":[0.0069725537,0.0019362152,0.008762691,0.16256838,0.38547108,0.0000075876014,0.00009274727,0.013643225,0.000010404176,0.000097870034,0.4159938,0.0044434248],"about_ca_topic_score_codex":0.000047222777,"about_ca_topic_score_gemma":0.0000614897,"teacher_disagreement_score":0.61943686,"about_ca_system_score_codex":0.000010337455,"about_ca_system_score_gemma":0.00003830114,"threshold_uncertainty_score":0.9937833},"labels":[],"label_agreement":null},{"id":"W6979274797","doi":"","title":"Visualization Tasks for Unlabelled Graphs","year":2025,"lang":"en","type":"article","venue":"ArXiv.org","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Abstraction; Visualization; Task (project management); Data visualization; Graph; Context (archaeology); Taxonomy (biology); Task analysis","score_opus":0.037168547120492446,"score_gpt":0.3366041361288301,"score_spread":0.29943558900833767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6979274797","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027940027,0.00006471486,0.9688116,0.0008746173,0.0004232277,0.0001819074,0.000007525665,0.00019471359,0.0015016769],"genre_scores_gemma":[0.9842426,0.00006271027,0.004388728,0.004503928,0.00004363509,0.000031371455,0.00012669836,0.000012096607,0.006588191],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99917805,0.000032167813,0.00021465977,0.00028750364,0.0001108876,0.00017675002],"domain_scores_gemma":[0.9992671,0.00007071808,0.00006657702,0.00040440535,0.00014470772,0.000046484784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018077623,0.00009730549,0.00011926384,0.00017156395,0.00016150597,0.00010335999,0.00051355246,0.000050876897,0.000017152843],"category_scores_gemma":[0.00013877767,0.000093784685,0.000059627484,0.0009020811,0.000026443686,0.00030976947,0.00014094387,0.000037878533,0.00005523739],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000041113267,0.00008972676,0.061352156,0.000035529774,0.000032065705,9.912467e-7,0.00012036998,0.000036090343,0.0007078904,0.91224104,0.022698998,0.0026810542],"study_design_scores_gemma":[0.002736191,0.00016810474,0.04598488,0.00013025186,0.00008311987,0.0000019083855,0.000111552814,0.46967295,0.018936897,0.034231547,0.42727843,0.0006641436],"about_ca_topic_score_codex":0.0000061207415,"about_ca_topic_score_gemma":0.0000062081117,"teacher_disagreement_score":0.9644229,"about_ca_system_score_codex":0.000018513694,"about_ca_system_score_gemma":0.00006525309,"threshold_uncertainty_score":0.38244286},"labels":[],"label_agreement":null},{"id":"W6981101502","doi":"","title":"Développement d’un modèle calibré pour la simulation énergétique de serres et analyse des résultats à l’aide d’indicateurs de performance","year":2022,"lang":"fr","type":"other","venue":"Espace École de technologie supérieure (École de technologie supérieure)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Periodic system; Western europe; Building construction","score_opus":0.045218534095989124,"score_gpt":0.311800379866325,"score_spread":0.26658184577033583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6981101502","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15070267,0.002286349,0.8063351,0.020404348,0.0003727447,0.002231716,0.00050973555,0.010441886,0.006715482],"genre_scores_gemma":[0.8339299,0.0056154113,0.11740597,0.003406428,0.00017830692,0.001018502,0.00046073308,0.0007840679,0.037200667],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9884724,0.0012576262,0.001736163,0.0030837422,0.0014625873,0.0039874907],"domain_scores_gemma":[0.991968,0.0011174815,0.0016143222,0.004045861,0.00051445066,0.0007399129],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity"],"category_scores_codex":[0.003713688,0.0022413495,0.0018646823,0.0030364066,0.0013519558,0.0011888087,0.008219916,0.0041515185,0.0017510664],"category_scores_gemma":[0.005754481,0.0024621568,0.00069707975,0.0067723254,0.0019720471,0.0011421902,0.004969176,0.00494553,0.00030742632],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001471498,0.0015253853,0.1593914,0.00068698975,0.0007282505,0.002055263,0.0026837753,0.753635,0.0038584145,0.024673749,0.021585053,0.029029569],"study_design_scores_gemma":[0.0018759152,0.0007289581,0.013027788,0.00058562856,0.00044482647,0.0005313334,0.006516449,0.80267584,0.017261228,0.00799463,0.1457173,0.0026400979],"about_ca_topic_score_codex":0.0005679117,"about_ca_topic_score_gemma":0.0016337271,"teacher_disagreement_score":0.6889291,"about_ca_system_score_codex":0.0032040956,"about_ca_system_score_gemma":0.0041050515,"threshold_uncertainty_score":0.99994814},"labels":[],"label_agreement":null},{"id":"W6983855315","doi":"","title":"Fluss der Wahrheit","year":2011,"lang":"de","type":"other","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Derogation","score_opus":0.04057957183862051,"score_gpt":0.2931605992304606,"score_spread":0.25258102739184013,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6983855315","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[2.010824e-7,0.00040038975,0.45486587,0.00011996548,0.00096452446,0.00007958134,0.000016079079,0.00014294195,0.5434104],"genre_scores_gemma":[0.000082556464,0.0004403227,0.014386536,0.0029808434,0.00045106962,0.000002652872,0.00010090969,0.000114178336,0.9814409],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99820524,0.00006740452,0.0003338264,0.0006617059,0.00035151243,0.00038033415],"domain_scores_gemma":[0.99829686,0.000021975373,0.00019282801,0.0011791775,0.00009225327,0.0002169056],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00016492471,0.00034194393,0.00033009343,0.000247541,0.00007902292,0.00034986623,0.0016543973,0.00028162828,0.1499097],"category_scores_gemma":[0.000029715313,0.00028668588,0.00012606662,0.0004258879,0.00008855852,0.00019144965,0.0005846558,0.00016631733,0.11203664],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.928601e-7,0.00007815493,0.0000445816,0.000027515243,0.00009419099,0.0000135961445,0.00014998578,6.0587627e-7,0.0000019474096,0.27849498,0.713532,0.0075618606],"study_design_scores_gemma":[0.00016971907,0.000029469591,0.000030788844,0.00008029147,0.0000571443,0.0000039446522,0.0000102690465,0.018590648,0.000066329994,0.0006085837,0.9799312,0.0004216611],"about_ca_topic_score_codex":0.00010426143,"about_ca_topic_score_gemma":0.00006216459,"teacher_disagreement_score":0.44047934,"about_ca_system_score_codex":0.000022493132,"about_ca_system_score_gemma":0.00014520237,"threshold_uncertainty_score":0.9999585},"labels":[],"label_agreement":null},{"id":"W6986982193","doi":"","title":"THE ROLE OF EMOTION IN VISUALIZATION","year":2013,"lang":"en","type":"other","venue":"NC Digital Online Collection of Knowledge and Scholarship (The University of North Carolina at Greensboro)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Visualization; Perception; Cognition; Task (project management); Emotion perception; Emotion recognition; Psychological research; Key (lock); Emotion classification","score_opus":0.010970618252040886,"score_gpt":0.2326512820945135,"score_spread":0.22168066384247262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6986982193","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.72241855,0.009509501,0.031909022,0.0006220088,0.001283592,0.0035533635,0.0010919648,0.00040968004,0.22920233],"genre_scores_gemma":[0.89453804,0.0013529647,0.00019016572,0.00000997926,0.000045100034,4.6978155e-7,0.00018963171,0.00004076313,0.10363288],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989182,0.0001214168,0.00030828413,0.0002547907,0.0002642177,0.0001331163],"domain_scores_gemma":[0.99855727,0.00011100861,0.0005056789,0.00038322163,0.0003817687,0.00006106182],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017456064,0.00016765413,0.00030304713,0.0003787823,0.00017771145,0.000016312002,0.00062730676,0.00014124594,0.000024370927],"category_scores_gemma":[0.00009850143,0.00013887594,0.000102254715,0.0010306375,0.00022368724,0.00040903114,0.00034628992,0.00014912274,0.000012068381],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005775914,0.00032084607,0.95222723,0.00011436522,0.00007942731,0.0000014610927,0.00070268055,0.000023670254,0.000012382248,0.0042446326,0.009146522,0.033069003],"study_design_scores_gemma":[0.0010904447,0.00017886171,0.78243136,0.00020386843,0.000047778136,0.000005107793,0.000037890855,0.020090511,0.000055440814,0.00026171273,0.19538322,0.00021377935],"about_ca_topic_score_codex":0.00014444778,"about_ca_topic_score_gemma":0.005934434,"teacher_disagreement_score":0.1862367,"about_ca_system_score_codex":0.000069375616,"about_ca_system_score_gemma":0.00013941634,"threshold_uncertainty_score":0.56631964},"labels":[],"label_agreement":null},{"id":"W6991290012","doi":"","title":"Frecuencia de los eventos cerebro-vasculares determinados mediante estudio tomográfico en el hospital Vicente Corral Moscoso","year":2016,"lang":"es","type":"dissertation","venue":"Repositorio Institucional (Universidad de Cuenca)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Poison control; Residence; Nova scotia","score_opus":0.007537561954211544,"score_gpt":0.28493649395269904,"score_spread":0.2773989319984875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6991290012","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84420216,0.0011106787,0.12914482,0.0010015477,0.015411788,0.0014533743,0.00084363087,0.0005579939,0.006274024],"genre_scores_gemma":[0.98118114,0.0012207999,0.005264406,0.00026549012,0.0025545105,0.00004617106,0.0013415072,0.00013633809,0.007989635],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9937779,0.0004064079,0.0009222887,0.0016863681,0.0019504755,0.001256585],"domain_scores_gemma":[0.9954522,0.00026907367,0.0010198618,0.0012851149,0.0010599149,0.00091378804],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00054386596,0.0010213578,0.0009371777,0.0008820551,0.0011295958,0.0007955313,0.0028401138,0.0009910495,0.00011562895],"category_scores_gemma":[0.00041079568,0.0010728267,0.0007436724,0.0011972912,0.00020262887,0.00212808,0.0005772645,0.00083184324,0.00023702193],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013234741,0.0069401395,0.32828626,0.0050684735,0.007913593,0.026452472,0.06671052,0.0018391527,0.066911906,0.3883558,0.02596937,0.07422884],"study_design_scores_gemma":[0.018366735,0.004467362,0.44362947,0.029500531,0.005975471,0.0040185642,0.01764178,0.21815819,0.04023399,0.0036231251,0.19720225,0.01718252],"about_ca_topic_score_codex":0.00082923705,"about_ca_topic_score_gemma":0.00042513522,"teacher_disagreement_score":0.38473266,"about_ca_system_score_codex":0.0019047891,"about_ca_system_score_gemma":0.0032636682,"threshold_uncertainty_score":0.9991722},"labels":[],"label_agreement":null},{"id":"W6991697474","doi":"","title":"An IFLAS open lecture with Kate Rawles - The life cycle: a biodiversity bike ride","year":2018,"lang":"en","type":"other","venue":"Insight (University of Cumbria)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Wildlife; Endangered species; Adventure; Club; Biodiversity; Rainforest; Variety (cybernetics); Rhinoceros; Amazon rainforest","score_opus":0.02067241192109339,"score_gpt":0.24176444502876457,"score_spread":0.22109203310767117,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6991697474","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010428117,0.00027260985,0.48466069,0.0030538854,0.0006678511,0.0009529657,0.00046520174,0.00059806206,0.50828594],"genre_scores_gemma":[0.040108867,0.0015753085,0.06784107,0.007895894,0.0011084678,0.000001574588,0.0013223739,0.0004324924,0.87971395],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99869734,0.00014350888,0.000091205606,0.0005022699,0.0003663915,0.00019929133],"domain_scores_gemma":[0.9981603,0.00002833985,0.0003474403,0.0011221049,0.000169003,0.00017280279],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00015153486,0.00022309434,0.00034493662,0.00026003277,0.0003276068,0.00026706886,0.0042538154,0.00018546343,0.0011741084],"category_scores_gemma":[0.00001674997,0.00018519568,0.000064268985,0.0007669674,0.0004026975,0.0006709777,0.0010654585,0.00013718393,0.0003602565],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004113386,0.0001174534,0.00026745422,0.00003683976,0.00027596354,0.00005816624,0.0013981027,0.000035542816,0.000012283356,0.0060673435,0.99018407,0.0015056635],"study_design_scores_gemma":[0.0008963819,0.00015205222,0.00045994896,0.000103794104,0.000115785675,0.000005500034,0.00022831993,0.005670676,0.000021292053,0.00015475969,0.99185365,0.00033784058],"about_ca_topic_score_codex":0.00246121,"about_ca_topic_score_gemma":0.0043772785,"teacher_disagreement_score":0.41681963,"about_ca_system_score_codex":0.000025329648,"about_ca_system_score_gemma":0.0003126458,"threshold_uncertainty_score":0.99973893},"labels":[],"label_agreement":null},{"id":"W6995703818","doi":"","title":"Perspective-enabled story understanding","year":2017,"lang":"en","type":"dissertation","venue":"DSpace@MIT (Massachusetts Institute of Technology)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Work (physics); Context (archaeology); Key (lock); Exposition (narrative)","score_opus":0.035883841565155936,"score_gpt":0.3141430807917066,"score_spread":0.27825923922655066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6995703818","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0066426783,0.006605459,0.5331793,0.030413782,0.017491315,0.0022886377,0.00052059983,0.0050219367,0.39783633],"genre_scores_gemma":[0.80517614,0.0022097493,0.049206153,0.00038106134,0.0004357653,0.00013361167,0.0014262274,0.00027657466,0.14075473],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9972158,0.000043857148,0.0004987242,0.0010337995,0.0006627288,0.0005450913],"domain_scores_gemma":[0.9956415,0.00002871425,0.0012036926,0.0025087292,0.00049094774,0.00012636132],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003593676,0.00055350986,0.00082743645,0.0019872664,0.00074629363,0.0003013265,0.003899551,0.0010868652,0.00003827772],"category_scores_gemma":[0.00081105065,0.000580788,0.0002488322,0.0009792644,0.0004779689,0.001280936,0.0003322871,0.0010071374,0.00006242211],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016009735,0.00014631466,0.00019849552,0.00021103,0.00036054748,0.00009055712,0.0007887248,0.000025855239,0.0008462028,0.9706179,0.021458356,0.0052400013],"study_design_scores_gemma":[0.0020748246,0.0003160048,0.00051799783,0.0016249116,0.00038821757,0.000037328115,0.0074617052,0.0043494855,0.008292381,0.079867125,0.892881,0.002189055],"about_ca_topic_score_codex":0.000054310825,"about_ca_topic_score_gemma":0.0005875913,"teacher_disagreement_score":0.89075077,"about_ca_system_score_codex":0.00082531665,"about_ca_system_score_gemma":0.0007870639,"threshold_uncertainty_score":0.99966437},"labels":[],"label_agreement":null},{"id":"W6996970555","doi":"","title":"Teaching Data Preparation to Non-technical Audiences Using Tableau Prep Builder","year":2025,"lang":"en","type":"article","venue":"Journal of the Association for Information Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Analytics; Coding (social sciences); Visualization; Data visualization; Data analysis","score_opus":0.032841384410112986,"score_gpt":0.36632862558951135,"score_spread":0.3334872411793984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6996970555","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011005945,0.0000132855,0.9923401,0.0013904886,0.0017187305,0.00037204835,0.000030103369,0.000023055176,0.003011598],"genre_scores_gemma":[0.9754158,0.0000051454085,0.020064589,0.0011774075,0.00023113548,0.000009082686,0.0000328338,0.000004557363,0.0030594221],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99827045,0.00010596457,0.0008752165,0.000086334396,0.00053426565,0.00012775273],"domain_scores_gemma":[0.99711144,0.00015368588,0.0015484372,0.00045006763,0.0006958168,0.00004056764],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035904094,0.000072961215,0.00017112697,0.00024116659,0.00030451824,0.00075189245,0.0014473205,0.000067846704,3.4907396e-7],"category_scores_gemma":[0.0016175036,0.000052388918,0.00006801231,0.00053366646,0.000005566544,0.004618846,0.0003481419,0.00011609111,0.000005269448],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005656459,0.00014577791,0.0073806755,0.0003306646,0.00036358435,2.1884418e-7,0.005405828,0.20798716,0.0012204362,0.2558018,0.515362,0.0059452965],"study_design_scores_gemma":[0.0003228242,0.00003561186,0.0008079001,0.00017793049,0.000037900252,0.000007680032,0.00022442041,0.722882,0.00012209489,0.00022170598,0.27508026,0.00007972534],"about_ca_topic_score_codex":0.00002901364,"about_ca_topic_score_gemma":0.0000052885266,"teacher_disagreement_score":0.9743152,"about_ca_system_score_codex":0.00039249106,"about_ca_system_score_gemma":0.00029227135,"threshold_uncertainty_score":0.7250516},"labels":[],"label_agreement":null},{"id":"W6997200063","doi":"","title":"Virtual Reality Representation of Information Systems and Decision Rules: An Exploratory Technique for Understanding Data Knowledge Structure","year":2003,"lang":"en","type":"article","venue":"NPARC","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Variety (cybernetics); Virtual reality; Representation (politics); Information system; Information structure; Knowledge representation and reasoning; Complete information; External Data Representation","score_opus":0.12346938976993277,"score_gpt":0.3699426624617791,"score_spread":0.24647327269184632,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6997200063","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009014455,0.000010947536,0.9978289,0.000010328611,0.00012104255,0.0002512523,0.00018849366,0.000033704186,0.0006538936],"genre_scores_gemma":[0.9297975,0.000019306028,0.06968154,0.000020825606,0.000015486152,0.000007886818,0.00044886876,0.000004048369,0.0000045505585],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992498,0.00008235856,0.00026130013,0.00017859378,0.00015059634,0.00007731221],"domain_scores_gemma":[0.99897194,0.00010385293,0.00014104518,0.0006199737,0.00011353479,0.000049671162],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058075605,0.00006284408,0.00010624027,0.00011552379,0.00008192831,0.00014802374,0.00035988158,0.000052270632,0.0000025851577],"category_scores_gemma":[0.0002382239,0.000058038164,0.000009719465,0.00023416604,0.000029770643,0.0025194678,0.00012546725,0.000035685618,6.896871e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006163513,0.00001791281,0.000042839358,0.000054240223,0.000005383508,1.00517546e-7,0.0009566289,0.000082874794,0.0022910272,0.9868174,0.0019363093,0.0077891],"study_design_scores_gemma":[0.00068009464,0.00014962285,0.000056136672,0.00011693718,0.000016375569,0.000009523667,0.004185815,0.7689899,0.0067012855,0.21468785,0.004195671,0.00021078331],"about_ca_topic_score_codex":0.0000023436162,"about_ca_topic_score_gemma":0.0000081746475,"teacher_disagreement_score":0.92889607,"about_ca_system_score_codex":0.000038140603,"about_ca_system_score_gemma":0.00006796013,"threshold_uncertainty_score":0.23667277},"labels":[],"label_agreement":null},{"id":"W6997213347","doi":"","title":"Visualizing mutations of a virus sequence","year":2012,"lang":"en","type":"dissertation","venue":"Summit (Simon Fraser University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"BC Cancer Agency; Simon Fraser University","keywords":"Visualization; CONTEST; Domain (mathematical analysis); Benchmark (surveying); Data visualization; Information visualization; Sequence (biology)","score_opus":0.03118161942996087,"score_gpt":0.28897586199741004,"score_spread":0.25779424256744915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6997213347","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2948633,0.0012637796,0.5286843,0.000263615,0.005361806,0.0014530186,0.0014545191,0.0015391803,0.16511643],"genre_scores_gemma":[0.9573314,0.00031908066,0.0045478903,0.00013476095,0.00010259307,0.0000013806455,0.0039215954,0.00005059358,0.033590708],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986426,0.000087717715,0.00026239888,0.00037859156,0.00036179816,0.0002668706],"domain_scores_gemma":[0.9985796,0.000066074186,0.00038057825,0.0005366956,0.00028510715,0.00015194931],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00011924987,0.00022700576,0.0002865808,0.0007427999,0.00015691912,0.00007030365,0.001196821,0.00020631375,0.00012210396],"category_scores_gemma":[0.000043937882,0.00027404193,0.00014219369,0.0015077837,0.00005298986,0.0009920256,0.00012635173,0.00019458603,0.000096598545],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010388459,0.0011546323,0.06288886,0.0011272569,0.000649974,0.00034404802,0.0019081971,0.00039783877,0.001694996,0.8701589,0.032081768,0.027489614],"study_design_scores_gemma":[0.0022235955,0.00026906084,0.0035657114,0.0010143855,0.000900486,5.2139015e-8,0.05346556,0.026171375,0.0530603,0.0023480782,0.85412854,0.0028528562],"about_ca_topic_score_codex":0.00022088838,"about_ca_topic_score_gemma":0.015373846,"teacher_disagreement_score":0.86781085,"about_ca_system_score_codex":0.00009677445,"about_ca_system_score_gemma":0.00024905198,"threshold_uncertainty_score":0.99997115},"labels":[],"label_agreement":null},{"id":"W6997312888","doi":"","title":"Visual analytics of topics in twitter in connection with political debates","year":2017,"lang":"en","type":"article","venue":"Americanae (AECID Library)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Set (abstract data type); Field (mathematics); Interpretation (philosophy); Subject (documents); Filter (signal processing)","score_opus":0.018943090347646695,"score_gpt":0.2927752245635436,"score_spread":0.2738321342158969,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6997312888","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8908867,0.00001765593,0.0955662,0.008132248,0.00012569845,0.00013015076,0.0000064593078,0.00006912493,0.005065746],"genre_scores_gemma":[0.9930634,0.000015384647,0.0053864014,0.0011497602,0.00003852429,0.0000025694278,0.000010903171,0.000009620907,0.00032345366],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99901956,0.000045015113,0.0002582681,0.00024762403,0.00017116319,0.00025838954],"domain_scores_gemma":[0.9991633,0.00005044324,0.00015955503,0.00050972984,0.000023978964,0.00009294448],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006296488,0.000105909836,0.00022663784,0.00023475972,0.000046321882,0.00009997728,0.00066273886,0.00003629955,0.00004730415],"category_scores_gemma":[0.0000612133,0.000091928734,0.000028619921,0.00038048593,0.0001833523,0.0012245374,0.00021419991,0.000095413976,0.000007713623],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007669572,0.00010172268,0.90421915,0.000008971042,0.000009649229,0.000027606226,0.00009130711,0.000064989596,0.000016219257,0.092545606,0.00047067835,0.0024363983],"study_design_scores_gemma":[0.0005302167,0.0002153252,0.91650504,0.000044890443,0.0000060605307,0.0000036078018,0.00015218896,0.07802122,0.001728395,0.0014875211,0.0011028011,0.00020272243],"about_ca_topic_score_codex":0.004197065,"about_ca_topic_score_gemma":0.00014009057,"teacher_disagreement_score":0.102176666,"about_ca_system_score_codex":0.000021168738,"about_ca_system_score_gemma":0.0001011789,"threshold_uncertainty_score":0.63447344},"labels":[],"label_agreement":null},{"id":"W7008606283","doi":"","title":"In Brief: Canada-wide Environemental Standards: Ontario's Role","year":2000,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Identification (biology); Process (computing); Set (abstract data type); Work (physics)","score_opus":0.003397872184433572,"score_gpt":0.18134653594665928,"score_spread":0.1779486637622257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7008606283","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000009548162,0.000108675944,0.000015340294,0.00018121449,0.00017135353,0.00019461139,0.00040531674,0.00006407576,0.99884987],"genre_scores_gemma":[0.0001843395,0.000114693205,0.0009826473,0.0014535136,0.00003875777,0.000004421806,0.0002701427,0.000043823202,0.99690765],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9981579,0.00004570203,0.00056428334,0.00022915617,0.00072514964,0.00027778425],"domain_scores_gemma":[0.99904263,0.000038611586,0.00031906337,0.00044726738,0.00003915561,0.000113262475],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00014518126,0.00025923477,0.00032236907,0.000091931135,0.000041165742,0.00009402446,0.00068555656,0.00016969618,0.39368615],"category_scores_gemma":[0.000028329736,0.00027771608,0.000064437576,0.000013501684,0.00005266106,7.2721525e-7,0.00013849315,0.0002015829,0.0010199914],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000968647,0.00003141304,0.000011432214,0.000056103756,0.00002026629,0.00003296342,0.00014795014,0.00022884771,3.2085563e-8,0.00012437868,0.99840283,0.00093410735],"study_design_scores_gemma":[0.00042738722,0.000038866812,0.000019503605,0.000114534654,0.000009796075,0.000016923806,0.000035544912,0.00019175958,0.0000043649407,0.000007606476,0.9988485,0.00028524172],"about_ca_topic_score_codex":0.9243975,"about_ca_topic_score_gemma":0.9867503,"teacher_disagreement_score":0.39266616,"about_ca_system_score_codex":0.00031767317,"about_ca_system_score_gemma":0.00048272422,"threshold_uncertainty_score":0.9999675},"labels":[],"label_agreement":null},{"id":"W7008966180","doi":"","title":"Data visualization and crowdsourcing approaches for complex data analysis","year":2019,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Genome Canada","keywords":"Crowdsourcing; Visualization; Data visualization; Intuition; Field (mathematics); Perspective (graphical); Data mapping; Visual analytics","score_opus":0.15099181726312513,"score_gpt":0.3424816080636114,"score_spread":0.19148979080048625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7008966180","genre_codex":"methods","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08833443,0.003057772,0.51832914,0.00036291673,0.007372253,0.01181131,0.30377874,0.0043211714,0.062632255],"genre_scores_gemma":[0.44028112,0.00044296213,0.055234563,0.0007374172,0.00011607282,0.000062643354,0.49594185,0.00026341167,0.0069199754],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9944865,0.00029807258,0.0010127076,0.002779671,0.0008436514,0.00057935796],"domain_scores_gemma":[0.99236697,0.00036240186,0.0009089465,0.00573288,0.00035841198,0.0002704143],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0019759873,0.00066041487,0.0009845728,0.0009250165,0.0009873739,0.00091520004,0.0061796666,0.00046712614,0.00004620859],"category_scores_gemma":[0.0009925726,0.00070759543,0.0001729675,0.0020597475,0.000049119804,0.0037638748,0.0024854415,0.00042974885,0.00005093794],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005866005,0.00032234614,0.00013733841,0.0011448695,0.0021553766,0.000007899655,0.00003969534,0.00048274262,0.0008924737,0.8251718,0.00029894567,0.16928782],"study_design_scores_gemma":[0.00064429716,0.00005558431,0.0005612874,0.00011647159,0.001512625,0.0000050031567,0.00027552378,0.88534707,0.00039502291,0.0028606344,0.107239366,0.0009870889],"about_ca_topic_score_codex":0.00009305924,"about_ca_topic_score_gemma":0.0009552454,"teacher_disagreement_score":0.88486433,"about_ca_system_score_codex":0.00013054584,"about_ca_system_score_gemma":0.00008804843,"threshold_uncertainty_score":0.9995375},"labels":[],"label_agreement":null},{"id":"W7009038793","doi":"","title":"Determining curricular coverage of student contributions to an online discourse environment: Using latent semantic analysis to construct differential term clouds","year":2009,"lang":"en","type":"article","venue":"Scholarship at UWindsor (University of Windsor)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Nucleofection; Gestational period; Dysgeusia; TSG101; Diafiltration; Liquation; Emperipolesis; Proteogenomics; Triacetin","score_opus":0.03061299513902706,"score_gpt":0.312042107374481,"score_spread":0.28142911223545397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7009038793","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7059676,0.0000076235915,0.29324386,0.00020836208,0.000050793446,0.00016706125,0.0003167618,0.000027903832,0.000010025967],"genre_scores_gemma":[0.9927091,0.000012133353,0.0068848263,0.0001451099,0.000026408114,1.1901919e-7,0.00016473421,0.000007365498,0.000050200764],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979018,0.000190606,0.00034425006,0.0005583254,0.0006501938,0.0003548152],"domain_scores_gemma":[0.9982998,0.000031263473,0.00028869734,0.0007957495,0.00015785135,0.00042667045],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002888094,0.00022664512,0.0005215337,0.0006331386,0.00034144046,0.000098165416,0.0012042937,0.00009909622,0.00012491246],"category_scores_gemma":[0.0000327182,0.00026129695,0.0002598916,0.0011790285,0.00009820706,0.0008131022,0.00060933665,0.0001656797,0.000014548533],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000097247044,0.002214927,0.87276953,0.000032132146,0.0010957945,0.00016521242,0.0052727377,0.026718564,0.07638151,0.004480167,0.000019839359,0.010752309],"study_design_scores_gemma":[0.0010672996,0.00035200064,0.9598621,0.00007539172,0.00082585274,0.000008208387,0.00044368696,0.03553883,0.0013096206,0.000094640454,0.000039506762,0.0003828378],"about_ca_topic_score_codex":0.000023167735,"about_ca_topic_score_gemma":0.000049365994,"teacher_disagreement_score":0.2867415,"about_ca_system_score_codex":0.00017776372,"about_ca_system_score_gemma":0.00006147206,"threshold_uncertainty_score":0.9999839},"labels":[],"label_agreement":null},{"id":"W7016009670","doi":"","title":"Visualizing demographic evolution using geographically inconsistent census data","year":2018,"lang":"en","type":"other","venue":"OSF Preprints (OSF Preprints)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Census; Demographic analysis; Consistency (knowledge bases); Analytics; Population statistics; Visualization; American Community Survey","score_opus":0.04342359909440731,"score_gpt":0.31805291396311147,"score_spread":0.2746293148687042,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7016009670","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00007825648,0.000012830801,0.42666012,0.000092265516,0.0011257401,0.00060950767,0.00019529407,0.0007560798,0.5704699],"genre_scores_gemma":[0.0024121623,0.00051949045,0.06498814,0.00044416438,0.0006048543,0.000040357514,0.0010409822,0.0005211162,0.92942876],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9924567,0.0008219972,0.0008888546,0.0041934475,0.0009449513,0.00069405715],"domain_scores_gemma":[0.98549724,0.00017751748,0.00087994017,0.012802135,0.0002575121,0.0003856641],"candidate_categories":["metaepi_narrow","open_science","insufficient_payload"],"consensus_categories":["open_science","insufficient_payload"],"category_scores_codex":[0.0041640736,0.0006149869,0.00067629205,0.0011422437,0.0003190073,0.00059851486,0.007186556,0.0006339521,0.10581648],"category_scores_gemma":[0.0014915098,0.00068893295,0.00025955433,0.0013915721,0.00043219503,0.0005761682,0.010760665,0.00046408002,0.27350858],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001674739,0.00055242795,0.013272564,0.00030646997,0.0007084098,0.00005743062,0.00012580778,0.00010121054,0.00031904154,0.036809962,0.9408044,0.0069254804],"study_design_scores_gemma":[0.00040898484,0.0000014983724,0.0007651861,0.00052430696,0.00018628893,0.00005867028,0.000026713502,0.101502016,0.000037047506,0.0020871537,0.8935647,0.0008374225],"about_ca_topic_score_codex":0.0007407637,"about_ca_topic_score_gemma":0.0003110873,"teacher_disagreement_score":0.36167198,"about_ca_system_score_codex":0.00018604974,"about_ca_system_score_gemma":0.00036768537,"threshold_uncertainty_score":0.9995562},"labels":[],"label_agreement":null},{"id":"W7016094043","doi":"","title":"Virtualisation and Visualisation: Le conseil national de recherches Canada visualise le monde en 3D","year":2003,"lang":"fr","type":"article","venue":"NPARC","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Work (physics); Virtualization; Agency (philosophy)","score_opus":0.0758067683733469,"score_gpt":0.3229581226137875,"score_spread":0.24715135424044057,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7016094043","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016480105,0.0015206727,0.8018151,0.06088017,0.0016585918,0.0004344792,0.00025731523,0.0001699033,0.11678367],"genre_scores_gemma":[0.83162653,0.00067053555,0.06016686,0.009669844,0.00037339842,0.000028228793,0.00022495375,0.0000534219,0.09718623],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99722105,0.0010454949,0.00040637975,0.00044424826,0.00052033656,0.00036251],"domain_scores_gemma":[0.998388,0.00055998954,0.0001680459,0.00025762914,0.0003740813,0.00025227916],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0016441358,0.00021612155,0.00020885764,0.00010873055,0.00032321064,0.00038570454,0.0002989992,0.00017727537,0.000118189266],"category_scores_gemma":[0.0015435199,0.00026610683,0.000038687584,0.0005176754,0.00020456535,0.00088154123,0.000096917414,0.00020424252,0.000017747552],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004413578,0.00013112678,0.00014861592,0.000046491015,0.00003521901,0.000012967672,0.0020544897,0.0002768118,0.0015494386,0.8431692,0.14858869,0.0039825463],"study_design_scores_gemma":[0.00097549486,0.00005682025,0.00056967983,0.00007433709,0.000026846657,0.00009912699,0.00087941106,0.2997544,0.005700467,0.060505494,0.6308905,0.00046740065],"about_ca_topic_score_codex":0.0880998,"about_ca_topic_score_gemma":0.016462754,"teacher_disagreement_score":0.8151464,"about_ca_system_score_codex":0.000537038,"about_ca_system_score_gemma":0.025726419,"threshold_uncertainty_score":0.99997914},"labels":[],"label_agreement":null},{"id":"W7017573500","doi":"","title":"Batailles pour le logement au Québec","year":2020,"lang":"es","type":"article","venue":"Repositori UJI (Universitat Jaume I)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Order (exchange); Gestodene; Term (time)","score_opus":0.024140203364118453,"score_gpt":0.24839001706245498,"score_spread":0.22424981369833652,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7017573500","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06678053,0.00114371,0.7335802,0.14383636,0.0034829322,0.00056411896,0.00012225247,0.00076223636,0.049727675],"genre_scores_gemma":[0.9854642,0.000099216646,0.004097111,0.0011166057,0.0009518599,9.189692e-7,0.000045233464,0.00003042297,0.008194419],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99784267,0.00013151288,0.000314266,0.00075121946,0.00052222586,0.00043811955],"domain_scores_gemma":[0.9982993,0.000083219726,0.00025464268,0.0006323651,0.00024056117,0.0004899289],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012793553,0.00029549297,0.00033155415,0.00014705848,0.0006275896,0.0005651021,0.0013331157,0.000120972036,0.00007312407],"category_scores_gemma":[0.00006919573,0.0003416874,0.00019653987,0.0008499694,0.00010085504,0.0011047774,0.0009138596,0.00018669433,0.0007170722],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011851774,0.0008947898,0.041063175,0.0006135169,0.0011154322,0.002288287,0.024889603,0.0014285466,0.009244931,0.45946166,0.43668962,0.022191942],"study_design_scores_gemma":[0.0018573287,0.00052200287,0.0076002427,0.0002010233,0.00029786638,0.00004826086,0.009816994,0.18983562,0.0028753113,0.00011341991,0.7856849,0.0011470303],"about_ca_topic_score_codex":0.013777315,"about_ca_topic_score_gemma":0.0005960792,"teacher_disagreement_score":0.9186837,"about_ca_system_score_codex":0.00043126472,"about_ca_system_score_gemma":0.00207636,"threshold_uncertainty_score":0.9999035},"labels":[],"label_agreement":null},{"id":"W7018573875","doi":"","title":"Discourse lines:visualising current policy and media storylines of opportunity and disadvantage with narrative exploration maps","year":2023,"lang":"en","type":"article","venue":"Monash University Research Portal (Monash University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Impact","funders":"Paul Ramsay Foundation","keywords":"Disadvantage; Narrative; Visualization; Variety (cybernetics); Data visualization","score_opus":0.10863324711425529,"score_gpt":0.3768628613435764,"score_spread":0.2682296142293211,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7018573875","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9651942,0.00007398823,0.027407127,0.0023275635,0.00011932202,0.0004947043,0.00041116873,0.00028995576,0.0036819698],"genre_scores_gemma":[0.992885,0.0020091252,0.0005537838,0.000017786493,0.00006753482,2.4528427e-7,0.00037899936,0.000016563446,0.0040709674],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9979035,0.00031608995,0.00015380661,0.00051982,0.00071384927,0.00039290648],"domain_scores_gemma":[0.99828213,0.00025788008,0.0001401585,0.0003597379,0.00049746,0.00046261467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052217883,0.00018503834,0.00025255975,0.0017273125,0.0005873513,0.00009526828,0.00060699316,0.00006883169,0.000010898061],"category_scores_gemma":[0.00019789634,0.0001914286,0.00004392413,0.003282643,0.0008294096,0.0023246321,0.0010623127,0.00027640752,0.00000464712],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003363608,0.00064714125,0.022851989,0.00033912607,0.00020289907,0.0026084026,0.03347977,0.0002833851,0.0009583608,0.9048259,0.007130813,0.026335826],"study_design_scores_gemma":[0.009414962,0.0018221565,0.040884666,0.0010937657,0.00024794077,0.00007675774,0.59191597,0.09926029,0.0014294568,0.007270644,0.24375235,0.0028310677],"about_ca_topic_score_codex":0.00023241295,"about_ca_topic_score_gemma":0.00050758326,"teacher_disagreement_score":0.8975553,"about_ca_system_score_codex":0.000090681,"about_ca_system_score_gemma":0.0005513118,"threshold_uncertainty_score":0.7806232},"labels":[],"label_agreement":null},{"id":"W7021250161","doi":"","title":"New study commissioned on development of Quebec's lithium-ion battery industry - Quebec industry gears up and takes the lead in projects that improve the life cycle of batteries for the benefit of the Quebec economy","year":2018,"lang":"en","type":"other","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Lead (geology); Battery (electricity); Lead–acid battery; Work (physics); Product life-cycle management","score_opus":0.043253961138796634,"score_gpt":0.2889799250665924,"score_spread":0.24572596392779578,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7021250161","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.52572286,0.0024562285,0.15923052,0.10804727,0.010753673,0.048199683,0.0008967257,0.00079486426,0.14389819],"genre_scores_gemma":[0.2004786,0.00002172349,0.001389708,0.0027982104,0.0003233769,0.00017745377,0.000025295349,0.00017078833,0.79461485],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.998089,0.00018851417,0.0006586664,0.00043295755,0.00038718747,0.00024363294],"domain_scores_gemma":[0.9972476,0.00043447697,0.0008819876,0.0012715847,0.00010002778,0.0000643219],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007638126,0.00034011572,0.0004674708,0.00016487775,0.00018657913,0.00019968822,0.0019554284,0.00044890647,0.00018775085],"category_scores_gemma":[0.000100832876,0.00014904198,0.00008350891,0.00035510425,0.00036338047,0.00019807226,0.00063650956,0.0005033192,0.0000028616344],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016247974,0.0011606794,0.03046222,0.00077413715,0.0012214953,0.0000012556666,0.053063095,0.00013318457,0.00018768845,0.020135053,0.7610049,0.13169377],"study_design_scores_gemma":[0.0068752333,0.0009375994,0.14461051,0.004779203,0.00052176113,0.000006835068,0.116907485,0.012205877,0.03263025,0.0007006123,0.67748594,0.002338668],"about_ca_topic_score_codex":0.059739925,"about_ca_topic_score_gemma":0.32679975,"teacher_disagreement_score":0.65071666,"about_ca_system_score_codex":0.000058109323,"about_ca_system_score_gemma":0.0013477948,"threshold_uncertainty_score":0.94652134},"labels":[],"label_agreement":null},{"id":"W7023869676","doi":"","title":"Parametric t-distributed stochastic exemplar-centered embeddin","year":2017,"lang":"en","type":"article","venue":"NPARC","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Embedding; Parametric statistics; Contrast (vision); Benchmark (surveying); Noise (video); Artificial neural network; Function (biology); Visualization","score_opus":0.044060126299520976,"score_gpt":0.3240579896455671,"score_spread":0.2799978633460461,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7023869676","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0035588625,0.000008129803,0.9910195,0.0008561919,0.00032700357,0.000076116936,0.00006181448,0.0001242364,0.0039681466],"genre_scores_gemma":[0.99002445,0.000005251848,0.009124812,0.0002204479,0.000045974368,0.000004067396,0.000056074758,0.0000064829314,0.00051241694],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99903274,0.000026868945,0.00016823743,0.00028088503,0.000251856,0.00023943612],"domain_scores_gemma":[0.99844134,0.000042649397,0.00015283572,0.0011565798,0.0000795399,0.0001270756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016492383,0.00010284932,0.00013400246,0.0001050117,0.00034328413,0.00074915745,0.0016039379,0.000042661133,0.00012701182],"category_scores_gemma":[0.00046360827,0.00009709946,0.000048148606,0.00023013397,0.000055849763,0.0005068772,0.00042467777,0.00008038872,0.00024977163],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023416707,0.00068664283,0.002704373,0.000052973963,0.00012264817,0.00012815563,0.00039851508,0.0009136534,0.0028206583,0.71862453,0.18970846,0.083815955],"study_design_scores_gemma":[0.00095330697,0.000064535656,0.005902268,0.000037874153,0.000016226402,0.000017434533,0.00001735121,0.95905274,0.0007006147,0.01704629,0.015851073,0.0003403058],"about_ca_topic_score_codex":0.000006208683,"about_ca_topic_score_gemma":0.0000029878317,"teacher_disagreement_score":0.98646563,"about_ca_system_score_codex":0.000026223639,"about_ca_system_score_gemma":0.000042128326,"threshold_uncertainty_score":0.72241426},"labels":[],"label_agreement":null},{"id":"W7026644997","doi":"","title":"Anthropometric Visual Data Mining: A Content-Based Approach","year":2003,"lang":"en","type":"article","venue":"NPARC","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Feature (linguistics); Population; Point (geometry); Visualization; Anthropometry; Feature vector; Pattern recognition (psychology)","score_opus":0.14568125639653176,"score_gpt":0.3462819260031809,"score_spread":0.20060066960664916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7026644997","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010103867,0.000031249343,0.9788342,0.00018091172,0.00014942234,0.00006760054,0.000013775247,0.00010776429,0.019604657],"genre_scores_gemma":[0.6553526,0.000010002313,0.34276307,0.00093868846,0.00003063513,0.000003550022,0.00019534938,0.000011544495,0.0006945644],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987593,0.00008559464,0.00018418967,0.00042852198,0.00032189646,0.0002204649],"domain_scores_gemma":[0.9986968,0.00006485464,0.00007067212,0.0009879726,0.00006984504,0.000109875196],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037186148,0.00010122904,0.0001320577,0.00023563314,0.00009442108,0.00021001714,0.0012230178,0.000037141486,0.00013267389],"category_scores_gemma":[0.0003964518,0.000091298745,0.000026341206,0.0014335527,0.000060162267,0.0004193014,0.0002218021,0.000057719804,0.000056666624],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010634865,0.0033316007,0.00659738,0.00010299669,0.000104195424,0.00005337318,0.00036764375,0.00013625613,0.0058348905,0.7876805,0.12956579,0.06621473],"study_design_scores_gemma":[0.00060546974,0.00008199427,0.0000820819,0.0000073257347,0.000009766322,0.000007626932,0.00016095262,0.9608211,0.002145093,0.0001560324,0.035722375,0.0002002044],"about_ca_topic_score_codex":0.0000028244451,"about_ca_topic_score_gemma":6.6886224e-7,"teacher_disagreement_score":0.96068484,"about_ca_system_score_codex":0.00001581638,"about_ca_system_score_gemma":0.000118672244,"threshold_uncertainty_score":0.37230548},"labels":[],"label_agreement":null},{"id":"W7026861655","doi":"","title":"Blue Earth Selects DCO Energy, LLC as EPC Contractor for the Alberta Co-Generation Energy Plant","year":2014,"lang":"en","type":"other","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Earth (classical element); Energy (signal processing); Work (physics); Energy consumption; Power station","score_opus":0.018190700791596022,"score_gpt":0.26636635487134414,"score_spread":0.24817565407974812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7026861655","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[3.3251837e-7,0.00018006342,0.8485592,0.00040857514,0.0005781638,0.00012541276,0.000090808426,0.0001398237,0.14991763],"genre_scores_gemma":[0.0008453177,0.00035780453,0.0016860217,0.007093944,0.0011781299,0.000042181462,0.0015213911,0.0001354052,0.9871398],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99861646,0.00007286932,0.00025361677,0.00047474378,0.0002959486,0.00028637322],"domain_scores_gemma":[0.9986122,0.0002582613,0.00023940047,0.0007056841,0.00007424957,0.00011017654],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014891334,0.00027474327,0.0002748203,0.00013815385,0.00013390442,0.00041053595,0.00092143274,0.00021645265,0.0008695165],"category_scores_gemma":[0.00007383651,0.00018225098,0.00009660745,0.00016688292,0.00003619309,0.00011511454,0.00008476682,0.000063966305,0.0001314382],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012379733,0.000020088102,5.114489e-7,0.0000048931665,0.00004759105,5.6898006e-7,0.000017475477,0.00002437947,0.00005312546,0.44487447,0.550931,0.0040246863],"study_design_scores_gemma":[0.00021896405,0.00004864181,6.0300323e-7,0.000015074356,0.000018978806,0.0000049726946,0.0000018762668,0.2656186,0.002263111,0.000083702864,0.731514,0.00021149463],"about_ca_topic_score_codex":0.002600298,"about_ca_topic_score_gemma":0.018216165,"teacher_disagreement_score":0.84687316,"about_ca_system_score_codex":0.000016414357,"about_ca_system_score_gemma":0.00022213228,"threshold_uncertainty_score":0.9996988},"labels":[],"label_agreement":null},{"id":"W7028293166","doi":"","title":"Evaluation of Passive Microwave-Based Sea Ice Edge and Marginal Ice Zone","year":2024,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Sea ice; Sea ice concentration; Sea ice thickness; Drift ice; Antarctic sea ice; Arctic ice pack; Cryosphere; Polar","score_opus":0.019368576677802566,"score_gpt":0.25477288528984665,"score_spread":0.2354043086120441,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7028293166","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9663694,0.0007414717,0.028255215,0.0017216703,0.00068845635,0.00050971843,0.00021443075,0.00011098958,0.0013886683],"genre_scores_gemma":[0.6315827,0.0003663817,0.026560292,0.00014291039,0.0001105156,0.0000018553468,0.0047230707,0.000070923925,0.3364414],"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984388,0.00013846256,0.00014129617,0.00041187616,0.00071702217,0.00015258588],"domain_scores_gemma":[0.9984069,0.000038512022,0.00028808677,0.00035452383,0.00083369145,0.00007830808],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000470507,0.00017937984,0.00028529135,0.0003967961,0.000099122146,0.00006324371,0.0005171444,0.0001636523,0.00006331456],"category_scores_gemma":[0.000025920406,0.00020818271,0.00009461425,0.00044021467,0.00007911553,0.00034155423,0.00011333873,0.00014292834,0.000032620064],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005486686,0.0013466306,0.0010592274,0.011243686,0.0021954055,0.00028470164,0.49735776,0.0019878095,0.06672199,0.053530518,0.06027573,0.30344787],"study_design_scores_gemma":[0.0032367727,0.00041775522,0.0058993716,0.0018946293,0.0027493422,0.000008326814,0.08391009,0.87079704,0.024187652,0.0015638865,0.004211928,0.0011231996],"about_ca_topic_score_codex":0.003248376,"about_ca_topic_score_gemma":0.010119543,"teacher_disagreement_score":0.8688092,"about_ca_system_score_codex":0.00007911793,"about_ca_system_score_gemma":0.00038801713,"threshold_uncertainty_score":0.8489445},"labels":[],"label_agreement":null},{"id":"W7028771369","doi":"","title":"Identification of Accipiters in Ontario","year":2024,"lang":"en","type":"article","venue":"Digital Commons - University of South Florida (University of South Florida)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Nucleofection; Gestational period; TSG101; Dysgeusia; Liquation; Diafiltration; Emperipolesis; Triacetin; Durvalumab","score_opus":0.021278862002846233,"score_gpt":0.20914691337944633,"score_spread":0.1878680513766001,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7028771369","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.79403216,0.00003521955,0.2008626,0.00017563379,0.00038474423,0.00016823313,0.00048212742,0.00012384065,0.0037354678],"genre_scores_gemma":[0.9974522,0.000007650698,0.00070478773,0.0000066974167,0.000011864006,2.383784e-8,0.00009391513,0.000009184178,0.0017136879],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99847883,0.000039443883,0.0003000178,0.00045978816,0.00047622918,0.00024569203],"domain_scores_gemma":[0.99865735,0.000074048985,0.0002915568,0.00063798757,0.00020600141,0.00013304061],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002334582,0.00018797198,0.0003920238,0.00080059137,0.00013648675,0.00010521525,0.001499731,0.00012007904,0.00007303017],"category_scores_gemma":[0.000023724748,0.00026244193,0.00024721012,0.0012635348,0.0003331554,0.002109854,0.00066672574,0.00024399071,0.0000624659],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005885428,0.0007714205,0.40725225,0.0011796328,0.0009836429,0.0006030854,0.38823825,0.0037029518,0.0011696856,0.18194711,0.003447834,0.010115576],"study_design_scores_gemma":[0.00875535,0.0010425865,0.47471404,0.0023099917,0.00079999946,0.00002665873,0.2265997,0.23445337,0.0018645986,0.004859246,0.041111168,0.0034633172],"about_ca_topic_score_codex":0.002326432,"about_ca_topic_score_gemma":0.0042323996,"teacher_disagreement_score":0.23075041,"about_ca_system_score_codex":0.00017592382,"about_ca_system_score_gemma":0.0003151435,"threshold_uncertainty_score":0.9999828},"labels":[],"label_agreement":null},{"id":"W7029279829","doi":"","title":"Hurricane Irene (2011): Lessons for Achieving a Weather-Ready Nation","year":2013,"lang":"en","type":"article","venue":"University of New Hampshire Scholars Repository (University of New Hampshire at Manchester)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Storm surge; Storm; Flooding (psychology); National weather service; Service (business); Administration (probate law); Training (meteorology); Coastal flood; Natural disaster","score_opus":0.037847709679898076,"score_gpt":0.2423374730466844,"score_spread":0.20448976336678631,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7029279829","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4672234,0.00038493198,0.5138591,0.010340359,0.0005995617,0.0012849304,0.00009604844,0.00048736343,0.0057242936],"genre_scores_gemma":[0.78227293,0.00027559884,0.10002633,0.00036844314,0.0001876104,3.953971e-7,0.00023983525,0.000062415515,0.11656641],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99766135,0.00014580121,0.00033146996,0.00081467675,0.00059942075,0.00044726374],"domain_scores_gemma":[0.9969616,0.00017624296,0.00075798377,0.0010779627,0.0005077245,0.0005184739],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00027997588,0.000336148,0.00057064585,0.00036900002,0.0008432573,0.00015347672,0.0020698092,0.00026901305,0.00022798512],"category_scores_gemma":[0.000057230427,0.00045333346,0.00034205784,0.00053590146,0.00023310709,0.0032597207,0.0008851611,0.00025202899,0.00015680162],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010516269,0.0023460092,0.04101629,0.0014029746,0.0021395376,0.00044142653,0.06973555,0.001130729,0.15793154,0.06980012,0.47162008,0.18138412],"study_design_scores_gemma":[0.014156792,0.001561756,0.16172373,0.0011540231,0.0008879,0.00024654425,0.021192282,0.048670635,0.005503568,0.0024026807,0.7391788,0.0033213308],"about_ca_topic_score_codex":0.0022378415,"about_ca_topic_score_gemma":0.00030274398,"teacher_disagreement_score":0.41383278,"about_ca_system_score_codex":0.0003368018,"about_ca_system_score_gemma":0.00046745673,"threshold_uncertainty_score":0.99979186},"labels":[],"label_agreement":null},{"id":"W7032266414","doi":"","title":"Canada at war.","year":2014,"lang":"en","type":"article","venue":"QSpace (Queen's University Library)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Work (physics); Natural (archaeology); Identification (biology)","score_opus":0.005979710022161141,"score_gpt":0.17789665771306468,"score_spread":0.17191694769090354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7032266414","genre_codex":"commentary","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010953098,0.0000121462635,0.4334667,0.43722624,0.00088580645,0.00023046363,0.00011069755,0.0011722068,0.11594264],"genre_scores_gemma":[0.3577118,0.000097271775,0.015263656,0.007493697,0.0001122924,1.6768455e-7,0.00013244674,0.0000265982,0.6191621],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991031,0.00008089203,0.0000695111,0.00029165682,0.00022943136,0.00022539026],"domain_scores_gemma":[0.99915,0.000057506935,0.00006196029,0.00049762643,0.000024952837,0.00020800366],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002812586,0.00011193514,0.00011795382,0.00009568682,0.0001980171,0.00006658804,0.00096557994,0.000042670876,0.00020452357],"category_scores_gemma":[0.000016680628,0.00012240617,0.000038985094,0.00047897175,0.000033674565,0.001344265,0.0007555579,0.00007577917,0.000084283754],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000026158464,0.000012440502,0.004029179,0.0000065875874,0.000008407434,0.000032532454,0.00004820251,0.000053136657,0.0000011631959,0.094112225,0.90145576,0.000237726],"study_design_scores_gemma":[0.00017743658,0.000018955374,0.0020936183,0.0000074491186,0.0000052014693,2.4807798e-7,0.000041335683,0.0030311353,0.0006116308,0.00014712413,0.99369425,0.0001716186],"about_ca_topic_score_codex":0.23970057,"about_ca_topic_score_gemma":0.034333568,"teacher_disagreement_score":0.5032194,"about_ca_system_score_codex":0.000101651225,"about_ca_system_score_gemma":0.0003720913,"threshold_uncertainty_score":0.98328733},"labels":[],"label_agreement":null},{"id":"W7034344400","doi":"","title":"Swan River from St Georges Terrace, Perth, Western Australia","year":2004,"lang":"en","type":"other","venue":"ANU Open Research (Australian National University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Block (permutation group theory); Tower; Harbour; Quarter (Canadian coin); Natural (archaeology); Work (physics)","score_opus":0.1911103300446966,"score_gpt":0.41037568109527023,"score_spread":0.21926535105057363,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7034344400","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00029308736,0.000039534218,0.010558046,0.011494057,0.0006206185,0.0018280671,0.006249631,0.0004372739,0.9684797],"genre_scores_gemma":[0.0020493993,0.00011592349,0.004234206,0.00015651714,0.0002191612,0.0000020927562,0.0015791509,0.000085561864,0.991558],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99615,0.00033720123,0.00022611501,0.0009962133,0.0016986124,0.0005918238],"domain_scores_gemma":[0.99806124,0.00010504407,0.00018513265,0.00074060773,0.0005288696,0.00037907774],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005314313,0.00031827728,0.0003418059,0.0013209201,0.00030074627,0.0010729239,0.005558885,0.0003497388,0.0057102],"category_scores_gemma":[0.00007362519,0.00034967565,0.00010697357,0.0016961619,0.00040394504,0.0013254383,0.0019364248,0.0006211689,0.0021144145],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009628444,0.00014732774,0.00054694264,0.000020571531,0.00013606373,0.00025331372,0.0001101378,0.000015143492,0.000010588062,0.12725331,0.87125635,0.00024063453],"study_design_scores_gemma":[0.00082009716,0.000054289845,0.0011095657,0.00022582046,0.000014948701,0.0000035588287,0.00009801989,0.00006591183,0.00005068603,0.0032126592,0.9939316,0.00041286406],"about_ca_topic_score_codex":0.011657159,"about_ca_topic_score_gemma":0.0026498737,"teacher_disagreement_score":0.124040656,"about_ca_system_score_codex":0.00048924424,"about_ca_system_score_gemma":0.0009086916,"threshold_uncertainty_score":0.99996406},"labels":[],"label_agreement":null},{"id":"W7034651376","doi":"","title":"Two Essays on Analyst Information Processing","year":2023,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Subjectivity; Earnings; Private information retrieval; Information asymmetry; Quality (philosophy); Earnings management; Narrative","score_opus":0.022945403408314222,"score_gpt":0.2936177621932431,"score_spread":0.27067235878492885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7034651376","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11130088,0.00029136008,0.0012181143,0.0002279969,0.009449077,0.002405674,0.0033982245,0.0075266142,0.86418205],"genre_scores_gemma":[0.95262456,0.0003442533,0.0061647664,0.0027858682,0.00016563125,0.00017812039,0.016303316,0.0002898967,0.021143595],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9957996,0.0002018104,0.0010932737,0.00087504525,0.0013974443,0.0006327986],"domain_scores_gemma":[0.99681735,0.00012752057,0.0009442648,0.0011069186,0.00069686346,0.0003070832],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009766773,0.0006472843,0.00058683066,0.0012402436,0.0012099282,0.000955042,0.0018901112,0.0004266541,0.000053667984],"category_scores_gemma":[0.00070355204,0.00066958915,0.00026337543,0.0026029474,0.00002954532,0.004390778,0.00026242543,0.0009682942,0.0025231414],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025886242,0.000103075945,0.000005629206,0.0003614996,0.00010210939,0.000028203798,0.00003491617,0.00040266145,0.00033861422,0.495349,0.000091197144,0.5031572],"study_design_scores_gemma":[0.0067979284,0.00095646095,0.0023226868,0.006307609,0.0011870461,0.00007375505,0.0029374405,0.21038651,0.048984975,0.18257943,0.52752393,0.009942245],"about_ca_topic_score_codex":0.0001076017,"about_ca_topic_score_gemma":0.0003959506,"teacher_disagreement_score":0.84303844,"about_ca_system_score_codex":0.00040611552,"about_ca_system_score_gemma":0.00013292389,"threshold_uncertainty_score":0.99957556},"labels":[],"label_agreement":null},{"id":"W7036072675","doi":"","title":"Association between exposure to persistent organohalogen pollutants and epididymal and accessory sex gland function: multicentre study in Inuit and European populations.","year":2006,"lang":"en","type":"article","venue":"Università Politecnica delle Marche (Università Politecnica delle Marche)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Pollutant; Epididymis; Epidemiology; Association (psychology); Pregnancy","score_opus":0.026957781076201184,"score_gpt":0.2539462198117131,"score_spread":0.22698843873551194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7036072675","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97904867,0.00054514734,0.007030502,0.0055092075,0.00010134894,0.0010875766,0.00044527344,0.0002531486,0.005979154],"genre_scores_gemma":[0.9888217,0.00014331682,0.0021546758,0.00034078775,0.000112344576,0.0000013559852,0.00007918079,0.000038808357,0.008307835],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99594545,0.00089452113,0.0005342235,0.0011447958,0.00061490486,0.0008661023],"domain_scores_gemma":[0.99779135,0.00034615866,0.00029579524,0.0007430312,0.00020273507,0.00062092306],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009900418,0.0004547493,0.00055448955,0.0012176939,0.0006911812,0.00035488416,0.00093392463,0.00021891075,0.00009043523],"category_scores_gemma":[0.000110079476,0.0005313586,0.00013372861,0.0014950241,0.00016653145,0.0009932752,0.0024607058,0.00043089103,0.000026752065],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021890286,0.0006899924,0.92687774,0.00011354159,0.0005937638,0.00027373908,0.01927742,0.00044241824,0.00022240622,0.018045375,0.0018264622,0.031418238],"study_design_scores_gemma":[0.006240041,0.0007940304,0.9416955,0.000086820306,0.0005888138,0.000037275346,0.016516771,0.012669564,0.000015612417,0.0009312655,0.019218262,0.0012060461],"about_ca_topic_score_codex":0.0017020215,"about_ca_topic_score_gemma":0.0016806267,"teacher_disagreement_score":0.03021219,"about_ca_system_score_codex":0.00082321814,"about_ca_system_score_gemma":0.00016502205,"threshold_uncertainty_score":0.9997138},"labels":[],"label_agreement":null},{"id":"W7036220123","doi":"","title":"Blackout 2003 Toronto radio recordings","year":2003,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Blackout; Beauty; Power (physics); Thursday; George (robot); Microphone","score_opus":0.006679465031662604,"score_gpt":0.20419360118932134,"score_spread":0.19751413615765873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7036220123","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[2.052355e-7,0.00046773828,0.0004552602,0.000084839085,0.00068284106,0.0002596522,0.00007851821,0.0002822565,0.9976887],"genre_scores_gemma":[0.000005635849,0.0007769048,0.011162607,0.00082680595,0.000100142606,0.0000058850464,0.0002209568,0.000083222716,0.98681784],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982377,0.000081448714,0.0006213262,0.00028337396,0.0004630703,0.00031303192],"domain_scores_gemma":[0.99822825,0.000035245364,0.00061856216,0.0007102519,0.00024780913,0.00015986488],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00025766468,0.0003320902,0.00040896775,0.00006553816,0.000059431484,0.00017729402,0.000897679,0.00031667302,0.35750672],"category_scores_gemma":[0.00016905658,0.0003365732,0.000116041934,0.000022019181,0.00007287449,9.054665e-7,0.00014214631,0.0001513106,0.013023917],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000042055135,0.000031715703,8.3596876e-7,0.00014650995,0.000041582407,0.000006961272,0.00008528202,0.000022625805,6.8855044e-8,0.0017166786,0.9958941,0.0020494633],"study_design_scores_gemma":[0.00032258136,0.00006669481,6.8605533e-7,0.00013575688,0.000022309645,0.000037199192,0.000040382227,0.000405353,0.0000041739186,0.0000115535395,0.9985834,0.00036994924],"about_ca_topic_score_codex":0.0037764357,"about_ca_topic_score_gemma":0.0015248426,"teacher_disagreement_score":0.3444828,"about_ca_system_score_codex":0.00009319808,"about_ca_system_score_gemma":0.000069333335,"threshold_uncertainty_score":0.9999086},"labels":[],"label_agreement":null},{"id":"W7036396936","doi":"","title":"Canadian Solar Inc. (NASDAQ:CSIQ) Shares Sold by Grantham Mayo Van Otterloo &amp;amp; Co. LLC","year":2023,"lang":"en","type":"other","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics)","score_opus":0.026490334885289367,"score_gpt":0.294776924087995,"score_spread":0.26828658920270565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7036396936","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000016923264,0.00032213802,0.23007193,0.0030386571,0.001461957,0.00044759465,0.00465364,0.0028275908,0.7571748],"genre_scores_gemma":[0.000028950932,0.00030129016,0.0033808139,0.0064207464,0.0002429371,0.000014116884,0.0030241418,0.0005141685,0.98607284],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974271,0.00007505165,0.00037672653,0.0008547682,0.00054356526,0.0007227566],"domain_scores_gemma":[0.9976726,0.000048623206,0.00018460206,0.0014108674,0.00007112855,0.00061218604],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00023923014,0.0004595603,0.00043524028,0.0007615653,0.00017653794,0.0007253812,0.002176814,0.00037039915,0.013012694],"category_scores_gemma":[0.000058145375,0.00043527273,0.00011479745,0.0006686108,0.000074998636,0.00028099498,0.00030074533,0.00026512027,0.014888424],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.1454877e-7,0.000024741415,0.00012817002,0.000031598778,0.00005807412,0.0000165464,0.000086757296,0.0000012637009,0.0000060597795,0.006261906,0.9909414,0.002443175],"study_design_scores_gemma":[0.00016912218,0.000010959834,0.000009690092,0.00008651878,0.0000152451985,0.0000045634747,0.000014096761,0.0013912278,0.000014652302,0.00025617066,0.99744976,0.0005780055],"about_ca_topic_score_codex":0.1747929,"about_ca_topic_score_gemma":0.791103,"teacher_disagreement_score":0.61631006,"about_ca_system_score_codex":0.00013934572,"about_ca_system_score_gemma":0.0004171457,"threshold_uncertainty_score":0.9998099},"labels":[],"label_agreement":null},{"id":"W7037164358","doi":"","title":"Designing groundwater visualization interfaces","year":2009,"lang":"en","type":"dissertation","venue":"Summit (Simon Fraser University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Hydrogeology; Groundwater; Usability; Interface (matter); Visualization; User interface; Data visualization; Scalability","score_opus":0.017301964937166767,"score_gpt":0.25861414561880913,"score_spread":0.24131218068164237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7037164358","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018172877,0.00015890488,0.94524807,0.00012209857,0.0012273063,0.00035055034,0.000018787252,0.0007632015,0.033938225],"genre_scores_gemma":[0.7361221,0.0009674674,0.012374945,0.001174477,0.00033603405,0.0000021408875,0.00865848,0.00013957039,0.2402248],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99829155,0.00012968287,0.00025899362,0.0006301409,0.0003807104,0.00030890267],"domain_scores_gemma":[0.99881124,0.000036135832,0.00027098868,0.0005081274,0.0002410511,0.00013242649],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013264544,0.00032652245,0.00029620624,0.00086722616,0.00024663043,0.0004167628,0.0014056702,0.0002868363,0.00009140569],"category_scores_gemma":[0.000027283773,0.00037026015,0.00011355157,0.0012737019,0.00002549704,0.0013468036,0.000115304334,0.00022047889,0.00017563002],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039327604,0.0018545609,0.035095293,0.0009177192,0.0008907917,0.001301885,0.0019214918,0.0012005558,0.00047262534,0.43768102,0.38392022,0.13435057],"study_design_scores_gemma":[0.0019849318,0.0005702319,0.0008561847,0.0008614183,0.00038039312,3.3387597e-8,0.028996283,0.031656105,0.051109426,0.0025157619,0.8783601,0.0027091508],"about_ca_topic_score_codex":0.00006162472,"about_ca_topic_score_gemma":0.011749496,"teacher_disagreement_score":0.93287313,"about_ca_system_score_codex":0.00014755559,"about_ca_system_score_gemma":0.00013588976,"threshold_uncertainty_score":0.99987495},"labels":[],"label_agreement":null},{"id":"W7038862094","doi":"","title":"Jupiter in Aries, Moon in Virgo, Trinity Square Video &amp; Scotiabank Contact Photography Festival (Apr – July 2021)","year":2021,"lang":"en","type":"other","venue":"Goldsmiths (University of London)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Square (algebra); Exhibition; Photography; Jupiter (rocket family); Color photography","score_opus":0.015350999400479785,"score_gpt":0.2341781506965715,"score_spread":0.2188271512960917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7038862094","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0075572045,0.0031122628,0.3554487,0.0014362197,0.002116681,0.0020634823,0.001666258,0.00059644796,0.6260027],"genre_scores_gemma":[0.027422668,0.0026572084,0.029152846,0.00085413473,0.000214915,0.0000029636103,0.0020808382,0.00031619478,0.93729824],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977839,0.00025473605,0.00030161414,0.00078759616,0.00048245356,0.0003896721],"domain_scores_gemma":[0.9983179,0.00010251608,0.00037859735,0.0009489618,0.000097023905,0.00015499289],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00029437,0.00035261112,0.0007436621,0.0015190705,0.000060052855,0.00010289831,0.0013291013,0.0003490398,0.0026792174],"category_scores_gemma":[0.000055111796,0.00045022074,0.00024388771,0.0022022931,0.00015463524,0.00041782984,0.00058806426,0.00043653062,0.00023098047],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010133702,0.0009323331,0.032022342,0.0005981944,0.00022767672,0.0009208238,0.0017566523,0.00005750655,0.00009195914,0.009174483,0.9480616,0.0060550896],"study_design_scores_gemma":[0.0025118918,0.00007569977,0.012822849,0.0012018867,0.000042121537,0.000007835787,0.00023516001,0.0014989824,0.000024616973,0.00014274826,0.9807758,0.0006604509],"about_ca_topic_score_codex":0.004059759,"about_ca_topic_score_gemma":0.022225127,"teacher_disagreement_score":0.32629585,"about_ca_system_score_codex":0.00012406484,"about_ca_system_score_gemma":0.00032006623,"threshold_uncertainty_score":0.99979496},"labels":[],"label_agreement":null},{"id":"W7039678058","doi":"","title":"Musée Pointe-à-Callière, Montréal","year":2016,"lang":"fr","type":"other","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","score_opus":0.015386427713370815,"score_gpt":0.2429438000314674,"score_spread":0.22755737231809658,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7039678058","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00005297856,0.0013648103,0.53575027,0.020275146,0.00041878613,0.00021543542,0.0000993859,0.00023426295,0.44158894],"genre_scores_gemma":[0.004453655,0.0026483655,0.051737882,0.0008711444,0.00012380775,0.000023491239,0.0003012713,0.00018366196,0.93965673],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99146545,0.0050181397,0.0008124149,0.001235969,0.0007536272,0.00071442325],"domain_scores_gemma":[0.99176013,0.0013903674,0.0007705385,0.003351324,0.0022333795,0.00049422693],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0035931387,0.0005997979,0.0005817134,0.0003686329,0.00043506353,0.0010848076,0.0031649207,0.00042700148,0.010818013],"category_scores_gemma":[0.0016978689,0.0005599255,0.00033312172,0.0007630991,0.00052469113,0.00052922074,0.0015069736,0.00043022935,0.0062751565],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000034676652,0.0004500835,0.00025927546,0.000075950935,0.00008480015,0.000017597946,0.0017972596,0.0000032862367,0.0003195464,0.80870575,0.05582981,0.13245316],"study_design_scores_gemma":[0.0007331579,6.089711e-7,0.00047342273,0.0024117273,0.000051187846,0.000028729375,0.000037615933,0.040507145,0.0026420215,0.0031163807,0.94932556,0.0006724106],"about_ca_topic_score_codex":0.0023117848,"about_ca_topic_score_gemma":0.006555842,"teacher_disagreement_score":0.8934958,"about_ca_system_score_codex":0.00018303169,"about_ca_system_score_gemma":0.00045752098,"threshold_uncertainty_score":0.99995214},"labels":[],"label_agreement":null},{"id":"W7042481571","doi":"","title":"Preferences for course delivery in library and information science programs: a study of master's students in Canada and the United States","year":2016,"lang":"en","type":"other","venue":"NC Digital Online Collection of Knowledge and Scholarship (The University of North Carolina at Greensboro)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Preference; Accreditation; Graduate students; Online course; Information science; Association (psychology); Degree program; Sample (material)","score_opus":0.01619455942989954,"score_gpt":0.24112671271252945,"score_spread":0.22493215328262992,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7042481571","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99819756,0.00013064404,0.000083942796,0.00006162606,0.00003920835,0.0007583942,0.00017431712,0.000009692145,0.00054464786],"genre_scores_gemma":[0.99710083,0.0008309506,0.000059375754,0.00001844553,0.0000053621748,0.0000013216877,0.00008159142,0.000008319895,0.0018937957],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991076,0.00008283973,0.00024895012,0.00018293603,0.00026869183,0.0001089581],"domain_scores_gemma":[0.99911356,0.00015615644,0.00031409977,0.00017447797,0.00018713986,0.000054593314],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020800745,0.00012080812,0.00025724008,0.0005024853,0.00010664952,0.00003073624,0.00052864343,0.000039143426,0.0000021633275],"category_scores_gemma":[0.00003934694,0.0000852051,0.000019564184,0.0009682951,0.00035977995,0.001794243,0.00047605476,0.000086392116,1.5963188e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019077868,0.00018280729,0.9916048,0.00008689202,0.000031048083,7.9576716e-7,0.0014637802,0.00000884718,7.88577e-8,0.000106976695,0.00020637421,0.006116842],"study_design_scores_gemma":[0.003964529,0.00023105157,0.9861931,0.00018951824,0.00002986099,0.0000015438687,0.00031588445,0.0041388865,0.0000012879641,0.000030078509,0.0048037097,0.00010050272],"about_ca_topic_score_codex":0.021285584,"about_ca_topic_score_gemma":0.6111887,"teacher_disagreement_score":0.5899031,"about_ca_system_score_codex":0.000050291295,"about_ca_system_score_gemma":0.000553638,"threshold_uncertainty_score":0.98523176},"labels":[],"label_agreement":null},{"id":"W7066555716","doi":"","title":"Jonathan Wesley Garners National Sales Honors for Fourth Consecutive Quarter","year":2017,"lang":"en","type":"other","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Work (physics)","score_opus":0.035919646829292745,"score_gpt":0.330062275338005,"score_spread":0.2941426285087122,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7066555716","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[9.6034505e-8,0.000036538888,0.5128691,0.00046297236,0.00033315754,0.00014730057,0.00020950807,0.00014905614,0.48579222],"genre_scores_gemma":[0.00025849603,0.00006206574,0.030466346,0.0012983403,0.00027284116,0.000022314014,0.00048992375,0.00008609745,0.9670436],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99891096,0.000025545918,0.00013964096,0.0004062318,0.00032201552,0.00019561159],"domain_scores_gemma":[0.9989774,0.00007254576,0.00025960297,0.00046205695,0.0001423809,0.00008601976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015816533,0.00019785138,0.00021331567,0.00025552322,0.000103635124,0.00030702303,0.0010481332,0.00014894413,0.00032494604],"category_scores_gemma":[0.000094102834,0.00017168463,0.00010450567,0.00006564117,0.00009428992,0.00016555015,0.00012369976,0.00006666854,0.0002760998],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.169385e-7,0.00001637849,0.000017486576,0.000013849413,0.000045256867,0.0000011293421,0.00003756877,0.0000011077956,6.186921e-7,0.20868453,0.79064983,0.0005314418],"study_design_scores_gemma":[0.0003262286,0.000028271732,0.000017431166,0.000058242593,0.000009984085,0.000002667617,0.000019809217,0.017836152,0.000007994715,0.0014053443,0.98002946,0.00025840063],"about_ca_topic_score_codex":0.00004175789,"about_ca_topic_score_gemma":0.00035242084,"teacher_disagreement_score":0.4824028,"about_ca_system_score_codex":0.000029863224,"about_ca_system_score_gemma":0.000259651,"threshold_uncertainty_score":0.7001096},"labels":[],"label_agreement":null},{"id":"W7066708259","doi":"","title":"Interpretation of dairy data using interactive visualization","year":2004,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Visualization; Context (archaeology); Interactive visualization; Process (computing); Data visualization; Domain (mathematical analysis); Software; Matching (statistics)","score_opus":0.038962727786846986,"score_gpt":0.3350919441353535,"score_spread":0.2961292163485065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7066708259","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.687209,0.0013458185,0.14734559,0.000079176905,0.021506755,0.0054624765,0.020498702,0.0031639866,0.11338846],"genre_scores_gemma":[0.9713803,0.00015065787,0.012764234,0.00023672577,0.000044055967,0.000012917025,0.014394325,0.00012945372,0.00088732585],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9956402,0.0003523276,0.0012571018,0.0013748092,0.00096708344,0.0004084668],"domain_scores_gemma":[0.9952569,0.00016598767,0.001513189,0.002013227,0.00086032425,0.00019039461],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00079322554,0.00057513965,0.00068825524,0.00080068794,0.0004394339,0.00025572084,0.0030748637,0.00045875288,0.00007150234],"category_scores_gemma":[0.0010653044,0.00064542773,0.00018237827,0.001371709,0.000052174753,0.00488122,0.000838645,0.00062321854,0.00007371355],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020454527,0.00077160023,0.000019228344,0.001095185,0.00054875,0.000045967226,0.00022758191,0.002240295,0.025016222,0.7347248,0.000022121008,0.23508367],"study_design_scores_gemma":[0.0025757651,0.00042103606,0.00035302158,0.005288452,0.0007974223,0.00006450409,0.00133224,0.7727882,0.14093335,0.05815446,0.014277714,0.0030138316],"about_ca_topic_score_codex":0.00024797377,"about_ca_topic_score_gemma":0.00042191034,"teacher_disagreement_score":0.7705479,"about_ca_system_score_codex":0.00061329996,"about_ca_system_score_gemma":0.00024233041,"threshold_uncertainty_score":0.9995997},"labels":[],"label_agreement":null},{"id":"W7070471136","doi":"","title":"Physician perspectives on gender-affirming care for trans youth","year":2024,"lang":"en","type":"dissertation","venue":"Mspace (University of Manitoba)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Health care; Primary care; Medical care; Population; MEDLINE; Qualitative research","score_opus":0.0290373547430342,"score_gpt":0.25974857126771533,"score_spread":0.23071121652468113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7070471136","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15352425,0.0028216338,0.7578894,0.0016304613,0.0033063386,0.0018774846,0.0018612103,0.0010773015,0.07601195],"genre_scores_gemma":[0.98704374,0.00029694597,0.006258405,0.00009309064,0.0002014199,8.2182646e-7,0.002127163,0.000056880544,0.0039215204],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9990119,0.00002403025,0.00006946278,0.00046326578,0.0002672018,0.00016417858],"domain_scores_gemma":[0.99926794,0.000026200127,0.00012037469,0.00032506592,0.00020804525,0.00005238931],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000051432373,0.00018030632,0.00024204278,0.00027931953,0.00021902904,0.000083472805,0.0006992915,0.00012145136,0.0000015145548],"category_scores_gemma":[0.00000708677,0.00023016515,0.0002193866,0.00030699512,0.000029005467,0.00023594427,0.000046392986,0.00014488315,0.000025591737],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018683821,0.0003965178,0.00007556281,0.0036544811,0.00062929315,0.00006106013,0.6839377,0.0005007397,0.0004013812,0.27841008,0.010576158,0.021170186],"study_design_scores_gemma":[0.00031352107,0.00013811271,0.0006722405,0.0002862059,0.00021315864,2.2980342e-7,0.9810957,0.008540982,0.00025335135,0.00027512494,0.007891331,0.00032005747],"about_ca_topic_score_codex":0.0001282427,"about_ca_topic_score_gemma":0.025488196,"teacher_disagreement_score":0.8335195,"about_ca_system_score_codex":0.000113277034,"about_ca_system_score_gemma":0.000102294995,"threshold_uncertainty_score":0.99229413},"labels":[],"label_agreement":null},{"id":"W7083589183","doi":"10.61091/um124-08","title":"On signless and normalized Laplacian spectra of a subgraph of the total graph of Zn","year":2025,"lang":"en","type":"article","venue":"Utilitas Mathematica","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Modulo; Graph; Eigenvalues and eigenvectors; Laplacian matrix; Laplace operator; Spectrum (functional analysis); Algebraic connectivity","score_opus":0.011047955771920666,"score_gpt":0.2681738448474695,"score_spread":0.2571258890755488,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7083589183","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.54828477,0.00023656634,0.4190165,0.0007297333,0.00017447429,0.00054631894,0.000100674224,0.000058559497,0.030852417],"genre_scores_gemma":[0.99548215,0.00000878093,0.004268806,0.000048910664,0.0000015085124,0.0000019056828,0.0000011544442,0.0000027578933,0.00018405756],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991738,0.000052475618,0.0003421293,0.0001301095,0.00020916377,0.00009232305],"domain_scores_gemma":[0.99901706,0.0002114048,0.00015506711,0.0005263783,0.000066031665,0.00002406807],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025295457,0.00007961881,0.00023533008,0.00013468676,0.000030250585,0.000013654683,0.0004324031,0.000029468145,0.000022293567],"category_scores_gemma":[0.00013925167,0.000054179043,0.00008763123,0.00062758895,0.00016775745,0.00006956513,0.00015607609,0.00004254223,8.701691e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006927092,0.00015986961,0.0001798756,0.0003184995,0.000032750024,2.350869e-7,0.0006975611,0.0000062350487,0.001002231,0.99694943,0.00035268778,0.00029368023],"study_design_scores_gemma":[0.0016082862,0.00030552136,0.013391066,0.0013693688,0.00014312264,0.000008140165,0.00083574787,0.081902854,0.1176588,0.78229946,0.00018592435,0.00029170795],"about_ca_topic_score_codex":0.000005993942,"about_ca_topic_score_gemma":0.000002208085,"teacher_disagreement_score":0.44719738,"about_ca_system_score_codex":0.0000036892825,"about_ca_system_score_gemma":0.000036916972,"threshold_uncertainty_score":0.22093573},"labels":[],"label_agreement":null},{"id":"W7093626641","doi":"","title":"Toujours debouttes ! Perspectives sur le renouveau féministe au Québec \"Toujours debouttes!\" The perspectives for the feminist revival in Quebec","year":2019,"lang":"fr","type":"other","venue":"OpenEdition (OpenEdition)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Subject (documents); Perspective (graphical); Field (mathematics)","score_opus":0.025791947105455217,"score_gpt":0.2769754749343148,"score_spread":0.25118352782885955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7093626641","genre_codex":"commentary","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00044974603,0.011902387,0.12910965,0.6571679,0.008010559,0.007435868,0.0023285202,0.00034912184,0.18324623],"genre_scores_gemma":[0.13910764,0.002220642,0.0016319198,0.027048834,0.0049496572,0.0013644875,0.0010948329,0.00050509605,0.82207686],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99321,0.00092034746,0.0013863785,0.0019918669,0.0012248865,0.0012665261],"domain_scores_gemma":[0.992193,0.002584843,0.0014164144,0.0022682322,0.0011967118,0.0003408041],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0018892136,0.0011718355,0.001235419,0.00050146726,0.0021851999,0.0027987878,0.0038601952,0.0005507605,0.002871664],"category_scores_gemma":[0.0016946782,0.00087730057,0.0007389768,0.0012708659,0.0015889267,0.006912846,0.00077359163,0.0009428677,0.0014132343],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000099898185,0.00088810705,0.00036578905,0.00021643075,0.00038870305,0.000029522305,0.02791015,0.00056120404,0.000023981394,0.86253566,0.1005153,0.0064652897],"study_design_scores_gemma":[0.0023700458,0.00036200133,0.009384124,0.0012992067,0.00033302198,0.00008038622,0.1012094,0.011487194,0.0000706329,0.00083300075,0.87120056,0.001370451],"about_ca_topic_score_codex":0.1374368,"about_ca_topic_score_gemma":0.68253756,"teacher_disagreement_score":0.8617026,"about_ca_system_score_codex":0.0019630024,"about_ca_system_score_gemma":0.0069992426,"threshold_uncertainty_score":0.9993678},"labels":[],"label_agreement":null},{"id":"W7099273180","doi":"","title":"Detection of Neonicotinoid Insecticides in Wetlands of Canada’s Prairie Pothole","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Neonicotinoid; Pothole (geology); Wetland; Period (music); Imidacloprid","score_opus":0.009774670390174075,"score_gpt":0.23481976775314345,"score_spread":0.22504509736296938,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7099273180","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08951906,0.0000064035057,0.90190613,0.000402881,0.00010920021,0.000040431005,0.0000021044918,0.000021270536,0.00799252],"genre_scores_gemma":[0.9979533,0.0000010553173,0.0016007718,0.00014709804,0.0000064559867,4.3411254e-7,0.0000014794325,0.0000018598445,0.00028755952],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994611,0.000035333313,0.00018897447,0.00009258682,0.00014048208,0.00008148186],"domain_scores_gemma":[0.9996035,0.000042734457,0.00008012475,0.00019049374,0.00005641678,0.000026700918],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019586383,0.000039706716,0.00009244139,0.00008034472,0.000014330756,0.00001091133,0.00020622229,0.0000180509,0.0000073024767],"category_scores_gemma":[0.00012097107,0.000035067245,0.000012392928,0.0002729489,0.000014736167,0.00012284296,0.00005289789,0.000028818988,5.874249e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025262445,0.00041785632,0.17263341,0.0002859298,0.00004035505,0.0000045287043,0.0011728836,0.0054201097,0.063988976,0.6750258,0.007191151,0.07379373],"study_design_scores_gemma":[0.0005408871,0.00015798332,0.09195008,0.000030200748,0.0000041937938,0.000004022019,0.00007965235,0.5977162,0.29775998,0.0014462323,0.010152758,0.00015780958],"about_ca_topic_score_codex":0.08116665,"about_ca_topic_score_gemma":0.726721,"teacher_disagreement_score":0.9084342,"about_ca_system_score_codex":0.000019015473,"about_ca_system_score_gemma":0.0001763465,"threshold_uncertainty_score":0.924952},"labels":[],"label_agreement":null},{"id":"W7100288515","doi":"","title":"Qualitative and Quantitative Evaluation of Software Visualization Tools. Master&amp;apos;s thesis, Université de","year":2000,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Taxonomy (biology); Visualization; Software; Qualitative analysis; Data visualization; Software visualization; Software tool; Information visualization","score_opus":0.27454900314111824,"score_gpt":0.4468578270857878,"score_spread":0.17230882394466956,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7100288515","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17019887,0.0001054453,0.82566476,0.00017106529,0.0000179733,0.00013740093,0.000025761226,0.00006916851,0.0036095236],"genre_scores_gemma":[0.83925045,0.00035781393,0.15204506,0.0007005117,0.000016087617,0.0000076034344,0.00027394775,0.000019841678,0.0073286756],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986407,0.0004372388,0.00019417582,0.00021826712,0.00039372244,0.0001158739],"domain_scores_gemma":[0.9990919,0.00023553551,0.000100012905,0.00021012862,0.00030632268,0.000056073608],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009459803,0.000088726614,0.000119988596,0.00010003634,0.000094350136,0.00007175175,0.00021452413,0.000039564315,0.0006861869],"category_scores_gemma":[0.00021932316,0.000082716695,0.00002691217,0.00038233792,0.00005774328,0.000680941,0.00007876815,0.000025066269,0.000039973253],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005316805,0.0001959481,0.0015817526,0.00006252854,0.00010320484,0.000001359391,0.11419824,0.0015610495,0.00080953655,0.71823496,0.003277183,0.15992108],"study_design_scores_gemma":[0.0024394116,0.00034795384,0.010416299,0.00012980773,0.00019850433,0.000013082654,0.012148719,0.92791146,0.0065968353,0.02221226,0.01689619,0.00068949163],"about_ca_topic_score_codex":0.00004012523,"about_ca_topic_score_gemma":0.00007787807,"teacher_disagreement_score":0.9263504,"about_ca_system_score_codex":0.000080304046,"about_ca_system_score_gemma":0.000085672706,"threshold_uncertainty_score":0.7513265},"labels":[],"label_agreement":null},{"id":"W7106824282","doi":"10.4230/lipics.gd.2025.41","title":"Graph Drawing Contest Report (Graph Drawing Contest Report)","year":2025,"lang":"en","type":"article","venue":"Leibniz-Zentrum für Informatik (Schloss Dagstuhl)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"CONTEST; Graph; Graph drawing; Visualization; Conjunction (astronomy); Information visualization","score_opus":0.01465190933736341,"score_gpt":0.30191573393514326,"score_spread":0.2872638245977798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7106824282","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02473553,0.000593837,0.85102516,0.0052072816,0.004338534,0.0014077167,0.00010781235,0.0022191724,0.11036497],"genre_scores_gemma":[0.97281396,0.00018004022,0.008766915,0.0083452165,0.00027089432,0.00010352025,0.001067926,0.00007310306,0.008378417],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9933289,0.00012338156,0.0029953106,0.0009306861,0.0013132566,0.0013084218],"domain_scores_gemma":[0.9940114,0.0003435166,0.001491369,0.0029586728,0.0007258307,0.00046921527],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0018364597,0.0007700213,0.00097426184,0.0011121773,0.0011050258,0.002339804,0.0026894344,0.00030859633,0.00007722148],"category_scores_gemma":[0.0014882764,0.00074371963,0.00048076973,0.0032066342,0.00034902667,0.005041274,0.0014961573,0.0007149592,0.00023196475],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008353227,0.0009232001,0.14147024,0.0010492227,0.0012103838,0.0056388895,0.008585535,0.0010748429,0.0006469311,0.6770127,0.13368705,0.02861747],"study_design_scores_gemma":[0.0064740153,0.00036421776,0.023475835,0.0022587266,0.00037332444,0.005479166,0.004005979,0.08918876,0.00706608,0.017558051,0.8397634,0.0039924323],"about_ca_topic_score_codex":0.00022063447,"about_ca_topic_score_gemma":0.00008764881,"teacher_disagreement_score":0.94807845,"about_ca_system_score_codex":0.00019895419,"about_ca_system_score_gemma":0.0007005163,"threshold_uncertainty_score":0.9995014},"labels":[],"label_agreement":null},{"id":"W7109050986","doi":"10.59350/17m60-bgs34","title":"Co-located Collaborative Tree Comparison","year":2009,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Tree (set theory); Visualization; Data visualization; Set (abstract data type); Information visualization","score_opus":0.03762586005235802,"score_gpt":0.36121925002426747,"score_spread":0.32359338997190945,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7109050986","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004720831,0.00033867743,0.8482101,0.0052659116,0.00038230314,0.0002723329,0.000041007428,0.00025651942,0.14476104],"genre_scores_gemma":[0.9742871,0.00017246304,0.008190538,0.005021291,0.00011412026,0.0000014314463,0.00013102588,0.000010383235,0.012071625],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99735904,0.00019517499,0.0007329389,0.00065461826,0.00058055733,0.00047767497],"domain_scores_gemma":[0.997989,0.000061947496,0.00027665144,0.00079394475,0.00055909826,0.00031934158],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00031518217,0.00032059068,0.00046941557,0.00021336944,0.00029849113,0.0010670363,0.001176839,0.00013864531,0.00075758155],"category_scores_gemma":[0.00008380297,0.00030233114,0.00007871626,0.0027885886,0.00012647639,0.000881174,0.00007300532,0.00018878991,0.0013432853],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002554765,0.0012471239,0.0008972359,0.0000116825295,0.000050597828,0.000022581908,0.0029187326,0.00043315184,0.0007254323,0.43424997,0.37964135,0.17977661],"study_design_scores_gemma":[0.00084037316,0.0006536251,0.0025135477,0.00003575062,0.00002975003,0.000003145278,0.0005238646,0.88528955,0.010634664,0.00071555976,0.09828852,0.0004716188],"about_ca_topic_score_codex":0.000012209496,"about_ca_topic_score_gemma":0.000035270405,"teacher_disagreement_score":0.973815,"about_ca_system_score_codex":0.00007045392,"about_ca_system_score_gemma":0.00039133788,"threshold_uncertainty_score":0.99996996},"labels":[],"label_agreement":null},{"id":"W7109087591","doi":"10.1145/3769841","title":"Visualization-Oriented Progressive Time Series Transformation","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ACM on Management of Data","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Transformation (genetics); Computation; Visualization; Data visualization; Multivariate statistics; Data transformation; Time series; Data manipulation language","score_opus":0.0252930631897247,"score_gpt":0.31984117046811056,"score_spread":0.2945481072783859,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7109087591","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029771065,0.00037489142,0.71232307,0.058202118,0.0013170706,0.005550721,0.0009575433,0.000996175,0.19050732],"genre_scores_gemma":[0.6375569,0.0010502848,0.33072367,0.0036652284,0.000109197936,0.00010952417,0.0018302874,0.00007139159,0.024883496],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99902546,0.000006329768,0.000291778,0.00023297538,0.0003459248,0.000097526514],"domain_scores_gemma":[0.9985188,0.000013757867,0.00023854543,0.0010275088,0.00018580997,0.000015557765],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000291861,0.00008721089,0.00011686262,0.00013523138,0.000075258635,0.00008137524,0.0049718097,0.000021441905,0.000009908508],"category_scores_gemma":[0.00013000658,0.000065448876,0.000027579117,0.0010083795,0.00005437928,0.0015575404,0.0028584388,0.000034363115,0.0000062253303],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014700993,0.00012308438,0.00023253744,0.00047057535,0.00008837985,1.1420854e-7,0.00015980986,0.0000073280034,0.00020776127,0.9688689,0.02416655,0.0056602187],"study_design_scores_gemma":[0.004386214,0.0006381386,0.009459635,0.0062697274,0.0007944943,0.000004516797,0.0031302576,0.39501077,0.15605439,0.119338185,0.30380583,0.0011078137],"about_ca_topic_score_codex":7.562608e-7,"about_ca_topic_score_gemma":9.173595e-8,"teacher_disagreement_score":0.84953076,"about_ca_system_score_codex":0.000011834423,"about_ca_system_score_gemma":0.000013660311,"threshold_uncertainty_score":0.9238942},"labels":[],"label_agreement":null},{"id":"W7115017221","doi":"10.5281/zenodo.17912387","title":"Urban Data Analytics, Visualization, and Storytelling","year":2025,"lang":"en","type":"book","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Craft; Storytelling; Variety (cybernetics); Key (lock); Narrative; Urban computing","score_opus":0.07161457888270659,"score_gpt":0.2962739931513268,"score_spread":0.2246594142686202,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7115017221","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000011384614,0.00047749392,0.58645606,0.00026140668,0.00018498464,0.00028226234,0.00093602826,0.0009699903,0.4104306],"genre_scores_gemma":[0.0007409465,0.0028679357,0.0032742552,0.0014971489,0.0007426421,3.3407787e-8,0.08401002,0.0024442212,0.9044228],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974348,0.00023890297,0.00043599278,0.0010244672,0.00054353435,0.00032232096],"domain_scores_gemma":[0.99667674,0.00005162196,0.00025259572,0.0020062702,0.0008040782,0.00020871521],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0009163297,0.00026498202,0.00029125393,0.0006156544,0.0016726098,0.0026310121,0.004703049,0.00016452692,0.0013115371],"category_scores_gemma":[0.0005573864,0.00030248193,0.0000420974,0.0006637671,0.00017894364,0.000742453,0.0073636444,0.00033445406,0.0013189738],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021922742,0.00003671373,3.927119e-7,0.00010942499,0.000053702177,0.000006531639,0.00021166925,0.000011549695,0.0000031909865,0.26066193,0.7232268,0.015675921],"study_design_scores_gemma":[0.00019910077,0.000048714926,0.0000054172474,0.00012565809,0.000044767225,0.000019099203,0.00003525663,0.068803094,0.0000058253213,0.00087381736,0.9295649,0.00027432517],"about_ca_topic_score_codex":0.000003521736,"about_ca_topic_score_gemma":3.856169e-7,"teacher_disagreement_score":0.58318186,"about_ca_system_score_codex":0.00018312519,"about_ca_system_score_gemma":0.00004488338,"threshold_uncertainty_score":0.9999427},"labels":[],"label_agreement":null},{"id":"W7115018318","doi":"10.5281/zenodo.17912386","title":"Urban Data Analytics, Visualization, and Storytelling","year":2025,"lang":"en","type":"book","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Craft; Storytelling; Variety (cybernetics); Key (lock); Narrative; Urban computing","score_opus":0.07161457888270659,"score_gpt":0.2962739931513268,"score_spread":0.2246594142686202,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7115018318","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000011384614,0.00047749392,0.58645606,0.00026140668,0.00018498464,0.00028226234,0.00093602826,0.0009699903,0.4104306],"genre_scores_gemma":[0.0007409465,0.0028679357,0.0032742552,0.0014971489,0.0007426421,3.3407787e-8,0.08401002,0.0024442212,0.9044228],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974348,0.00023890297,0.00043599278,0.0010244672,0.00054353435,0.00032232096],"domain_scores_gemma":[0.99667674,0.00005162196,0.00025259572,0.0020062702,0.0008040782,0.00020871521],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0009163297,0.00026498202,0.00029125393,0.0006156544,0.0016726098,0.0026310121,0.004703049,0.00016452692,0.0013115371],"category_scores_gemma":[0.0005573864,0.00030248193,0.0000420974,0.0006637671,0.00017894364,0.000742453,0.0073636444,0.00033445406,0.0013189738],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021922742,0.00003671373,3.927119e-7,0.00010942499,0.000053702177,0.000006531639,0.00021166925,0.000011549695,0.0000031909865,0.26066193,0.7232268,0.015675921],"study_design_scores_gemma":[0.00019910077,0.000048714926,0.0000054172474,0.00012565809,0.000044767225,0.000019099203,0.00003525663,0.068803094,0.0000058253213,0.00087381736,0.9295649,0.00027432517],"about_ca_topic_score_codex":0.000003521736,"about_ca_topic_score_gemma":3.856169e-7,"teacher_disagreement_score":0.58318186,"about_ca_system_score_codex":0.00018312519,"about_ca_system_score_gemma":0.00004488338,"threshold_uncertainty_score":0.9999427},"labels":[],"label_agreement":null},{"id":"W7116755697","doi":"10.1109/tvcg.2025.3646847","title":"Do You “Trust” This Visualization? An Inventory to Measure Trust in Visualizations","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Science Foundation","keywords":"Visualization; Set (abstract data type); Data visualization; Trustworthiness; Consistency (knowledge bases); Reliability (semiconductor); Measure (data warehouse); Information visualization","score_opus":0.028100781176951313,"score_gpt":0.31794306725934823,"score_spread":0.2898422860823969,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7116755697","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004068621,0.000064957574,0.99303657,0.000255731,0.0010285284,0.00058122166,0.00003060881,0.0005079366,0.00042582405],"genre_scores_gemma":[0.9822733,0.00045633205,0.0028110489,0.012726721,0.00010958657,0.0001396795,0.00014112609,0.000079884376,0.0012623522],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.996663,0.00043118754,0.0007631307,0.0010629265,0.00063214445,0.00044765917],"domain_scores_gemma":[0.9980449,0.00008266813,0.00015393882,0.00089391926,0.00047373504,0.0003508521],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006385724,0.00044193614,0.00041865854,0.0025309923,0.00058912847,0.0008283389,0.00084785506,0.00026604102,0.00006939653],"category_scores_gemma":[0.000025825373,0.00048692527,0.00012131897,0.005826417,0.00011247234,0.0011925125,0.00003149292,0.00026177897,0.000029119672],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022217278,0.000813051,0.0016664299,0.000057562283,0.00005439812,0.000004627733,0.0019321335,0.0032034474,0.000018526069,0.9839629,0.0014904209,0.0067743175],"study_design_scores_gemma":[0.0010557743,0.00026307083,0.0007588315,0.00018519726,0.00004206877,0.000005857533,0.0001469759,0.9848113,0.0005484794,0.0016905164,0.009954445,0.0005374743],"about_ca_topic_score_codex":0.000043499836,"about_ca_topic_score_gemma":0.00015992936,"teacher_disagreement_score":0.9902255,"about_ca_system_score_codex":0.00011205398,"about_ca_system_score_gemma":0.00019663638,"threshold_uncertainty_score":0.99975824},"labels":[],"label_agreement":null},{"id":"W7116777300","doi":"10.2196/83318","title":"Artificial Intelligence Models for Predicting Triage in Emergency Departments: Seven-Month Retrospective Comparative Study of Natural Language Processing, Large Language Model, and Joint Embedding Predictive Architectures","year":2025,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Triage; Retrospective cohort study; Emergency department; Emergency response; MEDLINE","score_opus":0.0312730149266279,"score_gpt":0.3842273950826731,"score_spread":0.3529543801560452,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7116777300","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.351061,0.00013760835,0.64743304,0.00003407218,0.00008079318,0.00084326026,0.000058830705,0.00006130729,0.000290107],"genre_scores_gemma":[0.993191,0.000011720454,0.0064683137,0.00010582486,0.00002655448,0.000112574955,0.0000403821,0.000006383338,0.000037227386],"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976212,0.00007614141,0.0011431514,0.00023808092,0.00061266543,0.0003088094],"domain_scores_gemma":[0.9989988,0.000093499846,0.00037875734,0.00026369814,0.0001576322,0.00010762114],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007759709,0.00019854083,0.00044776098,0.00033820298,0.00013315567,0.000078121666,0.0004504428,0.000094461495,0.000005205581],"category_scores_gemma":[0.00035383392,0.00016528128,0.0000518895,0.0006743291,0.000068046,0.0005783542,0.00038852316,0.00033899996,4.2257955e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019651538,0.0021553165,0.0017675287,0.00087165216,0.00020480753,0.0000132067025,0.8952168,0.052812193,0.000028450057,0.022291629,0.0004384736,0.024003427],"study_design_scores_gemma":[0.0005333964,0.00022661578,0.00030115922,0.00017061844,0.000019362731,0.0000013751524,0.05788161,0.9369791,0.00014901585,0.0036038307,0.0000021810226,0.00013172084],"about_ca_topic_score_codex":0.000013054218,"about_ca_topic_score_gemma":0.00026046304,"teacher_disagreement_score":0.8841669,"about_ca_system_score_codex":0.00007325905,"about_ca_system_score_gemma":0.00015793122,"threshold_uncertainty_score":0.67399746},"labels":[],"label_agreement":null},{"id":"W7116866109","doi":"10.1109/viscomm69388.2025.00009","title":"Visualization Literacy or Skillset? Beyond the Analogy to Textual Literacy","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Science Foundation","keywords":"Visualization; Analogy; Literacy; Flexibility (engineering); Visual literacy; Meaning (existential)","score_opus":0.014183662270053705,"score_gpt":0.36393596020761837,"score_spread":0.3497522979375647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7116866109","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005853501,0.0002732142,0.9650667,0.013072669,0.0016486126,0.00063306314,0.00008512732,0.00017479464,0.018460482],"genre_scores_gemma":[0.50804025,0.000672023,0.014936299,0.17463337,0.0006430677,0.00005568713,0.000495747,0.000059759623,0.3004638],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99562764,0.0005018176,0.0012717749,0.0011708676,0.0006656605,0.00076222117],"domain_scores_gemma":[0.9958899,0.00066639984,0.00025974834,0.0017989235,0.0010583746,0.00032667356],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00086351123,0.00050098175,0.00048851734,0.00086082966,0.0007870913,0.0041768244,0.0026715628,0.00018566355,0.0021334009],"category_scores_gemma":[0.0008362394,0.0003303045,0.00017844333,0.007514822,0.0001708423,0.0020480636,0.0017281225,0.00025620536,0.00090178056],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003847685,0.0003638348,0.00048805965,0.000061355546,0.000090770285,0.000016931492,0.0050888495,0.00023052904,0.00003073571,0.6361368,0.11806079,0.23939292],"study_design_scores_gemma":[0.00051071605,0.00021599891,0.0010599189,0.00016620531,0.000069094785,0.00001220507,0.00023923985,0.4962318,0.00026859503,0.002401769,0.49842134,0.00040312565],"about_ca_topic_score_codex":0.000079355974,"about_ca_topic_score_gemma":0.00009553746,"teacher_disagreement_score":0.9501304,"about_ca_system_score_codex":0.00012020134,"about_ca_system_score_gemma":0.0007144644,"threshold_uncertainty_score":0.9999149},"labels":[],"label_agreement":null},{"id":"W7117541949","doi":"10.1109/iisa66859.2025.11311338","title":"Visual Querying for Insights into Social Platform Activities","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Visual language; Subject (documents); Software; Visualization; Data visualization; Visual methods; Social media; Data collection","score_opus":0.03319923897023624,"score_gpt":0.3559298343343804,"score_spread":0.32273059536414417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117541949","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0034498023,0.00014548741,0.97703105,0.0013249564,0.0013426454,0.0003016937,0.0000072408543,0.00014592071,0.016251221],"genre_scores_gemma":[0.9685566,0.00009203371,0.0061298306,0.0037852388,0.00034455524,0.00002620615,0.00004736065,0.000016108102,0.021002075],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99814874,0.000050584003,0.00051085703,0.0005660239,0.0003081521,0.00041563474],"domain_scores_gemma":[0.9990118,0.0002845841,0.00015335009,0.00027655927,0.0001855104,0.00008815321],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00031394136,0.00027496996,0.0003552015,0.00040761245,0.0011411824,0.0011421256,0.00078054174,0.00018495947,0.00007769402],"category_scores_gemma":[0.000109851186,0.00026826325,0.00019291454,0.0009601882,0.0001521993,0.0017095284,0.0006376949,0.0001429465,0.000026359396],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001892211,0.00016776107,0.000025711419,0.00017824511,0.00008993903,0.0000011490426,0.0043426636,0.000012939768,0.0002321071,0.8447019,0.013197555,0.13703111],"study_design_scores_gemma":[0.0007773592,0.00010120644,0.000055909055,0.00008702125,0.00005054493,4.1452822e-7,0.0018346526,0.8371878,0.008191256,0.025822124,0.1255114,0.0003803185],"about_ca_topic_score_codex":0.00004754189,"about_ca_topic_score_gemma":0.00015906665,"teacher_disagreement_score":0.9709012,"about_ca_system_score_codex":0.00014937557,"about_ca_system_score_gemma":0.00059910194,"threshold_uncertainty_score":0.99997693},"labels":[],"label_agreement":null},{"id":"W7117566625","doi":"10.1109/vis60296.2025.00006","title":"The Perils of Chart Deception: How Misleading Visualizations Affect Vision-Language Models","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; York University","funders":"","keywords":"Affect (linguistics); Chart; Perception; Pie chart; Visualization; Data visualization","score_opus":0.023978174152128558,"score_gpt":0.35435373827976774,"score_spread":0.3303755641276392,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117566625","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009964111,0.0010820323,0.97603565,0.0063844384,0.0009196758,0.00037937105,0.000030345125,0.00011087426,0.014061194],"genre_scores_gemma":[0.94427925,0.0013853059,0.0027579472,0.001047573,0.000092404065,0.000013761958,0.000043328822,0.000018984447,0.05036143],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99732006,0.0003258993,0.0006429933,0.00061657024,0.00062419364,0.00047025984],"domain_scores_gemma":[0.9973123,0.0004636753,0.00030083072,0.0012838378,0.00049377955,0.00014557657],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00096957065,0.00030943722,0.00037777072,0.00035199395,0.0010020272,0.0015762385,0.0015674661,0.00013599465,0.00023639246],"category_scores_gemma":[0.00031719875,0.00023419711,0.00023243231,0.002664311,0.00031146288,0.001273234,0.00070648396,0.00015724136,0.000043266416],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008647805,0.00021714371,0.000085823085,0.00012754193,0.00011951247,0.0000025516822,0.00291804,0.0023215057,0.0014719854,0.9185681,0.039385866,0.034773294],"study_design_scores_gemma":[0.0003693717,0.000088817054,0.00008774226,0.00028289997,0.0000614157,0.0000026278865,0.0022874412,0.98177224,0.0036509398,0.0016553538,0.009498673,0.0002424719],"about_ca_topic_score_codex":0.000018079325,"about_ca_topic_score_gemma":0.000054856137,"teacher_disagreement_score":0.97945076,"about_ca_system_score_codex":0.00006917306,"about_ca_system_score_gemma":0.00033720405,"threshold_uncertainty_score":0.9994602},"labels":[],"label_agreement":null},{"id":"W7117574341","doi":"10.1109/vis60296.2025.00049","title":"ViStruct: Simulating Expert-Like Reasoning Through Task Decomposition and Visual Attention","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Visualization; Chart; Visual reasoning; Task (project management); Pipeline (software); Key (lock); Data visualization; Decomposition","score_opus":0.01625456402249652,"score_gpt":0.35958989854197343,"score_spread":0.3433353345194769,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117574341","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02286895,0.0005667929,0.96930295,0.00076197216,0.00097159867,0.00020314679,0.0000072672137,0.00017227657,0.0051450394],"genre_scores_gemma":[0.95808464,0.00032585088,0.035972044,0.0031590755,0.00010139188,0.0000042804954,0.000092731236,0.000015901393,0.0022441002],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99742275,0.00017927423,0.00070690655,0.0008868083,0.0003764466,0.00042778315],"domain_scores_gemma":[0.99888635,0.00013909487,0.00024290911,0.00038820156,0.0002238552,0.00011957014],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0003311384,0.00032483414,0.00032812424,0.00019787923,0.0007766983,0.0014865062,0.00037188135,0.00015603667,0.00010486429],"category_scores_gemma":[0.00009532138,0.0003429722,0.00010300171,0.0010749815,0.00013258168,0.0018494126,0.000736219,0.0001765096,0.000029723684],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006063664,0.00064371584,0.008738145,0.00038923655,0.00034495062,0.000036420442,0.004128601,0.0015958111,0.012634313,0.6675297,0.007441826,0.2964566],"study_design_scores_gemma":[0.0007380875,0.00008722976,0.0019886359,0.00048328732,0.00004784778,0.000011267784,0.00052105053,0.98928833,0.0006416152,0.0013445944,0.004489609,0.0003584737],"about_ca_topic_score_codex":0.00012976289,"about_ca_topic_score_gemma":0.000015427142,"teacher_disagreement_score":0.9876925,"about_ca_system_score_codex":0.00009581646,"about_ca_system_score_gemma":0.00011197981,"threshold_uncertainty_score":0.99990225},"labels":[],"label_agreement":null},{"id":"W7117584455","doi":"10.1109/vis60296.2025.00061","title":"FlexPhys: A Workshop Cookbook for Operationalizing Data Physicalization Research Questions","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Operationalization; Process (computing); Interactivity; Toolbox; Core (optical fiber); Research data","score_opus":0.3102322545123683,"score_gpt":0.5213821856306846,"score_spread":0.21114993111831631,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117584455","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000012460473,0.00044012646,0.97547406,0.013633969,0.0006756225,0.0009832596,0.00027061533,0.00014545374,0.008364449],"genre_scores_gemma":[0.20742509,0.002361102,0.25061122,0.018409375,0.002491823,0.0006001582,0.015178676,0.00014296349,0.5027796],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9961051,0.0004545358,0.0007302426,0.0013667963,0.000652959,0.00069036667],"domain_scores_gemma":[0.9938427,0.0011205155,0.00010701318,0.00275421,0.0019947723,0.00018079004],"candidate_categories":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0026514933,0.00025723892,0.00030832173,0.0005650501,0.0015004299,0.0026292528,0.0034608683,0.00015905104,0.00019407267],"category_scores_gemma":[0.0022802805,0.000265798,0.00008242455,0.0034475606,0.00028955328,0.0025164378,0.002638435,0.00028724037,0.00015145009],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008551182,0.0003178838,0.00001538447,0.00008897311,0.000058194884,5.6818794e-7,0.00025335103,0.0012792636,0.00012580513,0.77781373,0.20399891,0.016039407],"study_design_scores_gemma":[0.00038336846,0.000029983132,0.000021348997,0.00032535533,0.000032971104,4.4354454e-7,0.00020150564,0.69018036,0.00015397777,0.014753804,0.2937302,0.00018668313],"about_ca_topic_score_codex":0.00007092407,"about_ca_topic_score_gemma":0.00017393236,"teacher_disagreement_score":0.7630599,"about_ca_system_score_codex":0.00016983756,"about_ca_system_score_gemma":0.0015718598,"threshold_uncertainty_score":0.99997944},"labels":[],"label_agreement":null},{"id":"W7118174980","doi":"10.1145/3731599.3787536","title":"10.1145/3731599.3787536","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Session (web analytics); Visualization; Data visualization; Component (thermodynamics); Key (lock)","score_opus":0.009981016311600185,"score_gpt":0.22323526223397996,"score_spread":0.2132542459223798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7118174980","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000025269834,0.000010818998,0.0024996107,0.00057437597,0.0000035654907,0.000056267938,0.0000075474604,0.00021137235,0.9966112],"genre_scores_gemma":[0.000082579136,3.9543875e-7,0.0019406977,0.00047697057,0.000047233356,0.0000023541093,0.000015789483,0.0000057426078,0.99742824],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99926686,0.000023263576,0.00012504148,0.00021308695,0.00019737333,0.00017434606],"domain_scores_gemma":[0.9993588,0.00001716504,0.000018281553,0.00043685085,0.00004141295,0.00012753603],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00010986689,0.00008012,0.000088724686,0.00006417268,0.000059985534,0.00015625519,0.0006441465,0.00002941039,0.9600613],"category_scores_gemma":[0.000019225748,0.00007739956,0.00003056667,0.00040999625,0.00001323222,0.00025351674,0.000098749755,0.000041668154,0.9790297],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000024216672,0.0000331561,1.5726896e-7,0.0000017118937,0.00000478501,0.000004114306,0.000018843386,0.000105700215,0.0000130821445,0.00051874004,0.32901546,0.6702818],"study_design_scores_gemma":[0.00008628995,0.00004117082,0.000012150399,0.0000052124587,0.0000026071236,0.000003694247,2.1394638e-7,0.036088374,0.000047586953,0.00003593724,0.963569,0.00010780465],"about_ca_topic_score_codex":0.0000053822146,"about_ca_topic_score_gemma":6.425029e-8,"teacher_disagreement_score":0.670174,"about_ca_system_score_codex":0.000013197023,"about_ca_system_score_gemma":0.000026880922,"threshold_uncertainty_score":0.31562626},"labels":[],"label_agreement":null},{"id":"W7119075833","doi":"10.1109/hfia68651.2025.00007","title":"Evaluating an Immersive Analytics Application at an Enterprise Business Intelligence Customer Conference","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Usability; Novelty; Formative assessment; Perspective (graphical); Context (archaeology); Analytics; Business intelligence; Pluralistic walkthrough","score_opus":0.08709432832887225,"score_gpt":0.4167100476550523,"score_spread":0.32961571932618006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7119075833","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005589066,0.000083975196,0.98570997,0.0007986064,0.00060383714,0.000542838,0.000036469453,0.000114341405,0.0065209065],"genre_scores_gemma":[0.9720805,0.0003790951,0.016254598,0.0023561919,0.0000943893,0.000025119027,0.0003259155,0.00002361735,0.008460534],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.995418,0.00039729974,0.0011221161,0.0016028861,0.00083034526,0.00062936073],"domain_scores_gemma":[0.9941662,0.00013925614,0.00051530404,0.002196711,0.0025748925,0.00040764897],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0011744132,0.0004953732,0.0004895063,0.0005755957,0.0006456798,0.0011682245,0.002644951,0.00021614424,0.00077462546],"category_scores_gemma":[0.00026225866,0.00051144516,0.000102594735,0.0040157624,0.00032243782,0.0023809252,0.0013916646,0.00025055537,0.0005642421],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000887335,0.0014607481,0.003725343,0.0002584819,0.00017122796,0.000009937564,0.003999055,0.027722795,0.0062185563,0.46371838,0.0010255311,0.4916012],"study_design_scores_gemma":[0.0002739111,0.00014535575,0.0011141632,0.00014221644,0.00016236478,0.0000047792023,0.0011124562,0.9880104,0.004509671,0.0015653169,0.0024153262,0.00054402766],"about_ca_topic_score_codex":0.0002771237,"about_ca_topic_score_gemma":0.00030567517,"teacher_disagreement_score":0.96945536,"about_ca_system_score_codex":0.0003352114,"about_ca_system_score_gemma":0.00085024256,"threshold_uncertainty_score":0.99986863},"labels":[],"label_agreement":null},{"id":"W7127272289","doi":"10.1109/ccece64018.2025.11364477","title":"Diagram Annotation and Classification for Visually Impaired People in Higher Education","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan College","funders":"","keywords":"Diagram; Visually impaired; Annotation; Higher education; Training set","score_opus":0.04772533480055934,"score_gpt":0.36481992492038634,"score_spread":0.317094590119827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7127272289","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010424241,0.00045128708,0.9617848,0.018893773,0.001754052,0.0011383572,0.00001900726,0.00009675618,0.0054377536],"genre_scores_gemma":[0.9672456,0.0002568893,0.005306925,0.0022834805,0.000075403164,0.00012197517,0.00022499145,0.000010024535,0.024474703],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99833286,0.00009811077,0.00056166603,0.0005899979,0.00016847602,0.00024890405],"domain_scores_gemma":[0.99886626,0.00014899833,0.00017423907,0.00038717836,0.0003369124,0.00008642271],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041921486,0.00018493808,0.00021794537,0.0004910394,0.00015554184,0.0006351133,0.0003194009,0.00013496663,0.000068489564],"category_scores_gemma":[0.00013266143,0.00019630401,0.00004855819,0.0015966286,0.000044813136,0.00090333546,0.00011645081,0.000075753145,0.000014518135],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015963875,0.0005918042,0.0139435185,0.00020292403,0.000014288127,8.225401e-8,0.00055339554,0.000024352177,0.00026446133,0.77516824,0.0116788205,0.19754215],"study_design_scores_gemma":[0.0005958086,0.00007651404,0.34324956,0.00009836676,0.000025567142,3.2001375e-7,0.00020100495,0.6364217,0.00007394465,0.006579619,0.0124965375,0.00018107759],"about_ca_topic_score_codex":0.000054178294,"about_ca_topic_score_gemma":0.00021830367,"teacher_disagreement_score":0.9568214,"about_ca_system_score_codex":0.00012244761,"about_ca_system_score_gemma":0.0006725465,"threshold_uncertainty_score":0.8005045},"labels":[],"label_agreement":null},{"id":"W7130353007","doi":"10.1109/bigdia68682.2025.11382701","title":"Text2Graph: A Method for Automatically Drawing Statistical Graphs Based on Large Language Models","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Natural Science Foundation of China","keywords":"Visualization; Process (computing); Statistical model; Graph drawing; Graph; Natural language; Data visualization; Visual language","score_opus":0.023971608341724335,"score_gpt":0.3779290183171736,"score_spread":0.3539574099754493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7130353007","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000010943263,0.000050684164,0.9818508,0.001916192,0.00037178045,0.00063732377,0.00060785783,0.0002967203,0.014257668],"genre_scores_gemma":[0.096641585,0.000009056201,0.8834852,0.016427273,0.000027275346,0.000044556353,0.00016962177,0.000025901316,0.003169559],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9964768,0.00037210408,0.00082308287,0.0009639596,0.0005876358,0.0007763859],"domain_scores_gemma":[0.99627894,0.0019855974,0.00013244284,0.001068475,0.00025868276,0.00027584782],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0017540847,0.00038588032,0.00053812243,0.00072208914,0.00041773933,0.00091238256,0.0010750178,0.00017882792,0.00039625278],"category_scores_gemma":[0.0006903241,0.00035057138,0.00027994785,0.0017246803,0.00008830729,0.00043642757,0.0002933008,0.00021756087,0.000036684945],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026261887,0.0005715843,0.00001667819,0.00020080378,0.00007038486,0.000011002985,0.00035890948,0.004790326,0.000031789335,0.94734234,0.010756781,0.035823144],"study_design_scores_gemma":[0.0014813573,0.00019015204,0.0000400854,0.0002125211,0.00011269334,6.549959e-7,0.0001674395,0.9115703,0.00019697784,0.08328839,0.0023933556,0.00034606372],"about_ca_topic_score_codex":0.000024719311,"about_ca_topic_score_gemma":0.000025973093,"teacher_disagreement_score":0.90678,"about_ca_system_score_codex":0.000052325602,"about_ca_system_score_gemma":0.00051120453,"threshold_uncertainty_score":0.9998946},"labels":[],"label_agreement":null},{"id":"W7132054887","doi":"","title":"A Web-based framework for product information sharing & visualization","year":2005,"lang":"en","type":"article","venue":"NPARC","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Visualization; Information visualization; Product (mathematics); Information sharing; Information system; Data visualization","score_opus":0.02366760773358928,"score_gpt":0.31445732052375086,"score_spread":0.2907897127901616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132054887","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00051344064,0.0000045838037,0.9952739,0.0019730087,0.00011748274,0.00018016757,0.000007705513,0.0002108895,0.0017188259],"genre_scores_gemma":[0.49096003,0.0000049468194,0.5048645,0.0036458217,0.0001929676,0.000035413483,0.00014063253,0.000007993161,0.00014769149],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992981,0.00001094166,0.00020347271,0.0001603434,0.00018194591,0.0001451859],"domain_scores_gemma":[0.99935895,0.000034536737,0.00009326658,0.00032995557,0.00013589372,0.000047379428],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022704873,0.00007206457,0.00007075252,0.000119605436,0.00009748358,0.00029030544,0.00039998052,0.00003444957,0.00005343469],"category_scores_gemma":[0.00023902039,0.000071160306,0.000031783966,0.00037301632,0.000010557753,0.0013598858,0.000063401196,0.00004113986,0.000082158724],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003139665,0.000034974695,0.00016654075,0.000029263258,0.0000036771687,6.3703006e-8,0.0002382099,0.0010522406,0.000312883,0.94562787,0.006196686,0.046334457],"study_design_scores_gemma":[0.00023945536,0.000018567764,0.000058094785,0.00002123078,0.0000032763844,4.0912025e-7,0.000005353261,0.85728407,0.003211208,0.012845492,0.12622349,0.00008934319],"about_ca_topic_score_codex":4.555323e-7,"about_ca_topic_score_gemma":0.0000012522936,"teacher_disagreement_score":0.93278235,"about_ca_system_score_codex":0.000032676708,"about_ca_system_score_gemma":0.000065526365,"threshold_uncertainty_score":0.2901833},"labels":[],"label_agreement":null},{"id":"W7132867676","doi":"","title":"Uncertainty Displays for Public Health Decision Support Tools","year":2024,"lang":"","type":"dissertation","venue":"TSpace","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Decision support system; Public health; Resource (disambiguation); Population; Decision analysis; Resource allocation; Population health; Disease; Health care","score_opus":0.1069035851834874,"score_gpt":0.44155570353521423,"score_spread":0.3346521183517268,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132867676","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000946107,0.0008371377,0.9772292,0.010069928,0.0059422846,0.0013924525,0.00049504015,0.00028166838,0.0028061997],"genre_scores_gemma":[0.16544412,0.008848006,0.11260692,0.020143079,0.003230457,0.000867011,0.109519616,0.0008482801,0.5784925],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99456245,0.00015020637,0.0012584185,0.0017005157,0.0011421505,0.0011862804],"domain_scores_gemma":[0.9956679,0.00063735625,0.0007570583,0.0013949061,0.00074958545,0.0007932209],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0020792421,0.00071342615,0.00089949113,0.00065301085,0.00065326504,0.0039494038,0.0019526627,0.00040130803,0.00061548303],"category_scores_gemma":[0.0009966305,0.00069081667,0.0004857719,0.0018265769,0.000073651296,0.0010593641,0.00037605732,0.00048653156,0.0009680075],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006361792,0.00034118915,0.000016983799,0.0018120912,0.00017264455,0.000019854033,0.031074641,0.0005097116,0.000033050997,0.25917628,0.29297525,0.4138047],"study_design_scores_gemma":[0.0005008509,0.00047599222,0.00007874449,0.0005891991,0.00005989127,0.0000094889965,0.0045749336,0.40208232,0.000034475037,0.0019955996,0.58895075,0.0006477536],"about_ca_topic_score_codex":0.0001406353,"about_ca_topic_score_gemma":0.000521329,"teacher_disagreement_score":0.86462224,"about_ca_system_score_codex":0.00044305486,"about_ca_system_score_gemma":0.003966748,"threshold_uncertainty_score":0.99980986},"labels":[],"label_agreement":null},{"id":"W7133057016","doi":"","title":"Application of Visualization-based Analytic Methods in Population Health and Health Services Research to Rehabilitation Sciences","year":2022,"lang":"","type":"dissertation","venue":"TSpace","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Rehabilitation Institute","funders":"Ontario Neurotrauma Foundation","keywords":"Knowledge translation; Dashboard; Health care; Population; Leverage (statistics); Analytics; Visual analytics; Rehabilitation","score_opus":0.09482425852205172,"score_gpt":0.589275130634609,"score_spread":0.4944508721125573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7133057016","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028782913,0.0029957695,0.9525481,0.0107000945,0.00038347725,0.0042701024,0.000040961837,0.00010953404,0.00016905465],"genre_scores_gemma":[0.7940892,0.00069328013,0.19616228,0.0032756426,0.00006584951,0.0003784519,0.0047799973,0.00008506882,0.0004702058],"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.98988974,0.0040143505,0.0018109636,0.0016202887,0.0019437181,0.0007209508],"domain_scores_gemma":[0.995153,0.001221943,0.0015650555,0.00088035903,0.00073112734,0.00044852382],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.017976629,0.00038023083,0.0008981856,0.0039173746,0.0011767073,0.00036731624,0.0011291045,0.00015875495,0.00006511963],"category_scores_gemma":[0.0004451786,0.0004455495,0.0000890325,0.012673826,0.0001760785,0.0005489183,0.00027936944,0.0004066793,0.000006250129],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002188103,0.0016829302,0.11842652,0.013667512,0.000056709316,8.8096795e-7,0.30848643,0.08473612,0.00049767084,0.2510943,0.00054177584,0.22059031],"study_design_scores_gemma":[0.00042871406,0.0018457713,0.05165707,0.0009062495,0.000009786135,5.522185e-7,0.040423024,0.9012099,0.00008816025,0.001425657,0.0016533524,0.00035177518],"about_ca_topic_score_codex":0.026034147,"about_ca_topic_score_gemma":0.0052311337,"teacher_disagreement_score":0.8164738,"about_ca_system_score_codex":0.00082033797,"about_ca_system_score_gemma":0.0024681122,"threshold_uncertainty_score":0.9997996},"labels":[],"label_agreement":null},{"id":"W7134182942","doi":"10.1109/bigdata66926.2025.11401441","title":"Visualizing Asthma-Related Digital Health Data for Everyday Users","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Digital health; eHealth; Health data; mHealth; Everyday life; Data visualization","score_opus":0.0560202523550228,"score_gpt":0.3851307975732202,"score_spread":0.32911054521819744,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7134182942","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006568034,0.0006400153,0.979915,0.00982084,0.0018104523,0.0006288293,0.001113321,0.00026117457,0.005744673],"genre_scores_gemma":[0.620547,0.0020212722,0.06493035,0.056816775,0.00045002336,0.000036272966,0.017342197,0.00018269086,0.23767342],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9959835,0.00011239342,0.0012336008,0.0014277953,0.00044225852,0.00080045324],"domain_scores_gemma":[0.99601674,0.00032089546,0.00037097937,0.0027214056,0.00025297012,0.0003170057],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0012530634,0.00036884152,0.0005308959,0.00039953782,0.0005826182,0.0027497297,0.0036967215,0.00014724459,0.00012472509],"category_scores_gemma":[0.000615689,0.00036977872,0.0001429407,0.0021117353,0.0001282303,0.0037943725,0.002955417,0.0001877961,0.00014063067],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013877177,0.00038611048,0.00047281987,0.00029468007,0.00024156625,0.0000028249092,0.0003725836,0.00015278159,0.0000043871532,0.44652835,0.36650443,0.18502559],"study_design_scores_gemma":[0.0007437675,0.00010868969,0.00009987858,0.00022039242,0.000016620952,0.0000023293378,0.00020480149,0.6390169,0.000017894658,0.0012004307,0.35810396,0.00026428184],"about_ca_topic_score_codex":0.000042694122,"about_ca_topic_score_gemma":0.00003630287,"teacher_disagreement_score":0.91498464,"about_ca_system_score_codex":0.0001439269,"about_ca_system_score_gemma":0.0015754105,"threshold_uncertainty_score":0.9998754},"labels":[],"label_agreement":null},{"id":"W7134252779","doi":"10.1145/3742413.3801717","title":"10.1145/3742413.3801717","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Session (web analytics); Visualization; Data visualization; Storytelling; Information visualization","score_opus":0.010522419092594429,"score_gpt":0.2260016470638379,"score_spread":0.21547922797124347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7134252779","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000024855417,0.000011900264,0.0033487957,0.0005832712,0.0000034936807,0.000056695062,0.000007942748,0.00020928313,0.99575377],"genre_scores_gemma":[0.00009207807,3.902334e-7,0.0017376498,0.00044448485,0.000048106333,0.0000023733373,0.00001535955,0.0000067579467,0.9976528],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99929357,0.000024012597,0.00012271397,0.00021249712,0.00017397373,0.00017325718],"domain_scores_gemma":[0.999347,0.000017879065,0.000018838875,0.00045268866,0.00003599345,0.0001276577],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001036948,0.00007981721,0.000087846915,0.000059882426,0.00006695086,0.0001636766,0.0006667495,0.000025818454,0.9569741],"category_scores_gemma":[0.000019357007,0.00007719879,0.000030436022,0.00037395535,0.000013149755,0.0002568975,0.00010236098,0.000037504546,0.9780438],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002470809,0.000033369295,1.5353962e-7,0.0000017507061,0.000004859078,0.0000043735645,0.000019562747,0.00010708292,0.000011213369,0.0004354738,0.34736097,0.6520187],"study_design_scores_gemma":[0.0000847867,0.000042451822,0.000011789176,0.0000052968185,0.000002610597,0.0000035086687,2.0110944e-7,0.039072134,0.00004414892,0.000028163626,0.96059793,0.000107000844],"about_ca_topic_score_codex":0.00000504907,"about_ca_topic_score_gemma":6.1913696e-8,"teacher_disagreement_score":0.65191174,"about_ca_system_score_codex":0.00001284525,"about_ca_system_score_gemma":0.000024179897,"threshold_uncertainty_score":0.31480753},"labels":[],"label_agreement":null},{"id":"W7135159007","doi":"","title":"Interaction Techniques for Stacked-Dimension Visualizations","year":2025,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria; University of Saskatchewan","funders":"University of Saskatchewan","keywords":"Visualization; Data visualization; Focus (optics); Feature (linguistics); Perspective (graphical)","score_opus":0.01670314902045808,"score_gpt":0.30255103898585906,"score_spread":0.285847889965401,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7135159007","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000732343,0.00006702196,0.97024757,0.009905793,0.00014648863,0.00026960712,0.00001501726,0.0004291755,0.018186957],"genre_scores_gemma":[0.3273267,0.00039967237,0.6369301,0.0022142502,0.00002695315,0.00015505354,0.0007740656,0.000038029277,0.032135177],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979936,0.0009065834,0.00033049015,0.00040473873,0.00017730762,0.00018728862],"domain_scores_gemma":[0.99638224,0.0007311984,0.00017320701,0.0010068802,0.0016371506,0.000069339534],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018740755,0.00013289259,0.00014392906,0.0002695718,0.00037621974,0.000436892,0.0008147509,0.000076209115,0.000025097428],"category_scores_gemma":[0.0007914418,0.00014035698,0.00008451852,0.00084063347,0.00006282304,0.00051061064,0.00028856384,0.00009450854,0.000015528896],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000254546,0.00022375719,0.00016485741,0.00003008342,0.000017550228,3.0246056e-7,0.00102505,0.000008890039,0.0027055764,0.9375724,0.01196663,0.046282366],"study_design_scores_gemma":[0.00040202084,8.1649983e-7,0.00021819891,0.00048708648,0.000022046597,0.000002782022,0.000086242166,0.36648884,0.23451081,0.012152711,0.38537782,0.0002506176],"about_ca_topic_score_codex":0.00005982255,"about_ca_topic_score_gemma":0.00015600558,"teacher_disagreement_score":0.9254197,"about_ca_system_score_codex":0.0000663533,"about_ca_system_score_gemma":0.000115996096,"threshold_uncertainty_score":0.57235914},"labels":[],"label_agreement":null},{"id":"W7138338901","doi":"10.18653/v1/2025.ijcnlp-demo.8","title":"StanceMining: An open-source stance detection library supporting time-series and visualization","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Visualization; Information visualization; Data visualization; Key (lock); Feature (linguistics)","score_opus":0.0174917296615402,"score_gpt":0.3169288951524408,"score_spread":0.2994371654909006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7138338901","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0041854633,0.00027384877,0.9767729,0.00067986664,0.00040532817,0.00039595127,0.000023042488,0.00043167433,0.016831907],"genre_scores_gemma":[0.7115602,0.0013503474,0.033505335,0.0056888983,0.00021255823,0.00002669768,0.00031037335,0.0001052771,0.24724033],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970533,0.00026252202,0.0008650768,0.0010326591,0.0003287184,0.0004577259],"domain_scores_gemma":[0.99831,0.00008640301,0.00043734995,0.00076814025,0.00017343534,0.00022461827],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0006449839,0.0003343106,0.00038855246,0.0003200976,0.00072049844,0.005104191,0.0013340515,0.00015960934,0.0005878167],"category_scores_gemma":[0.00017311062,0.00036019032,0.00003231313,0.0021028302,0.00016935126,0.011741837,0.0017944877,0.00015346956,0.000032456683],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021352005,0.0004574493,0.005073333,0.00037455137,0.00010557301,0.000013641833,0.0028808052,0.0003180478,0.0035991294,0.5585353,0.010118669,0.41831],"study_design_scores_gemma":[0.0006229566,0.00049252814,0.00047461325,0.00027838617,0.00004064434,0.000007757744,0.00091241574,0.8846139,0.017788675,0.0029145877,0.0913609,0.0004926638],"about_ca_topic_score_codex":0.0000180342,"about_ca_topic_score_gemma":0.00003885259,"teacher_disagreement_score":0.9432676,"about_ca_system_score_codex":0.00004375404,"about_ca_system_score_gemma":0.00038001122,"threshold_uncertainty_score":0.999885},"labels":[],"label_agreement":null},{"id":"W7146946694","doi":"10.1145/3769872.3769896","title":"Interaction Techniques for Stacked-Dimension Visualizations","year":2025,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria; University of Saskatchewan","funders":"","keywords":"Table (database); Usability; Domain (mathematical analysis); Generalizability theory; Filter (signal processing); Point (geometry); Data exploration","score_opus":0.026265697222357415,"score_gpt":0.3836255835455659,"score_spread":0.3573598863232085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7146946694","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00005677162,0.000006238239,0.9896642,0.0015209126,0.00019470748,0.00014576963,0.0000031579962,0.00037157067,0.008036671],"genre_scores_gemma":[0.21189246,0.00013981962,0.71792245,0.021308841,0.00011876714,0.00015468842,0.00037001097,0.000024701796,0.048068266],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995291,0.000015759873,0.00014358087,0.00016485305,0.00006475123,0.000081950435],"domain_scores_gemma":[0.99951434,0.00005311886,0.000034388064,0.00023016095,0.00014677813,0.000021213233],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000106943866,0.00005371343,0.000060746108,0.00016687677,0.00010003575,0.00014333843,0.00022674592,0.000028177235,0.000019067571],"category_scores_gemma":[0.000044118417,0.000048121234,0.000030068508,0.00041647154,0.000009575641,0.0004197003,0.000072601484,0.00002288289,0.000011346796],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012202424,0.000040371855,0.00003536473,0.000009247254,0.0000058933733,9.9073816e-8,0.000039261355,0.000011209482,0.00067592296,0.90377545,0.08463051,0.0107754385],"study_design_scores_gemma":[0.000118475786,0.000034154255,0.000024917348,0.000023976576,0.000006604683,5.867892e-7,0.000037883245,0.37443915,0.04561841,0.0093413135,0.57026803,0.000086509106],"about_ca_topic_score_codex":0.0000047633994,"about_ca_topic_score_gemma":0.0000071767627,"teacher_disagreement_score":0.89443415,"about_ca_system_score_codex":0.000024392868,"about_ca_system_score_gemma":0.00003242947,"threshold_uncertainty_score":0.1962327},"labels":[],"label_agreement":null},{"id":"W7146975720","doi":"10.1145/3769872.3769897","title":"iTrace: Interactive tracing of Cross-View Data Relationships","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Science Foundation","keywords":"Focus (optics); Visualization; Data visualization; Task (project management); TRACE (psycholinguistics); Visual analytics; Tracing; Perspective (graphical)","score_opus":0.135828189647773,"score_gpt":0.43643808393301614,"score_spread":0.30060989428524315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7146975720","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00054537284,0.0008581218,0.950717,0.0014199818,0.0008334355,0.00019304806,0.00017208868,0.000056735378,0.04520425],"genre_scores_gemma":[0.9644345,0.00045070107,0.014249959,0.00065979734,0.000041609364,0.0000017367668,0.00020680213,0.00000917303,0.019945722],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973083,0.00030131405,0.0010177072,0.0007770548,0.00033901428,0.00025661653],"domain_scores_gemma":[0.99593204,0.0006447656,0.00037105987,0.002448714,0.000509649,0.00009375857],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014804562,0.0002055302,0.00035383325,0.00030841172,0.00031537595,0.00078583776,0.002812656,0.00012310034,0.0004729812],"category_scores_gemma":[0.0016085146,0.00020311806,0.00008000695,0.0019471316,0.00021758022,0.0037613313,0.002066481,0.00041120197,0.00011216435],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021679058,0.0006080918,0.011342793,0.00054816075,0.0002702115,0.0000065426702,0.0017320458,0.0008750935,0.00008351238,0.8700543,0.019282468,0.09517509],"study_design_scores_gemma":[0.00040094153,0.000027974555,0.0055769603,0.0007084081,0.00008782436,0.0000030912465,0.00037481173,0.96405065,0.0010581261,0.0027875395,0.02470267,0.0002210064],"about_ca_topic_score_codex":0.00003893703,"about_ca_topic_score_gemma":0.000062160456,"teacher_disagreement_score":0.9638891,"about_ca_system_score_codex":0.0000488601,"about_ca_system_score_gemma":0.000501294,"threshold_uncertainty_score":0.8282914},"labels":[],"label_agreement":null},{"id":"W7147040269","doi":"10.1145/3769872.3769894","title":"Exploring Emerging Opportunities in Visualization Comprehension Research","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Visualization; Comprehension; Perspective (graphical); Data visualization; Information visualization; Visual analytics","score_opus":0.5984097816517348,"score_gpt":0.4717902432995162,"score_spread":0.12661953835221856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7147040269","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01657238,0.00057121465,0.9293884,0.0046854853,0.0017251786,0.00040543408,0.000004632159,0.00019235259,0.046454933],"genre_scores_gemma":[0.9709339,0.008801873,0.001365614,0.0012052765,0.00008505378,0.00003279295,0.000055794913,0.000021559787,0.017498096],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99606496,0.0007803794,0.0008673493,0.00072184077,0.00088149344,0.0006839812],"domain_scores_gemma":[0.9979872,0.000305976,0.00009105916,0.00077750994,0.0006990022,0.00013922247],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0024308332,0.00022905049,0.0003136492,0.0027205204,0.0005178837,0.0009084462,0.0010032839,0.00009228257,0.00022302323],"category_scores_gemma":[0.0002736213,0.00025146463,0.0000609889,0.005434417,0.00017305251,0.0025245484,0.0014590248,0.0003534456,0.00007814866],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008781634,0.00022942503,0.0017195651,0.000181326,0.0000160746,0.000030412342,0.0022269683,0.0007917852,0.00016008131,0.9050846,0.004984422,0.08456653],"study_design_scores_gemma":[0.00048736334,0.000053618813,0.001964091,0.0009705075,0.000005864741,0.0000011086772,0.006900739,0.9202559,0.001145461,0.0023947859,0.06554836,0.00027217134],"about_ca_topic_score_codex":0.00027064272,"about_ca_topic_score_gemma":0.00011559912,"teacher_disagreement_score":0.95436156,"about_ca_system_score_codex":0.00019130397,"about_ca_system_score_gemma":0.00048365502,"threshold_uncertainty_score":0.99999374},"labels":[],"label_agreement":null},{"id":"W7147399370","doi":"10.1145/3769872.3769895","title":"Design and Evaluation of Visual Summaries to Improve Readability of Large Network Visualizations","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Readability; Visualization; Interpretability; Infographic; Data visualization; Interpretation (philosophy); Information visualization; Domain (mathematical analysis)","score_opus":0.03877080282877359,"score_gpt":0.38617283931015417,"score_spread":0.34740203648138057,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7147399370","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006591304,0.0003516614,0.9901535,0.0004219589,0.00042316795,0.0010699116,0.00005525568,0.000031939704,0.0009013265],"genre_scores_gemma":[0.96621585,0.00011817542,0.032114193,0.0006203222,0.000040665247,0.000023300585,0.000056801866,0.000010667298,0.00080000586],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99619734,0.0009422331,0.0010922103,0.00062489364,0.00079360406,0.00034972397],"domain_scores_gemma":[0.996152,0.0004823018,0.0003492043,0.00070541265,0.0021799733,0.00013115112],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005768826,0.00022365103,0.0004721794,0.0002803942,0.0002200347,0.00017845172,0.00047484774,0.00013077611,0.00017005834],"category_scores_gemma":[0.001215156,0.0002231379,0.000068105146,0.002591014,0.00019270596,0.00049114705,0.00077806925,0.00007561238,0.0000036699],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011235872,0.0016496552,0.010615767,0.00056956086,0.00029595877,3.23659e-7,0.0023090497,0.047388095,0.0013320539,0.82435423,0.011708599,0.09966432],"study_design_scores_gemma":[0.000427751,0.00031294522,0.0021855936,0.00015971837,0.0002523214,1.71769e-7,0.00020777156,0.9774531,0.010829796,0.0071236934,0.00086376374,0.00018338006],"about_ca_topic_score_codex":0.00006414433,"about_ca_topic_score_gemma":0.000076674536,"teacher_disagreement_score":0.9596246,"about_ca_system_score_codex":0.00006598741,"about_ca_system_score_gemma":0.0010291018,"threshold_uncertainty_score":0.90992993},"labels":[],"label_agreement":null},{"id":"W7147457981","doi":"10.1145/3769872.3769899","title":"Exploring Comparative Visual Approaches for Understanding Model Trade-offs in Adversarial Machine Learning","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Adversarial system; Leverage (statistics); Robustness (evolution); Empirical research; Visual analytics; Visualization; Design science","score_opus":0.47885880600736586,"score_gpt":0.37515151093795274,"score_spread":0.10370729506941312,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7147457981","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009503126,0.000118912365,0.98988503,0.0011124696,0.000578761,0.0005747989,0.000020970154,0.000115879775,0.006642884],"genre_scores_gemma":[0.98465806,0.000120324235,0.013130236,0.00025899697,0.00007368074,0.000046663226,0.00008400445,0.000017098258,0.0016109111],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971568,0.0001988898,0.00079056923,0.0008890835,0.0003499015,0.0006147792],"domain_scores_gemma":[0.9989941,0.000363773,0.00018546004,0.0002856352,0.000038820697,0.00013217145],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00082489935,0.00038632003,0.00060102966,0.0006997751,0.00051750307,0.0006040649,0.0006989913,0.00011674605,0.000017837428],"category_scores_gemma":[0.0001055206,0.00040660976,0.00017363558,0.001542957,0.00012360227,0.0018501199,0.00044645154,0.0004227018,0.0000051643724],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008099292,0.00025218615,0.00027907046,0.00009883473,0.00007369268,0.0000014419074,0.006262029,0.33322135,0.000019589805,0.6563235,0.00018076615,0.0032065583],"study_design_scores_gemma":[0.0023206268,0.00013480184,0.00003251669,0.00017438148,0.000048740283,5.663989e-7,0.007533982,0.98120815,0.00029157018,0.0072693,0.0005824267,0.00040291814],"about_ca_topic_score_codex":0.00003986469,"about_ca_topic_score_gemma":0.00016610931,"teacher_disagreement_score":0.9837078,"about_ca_system_score_codex":0.00047449267,"about_ca_system_score_gemma":0.0003665402,"threshold_uncertainty_score":0.9998386},"labels":[],"label_agreement":null},{"id":"W7147672938","doi":"10.1145/3769872.3769900","title":"Map Visualizations for Graphs with Group Restrictions","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Visualization; Graph drawing; Graph; Data visualization; Set (abstract data type); Graph Layout","score_opus":0.022843661880728047,"score_gpt":0.3267618018503492,"score_spread":0.30391813996962114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7147672938","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000028076109,0.00013624797,0.9821836,0.005066177,0.0009570961,0.0006405776,0.00008730762,0.00024260019,0.010658313],"genre_scores_gemma":[0.36710483,0.001310129,0.31958333,0.019570021,0.00034468333,0.00053553696,0.0013108638,0.0001207609,0.29011983],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997992,0.00007375584,0.0005270298,0.00070070376,0.00028341397,0.00042309857],"domain_scores_gemma":[0.998125,0.000196684,0.00014783336,0.000856995,0.00051658036,0.00015691332],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023932385,0.00026420638,0.00025635865,0.00070404325,0.0008806518,0.00090199785,0.00084961817,0.00011368518,0.00017061597],"category_scores_gemma":[0.00007061436,0.0002341704,0.00013262792,0.0033766408,0.00014562579,0.000747261,0.00024132484,0.000104911305,0.000059494807],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009684282,0.00033452248,0.000775531,0.00008450408,0.00010343131,0.0000010744584,0.0001064784,0.000264779,0.000010585834,0.90867376,0.08688154,0.0027541085],"study_design_scores_gemma":[0.0010865217,0.0002954257,0.00056840363,0.00014424257,0.00017662956,0.000002228719,0.00021529428,0.6272862,0.00009690687,0.02642032,0.34335735,0.00035046344],"about_ca_topic_score_codex":0.00006431539,"about_ca_topic_score_gemma":0.00027006614,"teacher_disagreement_score":0.8822534,"about_ca_system_score_codex":0.00006651919,"about_ca_system_score_gemma":0.0003913217,"threshold_uncertainty_score":0.95491916},"labels":[],"label_agreement":null},{"id":"W7154014739","doi":"10.1145/3772318.3808881","title":"10.1145/3772318.3808881","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Session (web analytics); Visualization; Data visualization; Component (thermodynamics)","score_opus":0.010033356810617112,"score_gpt":0.22338076707772103,"score_spread":0.2133474102671039,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7154014739","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000027537953,0.000012139984,0.003724017,0.00058817,0.0000035993216,0.00005789453,0.000007831162,0.00021643238,0.9953624],"genre_scores_gemma":[0.00007730199,3.9924265e-7,0.0020778035,0.00048252085,0.000049165777,0.0000023721132,0.000015849013,0.0000068611585,0.99728775],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992878,0.000023851517,0.00012491712,0.0002132234,0.00017534509,0.00017490056],"domain_scores_gemma":[0.99936205,0.000017928549,0.000018244056,0.00043704646,0.00003566003,0.00012909876],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00010218532,0.000080246995,0.000088079156,0.00006422781,0.00006038837,0.00015554905,0.0006440965,0.000025929556,0.96198356],"category_scores_gemma":[0.000018529734,0.00007753154,0.000030542167,0.0004095623,0.000013208244,0.00025356843,0.000099446435,0.000037305774,0.98015475],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000024074095,0.000032512897,1.3956421e-7,0.0000016625031,0.000004758797,0.000004150966,0.000017972248,0.00012665811,0.000011677411,0.00041624994,0.34577438,0.6536074],"study_design_scores_gemma":[0.00008645445,0.000041820207,0.000011274887,0.0000053914396,0.0000026116095,0.0000035827486,2.027366e-7,0.040297568,0.000047947746,0.00003076584,0.95936495,0.00010741335],"about_ca_topic_score_codex":0.0000047621334,"about_ca_topic_score_gemma":6.065345e-8,"teacher_disagreement_score":0.6535,"about_ca_system_score_codex":0.000013205289,"about_ca_system_score_gemma":0.00002498492,"threshold_uncertainty_score":0.31616446},"labels":[],"label_agreement":null},{"id":"W7154016519","doi":"10.1145/3772318.3809057","title":"10.1145/3772318.3809057","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Session (web analytics); Visualization; Data visualization; Component (thermodynamics); Data collection","score_opus":0.010033356810617112,"score_gpt":0.22338076707772103,"score_spread":0.2133474102671039,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7154016519","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000028162405,0.000012232614,0.003246699,0.00061050616,0.0000036393244,0.000057795376,0.000007853555,0.00021669136,0.9958164],"genre_scores_gemma":[0.000082727165,4.0964116e-7,0.0018085378,0.00048627626,0.00004924204,0.0000023642513,0.000015867761,0.0000068849786,0.9975477],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992865,0.000023987946,0.00012513359,0.00021358146,0.00017561545,0.00017523178],"domain_scores_gemma":[0.9993608,0.000017932933,0.000018273882,0.000437939,0.00003576941,0.00012926673],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001022412,0.00008032533,0.0000882852,0.00006425025,0.000060593695,0.00015555306,0.0006457659,0.000025960462,0.9616149],"category_scores_gemma":[0.00001860512,0.00007759149,0.00003058661,0.0004100889,0.0000132234745,0.0002539047,0.000099544384,0.00003735256,0.98092276],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000023692469,0.00003227734,1.4671159e-7,0.0000016549989,0.000004700194,0.0000040370455,0.00001789016,0.00012350683,0.0000111641175,0.00037935862,0.3480222,0.6514007],"study_design_scores_gemma":[0.00008628237,0.000041985306,0.000011741528,0.0000053131753,0.0000026076154,0.0000035286769,2.0588439e-7,0.04043147,0.000046047877,0.000029443385,0.9592339,0.00010749109],"about_ca_topic_score_codex":0.0000048968495,"about_ca_topic_score_gemma":6.104648e-8,"teacher_disagreement_score":0.6512932,"about_ca_system_score_codex":0.000013242929,"about_ca_system_score_gemma":0.000024998428,"threshold_uncertainty_score":0.3164089},"labels":[],"label_agreement":null},{"id":"W7154076678","doi":"10.1145/3772318.3808949","title":"10.1145/3772318.3808949","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Session (web analytics); Data visualization; Visualization; Component (thermodynamics); Data collection","score_opus":0.010010487345823948,"score_gpt":0.22324052123657284,"score_spread":0.2132300338907489,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7154076678","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00002755692,0.000012157974,0.0032498767,0.00060071464,0.0000036130236,0.000057402794,0.0000078105695,0.00021304731,0.9958278],"genre_scores_gemma":[0.00008478816,4.0462945e-7,0.0018092034,0.00048557782,0.000049241924,0.000002363986,0.000015696229,0.000006865346,0.99754584],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992866,0.000023825216,0.0001253495,0.00021351298,0.00017552363,0.00017519643],"domain_scores_gemma":[0.99936086,0.000017918434,0.000018298348,0.00043791556,0.00003575779,0.00012927651],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00010230691,0.00008030808,0.000088216286,0.000064204905,0.00006059753,0.0001558521,0.00064568827,0.000025951715,0.96375495],"category_scores_gemma":[0.000018580518,0.000077569945,0.000030562605,0.00040957172,0.000013221914,0.00025406113,0.000099612116,0.000037350048,0.98058885],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000023540208,0.000031990287,1.4483591e-7,0.000001620159,0.0000047041344,0.000004001613,0.000017933648,0.00012189306,0.000011145576,0.00037120935,0.34962037,0.64981264],"study_design_scores_gemma":[0.00008636555,0.000041692463,0.000012077958,0.000005304283,0.0000026351593,0.0000035281262,2.0339915e-7,0.04055437,0.00004660297,0.00002912418,0.9591106,0.0001074544],"about_ca_topic_score_codex":0.0000050476783,"about_ca_topic_score_gemma":6.306911e-8,"teacher_disagreement_score":0.6497052,"about_ca_system_score_codex":0.000013222154,"about_ca_system_score_gemma":0.000024876792,"threshold_uncertainty_score":0.31632105},"labels":[],"label_agreement":null},{"id":"W7154125967","doi":"10.1145/3772318.3808944","title":"10.1145/3772318.3808944","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Session (web analytics); Visualization; Data visualization; Information visualization; Data collection","score_opus":0.010210015743344809,"score_gpt":0.22322122441404088,"score_spread":0.21301120867069606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7154125967","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000027881058,0.000012201491,0.0032353448,0.00060900446,0.0000036319414,0.00005773592,0.000007841629,0.00021645137,0.9958299],"genre_scores_gemma":[0.0000829711,4.115328e-7,0.0018085499,0.00048573464,0.000049261034,0.0000023640466,0.000015869058,0.000006867912,0.997548],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99928665,0.000023830336,0.00012514438,0.00021357146,0.00017560562,0.00017522398],"domain_scores_gemma":[0.99936116,0.000017931907,0.000018263494,0.00043801896,0.000035367866,0.0001292692],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000102045924,0.000080318445,0.000088265326,0.00006461023,0.000060608956,0.00015585127,0.00064602424,0.000025957814,0.9623852],"category_scores_gemma":[0.000018474328,0.00007758557,0.00003058652,0.0004120399,0.0000132249825,0.00025393552,0.0000996062,0.000037355123,0.98003376],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000023665095,0.00003209265,1.4461206e-7,0.0000016267393,0.0000046736745,0.0000040143655,0.000018028246,0.00012261733,0.00001120774,0.00037106135,0.34545797,0.6539742],"study_design_scores_gemma":[0.00008664976,0.000042032298,0.0000113841925,0.000005312499,0.000002609364,0.000003528895,2.054455e-7,0.04042117,0.00004688583,0.00002954688,0.9592432,0.000107479165],"about_ca_topic_score_codex":0.0000048979277,"about_ca_topic_score_gemma":6.154425e-8,"teacher_disagreement_score":0.6538667,"about_ca_system_score_codex":0.000013245893,"about_ca_system_score_gemma":0.0000249925,"threshold_uncertainty_score":0.3163848},"labels":[],"label_agreement":null},{"id":"W7154134677","doi":"10.1145/3772318.3809016","title":"10.1145/3772318.3809016","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Session (web analytics); Debugging; Visualization; Interactive visualization; Data visualization","score_opus":0.009625299979264274,"score_gpt":0.2219694069171878,"score_spread":0.21234410693792352,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7154134677","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000024333673,0.000011878695,0.0032749188,0.00064348173,0.00000349371,0.00005623611,0.000008421021,0.00020992849,0.9957673],"genre_scores_gemma":[0.0000723467,4.6507034e-7,0.0016703571,0.00046989086,0.000049651248,0.000002358447,0.000014863741,0.0000068249765,0.99771327],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99929255,0.000023792663,0.00012386331,0.0002120286,0.00017229305,0.00017545559],"domain_scores_gemma":[0.9993688,0.000018503362,0.000018105937,0.00043159295,0.00003527508,0.00012773834],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00010054088,0.00007949694,0.000086879736,0.000063543164,0.000059643142,0.0001485371,0.00063480315,0.000025526046,0.96497124],"category_scores_gemma":[0.000018298531,0.000074899435,0.00003032356,0.00039221303,0.00001319632,0.0002537797,0.00009892666,0.000035238067,0.9829257],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000023623218,0.000030493515,1.3067972e-7,0.0000015679644,0.0000044966614,0.000003831104,0.000016286893,0.00009114718,0.000011689547,0.0003647849,0.35192722,0.647546],"study_design_scores_gemma":[0.00008957858,0.000041153442,0.000010646642,0.000005904383,0.00000252608,0.0000034157279,1.99273e-7,0.03323984,0.000045317018,0.000029838313,0.96642447,0.00010713948],"about_ca_topic_score_codex":0.0000043813243,"about_ca_topic_score_gemma":5.472788e-8,"teacher_disagreement_score":0.6474388,"about_ca_system_score_codex":0.000013573955,"about_ca_system_score_gemma":0.00002541356,"threshold_uncertainty_score":0.30543104},"labels":[],"label_agreement":null},{"id":"W7154135884","doi":"10.1145/3772318.3809053","title":"10.1145/3772318.3809053","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Session (web analytics); Perception; Cognition; Data visualization","score_opus":0.010033356810617112,"score_gpt":0.22338076707772103,"score_spread":0.2133474102671039,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7154135884","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000029547673,0.000012154769,0.0031869924,0.000595779,0.0000036324145,0.0000576922,0.000007869712,0.00021649488,0.99588984],"genre_scores_gemma":[0.000084805666,4.08293e-7,0.001782937,0.0004850748,0.000048994083,0.0000023636471,0.000015930047,0.000006883539,0.9975726],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992871,0.00002393624,0.00012496198,0.00021345622,0.00017541858,0.00017509701],"domain_scores_gemma":[0.99936175,0.000017871676,0.000017832279,0.00043771247,0.000035669407,0.00012917352],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00010194428,0.00008028369,0.00008814877,0.00006433893,0.000060521925,0.00015558019,0.00064567366,0.000025941028,0.9617681],"category_scores_gemma":[0.000018536672,0.00007756547,0.000030554267,0.00041054576,0.000013208598,0.00025364617,0.00009959726,0.000037319984,0.9808923],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000023339392,0.00003198051,1.4760913e-7,0.0000016329471,0.0000046547543,0.0000032369273,0.000017412043,0.00012277064,0.000011277773,0.00037893403,0.3417103,0.6577153],"study_design_scores_gemma":[0.000090266316,0.000041546144,0.000011803223,0.0000052856312,0.0000026082187,0.000002763912,2.0391208e-7,0.041527275,0.000046920013,0.000029359493,0.95813465,0.00010733076],"about_ca_topic_score_codex":0.0000048822144,"about_ca_topic_score_gemma":6.0524975e-8,"teacher_disagreement_score":0.65760803,"about_ca_system_score_codex":0.000013258951,"about_ca_system_score_gemma":0.000024979672,"threshold_uncertainty_score":0.3163028},"labels":[],"label_agreement":null},{"id":"W7160158898","doi":"10.1109/iccv51701.2025.00793","title":"Beyond Pixel Uncertainty: Bounding the OoD Objects in Road Scenes","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Pixel; Object (grammar); Bounding overwatch; Feature (linguistics); Object detection","score_opus":0.01985589265385124,"score_gpt":0.31667053506766896,"score_spread":0.2968146424138177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7160158898","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009841905,0.002315555,0.77479255,0.021862805,0.0049245767,0.00076095696,0.000020287107,0.00021130673,0.18527006],"genre_scores_gemma":[0.9666258,0.00046816588,0.0010247019,0.009264613,0.00010189167,0.000008943164,0.000013501416,0.000010417011,0.022481935],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974211,0.00024795084,0.00063732,0.00067489245,0.00043985038,0.00057887833],"domain_scores_gemma":[0.9983644,0.00021424664,0.000137001,0.0010341712,0.00015014036,0.00010007006],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0010630008,0.0002801975,0.00031231926,0.0004205898,0.00051658164,0.0017039803,0.0018754508,0.00011426557,0.0001912477],"category_scores_gemma":[0.0003119328,0.00020466236,0.00010866271,0.0034151166,0.0002057042,0.0006563645,0.0010189741,0.00027121868,0.00011416257],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007971238,0.00023337203,0.0028087052,0.000075010415,0.000056540182,0.000010725311,0.002504627,0.0015498995,0.000120957215,0.8927841,0.006934742,0.092913345],"study_design_scores_gemma":[0.0006659354,0.000042879194,0.0019522309,0.00029409648,0.00003196481,0.000003070945,0.0016712253,0.954614,0.0003430103,0.015635043,0.024435133,0.0003114165],"about_ca_topic_score_codex":0.00043984357,"about_ca_topic_score_gemma":0.0019212015,"teacher_disagreement_score":0.95678395,"about_ca_system_score_codex":0.00014566824,"about_ca_system_score_gemma":0.0007248131,"threshold_uncertainty_score":0.99933237},"labels":[],"label_agreement":null},{"id":"W7162026875","doi":"10.82308/20630","title":"Interpretation of dairy data using interactive visualization","year":2004,"lang":"en","type":"dissertation","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Visualization; Context (archaeology); Interactive visualization; Process (computing); Data visualization; Domain (mathematical analysis); Software; Matching (statistics)","score_opus":0.04617249599268687,"score_gpt":0.39642079184694634,"score_spread":0.3502482958542595,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7162026875","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011941605,0.00005583976,0.99298674,0.000011434999,0.00079295214,0.00014622048,0.000058165773,0.00009116462,0.004663308],"genre_scores_gemma":[0.8867413,0.00013979775,0.0640628,0.00032604416,0.00013269835,0.00000503077,0.04447738,0.000072475166,0.004042486],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99841714,0.000059503982,0.0005227877,0.0005157898,0.0003643848,0.00012041338],"domain_scores_gemma":[0.99795496,0.000044368,0.0005927455,0.0010102704,0.0003530871,0.000044541415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001886562,0.00018782527,0.00026424567,0.00036141573,0.000048970327,0.00016729356,0.0015651432,0.00013727472,0.000064294305],"category_scores_gemma":[0.00016891467,0.00018725294,0.000050202867,0.0005747017,0.000016872982,0.0018122246,0.0002860191,0.000108106884,0.000017217584],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020889462,0.0012093736,0.00018929168,0.0021168056,0.0007582007,0.000020984766,0.02717064,0.008855319,0.006457782,0.831642,0.0055990457,0.11577172],"study_design_scores_gemma":[0.00019439445,0.000032092186,0.00007492034,0.0004512448,0.000053287364,0.0000022564145,0.0006739977,0.9925154,0.004056369,0.0014026841,0.0003236614,0.00021968808],"about_ca_topic_score_codex":0.00012127773,"about_ca_topic_score_gemma":0.00016328829,"teacher_disagreement_score":0.9836601,"about_ca_system_score_codex":0.000085775966,"about_ca_system_score_gemma":0.00039269624,"threshold_uncertainty_score":0.76359534},"labels":[],"label_agreement":null},{"id":"W7165679016","doi":"10.2196/86583","title":"A Network Visualization Query System for Multi-Drug Compatibility Based on a WeChat Mini Program: A Preliminary Usability and Efficiency Evaluation (Preprint)","year":2025,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Usability; Compatibility (geochemistry); Visualization; Pairwise comparison; Scalability; System usability scale; Mobile device","score_opus":0.10987991685269523,"score_gpt":0.47793696917588585,"score_spread":0.36805705232319064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7165679016","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.053998683,0.000051834268,0.93879783,0.00040409135,0.00015963979,0.0058163446,0.000025049072,0.00024142236,0.00050508423],"genre_scores_gemma":[0.9886638,0.0000031789368,0.009348059,0.000098006116,0.00002128596,0.0017013097,0.000104568564,0.000007951916,0.000051836294],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9958605,0.0014933988,0.0005363771,0.00066011486,0.0009803277,0.00046926324],"domain_scores_gemma":[0.9965918,0.0009952466,0.00015265134,0.0008002274,0.0013447552,0.000115284995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008922552,0.00017562021,0.00025551746,0.00037233206,0.00061148335,0.0004124696,0.00061673555,0.00008529787,0.000005451354],"category_scores_gemma":[0.00074955355,0.00015354442,0.000069852504,0.0017548136,0.00020068779,0.00060838996,0.00044781668,0.00021036719,0.0000111322],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001621912,0.012945376,0.028792836,0.011363321,0.00013677403,0.000004295713,0.029841239,0.039013032,0.00009585538,0.45238277,0.02136545,0.40243712],"study_design_scores_gemma":[0.0012160777,0.0005990299,0.014467435,0.00044292197,0.000007743759,5.281434e-7,0.000804147,0.9807162,0.00027038765,0.00088645745,0.00045581855,0.00013325004],"about_ca_topic_score_codex":0.00002528827,"about_ca_topic_score_gemma":0.00001846436,"teacher_disagreement_score":0.94170314,"about_ca_system_score_codex":0.00045353686,"about_ca_system_score_gemma":0.00043790648,"threshold_uncertainty_score":0.62613595},"labels":[],"label_agreement":null},{"id":"W7571504","doi":"10.46743/2160-3715/2013.1487","title":"Diagrammatic Elicitation: Defining the Use of Diagrams in Data Collection","year":2015,"lang":"en","type":"article","venue":"The Qualitative Report","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University Health Network","funders":"","keywords":"Diagrammatic reasoning; Terminology; Data collection; Process (computing); Computer science; Diagram; Data science; Management science; Sociology; Linguistics; Engineering","score_opus":0.45076305736260763,"score_gpt":0.5023918840145921,"score_spread":0.05162882665198448,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7571504","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011090776,0.00010595051,0.9837889,0.0038989517,0.00019552735,0.00023891169,0.000008809593,0.00004340008,0.0006287433],"genre_scores_gemma":[0.9710083,0.000040207662,0.0266737,0.00059780356,0.000035506517,0.0000311135,0.00027976063,0.000013225337,0.0013203735],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99787545,0.00085003296,0.00051974144,0.00021533291,0.00042012546,0.000119341756],"domain_scores_gemma":[0.9966313,0.001523195,0.00039511442,0.0011710726,0.00023961872,0.000039648217],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0045892126,0.000079219564,0.00014494998,0.00006983059,0.00008374783,0.00012676214,0.0007893251,0.00002214321,0.000002144123],"category_scores_gemma":[0.0048607653,0.000045342003,0.000023769338,0.0010931155,0.00012372943,0.0006994,0.00031345352,0.0000862235,0.000014035738],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015633694,0.00014020265,0.0023355929,0.00002467495,0.00006434372,0.000042159136,0.15233132,0.0011852556,0.00001233088,0.80749285,0.029236652,0.00711897],"study_design_scores_gemma":[0.0006992211,0.00016824047,0.0037833662,0.000079762096,0.000047677306,0.0001523095,0.034270342,0.8144464,0.00017122524,0.11157523,0.034264,0.00034222714],"about_ca_topic_score_codex":0.00038111297,"about_ca_topic_score_gemma":0.00023122663,"teacher_disagreement_score":0.95991755,"about_ca_system_score_codex":0.000035278652,"about_ca_system_score_gemma":0.00018417634,"threshold_uncertainty_score":0.5819141},"labels":[],"label_agreement":null},{"id":"W76396976","doi":"10.1007/978-94-017-1689-5_19","title":"Archimedean Kaleidoscope: A Cognitive Tool to Support Thinking and Reasoning about Geometric Solids","year":2004,"lang":"en","type":"book-chapter","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Kaleidoscope; Interactivity; Polyhedron; Computer science; Cognition; Metaphor; Human–computer interaction; Visualization; Cognitive science; Psychology; Multimedia; Artificial intelligence; Mathematics; Geometry","score_opus":0.024340177968182088,"score_gpt":0.2946848987116401,"score_spread":0.270344720743458,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W76396976","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000032416687,0.00008763593,0.54629016,0.00015368985,0.00014804119,0.00026223206,0.00004566072,0.0001998072,0.45278034],"genre_scores_gemma":[0.016885202,0.00069034635,0.116532765,0.014658624,0.00043686177,0.000017913144,0.00053017674,0.00014946001,0.85009867],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977489,0.000014897048,0.00042659816,0.00079875905,0.00063332415,0.00037750375],"domain_scores_gemma":[0.9987564,0.00011336391,0.00018452325,0.00048204255,0.00019159116,0.000272064],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00040890175,0.0003768603,0.00041838762,0.00093695143,0.00020878765,0.00076705357,0.00080414827,0.0001725298,0.00054168026],"category_scores_gemma":[0.00016992363,0.00035835753,0.00009025506,0.0003415007,0.00007186712,0.0004003586,0.0010171186,0.0003090076,0.00040238455],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000338326,0.000015786844,0.000059285485,0.000039402712,0.00006051799,0.00007162467,0.0005707854,0.000007698149,0.0000011531189,0.9374836,0.0021199763,0.05956678],"study_design_scores_gemma":[0.0057311202,0.0032245053,0.0024752533,0.009899293,0.00076386606,0.00060646265,0.00031525877,0.017328257,0.0006790513,0.32413724,0.6259531,0.008886637],"about_ca_topic_score_codex":0.000023638304,"about_ca_topic_score_gemma":0.000015812098,"teacher_disagreement_score":0.6238331,"about_ca_system_score_codex":0.00007533899,"about_ca_system_score_gemma":0.0003126204,"threshold_uncertainty_score":0.9998868},"labels":[],"label_agreement":null},{"id":"W7692735","doi":"10.1007/978-3-319-08786-3_16","title":"Te,Te,Hi,Hi: Eye Gaze Sequence Analysis for Informing User-Adaptive Information Visualizations","year":2014,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Visualization; Human–computer interaction; Gaze; Task (project management); Information visualization; Eye tracking; Sequence (biology); User interface; Data visualization; Perception; Artificial intelligence; Information retrieval; Programming language","score_opus":0.030542549745933834,"score_gpt":0.30622899857993097,"score_spread":0.2756864488339971,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7692735","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000014366049,0.00004227608,0.99696845,0.0004092895,0.000688494,0.00054780004,0.000086654545,0.00022994404,0.0010127019],"genre_scores_gemma":[0.2486777,0.00010446204,0.73551905,0.012563232,0.0006334549,0.00006320111,0.00088229316,0.000071267554,0.0014853366],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99608666,0.000039662224,0.0010370883,0.0010139513,0.0011514941,0.00067112525],"domain_scores_gemma":[0.9960083,0.00051502266,0.0007986327,0.0014227079,0.0010169386,0.00023842069],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0010858806,0.0005759641,0.00070961623,0.0025223172,0.0005358038,0.0014567882,0.0030825222,0.00033872842,0.000021948032],"category_scores_gemma":[0.00038574784,0.0005543181,0.00028708155,0.0028428582,0.0004697369,0.0029652512,0.0009971943,0.00040033937,0.000058108075],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000059214713,0.000022265465,0.00026737092,0.00007625363,0.000115157054,0.000004629308,0.0017879205,0.16550483,0.000011352758,0.43658996,0.00013882531,0.3954755],"study_design_scores_gemma":[0.000246068,0.00013484039,0.00006572655,0.00018063076,0.00008852209,0.000006634506,0.0000024093376,0.95389605,0.00024342786,0.016608944,0.027857104,0.0006696352],"about_ca_topic_score_codex":0.000044194992,"about_ca_topic_score_gemma":0.0002307896,"teacher_disagreement_score":0.78839123,"about_ca_system_score_codex":0.00035610315,"about_ca_system_score_gemma":0.0007234845,"threshold_uncertainty_score":0.99969083},"labels":[],"label_agreement":null},{"id":"W789599104","doi":"10.1007/s10845-015-1118-5","title":"Towards a product design assessment of visual analytics in decision support applications: a systematic review","year":2015,"lang":"en","type":"review","venue":"Journal of Intelligent Manufacturing","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"University of Calgary","keywords":"Visual analytics; Analytics; Computer science; Data science; Product (mathematics); Field (mathematics); Management science; Systematic review; Product design; Visualization; Knowledge management; Engineering; Artificial intelligence","score_opus":0.11162597024995537,"score_gpt":0.4376284654445435,"score_spread":0.3260024951945881,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W789599104","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[5.6065797e-8,0.49993676,0.49892533,0.000012168005,0.000099813835,0.0009822551,0.0000032557011,0.0000072047014,0.00003316349],"genre_scores_gemma":[0.00001418873,0.9550298,0.044683103,0.0000640778,0.00007174703,0.000047366786,0.000015004693,0.000025305451,0.000049431954],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.99338984,0.00052517705,0.004154374,0.0003771587,0.0012986488,0.00025478026],"domain_scores_gemma":[0.9937497,0.0003409285,0.0042431797,0.00086205924,0.00060727214,0.0001968562],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0060913535,0.00041512685,0.0034641295,0.0011306287,0.000029301425,0.00015897148,0.00210289,0.000113298964,0.000023432834],"category_scores_gemma":[0.00050366734,0.00028495266,0.00062155986,0.0008925824,0.000028126145,0.00042129064,0.00036918162,0.00049559533,0.000021594482],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000014682189,0.0002614863,4.6157496e-7,0.51875645,0.00021714586,0.000044876662,0.00003943757,0.00032616162,7.213175e-8,0.0003560661,0.0006652865,0.4793311],"study_design_scores_gemma":[0.00016171957,0.00028274988,7.052428e-7,0.77047795,0.002081278,0.0005576061,0.000029484672,0.0050850436,0.00012725775,0.00042959207,0.22025917,0.0005074165],"about_ca_topic_score_codex":0.0000018121456,"about_ca_topic_score_gemma":7.3585187e-7,"teacher_disagreement_score":0.4788237,"about_ca_system_score_codex":0.00058177015,"about_ca_system_score_gemma":0.0016754642,"threshold_uncertainty_score":0.99996024},"labels":[],"label_agreement":null},{"id":"W815572053","doi":"10.4018/ijiscram.2014070101","title":"Designing Visual Analytic Tools for Emergency Operation Centers","year":2014,"lang":"en","type":"article","venue":"International Journal of Information Systems for Crisis Response and Management","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"","keywords":"Visual analytics; Analytics; Multidisciplinary approach; Computer science; Field (mathematics); Data science; Cultural analytics; Design science; Knowledge management; Human–computer interaction; Visualization; Management science; Engineering; World Wide Web; Artificial intelligence; Semantic analytics; The Internet","score_opus":0.02220224816747146,"score_gpt":0.3263231989456159,"score_spread":0.30412095077814444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W815572053","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018737473,0.000034494922,0.99513733,0.0012094505,0.0012383142,0.00032199966,0.000016008034,0.000016596958,0.00015205175],"genre_scores_gemma":[0.96333927,0.0006491026,0.03408702,0.0012363715,0.00025362274,0.00006224965,0.000089036555,0.000010110048,0.0002732043],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984728,0.00008959803,0.00081807416,0.00009162465,0.00041408342,0.00011382585],"domain_scores_gemma":[0.9983124,0.00016223211,0.00056409,0.00010812126,0.0007850091,0.00006811383],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002041829,0.000095547286,0.00014969392,0.00056771754,0.0000957339,0.0008519401,0.00045381216,0.00003195409,0.0000029559797],"category_scores_gemma":[0.00029528266,0.000083650884,0.00010115403,0.00010938941,0.000006988629,0.003382424,0.000076114455,0.000033198306,0.000005258244],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030557143,0.00022821367,0.00027334996,0.00072628376,0.0017030006,0.000006913806,0.0043791705,0.03061431,0.00073009526,0.66573626,0.15330051,0.13924618],"study_design_scores_gemma":[0.0018615209,0.00036545808,0.00037437683,0.00009834355,0.000048792095,0.00002825725,0.002105216,0.4943733,0.0003122734,0.00031607656,0.49995226,0.000164143],"about_ca_topic_score_codex":0.000002816753,"about_ca_topic_score_gemma":4.1820962e-7,"teacher_disagreement_score":0.96146554,"about_ca_system_score_codex":0.00006938343,"about_ca_system_score_gemma":0.000025303701,"threshold_uncertainty_score":0.8215278},"labels":[],"label_agreement":null},{"id":"W97627123","doi":"","title":"CIVDDD collaborative research in big data analytics and visualization","year":2013,"lang":"en","type":"article","venue":"OCAD University Open Research Repository (OCAD University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"York University","funders":"","keywords":"Visualization; Data science; Big data; Computer science; Data visualization; Visual analytics; Analytics; Presentation (obstetrics); Information visualization; Cloud computing; World Wide Web; Data mining","score_opus":0.25361028828104015,"score_gpt":0.39611339862821066,"score_spread":0.1425031103471705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W97627123","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04162446,0.00012409869,0.04793029,0.0027648862,0.00029198788,0.002112655,0.00009592243,0.00015279137,0.90490294],"genre_scores_gemma":[0.84841,0.0013454468,0.003644935,0.00010606548,0.00013056182,0.0000012980952,0.00024882064,0.000035302848,0.14607756],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9945283,0.0023062564,0.00023213249,0.0011312243,0.001102978,0.0006991255],"domain_scores_gemma":[0.9956543,0.0004188122,0.000115054914,0.0016744739,0.0017030184,0.00043437365],"candidate_categories":["sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.002522699,0.00018835353,0.0002922151,0.002004929,0.0014323315,0.0014680083,0.005753521,0.0001928973,0.0000023946693],"category_scores_gemma":[0.00017439823,0.00022297658,0.000028391936,0.008280757,0.0007332458,0.005121442,0.005838815,0.0006584183,0.000072012954],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003979907,0.0001752639,0.004214777,0.000025727704,0.000040131177,0.00036443758,0.0005836369,0.000030766154,0.00032604559,0.9872016,0.004789698,0.0022081556],"study_design_scores_gemma":[0.0031726868,0.00049186917,0.011322969,0.00025500453,0.000032526947,0.000023361988,0.016028602,0.21629706,0.0006303583,0.0013808741,0.749584,0.0007806943],"about_ca_topic_score_codex":0.003935977,"about_ca_topic_score_gemma":0.0011084478,"teacher_disagreement_score":0.9858207,"about_ca_system_score_codex":0.000599577,"about_ca_system_score_gemma":0.001186379,"threshold_uncertainty_score":0.9998677},"labels":[],"label_agreement":null},{"id":"W993171468","doi":"10.1007/978-3-642-21619-0_71","title":"A Comparison of Children’s and Adults’ Retrieval Performances and Affective Reactions When Using a Conventional Interface and an Information Visualization Interface","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Visualization; Interface (matter); Information visualization; Computer science; Subject (documents); Human–computer interaction; User interface; Information retrieval; Psychology; World Wide Web; Artificial intelligence","score_opus":0.026679086115622218,"score_gpt":0.32432169139138023,"score_spread":0.29764260527575803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W993171468","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028413521,0.00030112933,0.9706292,0.000029350675,0.00021968083,0.00026522152,0.000019967745,0.00004051659,0.00008137017],"genre_scores_gemma":[0.95182246,0.00011419037,0.0478859,0.000076935874,0.000046784608,9.548845e-7,0.000029787512,0.000009664416,0.0000133446865],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983612,0.000042552623,0.00049672375,0.00053414365,0.00038071346,0.0001847155],"domain_scores_gemma":[0.9987202,0.00009853987,0.0004903923,0.00030486716,0.000279129,0.00010682679],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046631202,0.000255652,0.0003398272,0.00062267715,0.0001895631,0.00037573092,0.00045881467,0.00015277551,0.0000084572675],"category_scores_gemma":[0.00006930492,0.00024385407,0.000025342595,0.0002522285,0.00061307364,0.0026450923,0.0006085644,0.00024993578,0.000001116467],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032106842,0.00038406288,0.024391215,0.0010145598,0.00017648349,0.0000033200013,0.07473124,0.017401226,0.0010087006,0.14502741,0.000043302785,0.7354974],"study_design_scores_gemma":[0.00037792392,0.00038955983,0.0021835314,0.00057277695,0.000018435556,0.000049534858,0.000007673789,0.98719096,0.0021965276,0.006652926,0.000066746485,0.00029342266],"about_ca_topic_score_codex":0.00006814767,"about_ca_topic_score_gemma":0.000045285477,"teacher_disagreement_score":0.96978974,"about_ca_system_score_codex":0.00006922683,"about_ca_system_score_gemma":0.00012091711,"threshold_uncertainty_score":0.9944081},"labels":[],"label_agreement":null}]}