{"meta":{"query_hash":"8dc80d0ecb93","filters":{"venue":"IEEE Symposium on Information Visualization"},"cohort_total":7,"direct_labels_cover":0,"predictions_cover":7,"exported":7,"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/8dc80d0ecb93","api":"https://metacan.xera.ac/api/v1/cohort?venue=IEEE+Symposium+on+Information+Visualization"},"results":[{"id":"W2033650322","doi":"10.1109/infovis.2004.53","title":"PhylloTrees: Harnessing Nature’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":"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":"W3139654456","doi":"10.1109/infvis.2004.60","title":"Steerable, Progressive Multidimensional Scaling","year":2005,"lang":"en","type":"article","venue":"IEEE Symposium on Information Visualization","topic":"Music and Audio Processing","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 British Columbia","funders":"","keywords":"Scaling; Computer science; Multidimensional scaling; Mathematics; Machine learning; Geometry","score_opus":0.010856089549899958,"score_gpt":0.27038138227509545,"score_spread":0.2595252927251955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3139654456","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015777625,0.000021588663,0.9734189,0.0015612604,0.0006235446,0.00025770438,0.0000026181167,0.00036694447,0.007969845],"genre_scores_gemma":[0.96239984,0.000011855855,0.027901117,0.008966076,0.0003348807,0.000047532474,0.00007192512,0.0000126261075,0.00025415173],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985617,0.000044254655,0.00044627252,0.00018074605,0.0005403419,0.00022669206],"domain_scores_gemma":[0.9990237,0.000039202954,0.0003099382,0.0002373979,0.0003076664,0.00008211639],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027570155,0.00015215241,0.00012022386,0.00023839691,0.00030833855,0.0003413629,0.00025072054,0.00008316742,0.00003233526],"category_scores_gemma":[0.000027579494,0.00013977436,0.00004115857,0.00043111155,0.000024186184,0.0048100096,0.00004387156,0.00008981686,0.00041090348],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006045808,0.00033317157,0.00024783803,0.00020144766,0.000045675974,0.0000033830756,0.0161728,0.29871985,0.008237708,0.4325465,0.025511103,0.21792005],"study_design_scores_gemma":[0.0006170812,0.00006592232,0.00015086941,0.00011638224,0.000004847813,0.000012766001,0.00003867062,0.89297616,0.05513583,0.00012764653,0.050492,0.00026179894],"about_ca_topic_score_codex":0.0000017695975,"about_ca_topic_score_gemma":3.3669005e-7,"teacher_disagreement_score":0.9466222,"about_ca_system_score_codex":0.00009259253,"about_ca_system_score_gemma":0.00008601435,"threshold_uncertainty_score":0.5699833},"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":"W3194854786","doi":"","title":"A Comparison of User-Generated and Automatic Graph Layouts","year":2009,"lang":"en","type":"article","venue":"IEEE Symposium on Information Visualization","topic":"Model-Driven Software Engineering Techniques","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 Calgary","funders":"","keywords":"Computer science; Graph; Theoretical computer science","score_opus":0.014528856586008285,"score_gpt":0.29656473716447396,"score_spread":0.2820358805784657,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3194854786","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.075156674,0.0000066025855,0.92338306,0.0001124492,0.00015388064,0.000240329,0.0000031132377,0.0007402385,0.00020367846],"genre_scores_gemma":[0.9520182,0.0000139874455,0.047636863,0.00025526655,0.000012532932,0.000013739582,0.000036086694,0.0000053876834,0.000007909328],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988413,0.000043193904,0.0005349491,0.00012567712,0.00031922135,0.00013568174],"domain_scores_gemma":[0.9991481,0.000022112241,0.00028287986,0.0002938345,0.00019578372,0.000057320143],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018811747,0.00014203333,0.00019518512,0.0003963512,0.00006770991,0.0001270613,0.00024319366,0.00009190082,0.0000020487623],"category_scores_gemma":[0.000008306252,0.00014253755,0.00003004625,0.00055040774,0.000017483662,0.0015897694,0.000022037597,0.00006415858,0.000008876317],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013188468,0.00019300927,0.0013208968,0.0001648598,0.000022131497,4.6897824e-7,0.008926375,0.087679684,0.013326813,0.837429,0.0027471771,0.048176378],"study_design_scores_gemma":[0.00025149187,0.00032535245,0.0024582478,0.000076422795,0.0000058730197,0.0000028794063,0.0000057806174,0.9398675,0.05482626,0.0003459106,0.0016650459,0.00016923939],"about_ca_topic_score_codex":0.0000045286683,"about_ca_topic_score_gemma":3.355697e-7,"teacher_disagreement_score":0.8768616,"about_ca_system_score_codex":0.000037964222,"about_ca_system_score_gemma":0.00002508209,"threshold_uncertainty_score":0.58125126},"labels":[],"label_agreement":null},{"id":"W4232685372","doi":"10.1109/infvis.2004.53","title":"PhylloTrees: Harnessing Nature’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":"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}]}