{"meta":{"query_hash":"9804555883e4","filters":{"venue":"International Conference on User Modeling, Adaptation, and Personalization"},"cohort_total":10,"direct_labels_cover":0,"predictions_cover":10,"exported":10,"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/9804555883e4","api":"https://metacan.xera.ac/api/v1/cohort?venue=International+Conference+on+User+Modeling%2C+Adaptation%2C+and+Personalization"},"results":[{"id":"W2056738047","doi":"10.5555/2021855.2021861","title":"Modeling mental workload using EEG features for intelligent systems","year":2011,"lang":"en","type":"article","venue":"International Conference on User Modeling, Adaptation, and Personalization","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","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":"Université de Montréal","funders":"","keywords":"Workload; Computer science; Electroencephalography; Context (archaeology); Human–computer interaction; Mental state; Cognition; Artificial intelligence; Cognitive psychology; Psychology","score_opus":0.26402168897947453,"score_gpt":0.3353452037903479,"score_spread":0.07132351481087335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2056738047","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44900954,0.00032911642,0.54800093,0.00023622092,0.00006961626,0.00007247974,0.00032407264,0.00070776686,0.0012501688],"genre_scores_gemma":[0.98666734,0.00007039151,0.01269982,0.000009971971,0.000014727194,0.000030794145,0.00008974116,0.000019522719,0.00039778993],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998723,0.00003914353,0.000010420923,0.000031753585,0.00002650191,0.000019919782],"domain_scores_gemma":[0.99958915,0.00026134704,0.000033519,0.000030436357,0.00006466912,0.000020862119],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031742646,0.000516074,0.00033113622,0.00041192974,0.0001616922,0.0007537438,0.0003090379,0.00037427485,0.0007685679],"category_scores_gemma":[0.0024005624,0.00023311785,0.00044461596,0.0003147832,0.00009121314,0.0006129362,0.0002475173,0.00044400117,0.00017973111],"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":[0.0006590534,0.00046236182,0.021459596,0.000119252916,0.00022337842,0.00018669128,0.00023291742,0.72463405,0.024791854,0.0015263209,0.0013474269,0.22435711],"study_design_scores_gemma":[0.000003094164,0.000023178449,0.0031451464,0.0000020298564,0.000008859515,0.000010855091,0.000007474589,0.99556524,0.000730377,0.00042639402,0.00007339562,0.000003884628],"about_ca_topic_score_codex":0.005933119,"about_ca_topic_score_gemma":0.0054283924,"teacher_disagreement_score":0.005933119,"about_ca_system_score_codex":0.00026833673,"about_ca_system_score_gemma":0.00025102255,"threshold_uncertainty_score":0.01179713},"labels":[],"label_agreement":null},{"id":"W2058274978","doi":"10.5555/2021855.2021873","title":"Leveraging collaborative filtering to tag-based personalized search","year":2011,"lang":"en","type":"article","venue":"International Conference on User Modeling, Adaptation, and Personalization","topic":"Recommender Systems and 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 Ottawa","funders":"","keywords":"Computer science; Social media; Collaborative filtering; Information retrieval; Ranking (information retrieval); World Wide Web; Personalized search; Personalization; Topic model; Recommender system","score_opus":0.2071017731377584,"score_gpt":0.317722292630621,"score_spread":0.11062051949286261,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058274978","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.066640414,0.0027174093,0.92213106,0.0006742051,0.0004341346,0.00018684186,0.00037456394,0.0018675342,0.0049738735],"genre_scores_gemma":[0.749397,0.0011652953,0.24031915,0.00037496974,0.00050655275,0.00012262775,0.00071296276,0.0001950543,0.007206391],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9955663,0.0017087053,0.0002681556,0.0008568859,0.0013109484,0.0002889987],"domain_scores_gemma":[0.987326,0.0074369116,0.00041971233,0.0026184183,0.0019423271,0.00025659252],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003990612,0.0011122947,0.0025839712,0.00370742,0.0012938583,0.0025953935,0.002084346,0.0022429854,0.0021078587],"category_scores_gemma":[0.016305706,0.0009158494,0.0018747743,0.004273115,0.0006432866,0.0044682147,0.001558214,0.0018740783,0.0021930449],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012079187,0.0019438606,0.019748034,0.00052764046,0.0015335069,0.00044763996,0.00096777314,0.12771285,0.02580919,0.0153931305,0.017630076,0.78707826],"study_design_scores_gemma":[0.000037990256,0.00020568444,0.00233229,0.00002816065,0.00023839685,0.0002443789,0.000075045085,0.97775954,0.005153516,0.010804232,0.003046622,0.00007419229],"about_ca_topic_score_codex":0.011581756,"about_ca_topic_score_gemma":0.02847911,"teacher_disagreement_score":0.011581756,"about_ca_system_score_codex":0.00068723067,"about_ca_system_score_gemma":0.0010518744,"threshold_uncertainty_score":0.023028672},"labels":[],"label_agreement":null},{"id":"W2397758814","doi":"","title":"Modeling Mobile User Planning-Context.","year":2014,"lang":"en","type":"article","venue":"International Conference on User Modeling, Adaptation, and Personalization","topic":"Usability and User Interface Design","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":"Wilfrid Laurier University","funders":"","keywords":"Computer science; Context (archaeology); Human–computer interaction","score_opus":0.10771484055470423,"score_gpt":0.30290044519479314,"score_spread":0.1951856046400889,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2397758814","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1100271,0.002864812,0.8619658,0.0011301182,0.00015381974,0.00025827606,0.0011300546,0.0013054543,0.021164464],"genre_scores_gemma":[0.88895947,0.001034444,0.10360667,0.000085085805,0.000038220718,0.0002241037,0.00055013044,0.00012878867,0.0053731087],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923885,0.00040010925,0.00003525701,0.00013685797,0.00010776417,0.00008117418],"domain_scores_gemma":[0.9984137,0.0009884209,0.00010410094,0.00016615496,0.00022141647,0.000106162646],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009771413,0.0007252386,0.00047122178,0.0007503468,0.00046219764,0.0017197555,0.0010490728,0.0008499771,0.0038268294],"category_scores_gemma":[0.0066687893,0.0006205199,0.00074322184,0.0006561227,0.0005334691,0.0019466783,0.0013066472,0.00088649185,0.00078691565],"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":[0.00036460813,0.00025331552,0.018884804,0.0004708488,0.00019429193,0.00047518325,0.0017248214,0.7611254,0.0024997604,0.091630004,0.006340479,0.11603647],"study_design_scores_gemma":[0.000014529137,0.000053087173,0.0012997506,0.000042897595,0.00006401283,0.00007277196,0.00023745935,0.96997607,0.0005822345,0.022979839,0.0046620555,0.000015401922],"about_ca_topic_score_codex":0.028097976,"about_ca_topic_score_gemma":0.043443747,"teacher_disagreement_score":0.028097976,"about_ca_system_score_codex":0.0009739835,"about_ca_system_score_gemma":0.0016939959,"threshold_uncertainty_score":0.055868864},"labels":[],"label_agreement":null},{"id":"W2398227848","doi":"","title":"Adaptive Information Visualization - Predicting user characteristics and task context from eye gaze.","year":2012,"lang":"en","type":"article","venue":"International Conference on User Modeling, Adaptation, and Personalization","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","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":"Computer science; Human–computer interaction; Eye tracking; Visualization; Task (project management); Gaze; Context (archaeology); Information visualization; User interface; Data visualization; Task analysis; Visual analytics; User modeling; Artificial intelligence; Engineering","score_opus":0.2694014997513866,"score_gpt":0.3953963308317035,"score_spread":0.1259948310803169,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2398227848","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8634178,0.0012893055,0.12936507,0.00036071637,0.0000407565,0.00020057111,0.00075114716,0.0015449328,0.0030296384],"genre_scores_gemma":[0.974682,0.00022101752,0.024411378,0.000029260118,0.000010263425,0.00006231553,0.00020791485,0.000026205324,0.00034973637],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99947006,0.0002365047,0.00002413993,0.00012833459,0.000106203646,0.00003483235],"domain_scores_gemma":[0.99651957,0.002200151,0.0005366189,0.0002968567,0.00031844067,0.00012840203],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011368527,0.00055252394,0.00036303158,0.00082854833,0.00019068949,0.00072402915,0.000309752,0.0005356582,0.0008687116],"category_scores_gemma":[0.009130269,0.00027575615,0.00030820462,0.0005002059,0.00014695918,0.0012439656,0.00041544207,0.00044992063,0.00028154993],"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":[0.0021697744,0.00085669174,0.30526674,0.0008308683,0.00044223704,0.00028129955,0.0025676254,0.032097936,0.18506122,0.0012829253,0.0034791573,0.46566358],"study_design_scores_gemma":[0.00008398995,0.0016649112,0.6484785,0.00012332427,0.00021469934,0.0006875583,0.0007224808,0.3157997,0.025904862,0.0033866165,0.002783172,0.00015004733],"about_ca_topic_score_codex":0.0040104,"about_ca_topic_score_gemma":0.0050954334,"teacher_disagreement_score":0.0040104,"about_ca_system_score_codex":0.00031451051,"about_ca_system_score_gemma":0.00030862718,"threshold_uncertainty_score":0.007974148},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17495403,0.006681601,0.5922034,0.0026247478,0.0024040935,0.008847085,0.006569174,0.11321206,0.09250394],"genre_scores_gemma":[0.57193,0.002917399,0.3463488,0.0033549317,0.0010462542,0.014557682,0.0074234065,0.0103448825,0.04207668],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99536055,0.0023178682,0.0003148516,0.00085913384,0.00085554784,0.0002922022],"domain_scores_gemma":[0.97166955,0.019981427,0.00082661,0.0035025596,0.0028420074,0.0011778584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00650708,0.0022499603,0.0010720396,0.0016031861,0.0006045661,0.0039342633,0.0030847169,0.002527008,0.042250454],"category_scores_gemma":[0.05681735,0.00069047994,0.0010953315,0.0010096051,0.0005107241,0.004657068,0.0053157993,0.0011525467,0.020586839],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004341465,0.0016528077,0.005681383,0.0046224613,0.00026427576,0.001337025,0.008953503,0.0036463188,0.049806245,0.0035685396,0.105332024,0.81079406],"study_design_scores_gemma":[0.0023289542,0.005126661,0.037749678,0.003195183,0.0010911383,0.005641721,0.011354042,0.12656797,0.07762233,0.067792416,0.6599736,0.0015562316],"about_ca_topic_score_codex":0.00072983705,"about_ca_topic_score_gemma":0.0007146823,"teacher_disagreement_score":0.042250454,"about_ca_system_score_codex":0.0006167414,"about_ca_system_score_gemma":0.0005551727,"threshold_uncertainty_score":0.14134187},"labels":[],"label_agreement":null},{"id":"W2403947344","doi":"","title":"The Student Advice Recommender Agent: SARA.","year":2015,"lang":"en","type":"article","venue":"International Conference on User Modeling, Adaptation, and Personalization","topic":"Online Learning 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 Saskatchewan","funders":"","keywords":"Advice (programming); Recommender system; Computer science; World Wide Web; Medical education; Mathematics education; Psychology; Medicine","score_opus":0.14239153711099323,"score_gpt":0.3452119152686587,"score_spread":0.20282037815766546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2403947344","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10196725,0.0063970084,0.52746576,0.0068356586,0.0024938502,0.002607546,0.011752305,0.2686269,0.07185379],"genre_scores_gemma":[0.40197796,0.0023424374,0.44982567,0.003001972,0.0005788933,0.0009045308,0.01905262,0.002604496,0.1197114],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993782,0.00013815388,0.000053334075,0.00015778451,0.00022042109,0.000051998275],"domain_scores_gemma":[0.9983885,0.00037563752,0.00011557432,0.0003200063,0.00046872374,0.00033154513],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012329022,0.00078015926,0.00071385043,0.0006476028,0.00058562116,0.0010237386,0.0013931593,0.0014612852,0.010339545],"category_scores_gemma":[0.0044004363,0.0005012691,0.00050593255,0.00040199957,0.0001239414,0.0012151708,0.0009527894,0.0014183782,0.008360991],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013148583,0.0014190817,0.021922309,0.00085626065,0.00039479526,0.0005657309,0.000519258,0.0077879084,0.019832432,0.0054374975,0.30957326,0.6303766],"study_design_scores_gemma":[0.00061053433,0.0008438281,0.011281092,0.00015768142,0.00041035961,0.0014556769,0.0002601682,0.33695757,0.027219797,0.005853458,0.61471975,0.00023011386],"about_ca_topic_score_codex":0.005744911,"about_ca_topic_score_gemma":0.010599548,"teacher_disagreement_score":0.010339545,"about_ca_system_score_codex":0.00032263852,"about_ca_system_score_gemma":0.0009581111,"threshold_uncertainty_score":0.03458929},"labels":[],"label_agreement":null},{"id":"W2404421657","doi":"","title":"Modeling trustworthiness of peer advice in a framework for presenting Web objects that supports peer commenta.","year":2012,"lang":"en","type":"article","venue":"International Conference on User Modeling, Adaptation, and Personalization","topic":"Recommender Systems and Techniques","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; Limiting; World Wide Web; Presentation (obstetrics); Semantic reasoner; Similarity (geometry); Trustworthiness; Selection (genetic algorithm); Advice (programming); Value (mathematics); The Internet; Web application; Information retrieval; Internet privacy; Artificial intelligence","score_opus":0.12764129107844233,"score_gpt":0.3403177239681906,"score_spread":0.21267643288974827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2404421657","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.072386615,0.0003460351,0.92061967,0.0006520678,0.00006134982,0.0003233764,0.00011444212,0.00048951566,0.0050068973],"genre_scores_gemma":[0.7165412,0.00023446642,0.27565363,0.00009611907,0.000082966566,0.00034940077,0.00013291466,0.0000940268,0.00681536],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9948738,0.0025928093,0.00023603214,0.0009394792,0.001005198,0.0003526706],"domain_scores_gemma":[0.9729355,0.01833873,0.0023010727,0.0023966376,0.0028514555,0.0011765958],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008921872,0.0009439928,0.0010755535,0.0018045625,0.0016851639,0.0030663947,0.0026613327,0.003575242,0.003737797],"category_scores_gemma":[0.043147363,0.0011557395,0.0015058345,0.0011462386,0.0021795065,0.004646907,0.0019011293,0.0021823125,0.0008801147],"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":[0.00039703428,0.00034889273,0.004811518,0.00019741335,0.0001607085,0.00037076973,0.001965588,0.8445791,0.004327728,0.10127501,0.001367048,0.04019917],"study_design_scores_gemma":[0.000030662944,0.00007898667,0.00037472945,0.000010929977,0.000034096767,0.000045277495,0.00008424654,0.9800734,0.00032188027,0.017960733,0.0009650682,0.000019985513],"about_ca_topic_score_codex":0.022279847,"about_ca_topic_score_gemma":0.019280788,"teacher_disagreement_score":0.022279847,"about_ca_system_score_codex":0.0032366095,"about_ca_system_score_gemma":0.0026836146,"threshold_uncertainty_score":0.04718393},"labels":[],"label_agreement":null},{"id":"W2405263560","doi":"","title":"Personalized presentation of multimedia objects for home healthcare environments: a peer-based intelligent tutoring approach.","year":2012,"lang":"en","type":"article","venue":"International Conference on User Modeling, Adaptation, and Personalization","topic":"Intelligent Tutoring Systems and Adaptive Learning","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; Presentation (obstetrics); Multimedia; Curriculum; Value (mathematics); Health care; Intelligent tutoring system; Personalized learning; Human–computer interaction; Order (exchange); World Wide Web; Teaching method; Open learning; Cooperative learning; Machine learning; Mathematics education; Psychology","score_opus":0.13330793312961417,"score_gpt":0.318181196506369,"score_spread":0.18487326337675483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2405263560","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.031948328,0.0002664596,0.95970494,0.00042009886,0.00002994856,0.0002739689,0.00009939117,0.002642359,0.004614495],"genre_scores_gemma":[0.5965346,0.00027677178,0.39863536,0.00012640443,0.000057867863,0.00020066429,0.0002599254,0.00016618529,0.003742198],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99807966,0.0008362222,0.000115694915,0.00040367534,0.0004853114,0.00007951701],"domain_scores_gemma":[0.99623907,0.0016895279,0.00037024755,0.0007226228,0.00069282996,0.00028565666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022565725,0.0007695566,0.00071570906,0.0009258484,0.0006350048,0.0022293855,0.0027497998,0.0018494214,0.0026875623],"category_scores_gemma":[0.010177744,0.00043192785,0.00073126185,0.00049305503,0.000737379,0.0032796457,0.0019498281,0.00089504576,0.0009674564],"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":[0.0006211416,0.0010200419,0.01491901,0.00077345676,0.00042808524,0.0014775794,0.005561695,0.19115613,0.046230387,0.039199412,0.008340021,0.690273],"study_design_scores_gemma":[0.0000538481,0.0003520709,0.0028879163,0.000075124255,0.0001569707,0.00083778193,0.00097164576,0.91821665,0.016278269,0.040670395,0.019416077,0.00008331825],"about_ca_topic_score_codex":0.0014094656,"about_ca_topic_score_gemma":0.0022825848,"teacher_disagreement_score":0.0027497998,"about_ca_system_score_codex":0.0006854825,"about_ca_system_score_gemma":0.00075359334,"threshold_uncertainty_score":0.011934042},"labels":[],"label_agreement":null},{"id":"W2405843357","doi":"","title":"Learning from a network of peers via peer-driven adjustment of a corpus.","year":2012,"lang":"en","type":"article","venue":"International Conference on User Modeling, Adaptation, and Personalization","topic":"Open Education and E-Learning","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; Similarity (geometry); Set (abstract data type); Probabilistic logic; Personalized learning; Order (exchange); Peer-to-peer; Value (mathematics); World Wide Web; Artificial intelligence; Multimedia; Machine learning; Mathematics education; Cooperative learning; Open learning; Teaching method","score_opus":0.0823489160565354,"score_gpt":0.2950400878113604,"score_spread":0.212691171754825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2405843357","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13028322,0.0002687544,0.8571628,0.00046868876,0.00009985938,0.0007943445,0.00011169043,0.00169075,0.009119977],"genre_scores_gemma":[0.71619946,0.00024052775,0.2736916,0.00013660322,0.000108406595,0.0009705561,0.0003775677,0.0003062409,0.007969052],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980806,0.0008316793,0.00006565302,0.0005005996,0.00043336532,0.000088116416],"domain_scores_gemma":[0.9941369,0.0031550422,0.00031402012,0.0012735664,0.0006570626,0.0004634088],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003251961,0.0007110707,0.00091783545,0.0008509353,0.0013001084,0.0016662992,0.00281621,0.0011106886,0.0039278576],"category_scores_gemma":[0.015954606,0.0005417996,0.0006005976,0.0007789978,0.00104089,0.0042576124,0.0035456307,0.0012946406,0.0013610519],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00068821904,0.0013835836,0.012536375,0.00057768554,0.00037074584,0.0009926301,0.006209651,0.41599363,0.046253823,0.05432831,0.009263638,0.45140174],"study_design_scores_gemma":[0.00007366191,0.00032076833,0.0023798805,0.00003094503,0.00008314779,0.0002859338,0.0009142354,0.93217796,0.0061223097,0.042116854,0.015423216,0.00007120178],"about_ca_topic_score_codex":0.0018886072,"about_ca_topic_score_gemma":0.002847428,"teacher_disagreement_score":0.0039278576,"about_ca_system_score_codex":0.00071616174,"about_ca_system_score_gemma":0.0010317646,"threshold_uncertainty_score":0.017198205},"labels":[],"label_agreement":null},{"id":"W78210347","doi":"","title":"Developing a scale for assessing instructor attitudes towards open learner models.","year":2012,"lang":"en","type":"article","venue":"International Conference on User Modeling, Adaptation, and Personalization","topic":"Intelligent Tutoring Systems and Adaptive Learning","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":"Scale (ratio); Computer science; Mathematics education; Psychology","score_opus":0.2877334313160527,"score_gpt":0.3777953652549678,"score_spread":0.0900619339389151,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W78210347","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8133554,0.00071882235,0.1222792,0.0023797634,0.0008712627,0.016006676,0.003290922,0.001124593,0.039973374],"genre_scores_gemma":[0.59862155,0.0005187652,0.37298453,0.0006912794,0.00010073227,0.01726471,0.0028398242,0.00010317656,0.006875407],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9944764,0.0020812836,0.0006618643,0.00020593629,0.002382507,0.00019208832],"domain_scores_gemma":[0.97832924,0.008849162,0.0022251678,0.0011014461,0.0077820495,0.0017128472],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009722134,0.0003953842,0.00031646737,0.0018668319,0.0005267534,0.0010436667,0.0010140438,0.00085731683,0.0022784034],"category_scores_gemma":[0.032233085,0.0003061339,0.00067152,0.00084655645,0.0004656221,0.0016239672,0.001706464,0.0014755299,0.0012706853],"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":[0.00043218202,0.002306432,0.38953194,0.0007521182,0.00017764392,0.00029729848,0.015843185,0.0019412716,0.016649477,0.005700917,0.030408574,0.5359589],"study_design_scores_gemma":[0.00075585704,0.0067281425,0.7475376,0.0011969015,0.00023256437,0.0017027475,0.02824426,0.026507644,0.017836783,0.016953407,0.15186137,0.0004426967],"about_ca_topic_score_codex":0.0007480586,"about_ca_topic_score_gemma":0.0015040352,"teacher_disagreement_score":0.009722134,"about_ca_system_score_codex":0.0006685201,"about_ca_system_score_gemma":0.0017750544,"threshold_uncertainty_score":0.05141616},"labels":[],"label_agreement":null}]}