{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":5,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":5,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"query_hash":"e0278ef8f724","filters":{"venue":"International Conference on Cognitive Modelling"}},"results":[{"id":"W112891330","doi":"","title":"Cognitive Modeling Versus Game Theory: Why cognition matters.","year":2004,"lang":"en","type":"article","venue":"International Conference on Cognitive Modelling","topic":"Opinion Dynamics and Social Influence","field":"Physics and Astronomy","cited_by":10,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"","keywords":"Game theory; Simple (philosophy); Computer science; Sequential game; Dependency (UML); Repeated game; Algorithmic game theory; Aggregate (composite); Mathematical economics; Non-cooperative game; Screening game; Combinatorial game theory; Cognition; Artificial intelligence; Mathematics; Psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.09340547506672858,"gpt":0.3372895031785608,"spread":0.2438840281118322,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001754997,0.0002643178,0.0002030559,0.000136938,0.0001806218,0.0002168745,0.0002126919,0.00006897143,0.0006273558],"category_scores_gemma":[0.00002492865,0.000285511,0.0001434603,0.0001031334,0.000115743,0.0003487476,0.00005981929,0.0003584446,0.0002695395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007117463,"about_ca_system_score_gemma":0.0001210728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002194379,"about_ca_topic_score_gemma":0.000006498989,"domain_scores_codex":[0.9984908,0.0000612497,0.0002998721,0.0004514153,0.0003994863,0.0002971476],"domain_scores_gemma":[0.9985016,0.0002040187,0.0001461949,0.00008221694,0.0009629987,0.0001029575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007376808,0.0002063012,0.00005384439,0.000005193055,0.0003161873,0.000005946324,0.001037956,0.141515,0.00006802056,0.8501272,0.000004590676,0.005922056],"study_design_scores_gemma":[0.002647861,0.00009651399,0.000005091572,0.000571022,0.00006047284,5.68609e-7,0.003232136,0.6457749,0.0004236196,0.3468293,0.00001952704,0.0003389711],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1100057,0.000009648229,0.8333613,0.0008016186,0.0005295618,0.0002257848,0.0003533384,0.00005053025,0.0546625],"genre_scores_gemma":[0.9974938,0.00002892762,0.0003657617,0.001063543,0.0003787421,0.00006902015,0.0004752568,0.00003102265,0.00009392657],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8874881,"threshold_uncertainty_score":0.9999597,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2064858","doi":"10.1038/sj.bdj.4807562","title":"The Environment as Theory: An Example Using the ACT-R/SOS Environment.","year":2004,"lang":"en","type":"article","venue":"International Conference on Cognitive Modelling","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"","keywords":"Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.1358320629614555,"gpt":0.2954661663969097,"spread":0.1596341034354542,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008031573,0.0002064373,0.000103692,0.00005674624,0.000766282,0.0005068092,0.001113847,0.00005613141,0.0001058187],"category_scores_gemma":[0.00002618131,0.0001369279,0.00006424338,0.00005269972,0.0001629925,0.0004078023,0.0001896246,0.0003424904,0.0001852721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001339676,"about_ca_system_score_gemma":0.0001261343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002613294,"about_ca_topic_score_gemma":0.000004747221,"domain_scores_codex":[0.9981956,0.0002011121,0.0002283591,0.0004875587,0.0005823005,0.000305106],"domain_scores_gemma":[0.998773,0.0005390119,0.0001578377,0.0003645702,0.00008103994,0.00008455111],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005081052,0.00006857863,0.00005012712,0.000001272509,0.00006119868,0.00001332398,0.002525799,0.4162274,0.0004000631,0.564836,0.000003315011,0.01576211],"study_design_scores_gemma":[0.0003283551,0.0001232496,0.00001843789,0.000107097,0.00001304868,0.00001209817,0.0005957928,0.8363132,0.001888263,0.1594875,0.0009125727,0.000200353],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04356603,0.00007747876,0.9496887,0.001094883,0.0002088326,0.000197131,0.000009651995,0.00005047803,0.005106835],"genre_scores_gemma":[0.9901452,0.0001286547,0.008725369,0.0005761025,0.00009445257,0.00002919048,0.00001797805,0.00001490865,0.0002681294],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9465792,"threshold_uncertainty_score":0.5893699,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W136834064","doi":"","title":"Teaching Computational Modeling to Non-Computer Scientists.","year":2004,"lang":"en","type":"article","venue":"International Conference on Cognitive Modelling","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"","keywords":"Implementation; Computer science; Focus (optics); Code (set theory); Simple (philosophy); Sample (material); Computational thinking; Software engineering; Theoretical computer science; Mathematics education; Programming language; Computer engineering; Artificial intelligence; Set (abstract data type); Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.07032030075495373,"gpt":0.3232691839808703,"spread":0.2529488832259166,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003149158,0.0002240278,0.0001678496,0.0003549444,0.0003360749,0.0005989961,0.001052761,0.00005451456,0.00002975769],"category_scores_gemma":[0.00002289814,0.0002192145,0.00007616442,0.0001680518,0.00003185573,0.0008760273,0.0004759603,0.0003300333,0.0003429129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001258914,"about_ca_system_score_gemma":0.0001605395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001741219,"about_ca_topic_score_gemma":0.000003979867,"domain_scores_codex":[0.9977886,0.00003541204,0.0003170681,0.0007590735,0.0007955037,0.000304332],"domain_scores_gemma":[0.9987711,0.00007562525,0.00008535864,0.0002202485,0.0006679341,0.0001797698],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001504399,0.00008115266,0.000003174847,0.000002527652,0.00001600896,0.0000198496,0.0005544623,0.7772565,0.00004696504,0.2015805,0.00001821534,0.02040564],"study_design_scores_gemma":[0.000567517,0.00009297959,0.00001065041,0.0004300946,0.000003260626,0.00001572225,0.00004184919,0.9330562,0.0001177155,0.06534714,0.00006040847,0.0002565034],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01765308,0.000004890446,0.9729313,0.001463489,0.001009543,0.0001958282,0.00003440215,0.0001240176,0.006583483],"genre_scores_gemma":[0.6623942,0.000002928771,0.3363395,0.0009305143,0.0001974786,0.00001557422,0.00004605322,0.000009783275,0.00006394956],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6447411,"threshold_uncertainty_score":0.8939306,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.1507201680497561,"gpt":0.3716975937796816,"spread":0.2209774257299255,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002022242,0.0001519305,0.0001397945,0.0001871123,0.0001080192,0.000180669,0.000831318,0.00003940901,0.00003794116],"category_scores_gemma":[0.00005245643,0.0001250442,0.00007269649,0.0002214339,0.00006315389,0.0004012261,0.0001787304,0.0001390641,0.00002778641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006551209,"about_ca_system_score_gemma":0.0001672625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005741879,"about_ca_topic_score_gemma":0.000008492822,"domain_scores_codex":[0.9986225,0.00003150744,0.0002915055,0.00034087,0.0005345061,0.0001791573],"domain_scores_gemma":[0.9987777,0.00008672887,0.0001461071,0.0001900813,0.0007226711,0.00007670531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001510993,0.00004301843,0.00000696646,0.000002685003,0.00002411623,0.000002122441,0.0005698536,0.6821209,0.00103436,0.3157257,0.00001499287,0.0004401429],"study_design_scores_gemma":[0.0003179158,0.00003917779,9.221353e-7,0.0002322557,0.00001169321,0.000002077015,0.000305369,0.9703475,0.007416635,0.02111994,0.00005705905,0.0001495179],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01141181,0.000007877065,0.9840149,0.001168832,0.0001570547,0.0001385997,0.00006803219,0.0000375639,0.002995312],"genre_scores_gemma":[0.9589384,0.00002448155,0.03690268,0.003949008,0.00004186714,0.000005603056,0.00002219599,0.00001147465,0.0001043424],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9475265,"threshold_uncertainty_score":0.5099155,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W88826980","doi":"","title":"Emergence of Bayesian Structure from Recurrent Networks.","year":2004,"lang":"en","type":"article","venue":"International Conference on Cognitive Modelling","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Computer science; Bayesian network; Cognition; Task (project management); Artificial intelligence; Plan (archaeology); Bayesian probability; Cognitive model; Order (exchange); Cognitive systems; Machine learning; Theoretical computer science; Cognitive science; Psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.06563824281277097,"gpt":0.2992075528561517,"spread":0.2335693100433808,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001109857,0.0002315167,0.0002202479,0.0001386564,0.00008063827,0.0001237723,0.0009770643,0.000102752,0.0002631924],"category_scores_gemma":[0.00003786364,0.0002250415,0.00009056336,0.0001957657,0.00007786662,0.0003717092,0.0001441125,0.0003434793,0.00002146484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003196881,"about_ca_system_score_gemma":0.0001517928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000180274,"about_ca_topic_score_gemma":0.00002925952,"domain_scores_codex":[0.9981962,0.00004922038,0.0004029031,0.000580682,0.0005200254,0.0002510029],"domain_scores_gemma":[0.9985784,0.00009216818,0.0002147369,0.0002528488,0.000750049,0.0001118511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007289,0.0001216875,0.00007615106,0.000005647734,0.00008220716,0.00001343348,0.0007297302,0.4372444,0.0006268987,0.5201105,0.00001979616,0.04089667],"study_design_scores_gemma":[0.0003337911,0.00009088919,0.00002850663,0.0004116737,0.000008404808,0.000002091726,0.0000858515,0.8104874,0.003080419,0.1852669,0.000004939613,0.0001990201],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01773145,0.0001169725,0.9760135,0.0004820898,0.0008957727,0.0001118056,0.00009494332,0.00007658714,0.004476911],"genre_scores_gemma":[0.9613796,0.0002191407,0.03794868,0.0002182043,0.0001372681,0.00000907224,0.00005662549,0.00001136117,0.00001998718],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9436482,"threshold_uncertainty_score":0.9176928,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}