{"id":"W2061826561","doi":"10.1145/2600057.2602907","title":"Level-0 meta-models for predicting human behavior in games","year":2014,"lang":"en","type":"article","venue":"","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Hierarchy; Game theory; Construct (python library); Action (physics); Artificial intelligence; Generality; Variance (accounting); Machine learning; Mathematical economics; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007135656,0.00010986,0.0003882875,0.0001837139,0.00007513971,0.00004969112,0.0001392947,0.00006088657,0.0006366244],"category_scores_gemma":[0.00002274603,0.0001063765,0.0001669837,0.00009396135,0.00001873324,0.0002043503,0.00002528766,0.00007091361,0.00003069441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002557057,"about_ca_system_score_gemma":0.000004760973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006256827,"about_ca_topic_score_gemma":0.0004604601,"domain_scores_codex":[0.998953,0.000002384718,0.0005131543,0.0002770362,0.00002254862,0.0002318803],"domain_scores_gemma":[0.9995161,0.00002973279,0.0001652728,0.0002244164,0.00002075155,0.00004372125],"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":[0.00000369528,0.00007988125,0.2445925,0.00002094602,0.00008223711,4.495186e-7,0.0001387329,0.002359105,0.000006783676,0.7513091,0.0005833825,0.0008231894],"study_design_scores_gemma":[0.001234094,0.0002087126,0.190017,0.000009900337,0.0001547149,0.000001993025,0.00006509175,0.618914,0.0001515584,0.1115759,0.07707035,0.0005966561],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8475391,0.0006340614,0.06576016,0.0003201464,0.000304444,0.0005085569,0.0001699438,0.00005924826,0.08470432],"genre_scores_gemma":[0.9927886,0.00002380099,0.001362657,0.0002033982,0.00009119325,0.0001310954,0.00001747597,0.0000181295,0.005363698],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6397332,"threshold_uncertainty_score":0.6970591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1927795935293128,"score_gpt":0.2800115969992416,"score_spread":0.08723200346992871,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}