{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005310938,0.002332856,0.001519321,0.001590675,0.000771734,0.003176185,0.003805676,0.002012365,0.00290193],"category_scores_gemma":[0.02755168,0.001551639,0.002179228,0.001092497,0.001310547,0.00511736,0.001939023,0.004321966,0.0006208535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003441656,"about_ca_system_score_gemma":0.00176672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007686116,"about_ca_topic_score_gemma":0.01335991,"domain_scores_codex":[0.997141,0.001574363,0.0001721272,0.0004334223,0.0005011479,0.0001780134],"domain_scores_gemma":[0.9805415,0.0142381,0.001590404,0.002056261,0.001019359,0.0005543813],"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":[0.000214808,0.0001194083,0.005179792,0.0001123289,0.0001549791,0.00003706398,0.0001660264,0.9587517,0.0004214864,0.02599334,0.000594257,0.008254798],"study_design_scores_gemma":[0.00001536586,0.00003715576,0.0002455793,0.00001649315,0.00002134722,0.000005952631,0.00001825451,0.9784592,0.0001895505,0.02075716,0.0002220315,0.00001182029],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2288817,0.001134587,0.7563712,0.001409535,0.0001218125,0.0004571609,0.001738537,0.002063182,0.007822359],"genre_scores_gemma":[0.7205002,0.0005502616,0.2756181,0.0003273501,0.00006041213,0.0005920672,0.0009333674,0.0002381943,0.001180155],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007686116,"threshold_uncertainty_score":0.02808726,"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."}}