{"id":"W3193439024","doi":"10.31234/osf.io/h8prg","title":"Efficient Coding and Risky Choice","year":2020,"lang":"en","type":"article","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Semtech (Canada)","funders":"","keywords":"Stochastic game; Lottery; Coding (social sciences); Perception; Mathematical economics; Decision maker; Economics; Regular polygon; Computer science; Econometrics; Microeconomics; Mathematics; Psychology; Operations research; Statistics","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":[0.003182733,0.0004733268,0.0004625273,0.0004737384,0.0002134027,0.001504656,0.000591194,0.0007891633,0.003682195],"category_scores_gemma":[0.0257665,0.0003024061,0.0003290071,0.0003220074,0.001528116,0.00153614,0.00128383,0.001143424,0.0002846031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007982376,"about_ca_system_score_gemma":0.0004297036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005491577,"about_ca_topic_score_gemma":0.0004149422,"domain_scores_codex":[0.9977416,0.000916668,0.000140297,0.0003579864,0.0006610129,0.0001823051],"domain_scores_gemma":[0.9719064,0.01880136,0.004664472,0.003264759,0.0005940495,0.000768983],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.006183446,0.003679532,0.1184834,0.0007726348,0.000515676,0.0005586288,0.002279342,0.121342,0.2820179,0.3161913,0.002175687,0.1458005],"study_design_scores_gemma":[0.0004339799,0.00288169,0.1297494,0.00007705018,0.0001394125,0.0005633209,0.0003758133,0.3292125,0.05331569,0.4802807,0.002791982,0.0001785247],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9591237,0.00008591052,0.03422821,0.0003050513,0.00001349278,0.0000441765,0.00008308054,0.00004220656,0.006074135],"genre_scores_gemma":[0.9957151,0.00003163577,0.003805287,0.00005481518,0.000005262877,0.00002219627,0.0000405996,0.000008552283,0.0003167391],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003682195,"threshold_uncertainty_score":0.01683211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2226638183130185,"score_gpt":0.4113413905840159,"score_spread":0.1886775722709974,"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."}}