{"id":"W2155176222","doi":"10.3389/fnins.2012.00129","title":"Optimal Short-Sighted Rules","year":2012,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Experimental Behavioral Economics Studies","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Foraging; Relevance (law); Profitability index; Optimal foraging theory; Computer science; Control (management); Intertemporal choice; Cognitive psychology; Ecology; Economics; Microeconomics; Artificial intelligence; Psychology; Biology","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":[0.00044573,0.00009872037,0.000140556,0.0001117875,0.0004234079,0.00006441266,0.0004105491,0.00004741193,0.00001646081],"category_scores_gemma":[0.0001064801,0.0001036754,0.00003726257,0.0003093051,0.0008298712,0.0007688217,0.000116705,0.0001105891,0.00001967376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001974887,"about_ca_system_score_gemma":0.00004657208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002279318,"about_ca_topic_score_gemma":0.00004462494,"domain_scores_codex":[0.9986704,0.00008472343,0.0001614058,0.0002513974,0.000220719,0.0006113272],"domain_scores_gemma":[0.9996389,0.00001875559,0.00003283525,0.0001341918,0.00001322115,0.0001621553],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000007629479,0.0001394759,0.9716741,0.000001436957,8.763723e-7,0.000004717444,0.00991019,0.0000217673,0.003699891,0.00638682,0.005736535,0.002416593],"study_design_scores_gemma":[0.0005666681,0.0001608074,0.5647979,0.00003316634,0.00002079562,0.000005965374,0.03231534,0.001116828,0.0103478,0.001004228,0.3883314,0.00129915],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9606769,0.000740596,0.0005653811,0.0003074782,0.005013262,0.0002000887,0.000005199471,0.00006790234,0.03242318],"genre_scores_gemma":[0.9901068,0.0001936833,0.00870063,0.0002503683,0.0001107522,0.00002451428,5.913371e-7,0.000008103124,0.0006045516],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4068762,"threshold_uncertainty_score":0.4227759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04621559973672312,"score_gpt":0.3304644187119959,"score_spread":0.2842488189752728,"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."}}