{"id":"W2139515132","doi":"","title":"Learning a value analysis tool for agent evaluation","year":2009,"lang":"en","type":"article","venue":"","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Variance (accounting); Estimator; Population; Limit (mathematics); Bellman equation; Function (biology); Domain (mathematical analysis); Monte Carlo method; Value (mathematics); Artificial intelligence; Machine learning; Mathematical optimization; Mathematics; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005782506,0.00004978547,0.0001214313,0.0001885845,0.0001786903,0.0001219489,0.0002269038,0.00002507865,0.001574942],"category_scores_gemma":[0.002041603,0.00003477451,0.0001701385,0.001155818,0.00001324395,0.0001068546,0.0000118662,0.00003729802,0.0002933864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001836017,"about_ca_system_score_gemma":0.00002331618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002077241,"about_ca_topic_score_gemma":0.000003249585,"domain_scores_codex":[0.9985847,0.000170931,0.0002720176,0.000249298,0.0006199899,0.0001030693],"domain_scores_gemma":[0.998593,0.0006907549,0.00009293406,0.0003019053,0.0002867238,0.00003473084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002106233,0.00007264509,0.001533045,3.117282e-7,0.00006303244,8.513483e-8,0.000528014,0.1148765,0.001968514,0.222937,0.002506247,0.6554936],"study_design_scores_gemma":[0.0002215793,0.00009100173,0.04589536,7.51327e-7,0.0002953733,3.43609e-7,0.0004771178,0.4090282,0.0008428743,0.5247833,0.01827003,0.0000940911],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5090919,0.00001176324,0.471099,0.001557823,0.00002216847,0.0003112317,0.000001736027,0.00003698525,0.0178674],"genre_scores_gemma":[0.9860689,7.61927e-7,0.004456519,0.0003475776,0.00003095068,0.00004578329,0.00000893188,0.000001505931,0.00903907],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6553994,"threshold_uncertainty_score":0.9993377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.178569046960018,"score_gpt":0.4774049186321165,"score_spread":0.2988358716720986,"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."}}