{"id":"W2402930259","doi":"","title":"Intelligent affect: rational decision making for socially aligned agents","year":2015,"lang":"en","type":"article","venue":"Uncertainty in Artificial Intelligence","topic":"Evolutionary Game Theory and Cooperation","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Affect (linguistics); Computer science; Probabilistic logic; Planner; Deception; Action (physics); Encoding (memory); Cognition; Monte Carlo tree search; Function (biology); Range (aeronautics); Artificial intelligence; Human–computer interaction; Monte Carlo method; Social psychology; Psychology; Mathematics; Engineering","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":[0.002264136,0.0006698942,0.0004500448,0.0004316198,0.0008562551,0.003162262,0.001200324,0.001746937,0.004427741],"category_scores_gemma":[0.008207993,0.0003228158,0.0006350042,0.0004090852,0.003141133,0.00280913,0.00201015,0.001293435,0.0005280924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00128152,"about_ca_system_score_gemma":0.001315721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002120927,"about_ca_topic_score_gemma":0.001555164,"domain_scores_codex":[0.9987367,0.0007205669,0.00005174187,0.0001813459,0.0002177589,0.00009181945],"domain_scores_gemma":[0.9976596,0.0014843,0.0002883018,0.0002110211,0.0001704163,0.000186409],"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":[0.00009295675,0.00004219087,0.0009786494,0.00009782626,0.00005565171,0.0002268472,0.0007672909,0.1971786,0.001337391,0.7741951,0.002076177,0.02295127],"study_design_scores_gemma":[0.00003027962,0.0000320701,0.0002453752,0.00002489489,0.00001582058,0.00004994103,0.0001584509,0.3779166,0.0004002454,0.6150615,0.006045255,0.00001967332],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04377419,0.0004863434,0.9115193,0.003831797,0.0001397458,0.0001353483,0.0001326893,0.0003388737,0.03964165],"genre_scores_gemma":[0.8080266,0.0004090542,0.1845642,0.0003081272,0.0000878903,0.00029014,0.0001042887,0.0000631804,0.006146511],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004427741,"threshold_uncertainty_score":0.01481223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1292949818094062,"score_gpt":0.4102366722908574,"score_spread":0.2809416904814511,"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."}}