{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003285697,0.0001701005,0.0002074662,0.0001797952,0.0005831034,0.0001533497,0.0004009673,0.0001746065,0.00036321],"category_scores_gemma":[0.00315034,0.0001808314,0.0001080022,0.0005797776,0.00031948,0.0003555228,0.00005408979,0.0001110095,0.0002121481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006682623,"about_ca_system_score_gemma":0.000922958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005297275,"about_ca_topic_score_gemma":0.01608373,"domain_scores_codex":[0.9975429,0.0004101693,0.0005847022,0.0003890973,0.0006055504,0.0004676525],"domain_scores_gemma":[0.9980585,0.0009761539,0.0001335436,0.0001749531,0.0004998751,0.0001569926],"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":[0.000505115,0.0001614709,0.0002098145,0.000004747006,0.000008603603,0.000003669736,0.01519488,0.06460082,0.00009619294,0.8059589,0.0008631611,0.1123926],"study_design_scores_gemma":[0.00008736321,0.0001607394,0.00009574724,0.0001008158,0.00001187927,0.000001009518,0.0164275,0.0496811,0.000759943,0.9220659,0.01029822,0.0003098036],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1754157,0.0002218876,0.8011575,0.003930798,0.002806247,0.002108643,0.0000352408,0.0001932827,0.01413076],"genre_scores_gemma":[0.9945097,0.0000373958,0.003864666,0.0004151308,0.0006458433,0.0001315401,0.00003282073,0.00001466258,0.0003482702],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.819094,"threshold_uncertainty_score":0.8975099,"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."}}