{"id":"W2189859038","doi":"10.1016/j.copsyc.2015.06.004","title":"An evolutionary threat-management approach to prejudices","year":2015,"lang":"en","type":"article","venue":"Current Opinion in Psychology","topic":"Psychology of Moral and Emotional Judgment","field":"Neuroscience","cited_by":77,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; Gilead Sciences; National Science Foundation","keywords":"Prejudice (legal term); Evolutionary psychology; Psychology; Selection (genetic algorithm); Social psychology; Natural selection; Natural (archaeology); Cognitive psychology; Artificial intelligence; Computer science; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002987947,0.0006066079,0.0004270094,0.001188248,0.001656289,0.003467031,0.00178551,0.002692435,0.01019654],"category_scores_gemma":[0.006594112,0.0002097335,0.0004388148,0.0006344652,0.005739222,0.002945789,0.001800961,0.003445507,0.0006870954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001791371,"about_ca_system_score_gemma":0.001161279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000946212,"about_ca_topic_score_gemma":0.001636949,"domain_scores_codex":[0.9986405,0.0006428271,0.00002970059,0.0002335526,0.0003132949,0.0001402203],"domain_scores_gemma":[0.9978707,0.0006317032,0.0003622728,0.0002522373,0.0005242227,0.0003589558],"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":[0.00006323719,0.000210193,0.00673604,0.0001128078,0.00007538663,0.0002978902,0.001552205,0.005580141,0.002886509,0.9001458,0.001941374,0.08039846],"study_design_scores_gemma":[0.00002318453,0.000125248,0.01230203,0.00007544973,0.00003267025,0.0005555084,0.0009666742,0.01406068,0.0005626416,0.9607268,0.01052758,0.00004160908],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2752133,0.004855754,0.2449397,0.0518413,0.001296263,0.0001545093,0.0001061432,0.0001239839,0.421469],"genre_scores_gemma":[0.9623685,0.001158542,0.02320437,0.001997931,0.0005449589,0.00005207813,0.00003789621,0.00003155465,0.01060419],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01019654,"threshold_uncertainty_score":0.03411078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3544260558078722,"score_gpt":0.4345873106701518,"score_spread":0.0801612548622796,"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."}}