{"id":"W2606129234","doi":"10.1016/j.jhevol.2017.02.009","title":"Selection to outsmart the germs: The evolution of disease recognition and social cognition","year":2017,"lang":"en","type":"article","venue":"Journal of Human Evolution","topic":"Zoonotic diseases and public health","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wildlife Conservation Society Canada; University of Lethbridge; McGill University","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Cognition; Sociality; Disease; Population; Kin selection; Selection (genetic algorithm); Psychology; Social cognition; Developmental psychology; Cognitive psychology; Biology; Medicine; Evolutionary biology; Psychiatry; Pathology; Environmental health","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009801182,0.00008517404,0.0001794455,0.0001190662,0.0009375995,0.00006222304,0.0001025611,0.00005063049,0.00005414229],"category_scores_gemma":[0.0003785031,0.00005113315,0.0001231969,0.00007272871,0.0001540906,0.0002896721,0.000027764,0.0002101585,0.000006686032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002758104,"about_ca_system_score_gemma":0.0003274312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001479221,"about_ca_topic_score_gemma":0.00005970428,"domain_scores_codex":[0.9988634,0.00012681,0.0003920368,0.00009823753,0.0003698557,0.0001496454],"domain_scores_gemma":[0.9984956,0.000041295,0.0006532068,0.000152099,0.0005041712,0.0001536167],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.02397538,0.005657397,0.310799,0.003672731,0.00202783,0.00007357899,0.01926391,0.000105145,0.06162029,0.06565114,0.09531357,0.41184],"study_design_scores_gemma":[0.001150182,0.0006833884,0.9806291,0.0002154431,0.0004964743,0.00005161314,0.001339298,0.0002172323,0.00004094189,0.01440534,0.0007005122,0.00007041769],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9856806,0.0001667871,0.001660682,0.01095898,0.0002457001,0.0003648953,0.00002041007,0.000008553679,0.0008933927],"genre_scores_gemma":[0.9985161,0.00001831316,0.00003898579,0.0002493087,0.001061755,0.000006663977,0.0000108291,0.000008936016,0.00008905291],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6698301,"threshold_uncertainty_score":0.7211353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04606412427792476,"score_gpt":0.3316372937476291,"score_spread":0.2855731694697043,"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."}}