{"id":"W3192890172","doi":"10.1016/j.cognition.2021.104875","title":"Evolution of emotion semantics","year":2021,"lang":"en","type":"article","venue":"Cognition","topic":"Language and cultural evolution","field":"Social Sciences","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; University of Toronto; Canada Foundation for Innovation","keywords":"Psychology; Semantics (computer science); Cognitive science; Cognitive psychology; Linguistics; Programming language","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":[0.0001248778,0.00002777496,0.00004593339,0.00001779752,0.0001377297,0.00001207926,0.00002497399,0.00005375338,0.0003068289],"category_scores_gemma":[0.000213655,0.00002766592,0.00003419482,0.0002149249,0.00005261023,0.0001650873,0.000007805183,0.00003191408,0.00004732316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000603551,"about_ca_system_score_gemma":0.00008255023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001304988,"about_ca_topic_score_gemma":0.0005489168,"domain_scores_codex":[0.9995189,0.00008689609,0.00008144527,0.00007093705,0.0001611611,0.00008066381],"domain_scores_gemma":[0.999554,0.0000145841,0.00004490296,0.00004392788,0.0003189801,0.00002365325],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006178375,0.0007149414,0.009041277,0.0002428313,0.00008887728,0.00005322204,0.05837374,0.00005078152,0.4144275,0.3852198,0.00913301,0.1225923],"study_design_scores_gemma":[0.002390308,0.0001986152,0.1906421,0.0006966806,0.0005108104,0.00003614622,0.2287705,0.0008899955,0.3188669,0.2138782,0.04221188,0.000907733],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9165946,0.0005096094,0.006605745,0.0007458858,0.0003628667,0.0001022419,0.000007490422,0.00006673161,0.07500485],"genre_scores_gemma":[0.9985342,0.00007856679,0.0001801721,0.00003322911,0.0001889831,0.000001860596,0.00004714167,0.000002019465,0.00093383],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1816009,"threshold_uncertainty_score":0.3359561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01893346826201498,"score_gpt":0.2870205426816425,"score_spread":0.2680870744196275,"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."}}