{"id":"W4248196157","doi":"10.1386/public_00009_7","title":"Biometric Aesthetics","year":2020,"lang":"en","type":"article","venue":"Public","topic":"Law in Society and Culture","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Biometrics; Eugenics; Face (sociological concept); Sociology; Photography; Identification (biology); Reading (process); Galton's problem; Diversity (politics); Aesthetics; Biometric data; Epistemology; Computer science; Visual arts; Social science; Law; Political science; Philosophy; Art; Artificial intelligence; Anthropology; Ecology; Biology","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":[0.004700295,0.0008255363,0.0003794511,0.002306889,0.005808273,0.01193044,0.00115104,0.003524559,0.02197335],"category_scores_gemma":[0.008940815,0.0003294629,0.0005674093,0.001400076,0.02678849,0.007145745,0.005431019,0.004068414,0.005099789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004826619,"about_ca_system_score_gemma":0.001420408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002358945,"about_ca_topic_score_gemma":0.001528449,"domain_scores_codex":[0.99264,0.003415113,0.0002360009,0.0008726376,0.002349397,0.000486979],"domain_scores_gemma":[0.9970324,0.001120002,0.0002728888,0.0007540028,0.000596549,0.0002242033],"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":[0.000004765291,0.000002865091,0.00005554355,0.00001161421,0.000001114525,0.00002463783,0.001433589,0.00005713506,0.00007063209,0.9857408,0.007096856,0.005500451],"study_design_scores_gemma":[0.000006911147,0.00001440269,0.0002685292,0.0001195962,0.000003753686,0.0004706153,0.00217244,0.0005789401,0.000188937,0.4873733,0.5087845,0.00001809941],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.005570447,0.003832895,0.02009219,0.02692921,0.001510056,0.00002516143,0.0001128589,0.0001638275,0.9417633],"genre_scores_gemma":[0.7337784,0.004800085,0.0129753,0.01173628,0.003044405,0.0002045862,0.0002430124,0.0004479559,0.2327699],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02197335,"threshold_uncertainty_score":0.07350814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07288829630401826,"score_gpt":0.3003787693750299,"score_spread":0.2274904730710117,"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."}}