{"id":"W3119628700","doi":"10.1038/s41598-020-79310-1","title":"Facial recognition technology can expose political orientation from naturalistic facial images","year":2021,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Evolutionary Psychology and Human Behavior","field":"Psychology","cited_by":203,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Politics; Facial recognition system; Face (sociological concept); Naturalism; Biology and political orientation; Orientation (vector space); Civil liberties; Personality; Similarity (geometry); EXPOSE; Psychology; Social psychology; Computer science; Artificial intelligence; Cognitive psychology; Sociology; Political science; Law; Pattern recognition (psychology); Social science; Image (mathematics); Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003284283,0.0001806033,0.0002186905,0.0003060556,0.0005435105,0.000121404,0.0001293542,0.0003582379,0.00794592],"category_scores_gemma":[0.0002591363,0.0001938742,0.0001046441,0.0005254912,0.0008374267,0.0001458843,0.00006359206,0.0003620107,0.0006395633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000107946,"about_ca_system_score_gemma":0.0001696243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001252259,"about_ca_topic_score_gemma":0.0002001044,"domain_scores_codex":[0.9972167,0.0001553044,0.0005553219,0.001201855,0.0003211499,0.0005496666],"domain_scores_gemma":[0.9984199,0.00005115418,0.0002060072,0.0007890001,0.000384365,0.0001495946],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003063576,0.003016061,0.3504283,0.00003237687,0.000326034,0.03354028,0.007960279,0.000002285787,0.223539,0.07854598,0.1961459,0.1061573],"study_design_scores_gemma":[0.001229691,0.0001230882,0.3833269,0.00005288755,0.0002556039,0.003543197,0.004896722,0.000002351955,0.03205612,0.5202368,0.053432,0.0008446916],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9572648,0.0002433502,0.0001082672,0.001173483,0.0302477,0.0002047063,0.0001935283,0.0002029921,0.01036116],"genre_scores_gemma":[0.9862838,8.73697e-7,0.0005698203,0.0001703649,0.0003598876,0.0000759543,0.002295153,0.00001768022,0.01022645],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4416908,"threshold_uncertainty_score":0.9929609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03703813391177391,"score_gpt":0.3392027796309756,"score_spread":0.3021646457192017,"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."}}