{"id":"W3203993786","doi":"10.18280/ts.380410","title":"Identify Attractive and Unattractive Individuals Based on Geometric Features Using Neural Network","year":2021,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Evolutionary Psychology and Human Behavior","field":"Psychology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Pattern recognition (psychology); Face (sociological concept); Computer science; Attractiveness; Feature (linguistics); Artificial neural network; Feature extraction; Focus (optics); Computer vision; Position (finance); Identification (biology); Mathematics; Psychology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002931084,0.0004041471,0.0003636367,0.0007690266,0.0001732013,0.0003773302,0.0002408288,0.0003156054,0.001469276],"category_scores_gemma":[0.0005848882,0.0001143577,0.0003344912,0.0002658587,0.0002316303,0.0003334037,0.0003131008,0.0002133625,0.0002685842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003039049,"about_ca_system_score_gemma":0.0001444209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001307348,"about_ca_topic_score_gemma":0.002014695,"domain_scores_codex":[0.9998246,0.00003659063,0.000006912393,0.00004994716,0.00005045223,0.00003153025],"domain_scores_gemma":[0.9998512,0.00005286582,0.00002672625,0.00001225077,0.0000440667,0.00001287767],"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":[0.0007111997,0.0003004493,0.05614575,0.0001611149,0.0001963248,0.0003162205,0.0001996069,0.05161643,0.1097462,0.002324252,0.002183666,0.7760988],"study_design_scores_gemma":[0.00001654,0.0003008451,0.09022216,0.00003351163,0.00009215844,0.0005908507,0.000167644,0.8850359,0.02003887,0.002291155,0.001171257,0.00003905749],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7606127,0.0005647138,0.2314335,0.0002545126,0.00008450545,0.0001128283,0.0002232526,0.0003372222,0.006376748],"genre_scores_gemma":[0.9575092,0.0001999579,0.03962421,0.00005338619,0.0000260546,0.00003177388,0.0001893396,0.00001237798,0.002353735],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001469276,"threshold_uncertainty_score":0.004915237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06104180829062781,"score_gpt":0.361117433027455,"score_spread":0.3000756247368272,"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."}}