{"id":"W4386325756","doi":"10.18280/ts.400431","title":"Deep Learning Based Gender Identification Using Ear Images","year":2023,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Identification (biology); Artificial intelligence; Computer science; Deep learning; Pattern recognition (psychology); Computer vision; Speech recognition; Biology","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":[0.0005435132,0.0008572976,0.0005917261,0.001123359,0.0002244119,0.0004788018,0.0006991469,0.0006597381,0.004590817],"category_scores_gemma":[0.0008703886,0.0001653411,0.0006078421,0.0005887488,0.0002402121,0.0007864191,0.0007375424,0.0005612407,0.002340809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004006126,"about_ca_system_score_gemma":0.0004457097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003698208,"about_ca_topic_score_gemma":0.00721438,"domain_scores_codex":[0.9997192,0.00003868795,0.00001117628,0.00007329266,0.00007697746,0.00008065745],"domain_scores_gemma":[0.9998226,0.00004215996,0.00002179605,0.00002802559,0.00006880755,0.00001675952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008409055,0.0003671837,0.01255959,0.000124165,0.0001145349,0.000424456,0.00007705467,0.04856538,0.03365954,0.003429401,0.01283126,0.8870065],"study_design_scores_gemma":[0.0000189246,0.0002059967,0.006399415,0.00003232362,0.00005692986,0.0003663589,0.00008994311,0.9612658,0.02242335,0.00356355,0.005552754,0.00002462254],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3972521,0.003478784,0.5664634,0.0008167856,0.0009945357,0.0002190992,0.004000422,0.006826807,0.01994808],"genre_scores_gemma":[0.8821198,0.000890696,0.08664155,0.0004715276,0.0001584428,0.00007528551,0.003384315,0.0001187126,0.02613964],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004590817,"threshold_uncertainty_score":0.01535779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05668951340752716,"score_gpt":0.2837552247068762,"score_spread":0.227065711299349,"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."}}