{"id":"W4353100313","doi":"10.18280/ts.400138","title":"Biometric User Authentication System via Fingerprints Using Novel Hybrid Optimization Tuned Deep Learning Strategy","year":2023,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Biometrics; Computer science; Authentication (law); Artificial intelligence; Deep learning; Fingerprint (computing); Pattern recognition (psychology); Computer security","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009874727,0.0001710939,0.0001733515,0.001856797,0.0003440178,0.0004449324,0.0005717623,0.00006559448,0.0001259292],"category_scores_gemma":[0.00005069091,0.0001806361,0.00008083107,0.006179016,0.00003322553,0.0005479184,0.0001439114,0.0001284437,0.0001903033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002065996,"about_ca_system_score_gemma":0.00005320643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004663304,"about_ca_topic_score_gemma":9.451837e-7,"domain_scores_codex":[0.9979184,0.0001190818,0.0004875224,0.0005070213,0.0006179806,0.0003499753],"domain_scores_gemma":[0.9990023,0.00009507163,0.000259262,0.000308017,0.0002161152,0.0001192706],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003167343,0.000794595,0.001642545,0.0003989518,0.0002265458,0.00004227843,0.002415085,0.7162458,0.1364079,0.02869016,0.0002170541,0.1128874],"study_design_scores_gemma":[0.0004143187,0.00003797079,0.00511786,0.00002183867,0.00001888674,0.00001845172,0.000109401,0.9917768,0.001900638,0.00003144028,0.0003536279,0.0001987918],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07222366,0.00003342319,0.9263996,0.00008262978,0.0003430985,0.0002765838,0.000005801115,0.0005407477,0.00009440845],"genre_scores_gemma":[0.9736797,0.00000730169,0.0259532,0.00002587583,0.00006736827,0.00002125206,0.0000997833,0.00001625402,0.0001292545],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9014561,"threshold_uncertainty_score":0.7366126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03930864097657536,"score_gpt":0.2583828054188267,"score_spread":0.2190741644422514,"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."}}