{"id":"W3124375572","doi":"10.18280/ria.340605","title":"An Automated Framework for Patient Identification and Verification Using Deep Learning","year":2020,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Face recognition and analysis","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial intelligence; Deep learning; Contrast (vision); Identification (biology); Face (sociological concept); Machine learning; Facial recognition system; Biometrics; Feature (linguistics); Identity (music); Feature extraction; Computer vision; Pattern recognition (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":[0.00091021,0.0008588523,0.0007472176,0.0008679996,0.0003998253,0.0007558776,0.00181702,0.00136733,0.002984145],"category_scores_gemma":[0.001396949,0.0004763435,0.000918271,0.0004449282,0.000428776,0.0009195887,0.001762653,0.001460371,0.001275275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001096746,"about_ca_system_score_gemma":0.002435375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01244395,"about_ca_topic_score_gemma":0.01670159,"domain_scores_codex":[0.9993686,0.00009175461,0.00003854974,0.0001578799,0.0002359153,0.0001073272],"domain_scores_gemma":[0.9995853,0.00008675937,0.00005124659,0.00007544229,0.000162955,0.00003820481],"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":[0.0003015954,0.000375134,0.002880068,0.0001375299,0.0001390906,0.0003390175,0.0000734718,0.2921871,0.01475874,0.008748648,0.01238873,0.6676708],"study_design_scores_gemma":[0.00001030121,0.00003551752,0.0002789173,0.000010084,0.00001178668,0.0000805025,0.000005581877,0.9922094,0.003504797,0.002471155,0.001372841,0.000009103664],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007289839,0.0003233392,0.9867415,0.0002351255,0.00006988321,0.0001042061,0.0002405988,0.003972281,0.001023346],"genre_scores_gemma":[0.3641198,0.0004873893,0.6252123,0.0005678759,0.0001088661,0.0004027302,0.00148623,0.000200249,0.007414637],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01244395,"threshold_uncertainty_score":0.02474308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05229975263533684,"score_gpt":0.3134222893284405,"score_spread":0.2611225366931037,"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."}}