{"id":"W4318053004","doi":"10.3390/diagnostics13030439","title":"Electrocardiogram (ECG)-Based User Authentication Using Deep Learning Algorithms","year":2023,"lang":"en","type":"article","venue":"Diagnostics","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Biometrics; Authentication (law); Deep learning; Convolutional neural network; Artificial intelligence; Fingerprint (computing); Artificial neural network; Fingerprint recognition; Machine learning; Data mining; Pattern recognition (psychology); Computer security","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003868703,0.0005666491,0.000438362,0.0006024813,0.0001864882,0.0004897108,0.0006230121,0.0006024219,0.001437491],"category_scores_gemma":[0.001037201,0.0002196022,0.0004334119,0.0004775683,0.0001837597,0.0005771759,0.0005826365,0.0007308993,0.0007418183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004710441,"about_ca_system_score_gemma":0.0005273308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003446409,"about_ca_topic_score_gemma":0.003900019,"domain_scores_codex":[0.9997315,0.00003976926,0.00002535138,0.00007537578,0.00009053188,0.00003745129],"domain_scores_gemma":[0.9997473,0.00007091595,0.00004014259,0.00002973498,0.00009927639,0.00001252322],"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":[0.0003459241,0.0002570278,0.004483591,0.0001561531,0.0001310228,0.0002209986,0.0000655992,0.1313155,0.03296521,0.002221395,0.003849492,0.8239881],"study_design_scores_gemma":[0.000008467259,0.00007974698,0.001591523,0.00001689591,0.00002208849,0.0001074122,0.000009991466,0.9856195,0.01049867,0.0009820217,0.001051308,0.00001231865],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0571147,0.001359327,0.9344893,0.000336796,0.0001534735,0.00008260422,0.0002357951,0.002989351,0.003238699],"genre_scores_gemma":[0.8436965,0.001210025,0.1469674,0.0002737484,0.00008635788,0.000120109,0.0006483043,0.00005568372,0.00694164],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003446409,"threshold_uncertainty_score":0.006852686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02435143304729278,"score_gpt":0.3137151867159193,"score_spread":0.2893637536686265,"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."}}