{"id":"W2147380014","doi":"10.1109/ntms.2008.ecp.29","title":"Biometric Identification System Based on Electrocardiogram Data","year":2008,"lang":"en","type":"article","venue":"","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Biometrics; Computer science; Identification (biology); Set (abstract data type); Signal processing; Artificial intelligence; SIGNAL (programming language); Variety (cybernetics); Data mining; Data set; Digital signal processing; Pattern recognition (psychology); Machine learning; Computer hardware","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":[0.0004282115,0.0003325754,0.0007624428,0.001076288,0.0002657984,0.0004503038,0.0004535436,0.0005529054,0.004793477],"category_scores_gemma":[0.001940357,0.0001087947,0.0001873551,0.0006747752,0.0001466119,0.0004818403,0.0003647046,0.0003435642,0.003319473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001434365,"about_ca_system_score_gemma":0.0001948512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002670137,"about_ca_topic_score_gemma":0.0002616789,"domain_scores_codex":[0.9993425,0.0001254061,0.00005016859,0.0001488371,0.0002987158,0.00003443767],"domain_scores_gemma":[0.9993433,0.0001586047,0.00009950532,0.0001015135,0.0002627159,0.00003439595],"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":[0.001026717,0.0002574002,0.01042279,0.0003425539,0.000107984,0.0006462412,0.0001721801,0.002500501,0.357214,0.002879002,0.01290155,0.6115291],"study_design_scores_gemma":[0.0005454856,0.003397024,0.1294788,0.0004064121,0.0005778766,0.01427764,0.0003155701,0.2803173,0.4668116,0.006872101,0.09653404,0.0004661818],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1818372,0.002202081,0.7776596,0.0009366968,0.001082528,0.0006418071,0.002646724,0.0143205,0.01867281],"genre_scores_gemma":[0.760435,0.001501121,0.2204038,0.0005609119,0.0004811443,0.000522192,0.00186595,0.0001468761,0.01408299],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004793477,"threshold_uncertainty_score":0.01603574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06974687530822352,"score_gpt":0.3108837474877183,"score_spread":0.2411368721794948,"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."}}