{"id":"W2120830095","doi":"10.1109/ccece.2006.277291","title":"Person Identification using Electrocardiograms","year":2006,"lang":"en","type":"article","venue":"","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Biometrics; Liveness; Computer science; Modal; Robustness (evolution); Artificial intelligence; Pattern recognition (psychology); Identification (biology); Speech recognition","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":[0.000515398,0.0003963973,0.0004658734,0.00120098,0.0001664036,0.0007836135,0.0003067848,0.0008945709,0.001763636],"category_scores_gemma":[0.002635375,0.0001087589,0.0001808939,0.000592934,0.0002247838,0.0009547749,0.0005140231,0.0003055863,0.0011782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000762378,"about_ca_system_score_gemma":0.00009562241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002777697,"about_ca_topic_score_gemma":0.0003077704,"domain_scores_codex":[0.9991498,0.000277319,0.0000549026,0.0001969339,0.0002756453,0.00004542938],"domain_scores_gemma":[0.9993526,0.000219743,0.0001183955,0.00009565316,0.000182701,0.00003076228],"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":[0.0006067973,0.0001439014,0.02995219,0.0006065109,0.0001460157,0.001147317,0.0003871907,0.004631886,0.1508296,0.004421507,0.004570238,0.8025569],"study_design_scores_gemma":[0.0001757278,0.002373404,0.2811822,0.000689008,0.0005558494,0.02640213,0.00131769,0.2175426,0.3676308,0.0178197,0.08389013,0.0004207463],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2604554,0.003963821,0.7092159,0.0006345845,0.0006832386,0.0002196165,0.0008718222,0.002753475,0.02120214],"genre_scores_gemma":[0.8209161,0.002724806,0.1697291,0.0003148903,0.00039312,0.00005719919,0.0004709964,0.00006501713,0.005328855],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001763636,"threshold_uncertainty_score":0.005899966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02235197834600261,"score_gpt":0.2792879186022184,"score_spread":0.2569359402562158,"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."}}