{"id":"W2164053975","doi":"10.1109/tim.2007.909996","title":"Wavelet Distance Measure for Person Identification Using Electrocardiograms","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Instrumentation and Measurement","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":360,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Biometrics; Artificial intelligence; Pattern recognition (psychology); Computer science; Wavelet transform; Modality (human–computer interaction); Measure (data warehouse); Identification (biology); Fingerprint (computing); Wavelet; Thumb; Residual; Speech recognition; Data mining; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002475726,0.0001271951,0.000176245,0.0001469353,0.0004249,0.00002312548,0.0000259046,0.00005070594,0.000008057164],"category_scores_gemma":[0.000006995043,0.0001230196,0.0001467061,0.0001978346,0.00004230922,0.00009662167,1.502634e-7,0.00009924493,0.000002898911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002781161,"about_ca_system_score_gemma":0.00006780716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003951953,"about_ca_topic_score_gemma":0.00001722748,"domain_scores_codex":[0.998845,0.00002955321,0.0002109879,0.0002508814,0.000501029,0.0001625886],"domain_scores_gemma":[0.9994403,0.000009950141,0.00007292837,0.0001387017,0.0002395791,0.00009852859],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009340776,0.0007423621,0.003306223,0.0002599473,0.001029439,0.000005999412,0.001887211,0.001072437,0.5751316,0.00003889474,0.0002089015,0.4153829],"study_design_scores_gemma":[0.007157358,0.0009361073,0.01141578,0.0004042118,0.001753112,0.0001855185,0.002635185,0.02545479,0.9480138,0.00003347716,0.001449382,0.0005613184],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2863048,0.00008699882,0.7126554,0.0002277473,0.0002449172,0.0003623519,0.000008799117,0.00004719315,0.00006177438],"genre_scores_gemma":[0.9963936,0.0001282883,0.002993644,0.00007475093,0.00007319168,0.00009665905,0.000009171553,0.0000168606,0.0002138638],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7100887,"threshold_uncertainty_score":0.5016595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09714402436983917,"score_gpt":0.2936976529173412,"score_spread":0.1965536285475021,"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."}}