{"id":"W2084847694","doi":"10.1016/j.medengphy.2011.01.007","title":"T wave alternans evaluation using adaptive time–frequency signal analysis and non-negative matrix factorization","year":2011,"lang":"en","type":"article","venue":"Medical Engineering & Physics","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University Health Network","funders":"","keywords":"T wave alternans; Sudden cardiac death; Robustness (evolution); Amplitude; Computer science; Algorithm; Mathematics; Pattern recognition (psychology); Cardiology; Medicine; Artificial intelligence; Physics","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":[0.0007483659,0.0007114978,0.0003815122,0.000819502,0.0002455998,0.0004459248,0.0004933244,0.0007485211,0.0006411765],"category_scores_gemma":[0.003134507,0.0001711838,0.0006598592,0.0005498414,0.0003324125,0.0006951688,0.0003899371,0.0004982917,0.0001810072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002571846,"about_ca_system_score_gemma":0.0004485832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003269767,"about_ca_topic_score_gemma":0.00360718,"domain_scores_codex":[0.9996468,0.0001035899,0.00002548218,0.00007814459,0.0001272314,0.00001870248],"domain_scores_gemma":[0.9990164,0.0005521447,0.0001453065,0.00005229009,0.0001998312,0.00003406504],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004773872,0.000258743,0.006625681,0.0003535741,0.0001430724,0.0005646863,0.0002256289,0.4128332,0.09857868,0.006954284,0.002455798,0.4705294],"study_design_scores_gemma":[0.00000662397,0.00003068035,0.0006875786,0.000003915846,0.000005530292,0.00006182719,0.000007358089,0.9967253,0.001738408,0.0005122555,0.0002135174,0.000006967196],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04209343,0.0002543904,0.9565051,0.0001256095,0.00004042464,0.00005485835,0.00004614077,0.000300369,0.000579614],"genre_scores_gemma":[0.4509827,0.0003453949,0.5473824,0.0001027869,0.00006215575,0.0001008068,0.0001816047,0.00005306565,0.0007891015],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003269767,"threshold_uncertainty_score":0.006501436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03743836089468269,"score_gpt":0.2802436631385511,"score_spread":0.2428053022438685,"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."}}