{"id":"W2036807601","doi":"10.1054/jelc.2002.37154","title":"Statistical and deterministic approaches to designing transformations of electrocardiographic leads","year":2002,"lang":"en","type":"article","venue":"Journal of Electrocardiology","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"Victoria General Hospital; Dalhousie University","funders":"","keywords":"Magnetocardiography; Myocardial infarction; Cardiology; Coronary artery disease; Electrocardiography; Collinearity; Population; Statistics; Ventricular tachycardia; Data set; Internal medicine; Regression analysis; Statistical model; Linear regression; Medicine; Torso; Regression; Mathematics","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":[0.007009549,0.0008629634,0.0009647057,0.001823122,0.000712482,0.001560334,0.001716411,0.001101936,0.001655654],"category_scores_gemma":[0.0425737,0.001575036,0.001676875,0.001480778,0.002102289,0.001674755,0.002083997,0.001751912,0.0004738573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001054276,"about_ca_system_score_gemma":0.002054342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002921234,"about_ca_topic_score_gemma":0.003933718,"domain_scores_codex":[0.9947144,0.002588621,0.0003951615,0.0007076755,0.001394759,0.0001994528],"domain_scores_gemma":[0.9605353,0.03157832,0.002644867,0.002313976,0.002612075,0.0003155351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000996895,0.00004841928,0.001811134,0.0001409475,0.00011658,0.0000912717,0.0001717376,0.7762407,0.002864226,0.09832288,0.0006523551,0.1194401],"study_design_scores_gemma":[0.00002074985,0.00005932629,0.0005788127,0.00001566035,0.00002586213,0.00007541999,0.00002306688,0.9416789,0.001475964,0.05477449,0.001244093,0.00002752233],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0009758674,0.00003807063,0.9987915,0.0000396213,0.000005628023,0.000008479587,0.000008605845,0.00004572739,0.00008655572],"genre_scores_gemma":[0.1612137,0.000559179,0.8362962,0.00008320605,0.0001561659,0.0002856175,0.0001975302,0.0001612127,0.001047206],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007009549,"threshold_uncertainty_score":0.03707051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07844350323240051,"score_gpt":0.2631496198755815,"score_spread":0.184706116643181,"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."}}