{"id":"W2893688548","doi":"10.1016/j.cjca.2018.07.252","title":"DRAG AND MAP STRATEGY FOR DYNAMIC DETECTION OF DISEASED MYOCARDIUM: INNOVATIVE OMNIPOLAR APPLICATION WITH ADVISOR HD GRID","year":2018,"lang":"en","type":"article","venue":"Canadian Journal of Cardiology","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Public Health","funders":"","keywords":"Medicine; Endocardium; Sinus rhythm; Ventricle; Beat (acoustics); Voltage; Biomedical engineering; Cardiology; Simulation; Internal medicine; Electrical engineering; Acoustics; Atrial fibrillation; Physics; Computer science; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0002240873,0.00008262156,0.0003875346,0.0002883525,0.00007239509,0.000006525007,0.00004699719,0.00007657357,0.000001214917],"category_scores_gemma":[0.00006969734,0.00006555567,0.00008231006,0.0002209059,0.0002224588,0.00004345971,0.000002585419,0.0001206544,6.789555e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009494498,"about_ca_system_score_gemma":0.0006161488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004464843,"about_ca_topic_score_gemma":0.001087645,"domain_scores_codex":[0.9993793,0.00004298564,0.0002384359,0.0001110044,0.00007070929,0.0001575635],"domain_scores_gemma":[0.9985669,0.00003729553,0.0002016232,0.000117648,0.0008365056,0.0002400687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00272529,0.00002231614,0.5409662,0.0005188725,0.005209963,0.0001228601,0.0006526784,0.001492836,0.1268701,0.0003149698,0.001959677,0.3191442],"study_design_scores_gemma":[0.005756453,0.008944053,0.9028791,0.0003002856,0.002345087,0.0008936346,0.001705482,0.002245725,0.01130002,0.0008953651,0.06232473,0.0004100254],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8559155,0.0009509907,0.1414141,0.0007558187,0.0003421738,0.0002590783,0.00006257761,0.000005990386,0.0002937338],"genre_scores_gemma":[0.9984449,0.00001899312,0.0003599656,0.00003144149,0.001084529,0.000007373303,0.00001268871,0.00001140016,0.0000287107],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3619129,"threshold_uncertainty_score":0.2673283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008795276823748054,"score_gpt":0.2552256392377315,"score_spread":0.2464303624139834,"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."}}