{"id":"W2985584091","doi":"10.1007/978-981-13-9097-5_11","title":"Novel Methodology for Cardiac Arrhythmias Classification Based on Long-Duration ECG Signal Fragments Analysis","year":2019,"lang":"en","type":"book-chapter","venue":"Series in bioengineering","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Duration (music); Normal Sinus Rhythm; Rhythm; Computer science; SIGNAL (programming language); Heart Rhythm; Set (abstract data type); Artificial intelligence; Sinus rhythm; Cardiac arrhythmia; Pattern recognition (psychology); Medicine; Data mining; Cardiology; Internal medicine; Atrial fibrillation","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":[0.0005261339,0.0007278752,0.0006147341,0.001399151,0.0003375779,0.001112969,0.0009196821,0.0007745547,0.002443117],"category_scores_gemma":[0.0008171846,0.0002093393,0.0007511291,0.001064078,0.0002944435,0.0009129186,0.0005710982,0.0006232341,0.002089804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002125369,"about_ca_system_score_gemma":0.0003999702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007641154,"about_ca_topic_score_gemma":0.001134585,"domain_scores_codex":[0.9995826,0.0000386277,0.00003478538,0.0001399894,0.0001726239,0.00003139123],"domain_scores_gemma":[0.9996226,0.00008658339,0.00003621338,0.00003889859,0.0001902238,0.00002555181],"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":[0.0001352573,0.00007981978,0.001931659,0.0001936541,0.0000765798,0.0001695473,0.00009402369,0.005025051,0.1075948,0.003753146,0.005063742,0.8758827],"study_design_scores_gemma":[0.00003786698,0.0004344979,0.01781716,0.00009228457,0.0002723488,0.002987878,0.0001920789,0.8195971,0.1113637,0.01104492,0.0360279,0.0001322977],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006265894,0.0008337253,0.9908088,0.00005705803,0.0001367158,0.00004030719,0.0001222146,0.0006832639,0.001051884],"genre_scores_gemma":[0.1364567,0.002159011,0.8498355,0.0001630827,0.0004382187,0.0001460512,0.00104959,0.0001727386,0.009579098],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002443117,"threshold_uncertainty_score":0.008172989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06454040691598538,"score_gpt":0.3046030131143934,"score_spread":0.240062606198408,"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."}}