{"id":"W4402307088","doi":"10.18280/ts.410416","title":"Arrhythmia Classification Using Noise Filtering and 1D CNN","year":2024,"lang":"en","type":"article","venue":"Traitement du signal","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Noise (video); Computer science; Artificial intelligence; Pattern recognition (psychology); Speech recognition; Image (mathematics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004966839,0.0008935772,0.0005059179,0.0006623514,0.000249094,0.0007224084,0.000686678,0.0008435075,0.0009788889],"category_scores_gemma":[0.001317918,0.0003499767,0.00098221,0.0004839473,0.0002427294,0.000609908,0.0005652,0.0005623783,0.0004094591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000903393,"about_ca_system_score_gemma":0.0005258956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008553158,"about_ca_topic_score_gemma":0.008081761,"domain_scores_codex":[0.9997407,0.00003002137,0.0000142761,0.00009042037,0.00007204858,0.0000525269],"domain_scores_gemma":[0.9997851,0.00006479076,0.00002922912,0.00002970924,0.00007703499,0.00001422279],"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":[0.0004928947,0.0001471611,0.0100199,0.0001324517,0.0002121345,0.0003723464,0.0001039801,0.3688951,0.05505903,0.003146214,0.00307868,0.55834],"study_design_scores_gemma":[0.000003291377,0.00003805786,0.001169568,0.000006585803,0.00001960492,0.00004294733,0.000006008148,0.9935457,0.004268871,0.0004914381,0.0004008739,0.00000708511],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1921058,0.00162704,0.7983982,0.0005787715,0.0003289006,0.0001030504,0.000494613,0.002282286,0.004081302],"genre_scores_gemma":[0.8439674,0.0008899227,0.1485385,0.0003304252,0.0001271406,0.0001050494,0.001046713,0.00009179166,0.004903018],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008553158,"threshold_uncertainty_score":0.0170067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04921973367134153,"score_gpt":0.3065836233227497,"score_spread":0.2573638896514082,"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."}}