{"id":"W4414015741","doi":"10.11159/icbes25.117","title":"Semantic Segmentation for Multi-Class ECG Beat Classification with Emphasis on Aberrant PAC Detection","year":2025,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Emphasis (telecommunications); Computer science; Segmentation; Class (philosophy); Artificial intelligence; Pattern recognition (psychology); Speech recognition; Machine learning; Telecommunications","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":[0.0009561022,0.0008487199,0.0007529997,0.003049016,0.0007834974,0.001372231,0.0008934636,0.001153612,0.001267154],"category_scores_gemma":[0.002093183,0.0002037502,0.0008261895,0.001588965,0.0006624609,0.001554909,0.0008202216,0.0008050151,0.0008514946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004463482,"about_ca_system_score_gemma":0.0008161963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001210373,"about_ca_topic_score_gemma":0.001941071,"domain_scores_codex":[0.9989792,0.0001686855,0.00008562225,0.0002713291,0.0003849782,0.000110224],"domain_scores_gemma":[0.9989943,0.0002966693,0.0001486006,0.0001810928,0.0003109616,0.000068437],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004084877,0.0002235571,0.006818855,0.0002104283,0.00008198366,0.0003126671,0.0003904566,0.01523277,0.1122488,0.008990317,0.002987789,0.8520938],"study_design_scores_gemma":[0.00004120146,0.0004435319,0.01617415,0.00008214905,0.0001372142,0.001449293,0.000391131,0.8707092,0.06804761,0.02766943,0.01476273,0.00009236195],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04297011,0.0005115404,0.9523168,0.0001746512,0.00009399121,0.0001129871,0.0001356562,0.001500733,0.002183552],"genre_scores_gemma":[0.4369589,0.0003765076,0.5598643,0.000186903,0.0001832537,0.000124023,0.0006455645,0.0002271528,0.001433327],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003049016,"threshold_uncertainty_score":0.005056441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01479443134254104,"score_gpt":0.2585298962757453,"score_spread":0.2437354649332042,"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."}}