{"id":"W4253217788","doi":"10.1007/s00500-015-1785-3","title":"Erratum to: Description, analysis, and classification of biomedical signals: a computational intelligence approach","year":2015,"lang":"en","type":"erratum","venue":"Soft Computing","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Computational intelligence; Artificial intelligence; Machine learning","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001031395,0.0002995475,0.001027132,0.00119215,0.0001151723,0.00006184546,0.0001932544,0.0003961963,0.000009521709],"category_scores_gemma":[0.0005458644,0.0002789584,0.0002620185,0.002348205,0.0001908725,0.00004314918,0.0001380434,0.0007217114,0.00001087389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001328722,"about_ca_system_score_gemma":0.0004527473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008114686,"about_ca_topic_score_gemma":0.000003614738,"domain_scores_codex":[0.9971786,0.0001257783,0.0008429587,0.0006644826,0.0008983199,0.0002898173],"domain_scores_gemma":[0.9977897,0.0001560765,0.000463299,0.0003467696,0.0008660188,0.0003781527],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000117401,0.0009820121,0.02386125,0.001712461,0.005950721,0.00002452397,0.003520074,0.01858214,0.0006535267,0.0001716467,0.8019442,0.14248],"study_design_scores_gemma":[0.0002561002,0.0002288581,0.01912883,0.0008737679,0.003377513,0.00002867897,0.0009539192,0.967185,0.00001810734,0.0005818062,0.006970467,0.0003969922],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002120463,0.001535759,0.989146,0.0004166837,0.001832299,0.0002466418,0.00002426207,0.0001049178,0.00457298],"genre_scores_gemma":[0.8992587,0.00004488291,0.08307501,0.0001700861,0.002504876,0.00001081972,0.003108166,0.00005822709,0.01176928],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9486028,"threshold_uncertainty_score":0.9999663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06001022890026272,"score_gpt":0.3288251212834895,"score_spread":0.2688148923832268,"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."}}