{"id":"W2612569538","doi":"10.1007/978-3-319-58466-9_37","title":"ECG Identification Based on PCA-RPROP","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Athabasca University","funders":"","keywords":"Computer science; Artificial intelligence; Pattern recognition (psychology); Redundancy (engineering); Data mining; Feature selection; Rprop; Feature extraction; Machine learning; Artificial neural network; Recurrent neural network","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":[0.0002816243,0.0008897379,0.0007097343,0.0007981004,0.0003124838,0.0007666733,0.0005245149,0.0007950671,0.005565323],"category_scores_gemma":[0.0008408697,0.0002846938,0.0006346321,0.0008727791,0.0002167138,0.00072301,0.000508471,0.0006803044,0.005293169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008080496,"about_ca_system_score_gemma":0.0002321539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004000228,"about_ca_topic_score_gemma":0.0009588927,"domain_scores_codex":[0.9996456,0.00004844981,0.00002126509,0.0001065984,0.0001523113,0.00002579597],"domain_scores_gemma":[0.9997658,0.00006376947,0.00001458628,0.00004301332,0.0001029876,0.000009896452],"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":[0.0001797906,0.00006302865,0.0008363803,0.0002794249,0.00006223865,0.0002143764,0.00003668191,0.002494395,0.1055406,0.001289363,0.006412696,0.8825909],"study_design_scores_gemma":[0.0000909575,0.0005550386,0.03071557,0.0002314372,0.0003786814,0.007963745,0.0001219135,0.6427594,0.2593414,0.007581187,0.05004222,0.0002183222],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01140601,0.002332243,0.9735377,0.0002147508,0.000433032,0.0001378143,0.0003467399,0.002943389,0.008648308],"genre_scores_gemma":[0.1865623,0.003042266,0.7917838,0.000337386,0.0005371604,0.000162741,0.001102406,0.0003687817,0.01610309],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005565323,"threshold_uncertainty_score":0.01861781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02508721434092201,"score_gpt":0.2915098952617813,"score_spread":0.2664226809208592,"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."}}