{"id":"W2169533318","doi":"10.1109/iembs.1990.691837","title":"ECG Beat Classification By A Neural Network","year":2005,"lang":"en","type":"article","venue":"","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Artificial neural network; Extractor; Computer science; Pattern recognition (psychology); Artificial intelligence; Feature extraction; Backpropagation; Sample (material); Feature (linguistics); Time delay neural network; Beat (acoustics); Data mining; Speech recognition; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.00005846921,0.00005115052,0.00009429108,0.0000196022,0.00004287972,0.00001033732,0.00002806781,0.00003449706,0.0001770541],"category_scores_gemma":[0.00001100859,0.00003880058,0.00005168919,0.0001250969,0.00001172625,0.00003442907,0.000006221727,0.00007060291,0.0001283937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002583351,"about_ca_system_score_gemma":0.000006822388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002498534,"about_ca_topic_score_gemma":0.000006033266,"domain_scores_codex":[0.9995615,0.000009695636,0.0000990862,0.0001095186,0.00009658813,0.0001235789],"domain_scores_gemma":[0.9997254,0.00001511469,0.00001987716,0.0001443357,0.00002488676,0.0000703644],"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":[0.00003115185,0.0001442694,0.278428,0.00001153594,0.00008644618,0.000003281385,0.00005359551,0.0004545439,0.01330449,0.0001058918,0.440588,0.2667888],"study_design_scores_gemma":[0.00116852,0.0001753462,0.0749605,0.00004841184,0.0003688979,0.00002203765,0.0002100351,0.5085576,0.005278331,0.00003713499,0.4089134,0.0002597572],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9213068,0.001057556,0.004121988,0.02912444,0.0001984995,0.0001268824,0.000001364479,0.0003031742,0.0437593],"genre_scores_gemma":[0.9622256,0.0000366183,0.003511936,0.0008491571,0.001015816,0.000004304132,0.00002191577,0.00000683032,0.03232782],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5081031,"threshold_uncertainty_score":0.1938618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02257551299043398,"score_gpt":0.2884667615074833,"score_spread":0.2658912485170493,"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."}}