{"id":"W7027651648","doi":"","title":"Deep learning and neural architecture search for cardiac arrhythmias classification","year":2022,"lang":"en","type":"other","venue":"Australasian Journal of Paramedicine","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Deep learning; Convolutional neural network; Cardiac arrhythmia; Economic shortage; Process (computing); Artificial neural network; TRACE (psycholinguistics); Clinical Practice","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0007689756,0.0006913386,0.000546307,0.0005492095,0.0002467257,0.0008328275,0.0008123829,0.000962854,0.001875755],"category_scores_gemma":[0.002870093,0.000417902,0.0005785746,0.0005848358,0.0003849434,0.0008118675,0.0007161839,0.001801235,0.0005220966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001018325,"about_ca_system_score_gemma":0.000936824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005399415,"about_ca_topic_score_gemma":0.0059955,"domain_scores_codex":[0.9997607,0.00006237224,0.00001799695,0.00006096511,0.0000566676,0.00004135623],"domain_scores_gemma":[0.9993826,0.0003516184,0.00006352794,0.00004298909,0.0001309357,0.00002837752],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009069833,0.0001172803,0.002617651,0.0001646808,0.00009128285,0.00009144055,0.00008517713,0.7426357,0.003856663,0.01322387,0.004208685,0.2328169],"study_design_scores_gemma":[0.000003299601,0.00001820874,0.0001521436,0.00001408621,0.000006567474,0.000008058448,0.000005938426,0.9938571,0.0005901118,0.004848524,0.0004931441,0.00000284137],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1020342,0.007799137,0.877288,0.002839699,0.0002103106,0.0000795218,0.0003634201,0.00155076,0.007834891],"genre_scores_gemma":[0.7851204,0.002756831,0.2030318,0.0005927524,0.0001397579,0.0001388644,0.0007239147,0.00008727765,0.007408401],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005399415,"threshold_uncertainty_score":0.01073593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02367557791201455,"score_gpt":0.3218737268180368,"score_spread":0.2981981489060223,"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."}}