{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005321349,0.0002548195,0.0009004035,0.0006654575,0.00009011642,0.00001930586,0.00009900889,0.0001983759,0.0008050625],"category_scores_gemma":[0.0001858165,0.0001967254,0.0003066431,0.0002384297,0.000116865,0.00002120528,0.00002275739,0.001522634,0.000002411023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000832436,"about_ca_system_score_gemma":0.00009246438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001726667,"about_ca_topic_score_gemma":0.000001961207,"domain_scores_codex":[0.9983219,0.0001324685,0.0004640281,0.0002504305,0.0005355498,0.0002956153],"domain_scores_gemma":[0.9987248,0.0001523606,0.000513675,0.0001850554,0.000106449,0.0003176339],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001165605,0.0002495223,0.2071495,0.002445596,0.005069346,0.001610797,0.002432752,0.0008156661,0.002584683,0.00009699285,0.1844955,0.591884],"study_design_scores_gemma":[0.003866618,0.003903591,0.01079788,0.001397152,0.003459685,0.002249368,0.005401618,0.001574629,0.00007856824,0.00002976717,0.9668214,0.0004197007],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.2204166,0.1878319,0.06192939,0.1408117,0.01945895,0.01085584,0.0003114961,0.001271474,0.3571127],"genre_scores_gemma":[0.4601814,0.003385778,0.008361463,0.0001596957,0.01468644,0.00003688668,0.0002352959,0.0006794841,0.5122736],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7823259,"threshold_uncertainty_score":0.8814871,"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."}}