{"id":"W3183946154","doi":"10.32920/22734317.v1","title":"ECG Heartbeat Classification Using Multimodal Fusion","year":2023,"lang":"en","type":"preprint","venue":"","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Heartbeat; Artificial intelligence; Computer science; Convolutional neural network; Pattern recognition (psychology); Support vector machine; Deep learning","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004676112,0.0006871373,0.0006030256,0.001243,0.000173138,0.0005822981,0.0004228649,0.0006408909,0.001473013],"category_scores_gemma":[0.001410929,0.0001174571,0.0006083976,0.0006245045,0.0001873646,0.0007031769,0.0007658249,0.0005004141,0.000562065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003056973,"about_ca_system_score_gemma":0.0003015116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00165566,"about_ca_topic_score_gemma":0.001816788,"domain_scores_codex":[0.9996588,0.00004937515,0.00001898339,0.00009952543,0.0001122018,0.00006107493],"domain_scores_gemma":[0.9997521,0.00005549687,0.0000357637,0.000038672,0.0000927763,0.00002519725],"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":[0.0007370356,0.000254053,0.009226443,0.00009989644,0.0001322681,0.0002953166,0.0000745314,0.05052876,0.07603611,0.001220959,0.004275934,0.8571187],"study_design_scores_gemma":[0.0000241888,0.0002358649,0.0101814,0.00002391009,0.00007787699,0.0003659943,0.00005489049,0.9548591,0.03036322,0.00190022,0.001879987,0.00003328924],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2718444,0.001762823,0.7150274,0.0006381945,0.0002194602,0.0001580069,0.001098537,0.003714377,0.005536686],"genre_scores_gemma":[0.9141932,0.0003960121,0.08229008,0.0001691423,0.0001261148,0.0000548717,0.001081289,0.00005113327,0.001638172],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00165566,"threshold_uncertainty_score":0.004927695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2024961594862609,"score_gpt":0.4001060265079818,"score_spread":0.1976098670217209,"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."}}