{"id":"W4381135294","doi":"10.32920/22734290.v1","title":"ECG Heartbeat Classification Using Multimodal Fusion","year":2023,"lang":"en","type":"preprint","venue":"","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","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; Machine learning","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0004721786,0.0006902536,0.000598576,0.001277186,0.0001731017,0.0005925414,0.0004137265,0.0006626434,0.001534523],"category_scores_gemma":[0.001412143,0.0001178947,0.0005942089,0.0005630202,0.0001850559,0.0006931353,0.0007405879,0.0004851306,0.0006070296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003112909,"about_ca_system_score_gemma":0.000300236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001640551,"about_ca_topic_score_gemma":0.001766918,"domain_scores_codex":[0.9996405,0.00005286637,0.00001976493,0.0001019633,0.000123232,0.00006165809],"domain_scores_gemma":[0.9997509,0.00005377114,0.00003596519,0.00003829511,0.00009640602,0.00002463452],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007321653,0.0002581532,0.008979729,0.00009634233,0.0001324219,0.0002889301,0.00006574025,0.04860615,0.08229449,0.00113032,0.004325417,0.8530902],"study_design_scores_gemma":[0.0000228742,0.0002286577,0.009605348,0.00002270346,0.000071792,0.0003524686,0.00004814861,0.9556521,0.03055372,0.001598248,0.001812453,0.00003157816],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2755832,0.001718822,0.7107999,0.0006400811,0.0002319492,0.0001652851,0.001068098,0.003874578,0.005918055],"genre_scores_gemma":[0.909885,0.0004008863,0.08640624,0.0001757688,0.0001279241,0.00005911593,0.001078225,0.0000515757,0.001815151],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001640551,"threshold_uncertainty_score":0.00513351,"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."}}