{"id":"W3156074825","doi":"10.36001/phmconf.2011.v3i1.1994","title":"Comparison of Parallel and Single Neural Networks in Heart Arrhythmia Detection by Using ECG Signal Analysis","year":2011,"lang":"en","type":"article","venue":"Annual Conference of the PHM Society","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Cardiac arrhythmia; Artificial neural network; Computer science; Pattern recognition (psychology); SIGNAL (programming language); Artificial intelligence; Speech recognition; Cardiology; Internal medicine; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002146092,0.0006035261,0.0007466876,0.001008698,0.0002907853,0.0006131545,0.0006233981,0.0005856753,0.001166991],"category_scores_gemma":[0.004058588,0.0002838793,0.0004462875,0.0006320354,0.0002896269,0.001287832,0.0005471073,0.0004165507,0.0002484747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005102346,"about_ca_system_score_gemma":0.0004660666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003520388,"about_ca_topic_score_gemma":0.003622417,"domain_scores_codex":[0.9993458,0.0002053223,0.00003966882,0.0001400704,0.0002023276,0.00006677348],"domain_scores_gemma":[0.9983631,0.000839635,0.000106852,0.0001309872,0.0005023376,0.00005712431],"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":[0.002167624,0.0004039007,0.007778907,0.0002294405,0.0002879126,0.0001877142,0.00008700492,0.3897899,0.00999204,0.002293263,0.0009170671,0.5858653],"study_design_scores_gemma":[0.00002762809,0.0001865806,0.001564358,0.00000785859,0.00005365134,0.00005288917,0.00001942758,0.9938686,0.003146312,0.000783933,0.000280165,0.000008587015],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4431176,0.002282078,0.5467178,0.0003792119,0.000250842,0.0001533208,0.00009620428,0.001017007,0.005985929],"genre_scores_gemma":[0.8975904,0.0007201525,0.09936266,0.00006442364,0.00008409954,0.00007888059,0.00008821974,0.00003944799,0.001971752],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003520388,"threshold_uncertainty_score":0.0113498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07046536101610062,"score_gpt":0.3083353862875996,"score_spread":0.237870025271499,"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."}}