{"id":"W2165921242","doi":"10.1109/tbme.2008.2003088","title":"Improved Event Interval Reconstruction in Synthetic Electrocardiograms","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Interval (graph theory); Event (particle physics); Computer science; Electrocardiography; Artificial intelligence; Mathematics; Physics; Medicine; Internal 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000116777,0.0001408411,0.0002771836,0.0004800437,0.00005153899,0.000004909868,0.00005054507,0.0001223073,0.00003401287],"category_scores_gemma":[0.00001521227,0.0001303298,0.0002253812,0.0005935053,0.0000569875,0.00004434213,5.783272e-7,0.0004496967,0.00001461817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001647937,"about_ca_system_score_gemma":0.00003878564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000693835,"about_ca_topic_score_gemma":0.000003549261,"domain_scores_codex":[0.9989934,0.00001429327,0.0002826501,0.0002291305,0.000214003,0.0002665404],"domain_scores_gemma":[0.9995621,0.00004035447,0.00002181876,0.00017114,0.00002241899,0.0001821816],"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":[0.0002356981,0.001022085,0.0005429125,0.0001685339,0.0005955723,0.0002962113,0.0002879903,0.01717821,0.2945058,0.000002778357,0.00003225825,0.6851319],"study_design_scores_gemma":[0.003105293,0.001259685,0.002294617,0.0010495,0.0003237643,0.002609499,0.000131871,0.8203668,0.1666725,0.000006224102,0.001605264,0.0005749655],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4235488,0.00006283999,0.5753123,0.0001922254,0.0006229234,0.00008859322,0.000001992954,0.0001449433,0.00002539447],"genre_scores_gemma":[0.9975746,0.0002658375,0.001806379,0.00002088774,0.0001421171,0.00003608519,0.000002389732,0.00002180785,0.0001299363],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8031886,"threshold_uncertainty_score":0.5314695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008626880901616096,"score_gpt":0.2261861341815082,"score_spread":0.2175592532798921,"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."}}