{"id":"W2089922425","doi":"10.1109/isbi.2012.6235837","title":"Integration of different cardiac electrophysiological models into a single simulation pipeline","year":2012,"lang":"en","type":"article","venue":"","topic":"Cardiovascular Function and Risk Factors","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sunnybrook Health Science Centre; Health Sciences Centre; St. Thomas Hospital","funders":"","keywords":"Cardiac electrophysiology; Computer science; Pipeline (software); Artificial intelligence; Electrophysiology; Orientation (vector space); Pattern recognition (psychology); Neuroscience","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":[0.0007582378,0.0009332721,0.0007572034,0.0005355197,0.0003262622,0.001135323,0.001465216,0.001117022,0.004073642],"category_scores_gemma":[0.002609916,0.000654744,0.001335882,0.0004512013,0.0003820103,0.001007537,0.001287939,0.001074767,0.001167189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000602448,"about_ca_system_score_gemma":0.001307966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005257191,"about_ca_topic_score_gemma":0.004798966,"domain_scores_codex":[0.9996988,0.00007129215,0.00003413242,0.00006248715,0.0001041501,0.00002921539],"domain_scores_gemma":[0.9993042,0.0003314794,0.0000379639,0.0001661491,0.0001125975,0.00004757064],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005013896,0.00003946442,0.0007807195,0.00005565831,0.00005445216,0.00006157348,0.00006471938,0.976454,0.003388836,0.003158611,0.0005678845,0.01532404],"study_design_scores_gemma":[0.00001233153,0.00001824713,0.0001234586,0.000006287328,0.0000139967,0.00001777697,0.000009619615,0.9953647,0.00132251,0.001642109,0.001458927,0.00001009239],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03273644,0.00009439584,0.9589408,0.0002204423,0.00006737576,0.0001774309,0.0006369709,0.003433804,0.003692391],"genre_scores_gemma":[0.5174851,0.0004679747,0.4733204,0.0001790777,0.00005459615,0.0007797448,0.002255152,0.001255211,0.004202775],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005257191,"threshold_uncertainty_score":0.01362771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03383499460225872,"score_gpt":0.2766494172559194,"score_spread":0.2428144226536607,"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."}}