{"id":"W2294410895","doi":"10.1109/embc.2015.7319390","title":"Computationally efficient method for localizing the spiral rotor source using synthetic intracardiac electrograms during atrial fibrillation","year":2015,"lang":"en","type":"article","venue":"","topic":"Cardiac electrophysiology and arrhythmias","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Wavefront; Spiral (railway); Atrial fibrillation; Ablation; Intracardiac injection; Rotor (electric); Computer science; Catheter ablation; Artifact (error); Medicine; Cardiology; Physics; Computer vision; Mathematics; Optics; Engineering; Electrical engineering","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":[0.0002271363,0.0003664269,0.0002025386,0.0002594866,0.0001619202,0.0002623003,0.0003663963,0.0004028733,0.0008092248],"category_scores_gemma":[0.001090477,0.0001567447,0.0002428216,0.0001904956,0.0002260067,0.0002899371,0.0003366197,0.0003068513,0.0001704614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001745026,"about_ca_system_score_gemma":0.0005338798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002351608,"about_ca_topic_score_gemma":0.002716237,"domain_scores_codex":[0.9999385,0.00001708529,0.000004173134,0.000007696663,0.00002656688,0.00000597661],"domain_scores_gemma":[0.9997167,0.0001501,0.00003302458,0.00002653739,0.00005879081,0.00001493026],"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":[0.0002120324,0.00003963236,0.001564704,0.00007613212,0.0000281716,0.0002067312,0.0001216729,0.8477035,0.03078645,0.004000698,0.0007276608,0.1145326],"study_design_scores_gemma":[0.00000975054,0.00001330338,0.0001366342,0.000001921345,0.000002186195,0.00003737264,0.0000060658,0.9978909,0.001381193,0.0003405367,0.0001772724,0.000002789567],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04237029,0.00008429545,0.9562218,0.00007754664,0.00002119055,0.00003174023,0.00002198548,0.0002633978,0.0009077545],"genre_scores_gemma":[0.4675165,0.0001439598,0.5309801,0.00004853907,0.00002554136,0.00007781986,0.00009767894,0.00005508427,0.001054748],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002351608,"threshold_uncertainty_score":0.004675806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02485856149753604,"score_gpt":0.3161939515810593,"score_spread":0.2913353900835233,"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."}}