{"id":"W2033130081","doi":"10.1532/hsf98.20081090","title":"Use of Magnetic Resonance Imaging to Assess Myocardial Perfusion after Transmyocardial Laser Revascularization","year":2009,"lang":"en","type":"article","venue":"The Heart Surgery Forum","topic":"Pain Management and Treatment","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Canadian Cardiovascular Society; Perfusion; Cardiology; Angina; Revascularization; Internal medicine; Magnetic resonance imaging; Coronary artery disease; Cardiac magnetic resonance imaging; Myocardial perfusion imaging; Perfusion scanning; Percutaneous; Radiology; Myocardial infarction","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003910342,0.0002026464,0.0001780581,0.0006141014,0.0001308826,0.0002052764,0.0001252844,0.0003103707,0.0007614216],"category_scores_gemma":[0.0011635,0.00008391742,0.0001217451,0.0001180507,0.0002017561,0.000254574,0.0001166999,0.0003367884,0.0001805306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001385895,"about_ca_system_score_gemma":0.00008079795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004787778,"about_ca_topic_score_gemma":0.0009377992,"domain_scores_codex":[0.9998943,0.00003633422,0.000008365616,0.00001765608,0.00001979935,0.00002360946],"domain_scores_gemma":[0.9994443,0.0001205548,0.0002435771,0.00002094417,0.00007379545,0.00009692895],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001936122,0.0004296581,0.8960001,0.00008520616,0.00009955009,0.002602443,0.0002586611,0.0002206447,0.05362087,0.00004341517,0.0003132078,0.04439006],"study_design_scores_gemma":[0.00009274998,0.002872539,0.9825638,0.00002356556,0.00007388237,0.005889843,0.0001537712,0.000670017,0.007296113,0.00003849731,0.0003062558,0.00001886204],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981765,0.0006535636,0.0003050641,0.00006340439,0.000006788608,0.00001305377,0.00002449505,0.00000924075,0.0007478847],"genre_scores_gemma":[0.9990522,0.0002578687,0.0004344604,0.0000547309,0.0000249849,0.00001519419,0.00004061441,0.000001367256,0.0001185059],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007614216,"threshold_uncertainty_score":0.002547204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02543020618437981,"score_gpt":0.2542185265055828,"score_spread":0.228788320321203,"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."}}