{"id":"W2025511147","doi":"10.1067/mnc.2002.120163","title":"Attenuation correction and gating synergistically improve the diagnostic accuracy of myocardial perfusion SPECT","year":2002,"lang":"en","type":"article","venue":"Journal of Nuclear Cardiology","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":105,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hôtel-Dieu de Montréal","funders":"National Heart, Lung, and Blood Institute","keywords":"Medicine; Correction for attenuation; Perfusion; Gating; Nuclear medicine; Single-photon emission computed tomography; Attenuation; Coronary artery disease; Right coronary artery; Stenosis; Sensitivity (control systems); Perfusion scanning; Myocardial perfusion imaging; Circumflex; Diagnostic accuracy; Radiology; Cardiology; Artery; Positron emission tomography; Coronary angiography; Physics; Optics; Myocardial infarction","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0005093457,0.00009681098,0.0004504522,0.00008505178,0.00008163959,0.00001364254,0.00004928847,0.00007140708,0.00003451362],"category_scores_gemma":[0.01387809,0.0000656363,0.000240048,0.00008833773,0.0001698703,0.00005906626,0.0000421396,0.0003548198,0.00001126735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004937872,"about_ca_system_score_gemma":0.00002823768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000119842,"about_ca_topic_score_gemma":2.905754e-7,"domain_scores_codex":[0.9989861,0.0001596619,0.0003917324,0.0001074366,0.0002151671,0.0001399529],"domain_scores_gemma":[0.9964458,0.002713023,0.0003252979,0.0001536672,0.0002832788,0.00007892678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001150503,0.0003139306,0.3725103,0.0002132058,0.00135479,0.001454938,0.003348734,0.002685965,0.09848931,0.00101586,0.1438671,0.3735954],"study_design_scores_gemma":[0.002678802,0.00210868,0.956381,0.0003347795,0.001611439,0.01162886,0.001134125,0.007449436,0.0003835334,0.000131726,0.01595935,0.0001983233],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9893335,0.001276339,0.0006876034,0.002482229,0.002150598,0.0001602034,0.000004454574,0.00001327431,0.003891812],"genre_scores_gemma":[0.9969152,0.001073642,0.0002740066,0.0003129863,0.001381624,8.591439e-7,0.000001133521,0.00001682026,0.00002376827],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5838707,"threshold_uncertainty_score":0.9944285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01397363695330581,"score_gpt":0.2505235904803609,"score_spread":0.2365499535270551,"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."}}