{"id":"W2781140631","doi":"10.1016/j.cjca.2017.12.026","title":"The State of Cardiovascular Magnetic Resonance Imaging in Canada: Results from the CanSCMR Pan-Canadian Survey","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Cardiology","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"St. Michael's Hospital; University of Calgary; University Health Network; University of Toronto; Sunnybrook Health Science Centre; McGill University Health Centre; University of Alberta; Health Sciences Centre","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Descriptive statistics; Magnetic resonance imaging; Referral; Cardiac magnetic resonance; Family medicine; Radiology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.001063978,0.0004396532,0.0005994776,0.002929598,0.002309364,0.002057074,0.001674383,0.0009784236,0.003134834],"category_scores_gemma":[0.005491506,0.0005012177,0.0009641887,0.01133871,0.0008804699,0.0008864669,0.001635472,0.00110161,0.0003880001],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04585168,"about_ca_system_score_gemma":0.06955918,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9978226,"about_ca_topic_score_gemma":0.9985968,"domain_scores_codex":[0.9970658,0.0001261114,0.0002699896,0.0003508419,0.001350222,0.0008368663],"domain_scores_gemma":[0.9916942,0.0002869444,0.001633902,0.000136171,0.004707367,0.001541472],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008863377,0.00004370813,0.983602,0.0002093601,0.0001594807,0.0001076719,0.0008657161,0.0002234656,0.000143431,0.0003233246,0.007673888,0.006559428],"study_design_scores_gemma":[0.000005710052,0.00001077945,0.995149,0.0001046892,0.00004584585,0.00008135315,0.001499855,0.0002109134,0.00003998548,0.00002853374,0.002799662,0.00002367534],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8924666,0.00776322,0.000441273,0.006157381,0.00008732253,0.0001382634,0.07723033,0.0001055149,0.01560997],"genre_scores_gemma":[0.9832187,0.004708047,0.0004717759,0.00103187,0.00002987113,0.00004035898,0.008943914,0.00002717088,0.001528167],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9541483,"threshold_uncertainty_score":0.3326787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01658311992127144,"score_gpt":0.2247244589007936,"score_spread":0.2081413389795221,"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."}}