{"id":"W2145887973","doi":"10.1186/1532-429x-13-25","title":"Comparison between cardiovascular magnetic resonance and transthoracic doppler echocardiography for the estimation of effective orifice area in aortic stenosis","year":2011,"lang":"en","type":"article","venue":"Journal of Cardiovascular Magnetic Resonance","topic":"Cardiac Valve Diseases and Treatments","field":"Medicine","cited_by":104,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; Université Laval","funders":"Institut universitaire de cardiologie et de pneumologie de Québec, Université Laval; Natural Sciences and Engineering Research Council of Canada; Consejo Nacional de Ciencia y Tecnología; Canadian Institutes of Health Research; Université Laval","keywords":"Medicine; Angiology; Stenosis; Cardiology; Magnetic resonance imaging; Internal medicine; Cardiac magnetic resonance; Radiology; Doppler echocardiography; Body orifice; Doppler effect; Magnetic resonance angiography; Anatomy; Blood pressure; Diastole","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00572374,0.0004411385,0.0005079558,0.001786375,0.0002706319,0.0007502493,0.0006488848,0.0009263213,0.0006012631],"category_scores_gemma":[0.02000172,0.0003606212,0.0002712614,0.0004005719,0.0005464851,0.0006315112,0.0006381235,0.0004816359,0.000371854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002277113,"about_ca_system_score_gemma":0.000197847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005641109,"about_ca_topic_score_gemma":0.0009498987,"domain_scores_codex":[0.9977283,0.0009106363,0.0002888096,0.0004208616,0.0005470501,0.000104389],"domain_scores_gemma":[0.986751,0.007819041,0.002023892,0.0007329998,0.001722789,0.0009502019],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001242811,0.0001053128,0.9838707,0.0000492265,0.0001101357,0.0003205807,0.000384299,0.0003124165,0.003952008,0.00004012312,0.00007886774,0.009533437],"study_design_scores_gemma":[0.00005316867,0.0005618878,0.9946774,0.00001496508,0.0000565333,0.0009777873,0.0001588132,0.002507068,0.0008218399,0.00005192128,0.000107077,0.00001161],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989244,0.0002817776,0.0004915335,0.00001740399,0.00001280961,0.00001112185,0.00002576397,0.0000071712,0.0002279573],"genre_scores_gemma":[0.9993568,0.00004298523,0.0004816485,0.00001160583,0.00001937737,0.000006110806,0.00004244532,0.00000339272,0.00003566603],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00572374,"threshold_uncertainty_score":0.0302704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02459707760822654,"score_gpt":0.3008374371514441,"score_spread":0.2762403595432176,"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."}}