{"id":"W2758198999","doi":"10.1016/j.cjca.2017.07.349","title":"USE OF THE VALVE VISUALIZATION ON ECHOCARDIOGRAPHY GRADE (VVEG) TOOL IMPROVES NEGATIVE PREDICTIVE VALUE OF TRANSTHORACIC ECHOCARDIOGRAM FOR RULING OUT VALVULAR VEGETATION","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Cardiology","topic":"Infective Endocarditis Diagnosis and Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Public Health","funders":"","keywords":"Medicine; Cardiology; Internal medicine; Endocarditis; Transthoracic echocardiogram; Vegetation (pathology); Infective endocarditis; Gold standard (test); Transesophageal echocardiogram; Ejection fraction; Tricuspid valve; Mitral valve; Radiology; Heart failure","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001616886,0.0008430772,0.000683561,0.00197898,0.0003281623,0.001502533,0.000772062,0.001001531,0.002071299],"category_scores_gemma":[0.01298835,0.0002258404,0.0007120398,0.0005612115,0.0003689487,0.00134423,0.0005517956,0.001019211,0.0005227111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002471421,"about_ca_system_score_gemma":0.0005703309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001583079,"about_ca_topic_score_gemma":0.003844037,"domain_scores_codex":[0.9984308,0.0003940069,0.0002963524,0.0001906408,0.0005071476,0.0001809774],"domain_scores_gemma":[0.994628,0.002579354,0.0008441285,0.0002635824,0.0008922706,0.0007926988],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004593454,0.0002074405,0.9655397,0.00009482071,0.0001235514,0.0009129809,0.00009999621,0.0002211875,0.003263761,0.0001334459,0.001019637,0.027924],"study_design_scores_gemma":[0.00009377661,0.001585113,0.9653397,0.0003866432,0.0005610854,0.01271926,0.0006465047,0.009688979,0.0047116,0.000913029,0.00328201,0.00007239898],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9770735,0.004884223,0.002904886,0.001591145,0.0005895806,0.00005881196,0.0004188414,0.0001619251,0.01231703],"genre_scores_gemma":[0.9969198,0.0004800087,0.001907089,0.0001467556,0.0001327546,0.000005693013,0.0001516637,0.00001058815,0.0002457609],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002071299,"threshold_uncertainty_score":0.008551002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03605329301864139,"score_gpt":0.3106103680751427,"score_spread":0.2745570750565013,"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."}}