{"id":"W3005132157","doi":"10.1177/0846537119895752","title":"The Utility of Short-Interval Follow-Up for Baseline High-Risk Screening Breast MRI","year":2020,"lang":"en","type":"article","venue":"Canadian Association of Radiologists Journal","topic":"MRI in cancer diagnosis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Juravinski Hospital; St. Joseph’s Healthcare Hamilton; University of Ottawa; McMaster University","funders":"","keywords":"Medicine; Magnetic resonance imaging; Breast MRI; Retrospective cohort study; Confidence interval; Radiology; Population; Breast imaging; Breast cancer; Mammography; Surgery; Cancer; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003411234,0.0001835237,0.0002294715,0.001204144,0.0002481082,0.0005942483,0.0004033933,0.0004142253,0.001064525],"category_scores_gemma":[0.02278234,0.00009621768,0.0003583753,0.0007054866,0.0002427373,0.000838909,0.0004042099,0.0003449692,0.0002190543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002591019,"about_ca_system_score_gemma":0.000412289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001278547,"about_ca_topic_score_gemma":0.002221225,"domain_scores_codex":[0.998515,0.0005495612,0.0003007712,0.0001094871,0.0004195753,0.0001055723],"domain_scores_gemma":[0.9782501,0.006514688,0.01159237,0.0007368404,0.002139383,0.0007666558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002960148,0.00005627779,0.9761395,0.00008996425,0.00003252471,0.0003156237,0.0001017504,0.00007144189,0.0003115601,0.00002337668,0.0001862255,0.0223758],"study_design_scores_gemma":[0.00001078661,0.0005239571,0.9949211,0.0001459526,0.00007306051,0.002832907,0.000234362,0.0002603837,0.0004200595,0.00002536324,0.0005448196,0.00000713355],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936737,0.003693107,0.0006072672,0.0002460651,0.00003430077,0.00003505838,0.0002212039,0.00001564062,0.001473533],"genre_scores_gemma":[0.9985847,0.0006062278,0.0004739153,0.00004341549,0.00005235146,0.00001776261,0.0001423534,0.000002565493,0.00007671806],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003411234,"threshold_uncertainty_score":0.01804054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0331721819906859,"score_gpt":0.281493331265026,"score_spread":0.2483211492743401,"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."}}