{"id":"W2741227544","doi":"10.1016/j.ejrad.2017.07.025","title":"Abbreviated breast magnetic resonance protocol: Value of high-resolution temporal dynamic sequence to improve lesion characterization","year":2017,"lang":"en","type":"article","venue":"European Journal of Radiology","topic":"MRI in cancer diagnosis","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Hôtel-Dieu de Montréal; Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"Medicine; McNemar's test; Breast MRI; Magnetic resonance imaging; Protocol (science); Radiology; Nuclear medicine; Population; Breast cancer; Pathology; Mammography; Internal medicine; Cancer","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":[0.001089791,0.0006171801,0.0003042847,0.0007507996,0.0005168294,0.000690399,0.0007197083,0.002089232,0.00994044],"category_scores_gemma":[0.004825097,0.0002786482,0.0002575367,0.000467897,0.0002983746,0.0008537194,0.0005554463,0.0012191,0.002092927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003353214,"about_ca_system_score_gemma":0.0009613077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009309705,"about_ca_topic_score_gemma":0.001410643,"domain_scores_codex":[0.9996964,0.0001198432,0.00006098218,0.00004039669,0.00005354275,0.00002893659],"domain_scores_gemma":[0.9991979,0.0002221846,0.00008299597,0.0001409835,0.0002800401,0.00007585766],"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":[0.007022468,0.001007618,0.00509376,0.001354168,0.0001659957,0.004447686,0.0002399223,0.01037031,0.4493266,0.006038137,0.04607484,0.4688585],"study_design_scores_gemma":[0.002476181,0.00699958,0.1122313,0.0011577,0.001186311,0.04637376,0.0003567809,0.1122637,0.3701503,0.01517525,0.3310654,0.0005638044],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3567239,0.01040146,0.5325723,0.01264376,0.002528173,0.008952931,0.004866744,0.004504206,0.06680647],"genre_scores_gemma":[0.4592756,0.005843,0.4870825,0.004910609,0.0006303342,0.006782641,0.005491739,0.001165875,0.02881784],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00994044,"threshold_uncertainty_score":0.03325409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02468610974250658,"score_gpt":0.307686439458869,"score_spread":0.2830003297163624,"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."}}