{"id":"W2921928513","doi":"10.3174/ajnr.a5997","title":"Gadolinium-Enhanced Susceptibility-Weighted Imaging in Multiple Sclerosis: Optimizing the Recognition of Active Plaques for Different MR Imaging Sequences","year":2019,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Discovery Air (Canada)","funders":"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Medicine; Susceptibility weighted imaging; Multiple sclerosis; Gadolinium; Magnetic resonance imaging; Nuclear medicine; Radiology","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":[0.006418322,0.0007488996,0.0004567783,0.002056276,0.0003211768,0.0006682994,0.0004285744,0.0006792163,0.0003750891],"category_scores_gemma":[0.0170741,0.0003243564,0.0003107876,0.000595245,0.0005049201,0.0008805252,0.0005442088,0.0003563,0.0003013306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001820596,"about_ca_system_score_gemma":0.0003199007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003953381,"about_ca_topic_score_gemma":0.000726832,"domain_scores_codex":[0.9984466,0.0007637871,0.0002575571,0.0002141047,0.0002455816,0.00007233035],"domain_scores_gemma":[0.9946465,0.003179773,0.000893067,0.0003519609,0.0006834648,0.0002452777],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001449501,0.0001387721,0.9029871,0.0002233358,0.0002093743,0.0005730491,0.0006750987,0.001517143,0.03266542,0.00007930228,0.0001491442,0.05933273],"study_design_scores_gemma":[0.0001132696,0.001548916,0.9554406,0.0001344754,0.0002775606,0.007022321,0.0005079937,0.01519653,0.01867452,0.0004409897,0.0005913931,0.00005146159],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995904,0.001095622,0.002644446,0.00002574829,0.000007472385,0.00003070261,0.00001310833,0.00002025101,0.0002586168],"genre_scores_gemma":[0.9936752,0.0002596291,0.005955243,0.00001146328,0.000009428957,0.00001062902,0.00002665111,0.000008212827,0.00004351946],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006418322,"threshold_uncertainty_score":0.03394371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03933468645985956,"score_gpt":0.307120522450998,"score_spread":0.2677858359911385,"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."}}