{"id":"W4387258954","doi":"10.3390/tomography9050144","title":"Neuroimaging Scoring Tools to Differentiate Inflammatory Central Nervous System Small-Vessel Vasculitis: A Need for Artificial Intelligence/Machine Learning?—A Scoping Review","year":2023,"lang":"en","type":"article","venue":"Tomography","topic":"Vasculitis and related conditions","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Toronto; University of Ottawa","funders":"","keywords":"Neuroimaging; Vasculitis; Artificial intelligence; Computer science; Medicine; Machine learning; Systemic vasculitis; Intensive care medicine; Pathology; Disease; Psychiatry","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004490058,0.0003255519,0.0006864027,0.0006630247,0.0004104385,0.0001352075,0.0001911166,0.0001056186,0.00004795718],"category_scores_gemma":[0.0002237473,0.0002976212,0.0007270729,0.001588933,0.00005848168,0.0001311903,0.00009841236,0.0004541309,0.0001028644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005304014,"about_ca_system_score_gemma":0.00009589931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004399295,"about_ca_topic_score_gemma":0.00001982856,"domain_scores_codex":[0.9973627,0.000112924,0.0008075306,0.0005657076,0.0003219174,0.0008292442],"domain_scores_gemma":[0.9986995,0.0001451888,0.0001609056,0.0004174654,0.0001658089,0.0004111074],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0007198021,0.0008140253,0.0713628,0.1955222,0.004864941,0.002323139,0.005499187,0.008314378,0.01453179,0.02731893,0.00356446,0.6651644],"study_design_scores_gemma":[0.005183935,0.002322797,0.2182419,0.6902043,0.007305591,0.00114239,0.004565448,0.05163166,0.007362166,0.001560336,0.006053176,0.004426296],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8942642,0.03686985,0.03951435,0.006560912,0.003343902,0.01340497,0.0001720193,0.004727088,0.00114274],"genre_scores_gemma":[0.9898914,0.006409179,0.0007692935,0.000649554,0.0006169398,0.0009160362,0.0004707195,0.0001357925,0.0001411549],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6607381,"threshold_uncertainty_score":0.9999476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04370664589605579,"score_gpt":0.2884216153368213,"score_spread":0.2447149694407655,"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."}}