{"id":"W2140382254","doi":"10.1002/jmri.21166","title":"Minimum detectable difference of MR diffusion maps in acute ischemic stroke","year":2008,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hotchkiss Brain Institute; Foothills Medical Centre; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Heritage Foundation for Medical Research; Fondation pour la Recherche Médicale","keywords":"Diffusion MRI; Fractional anisotropy; Region of interest; Medicine; Effective diffusion coefficient; Nuclear medicine; Stroke (engine); White matter; Acute stroke; Magnetic resonance imaging; Radiology; Internal medicine; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003472149,0.0004024432,0.0004489457,0.0008482977,0.000185591,0.000549782,0.000437777,0.0005097322,0.0004568233],"category_scores_gemma":[0.03874896,0.0001955458,0.0001707726,0.0003593993,0.000441679,0.0005305654,0.000488503,0.0003274769,0.0001529578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002588473,"about_ca_system_score_gemma":0.0001761689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000441881,"about_ca_topic_score_gemma":0.0004854748,"domain_scores_codex":[0.9978078,0.00107654,0.000262068,0.000343584,0.0004501503,0.00005995173],"domain_scores_gemma":[0.9869707,0.008682997,0.002357661,0.0007650994,0.0009768613,0.0002466853],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0104331,0.0004282939,0.569746,0.001217219,0.0007886159,0.001247616,0.001731186,0.01259364,0.07846594,0.0009599949,0.001950468,0.3204379],"study_design_scores_gemma":[0.0002623909,0.002573416,0.9064736,0.0000884054,0.0002353869,0.006711343,0.0003246896,0.04497463,0.03235658,0.004220185,0.001676035,0.0001033434],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9705262,0.001358555,0.02727715,0.00006472283,0.00001330479,0.00004869976,0.0001944082,0.0001313902,0.0003856348],"genre_scores_gemma":[0.9893379,0.0001168124,0.01025947,0.00001109126,0.00001269214,0.00003127933,0.0001522931,0.00001746025,0.00006096825],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003472149,"threshold_uncertainty_score":0.0183627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02539094773858129,"score_gpt":0.2952340528055675,"score_spread":0.2698431050669862,"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."}}