{"id":"W2266896131","doi":"10.1002/jmri.25168","title":"Does hydration status affect MRI measures of brain volume or water content?","year":2016,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia","funders":"Multiple Sclerosis Society of Canada","keywords":"Brain size; Urine specific gravity; Medicine; Magnetic resonance imaging; Neuroimaging; Reproducibility; Nuclear medicine; Body water; Dehydration; Urine; Radiology; Biomedical engineering; Body weight; Chemistry; Endocrinology; Chromatography","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":[0.0004643066,0.0002352118,0.0002437069,0.0001594054,0.0001404531,0.0003081462,0.0001189263,0.0003299302,0.0006476843],"category_scores_gemma":[0.003175649,0.0001104927,0.0001153692,0.0001102313,0.0006094325,0.0003218616,0.0001962229,0.0002127362,0.0001217791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001060396,"about_ca_system_score_gemma":0.0001291922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007633643,"about_ca_topic_score_gemma":0.001188668,"domain_scores_codex":[0.999803,0.0000715721,0.00001644332,0.00004594461,0.00004112306,0.00002193548],"domain_scores_gemma":[0.9992403,0.0002184667,0.0003190437,0.00005409849,0.00006801441,0.0001001706],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006652646,0.0004279515,0.7934925,0.0003265637,0.000398614,0.0009789907,0.0006414722,0.00024124,0.1480603,0.00009153262,0.0005557044,0.04813252],"study_design_scores_gemma":[0.00001674475,0.001477296,0.9928114,0.00001441229,0.00005502289,0.000477187,0.0001360866,0.0002251141,0.004447549,0.00007220424,0.0002595554,0.000007424017],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978218,0.0008850725,0.000621759,0.0001010938,0.00002087723,0.00002471322,0.00007886526,0.000008555417,0.0004372736],"genre_scores_gemma":[0.9992629,0.0002465366,0.0002297391,0.00006237145,0.00001685278,0.00001140544,0.00006184654,0.000003420372,0.0001049239],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007633643,"threshold_uncertainty_score":0.002455533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02554574604276429,"score_gpt":0.2990326441318196,"score_spread":0.2734868980890553,"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."}}