{"id":"W4403203239","doi":"10.1093/braincomms/fcae299","title":"Watershed regions are more susceptible to tissue microstructural injury in multiple sclerosis","year":2024,"lang":"en","type":"article","venue":"Brain Communications","topic":"Multiple Sclerosis Research Studies","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Multiple Sclerosis Society; Multiple Sclerosis Society; Health Services Research and Development; U.S. Department of Veterans Affairs","keywords":"Multiple sclerosis; White matter; Lesion; Magnetic resonance imaging; Watershed; Medicine; Partial volume; Myelin; Nuclear medicine; Pathology; Radiology; Central nervous system; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025497,0.0002335227,0.0003395835,0.000683238,0.0002745088,0.0004146089,0.0001336175,0.0002662965,0.002140534],"category_scores_gemma":[0.0009662124,0.0002456356,0.0002337818,0.0004833558,0.0002579835,0.0002760013,0.0003512316,0.000231495,0.0001148273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009328069,"about_ca_system_score_gemma":0.00009721862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001980839,"about_ca_topic_score_gemma":0.002364244,"domain_scores_codex":[0.9999074,0.00001920292,0.000009336809,0.0000349648,0.00001688485,0.00001226956],"domain_scores_gemma":[0.9996542,0.00006528943,0.0001803984,0.00002387638,0.000030103,0.00004611062],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000808129,0.00009326151,0.9700903,0.00005392582,0.0001684648,0.0011403,0.0008043545,0.0002454088,0.02065904,0.0001440806,0.0001118704,0.00568102],"study_design_scores_gemma":[0.000009422834,0.0001123979,0.9977877,0.000004732724,0.00002789567,0.0007983301,0.0001703448,0.0003418565,0.0004889597,0.0001683128,0.0000870945,0.000002915613],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997498,0.00004515125,0.0001112968,0.000006237075,6.024022e-7,0.000002753254,0.00002498993,0.000002816364,0.00005629618],"genre_scores_gemma":[0.9997571,0.00002218247,0.00009999257,0.000002273572,0.000001610515,0.00000207998,0.00003436081,0.000001602401,0.00007874515],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002140534,"threshold_uncertainty_score":0.007160783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1361652732229066,"score_gpt":0.3804796846378236,"score_spread":0.2443144114149169,"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."}}