{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003335092,0.0001989376,0.0003251062,0.0005024004,0.0003353623,0.0001089868,0.000686591,0.00009293194,0.0000954896],"category_scores_gemma":[0.001315737,0.0001757599,0.00009876592,0.001103362,0.0003500458,0.0001377202,0.0009209067,0.0005304126,0.0002629745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003002667,"about_ca_system_score_gemma":0.0001016105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009924662,"about_ca_topic_score_gemma":0.002138249,"domain_scores_codex":[0.9983656,0.0001690081,0.0003682109,0.0003753269,0.0002748652,0.0004469978],"domain_scores_gemma":[0.9969047,0.0007023775,0.00003471098,0.001980419,0.0001520788,0.0002257246],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001093596,0.0002397102,0.02691685,0.0002378749,0.0001336546,0.00001672019,0.008777933,0.00002230468,0.7392271,0.0006040065,0.2003787,0.02333584],"study_design_scores_gemma":[0.001311194,0.000252762,0.6791151,0.001921831,0.00004475845,0.0000229065,0.003801318,0.003883232,0.01703489,0.0001455273,0.2920159,0.0004505959],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6315398,0.002201416,0.0001915176,0.3623326,0.00014967,0.001926984,0.0002355888,0.0004134817,0.001008975],"genre_scores_gemma":[0.9870484,0.0009431359,0.008081337,0.00121586,0.00007717677,0.0004117574,0.0001880466,0.00004779521,0.00198649],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7221922,"threshold_uncertainty_score":0.7167279,"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."}}