{"id":"W4292941883","doi":"10.3389/fnimg.2022.970385","title":"The comorbidity and cognition in multiple sclerosis (CCOMS) neuroimaging protocol: Study rationale, MRI acquisition, and minimal image processing pipelines","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neuroimaging","topic":"Multiple Sclerosis Research Studies","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nova Scotia Health Authority; Dalhousie University; St. Francis Xavier University; University of Manitoba; Health Sciences Centre","funders":"Canadian Institutes of Health Research; Crohn's and Colitis Canada; Multiple Sclerosis Society; Seoul National University; Multiple Sclerosis Society of Canada; University of Minnesota; European Genomic Institute for Diabetes; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; Research Manitoba; Health Sciences Centre Foundation","keywords":"Neuroimaging; Cognition; Multiple sclerosis; Comorbidity; Functional neuroimaging; Medicine; Anxiety; Depression (economics); Psychology; Physical medicine and rehabilitation; Psychiatry","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":[0.01662469,0.002331249,0.002248923,0.001668162,0.004693235,0.002461689,0.002753492,0.002502057,0.02795556],"category_scores_gemma":[0.02276248,0.002192025,0.001344389,0.002323371,0.001986891,0.001823869,0.002129437,0.004376106,0.0121542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002520357,"about_ca_system_score_gemma":0.01140306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004231188,"about_ca_topic_score_gemma":0.008559273,"domain_scores_codex":[0.9959669,0.001976653,0.0007209759,0.0005300821,0.0005181982,0.0002872283],"domain_scores_gemma":[0.9926778,0.001390143,0.0007519525,0.001346376,0.003085941,0.0007478268],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.15992,0.02797168,0.03906208,0.02673458,0.00159057,0.004058661,0.009504693,0.007588044,0.02407728,0.04907238,0.3240709,0.3263491],"study_design_scores_gemma":[0.06612295,0.02504465,0.1186737,0.01391765,0.00220722,0.00446183,0.002804371,0.005985742,0.00930428,0.035959,0.7147447,0.0007740519],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"protocol","genre_gemma":"methods","genre_scores_codex":[0.02402591,0.002239236,0.02913531,0.001340632,0.0008608261,0.9145066,0.01739606,0.0005168127,0.009978645],"genre_scores_gemma":[0.007295337,0.0006865152,0.01568555,0.0004305047,0.0001759292,0.9702588,0.004301598,0.00005391281,0.001111976],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02795556,"threshold_uncertainty_score":0.0935207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06214190428429176,"score_gpt":0.3172561209140876,"score_spread":0.2551142166297958,"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."}}