{"id":"W4405391434","doi":"10.1093/braincomms/fcae434","title":"A data-driven model of disability progression in progressive 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":"McGill University","funders":"NextGenerationEU; Genentech; National Multiple Sclerosis Society; MedDay Pharmaceuticals; Ministero della Salute; Teva Pharmaceutical Industries; Ministerio de Ciencia e Innovación; International Progressive MS Alliance; Istituto Nazionale di Alta Matematica \"Francesco Severi\"; Instituto de Salud Carlos III; Gruppo Nazionale per il Calcolo Scientifico; Biogen","keywords":"Multiple sclerosis; Medicine; Physical medicine and rehabilitation; Data science; Psychology; Neuroscience; Computer science; Psychiatry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007380042,0.0001331793,0.0003084789,0.0001299527,0.0001271922,0.00003299992,0.001060398,0.00007226008,0.000023721],"category_scores_gemma":[0.002578855,0.0001077851,0.00007642722,0.0005756717,0.001017621,0.0002255375,0.002168263,0.0004204994,0.00001234084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001770179,"about_ca_system_score_gemma":0.0002138469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001061843,"about_ca_topic_score_gemma":0.0008275105,"domain_scores_codex":[0.9983162,0.0002333076,0.0004498155,0.000380144,0.0003719399,0.0002485814],"domain_scores_gemma":[0.9943664,0.001549902,0.00006704694,0.003776362,0.0001410936,0.00009917382],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004207027,0.007398494,0.2508255,0.002744786,0.0005792672,0.0000107978,0.008336132,0.001273204,0.1026769,0.003401865,0.02202526,0.6003071],"study_design_scores_gemma":[0.0007418707,0.00006823648,0.08392421,0.001823695,0.00003113549,0.000001880616,0.0002989267,0.9100849,0.0003505396,0.0001200048,0.0024503,0.0001042844],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7971345,0.0248895,0.00279492,0.1582738,0.0001247499,0.008049012,0.003414311,0.0007401569,0.004579148],"genre_scores_gemma":[0.9643424,0.001143462,0.03341805,0.00005752227,0.00002276918,0.0004670349,0.0004530767,0.00002361319,0.00007208725],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9088117,"threshold_uncertainty_score":0.4395349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3440879764444563,"score_gpt":0.45017590301681,"score_spread":0.1060879265723537,"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."}}