{"id":"W3048918455","doi":"10.1016/j.neurol.2020.06.008","title":"Alexithymia in multiple sclerosis: Clinical and radiological correlations","year":2020,"lang":"en","type":"article","venue":"Revue Neurologique","topic":"Psychosomatic Disorders and Their Treatments","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Alexithymia; Corpus callosum; Multiple sclerosis; Voxel-based morphometry; White matter; Toronto Alexithymia Scale; Psychology; Atrophy; Depression (economics); Brainstem; Medicine; Magnetic resonance imaging; Internal medicine; Neuroscience; Psychiatry; Radiology","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":[0.0005106864,0.0004591908,0.00041479,0.001795363,0.0004159309,0.0007661351,0.0004040162,0.0008108114,0.003443779],"category_scores_gemma":[0.005193752,0.0003252392,0.0002617123,0.001247089,0.001087872,0.0008018509,0.0005865347,0.0006588491,0.0005219817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002159025,"about_ca_system_score_gemma":0.0003375713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008406526,"about_ca_topic_score_gemma":0.0009636717,"domain_scores_codex":[0.9995721,0.00009396003,0.00008722147,0.0000586288,0.0001344498,0.00005364158],"domain_scores_gemma":[0.9972795,0.001006039,0.001139567,0.0001065716,0.0002047838,0.0002636477],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006875696,0.0001839636,0.9509031,0.0001167012,0.0001267814,0.02831403,0.0002795104,0.0002708511,0.005869099,0.0003069084,0.0003345321,0.0126069],"study_design_scores_gemma":[0.00002744365,0.0002834832,0.9595152,0.0000236351,0.00004816423,0.03850276,0.0002348485,0.000263482,0.0003712807,0.0004014831,0.0003149671,0.00001324182],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.989917,0.003322769,0.0002846131,0.0003125685,0.00004068294,0.00002160082,0.0001333093,0.00001468971,0.005952798],"genre_scores_gemma":[0.9986791,0.0007526143,0.0001317028,0.00003474154,0.00008140997,0.000007233219,0.0000777218,0.000001994182,0.0002334804],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003443779,"threshold_uncertainty_score":0.01152056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1172286461089039,"score_gpt":0.3029406335366312,"score_spread":0.1857119874277273,"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."}}