{"id":"W2045516163","doi":"10.1186/1471-2202-15-106","title":"White matter lesion filling improves the accuracy of cortical thickness measurements in multiple sclerosis patients: a longitudinal study","year":2014,"lang":"en","type":"article","venue":"BMC Neuroscience","topic":"Multiple Sclerosis Research Studies","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"White matter; Lesion; Voxel; Nuclear medicine; Magnetic resonance imaging; Multiple sclerosis; Neuroimaging; Partial volume; Medicine; Pathology; Radiology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001978894,0.0004326787,0.0004257056,0.0005793949,0.0004242783,0.0007525958,0.00035031,0.0006373579,0.0009902682],"category_scores_gemma":[0.005138743,0.0003586434,0.0004380007,0.0003773414,0.0002857301,0.0006765852,0.0003697766,0.0006758255,0.0003533347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002003244,"about_ca_system_score_gemma":0.0001791931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001695079,"about_ca_topic_score_gemma":0.001458958,"domain_scores_codex":[0.9994954,0.0001536019,0.00005578541,0.0001481964,0.0000919703,0.00005508945],"domain_scores_gemma":[0.9962359,0.0008040128,0.001493665,0.000448358,0.0006737857,0.0003443984],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001645805,0.0002510301,0.9892215,0.0000138003,0.0002081073,0.0001240588,0.0003214146,0.0001767321,0.001768324,0.000007202907,0.00009111395,0.006170776],"study_design_scores_gemma":[0.00001583423,0.0008343295,0.997543,0.000005109331,0.00008824062,0.0002568795,0.00006383396,0.0006035223,0.0004646764,0.00001405189,0.0001043412,0.000006257456],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995967,0.0001097406,0.0001099497,0.00001225097,0.000002865622,0.000005052982,0.00006160203,0.000008338567,0.00009349012],"genre_scores_gemma":[0.9995895,0.00003146748,0.0001356843,0.000006632838,0.000006971004,0.000004572647,0.0001143354,0.000003910014,0.0001068562],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001978894,"threshold_uncertainty_score":0.0104655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2742070209644277,"score_gpt":0.3578230498816828,"score_spread":0.08361602891725517,"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."}}