{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001380049,0.0001860708,0.0003386168,0.0001445195,0.0002989159,0.00005608359,0.0004212501,0.00003561305,0.00001626364],"category_scores_gemma":[0.01018954,0.0001158554,0.00007580822,0.0006055037,0.0004458573,0.0002212354,0.000397609,0.0003241496,0.00001367971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005348418,"about_ca_system_score_gemma":0.00006345879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001368779,"about_ca_topic_score_gemma":0.0002089081,"domain_scores_codex":[0.9967074,0.0004242408,0.0004944521,0.0005679145,0.001342271,0.0004636679],"domain_scores_gemma":[0.9980183,0.000867119,0.0001657061,0.0005680535,0.0002625213,0.0001183078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001595796,0.0008976599,0.9253761,0.00006796097,0.000003090215,5.236654e-7,0.0004259011,0.00005930649,0.07216366,9.526635e-7,0.00005586277,0.0007893858],"study_design_scores_gemma":[0.002220475,0.0005400465,0.9888098,0.0001675076,0.00001889673,0.000001031672,0.0002480088,0.005896766,0.001978444,0.00000218653,0.00001307621,0.0001037785],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972391,0.00001344671,0.0008861026,0.0002353472,0.000209377,0.0013148,0.000004313023,0.00001986462,0.00007762686],"genre_scores_gemma":[0.999207,0.00001481213,0.0003094099,0.0002873887,0.00003420742,0.00009944347,0.000001003513,0.00001605723,0.00003074239],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07018522,"threshold_uncertainty_score":0.998148,"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."}}