{"id":"W2800955969","doi":"10.1371/journal.pone.0195733","title":"Monitoring for myelopathic progression with multiparametric quantitative MRI","year":2018,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Cervical and Thoracic Myelopathy","field":"Medicine","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; University of Toronto","funders":"","keywords":"Medicine; Multiparametric MRI; Grey matter; Myelopathy; Atrophy; Magnetic resonance imaging; Fractional anisotropy; Nuclear medicine; Diffusion MRI; Radiology; Internal medicine; White matter; Spinal cord","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":[0.0002075802,0.0001277113,0.0002956474,0.0001279708,0.000114796,0.00001589598,0.00006366005,0.00007416907,0.00004737611],"category_scores_gemma":[0.0004301977,0.00008649609,0.00003885633,0.0004659354,0.0001024672,0.00006530357,0.00003119346,0.0001483945,0.0001162379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003823334,"about_ca_system_score_gemma":0.00005061141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006568694,"about_ca_topic_score_gemma":0.000002491411,"domain_scores_codex":[0.9988924,0.00002361695,0.0001722565,0.0002743177,0.0003811998,0.0002562192],"domain_scores_gemma":[0.9989442,0.000176116,0.00007587868,0.0002059463,0.0004469504,0.0001508996],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.01134646,0.009569203,0.4620148,0.003218493,0.001056525,0.00009816179,0.004419247,0.000001384801,0.09739296,0.0007697214,0.00004298763,0.4100701],"study_design_scores_gemma":[0.005213584,0.01560792,0.1633476,0.006879594,0.001039358,0.00002483191,0.000726785,0.008395833,0.7967557,0.0006666196,0.0007653219,0.000576814],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939643,0.0004642042,0.002671593,0.0006139419,0.00006613187,0.0009954971,0.000005286,0.0001195328,0.00109949],"genre_scores_gemma":[0.8464354,0.00004400336,0.1524194,0.00005812139,0.000513157,0.00009576412,0.000007082311,0.00002617684,0.0004008842],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6993628,"threshold_uncertainty_score":0.3527208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1058762956699832,"score_gpt":0.346508811264407,"score_spread":0.2406325155944238,"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."}}