{"id":"W2962733168","doi":"10.3390/diagnostics9030079","title":"Rethinking ME/CFS Diagnostic Reference Intervals via Machine Learning, and the Utility of Activin B for Defining Symptom Severity","year":2019,"lang":"en","type":"article","venue":"Diagnostics","topic":"Fibromyalgia and Chronic Fatigue Syndrome Research","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Judith Jane Mason and Harold Stannett Williams Memorial Foundation","keywords":"Medicine; Biomarker; ACVR2B; Internal medicine; Chronic fatigue syndrome; Creatinine; Group B; Etiology; Cohort; Pathology; Immunology; Gastroenterology; Biology; Transforming growth factor; TGF beta signaling pathway","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001233529,0.0001942179,0.0005587227,0.00007007954,0.0001205899,0.00002778027,0.0001750831,0.0001578969,0.0003295199],"category_scores_gemma":[0.01288995,0.0001366554,0.0001174782,0.0001537992,0.000343535,0.00006945844,0.0002080896,0.0006495304,0.00002719858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004967161,"about_ca_system_score_gemma":0.0001526371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002373336,"about_ca_topic_score_gemma":0.00001264262,"domain_scores_codex":[0.9982823,0.0002320104,0.0003806457,0.0003395805,0.0003954482,0.000370091],"domain_scores_gemma":[0.9848108,0.01431654,0.0001734095,0.000382621,0.000205073,0.0001116009],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001005471,0.0003014751,0.9705649,0.007333402,0.000355546,0.00002440762,0.003795476,0.00000855603,0.00123595,0.004171093,0.001071345,0.01013239],"study_design_scores_gemma":[0.02171343,0.004307556,0.8147717,0.009461881,0.001038894,0.0003336412,0.001061927,0.1057485,0.01783529,0.01883183,0.003896676,0.000998713],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923313,0.003526568,0.0009288141,0.0007542098,0.0001307142,0.001153859,0.0000522198,0.00004567781,0.001076607],"genre_scores_gemma":[0.996877,0.001933658,0.0006793323,0.0000307127,0.00001629334,0.0000626218,0.00009052844,0.0000298474,0.0002800558],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1557932,"threshold_uncertainty_score":0.9954249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02587640149479216,"score_gpt":0.305483866998901,"score_spread":0.2796074655041089,"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."}}