{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01371243,0.001166035,0.001288613,0.002819526,0.0004924771,0.002469141,0.00145003,0.001014491,0.0008229276],"category_scores_gemma":[0.03606373,0.0002602666,0.001177011,0.001346142,0.0005907,0.001036158,0.001358633,0.002197139,0.0004124172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007135859,"about_ca_system_score_gemma":0.0008866353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006806171,"about_ca_topic_score_gemma":0.005434874,"domain_scores_codex":[0.9952237,0.002335461,0.0004947499,0.001137471,0.0005804166,0.0002282965],"domain_scores_gemma":[0.9856866,0.008627194,0.001851008,0.001204713,0.002224922,0.0004055914],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003943753,0.0005752577,0.5507021,0.0007424225,0.001187231,0.0005560726,0.001009244,0.09539212,0.01306112,0.003456572,0.006756025,0.3226182],"study_design_scores_gemma":[0.0002551721,0.001756836,0.2257665,0.0008237206,0.0007146164,0.001045139,0.0006823351,0.7327739,0.01263473,0.01406766,0.009248352,0.0002309764],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6314133,0.01225118,0.3458132,0.001853289,0.0005339673,0.0002679749,0.002786962,0.001562727,0.003517569],"genre_scores_gemma":[0.9240201,0.0007332608,0.07177001,0.000360269,0.0001226052,0.0001558321,0.002258941,0.00009482084,0.0004841825],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01371243,"threshold_uncertainty_score":0.07251918,"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."}}