{"id":"W4415719597","doi":"10.3390/diagnostics15212755","title":"Leveraging Explainable Automated Machine Learning (AutoML) and Metabolomics for Robust Diagnosis and Pathophysiological Insights in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)","year":2025,"lang":"en","type":"article","venue":"Diagnostics","topic":"Fibromyalgia and Chronic Fatigue Syndrome Research","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"Princess Nourah Bint Abdulrahman University","keywords":"Metabolomics; Feature selection; Disease; Univariate; Interpretability; Precision medicine; Feature (linguistics); Computational model","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":[0.002224461,0.0008897896,0.0004903637,0.0009558238,0.0002993536,0.0008646774,0.0005615986,0.000558457,0.0007482992],"category_scores_gemma":[0.0029993,0.0002097263,0.0009637874,0.0005096049,0.0004690319,0.0007778599,0.001074402,0.0007904966,0.0003300338],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006226031,"about_ca_system_score_gemma":0.001032395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002679924,"about_ca_topic_score_gemma":0.004300076,"domain_scores_codex":[0.999358,0.0002790771,0.00002820066,0.0001830419,0.00009976057,0.00005199192],"domain_scores_gemma":[0.998849,0.0006713367,0.0001402241,0.0001517057,0.0001489385,0.00003873628],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004194663,0.0004858606,0.04156191,0.0004019623,0.0006123529,0.0003182467,0.0001468586,0.5873436,0.02031248,0.003083954,0.002834231,0.342479],"study_design_scores_gemma":[0.00001398465,0.0001185963,0.003901785,0.00001248724,0.00003391019,0.00004634541,0.00001482082,0.9898145,0.002485552,0.002840421,0.0007018283,0.00001575042],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4237256,0.002250975,0.5641442,0.001272159,0.00009004719,0.0001567391,0.001388031,0.004068546,0.002903703],"genre_scores_gemma":[0.9142302,0.0003151638,0.08302952,0.0002858731,0.00006832264,0.00008724543,0.001319049,0.00008164129,0.0005829061],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002679924,"threshold_uncertainty_score":0.01176423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02992420798899891,"score_gpt":0.2958085978829846,"score_spread":0.2658843898939857,"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."}}