{"id":"W2035254077","doi":"10.1038/srep06166","title":"Personalized Metabolomics for Predicting Glucose Tolerance Changes in Sedentary Women After High-Intensity Interval Training","year":2014,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Genomics Institute; Ontario Genomics","keywords":"Cardiorespiratory fitness; Medicine; Interval training; High-intensity interval training; Metabolomics; Internal medicine; Metabolic equivalent; Overweight; Endocrinology; Diabetes mellitus; Impaired glucose tolerance; Type 2 diabetes; Body mass index; Bioinformatics; Physical therapy; Biology; Physical activity","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004767578,0.0003969704,0.0003343978,0.0004764217,0.0001308942,0.0003618413,0.0001338339,0.0002995752,0.0005074704],"category_scores_gemma":[0.0009260022,0.0001232495,0.0002437543,0.0004096225,0.00008791072,0.0001288609,0.0001773793,0.0002669903,0.0001590439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001035586,"about_ca_system_score_gemma":0.0001753278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001672609,"about_ca_topic_score_gemma":0.002787408,"domain_scores_codex":[0.9998821,0.00005383706,0.000006050993,0.00002896151,0.00001825176,0.00001072121],"domain_scores_gemma":[0.9998292,0.00008071959,0.00003995742,0.00001607484,0.0000171936,0.00001693351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003605504,0.0005869148,0.8354036,0.0001176059,0.000510296,0.0001559406,0.0001759035,0.006053813,0.0660335,0.0001285894,0.0005199582,0.08670841],"study_design_scores_gemma":[0.00004904495,0.001171581,0.9414617,0.00001566454,0.0003155437,0.0002242817,0.0001400108,0.04758175,0.008337479,0.0002541691,0.0004281559,0.00002061883],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9882641,0.0005538271,0.009947742,0.00007085985,0.00001102862,0.00004319564,0.0005409621,0.000120072,0.0004483168],"genre_scores_gemma":[0.9935973,0.0001936162,0.005477607,0.00003433193,0.00001138099,0.00004274309,0.0003394956,0.00000821057,0.0002953084],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001672609,"threshold_uncertainty_score":0.00332576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01267193375816184,"score_gpt":0.2370921550457889,"score_spread":0.2244202212876271,"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."}}