{"id":"W2757145102","doi":"10.3389/fnut.2017.00049","title":"Carbohydrate-Restriction with High-Intensity Interval Training: An Optimal Combination for Treating Metabolic Diseases?","year":2017,"lang":"en","type":"article","venue":"Frontiers in Nutrition","topic":"Diet and metabolism studies","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Postprandial; Cardiorespiratory fitness; Medicine; High-intensity interval training; Interval training; Carbohydrate; Internal medicine; Physical therapy; Endocrinology; Insulin","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":[0.001047003,0.0006137452,0.001885095,0.0008146131,0.0002364866,0.001000726,0.0007054822,0.0009504628,0.0038337],"category_scores_gemma":[0.0009931433,0.0001577903,0.0007916405,0.0005955157,0.0003981442,0.001181133,0.0005391825,0.001622048,0.0007138157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001623441,"about_ca_system_score_gemma":0.000580296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003146041,"about_ca_topic_score_gemma":0.001260883,"domain_scores_codex":[0.9995832,0.0001428351,0.00005988939,0.0000712333,0.00009161812,0.0000511341],"domain_scores_gemma":[0.9997074,0.00007391413,0.00008351369,0.00002171781,0.00003096364,0.00008244914],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.01264894,0.007237896,0.00558895,0.009104167,0.001528057,0.0003013477,0.0001091819,0.0006824496,0.01091922,0.002639699,0.008336291,0.9409039],"study_design_scores_gemma":[0.04435089,0.1368723,0.2257012,0.04524645,0.02022621,0.006414572,0.003107563,0.008482308,0.0237517,0.0656685,0.4194685,0.0007097945],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1864816,0.7240004,0.01323341,0.05478481,0.004681916,0.0008336726,0.0005590563,0.0002278115,0.01519739],"genre_scores_gemma":[0.4752242,0.4470721,0.04698141,0.01650781,0.008841658,0.001060726,0.0005702885,0.00008357689,0.003658283],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0038337,"threshold_uncertainty_score":0.01282501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02370771814313586,"score_gpt":0.2778872596603666,"score_spread":0.2541795415172308,"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."}}