{"id":"W1594982188","doi":"10.1002/9781444303315.ch5","title":"Skeletal Muscle Metabolic Adaptations to Training","year":2008,"lang":"en","type":"other","venue":"","topic":"Mitochondrial Function and Pathology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Skeletal muscle; Mitochondrial biogenesis; Fatty acid; Endurance training; Biogenesis; Carbohydrate metabolism; Substrate (aquarium); Biochemistry; Training (meteorology); Chemistry; Biology; Mitochondrion; Endocrinology; Ecology; Geography; Gene","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":[0.0001433522,0.0003758328,0.0002809555,0.0004044645,0.000150573,0.0004489494,0.0003835529,0.0004245892,0.03487538],"category_scores_gemma":[0.0001506587,0.0001080733,0.0002768882,0.000427338,0.0001293483,0.0003587019,0.0004754463,0.000607671,0.006640044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002657865,"about_ca_system_score_gemma":0.0002204508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008611841,"about_ca_topic_score_gemma":0.002203869,"domain_scores_codex":[0.9999243,0.000007059604,0.000003924782,0.00002157243,0.00003328085,0.000009840402],"domain_scores_gemma":[0.9999638,0.00000743332,0.000004998502,0.000005056622,0.00001299465,0.000005726778],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000480336,0.000227912,0.0009950193,0.001578292,0.00004238669,0.0003382557,0.0001889035,0.000645264,0.1547694,0.007455681,0.0562834,0.7769951],"study_design_scores_gemma":[0.00006836767,0.0007285892,0.05983844,0.00102178,0.00008883655,0.001011293,0.0002195809,0.0006616328,0.06858046,0.006619696,0.8611189,0.00004252055],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.08602343,0.1611404,0.02625151,0.006981015,0.005648047,0.0003069749,0.006980425,0.002008863,0.7046593],"genre_scores_gemma":[0.1176265,0.1343912,0.01351376,0.002404722,0.001722913,0.0003157615,0.003785581,0.000485432,0.7257542],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03487538,"threshold_uncertainty_score":0.1166698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02703447757634419,"score_gpt":0.2612630997708203,"score_spread":0.2342286221944761,"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."}}