{"id":"W2096882143","doi":"10.1186/1743-7075-9-40","title":"Nutritional regulation of muscle protein synthesis with resistance exercise: strategies to enhance anabolism","year":2012,"lang":"en","type":"article","venue":"Nutrition & Metabolism","topic":"Muscle metabolism and nutrition","field":"Biochemistry, Genetics and Molecular Biology","cited_by":178,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Anabolism; Clinical nutrition; Muscle protein; Resistance training; Sarcopenia; Sports nutrition; Medicine; Internal medicine; Endocrinology; Physiology; Skeletal muscle; Physical therapy; Athletes","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003634759,0.0002760921,0.0003823732,0.0001990665,0.0001317769,0.00004246091,0.0002129931,0.0002011234,0.00008163736],"category_scores_gemma":[0.00007090886,0.0002700423,0.0001253473,0.0003677913,0.0001188927,0.0001100012,0.00004760653,0.0001042383,0.00001574471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001438932,"about_ca_system_score_gemma":0.00006339041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001704146,"about_ca_topic_score_gemma":0.00001442144,"domain_scores_codex":[0.9980958,0.0001498096,0.0004227185,0.0004384982,0.0004486993,0.0004445058],"domain_scores_gemma":[0.998707,0.00001896549,0.0002114881,0.0004945928,0.0003557611,0.0002121975],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008459526,0.0007149448,0.00004168028,0.000313804,0.00003113112,5.395284e-7,0.00008934474,0.000008184422,0.9786147,0.01247213,0.003213941,0.00365363],"study_design_scores_gemma":[0.0008456789,0.00004933645,0.04160562,0.0003605927,0.00007660961,0.000003058941,0.0001623585,0.000001192581,0.8141165,0.001848818,0.1406003,0.0003299696],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9728158,0.01986302,0.004283399,0.000515016,0.0002228162,0.001248868,0.0002670373,0.00004631205,0.0007376972],"genre_scores_gemma":[0.9763551,0.001167401,0.0194604,0.0001071689,0.001369751,0.0009744215,0.0002328004,0.00004529397,0.0002876041],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1644982,"threshold_uncertainty_score":0.9999752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007602412692716981,"score_gpt":0.2446933923081866,"score_spread":0.2370909796154697,"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."}}