{"id":"W2096840621","doi":"10.1186/1743-7075-8-68","title":"Skeletal muscle protein metabolism in the elderly: Interventions to counteract the 'anabolic resistance' of ageing","year":2011,"lang":"en","type":"article","venue":"Nutrition & Metabolism","topic":"Muscle metabolism and nutrition","field":"Biochemistry, Genetics and Molecular Biology","cited_by":553,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Sarcopenia; Anabolism; Ageing; Wasting; Leucine; Protein metabolism; Amino acid; Protein catabolism; Clinical nutrition; Skeletal muscle; Endocrinology; Internal medicine; Catabolism; Basal (medicine); Medicine; Ingestion; Muscle protein; Biology; Metabolism; Biochemistry; 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":[0.0003502901,0.0004668734,0.0005366016,0.0003263717,0.0002119284,0.0002572955,0.0002574867,0.0007661146,0.001216212],"category_scores_gemma":[0.000505286,0.00008957823,0.0003901186,0.0001875499,0.0001374787,0.0002799885,0.0003104137,0.0004291946,0.0003291006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001227489,"about_ca_system_score_gemma":0.0002660121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008168587,"about_ca_topic_score_gemma":0.001773821,"domain_scores_codex":[0.9999119,0.00003360284,0.00001029986,0.00001202089,0.00001687818,0.00001530424],"domain_scores_gemma":[0.9999192,0.00001432604,0.00002487541,0.000002943433,0.0000172467,0.00002138567],"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":[0.01188684,0.00908078,0.007085607,0.01261152,0.0008910778,0.0006825354,0.0006073202,0.0005875614,0.0401624,0.0006282458,0.008210074,0.907566],"study_design_scores_gemma":[0.01607847,0.1580739,0.5376056,0.01584896,0.006907792,0.004017009,0.001691893,0.002991523,0.01954119,0.004662653,0.2324267,0.0001544055],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5513961,0.4325071,0.002309349,0.005677535,0.001211413,0.0004443856,0.0002103853,0.0001880576,0.006055592],"genre_scores_gemma":[0.7605101,0.2178976,0.009108099,0.004667307,0.001840598,0.0006330537,0.0002563045,0.0000190537,0.005067872],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001216212,"threshold_uncertainty_score":0.004068613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02543646204648186,"score_gpt":0.2721134575355387,"score_spread":0.2466769954890568,"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."}}