{"id":"W3091967282","doi":"10.1017/s0029665120007892","title":"Nutrient-dense protein as a primary dietary strategy in healthy ageing: please sir, may we have more?","year":2020,"lang":"en","type":"review","venue":"Proceedings of The Nutrition Society","topic":"Muscle metabolism and nutrition","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"National Research Foundation of Korea; Conselho Nacional de Desenvolvimento Científico e Tecnológico; National Research Foundation","keywords":"Ingestion; Ageing; Skeletal muscle; Muscle mass; Sarcopenia; Muscle protein; Medicine; Dietary protein; Gerontology; Nutrient; Physiology; Biology; Endocrinology; Internal medicine","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":[0.0009018415,0.0005834681,0.001243062,0.001042999,0.0002550925,0.001143148,0.0008158187,0.001934257,0.003141181],"category_scores_gemma":[0.001641525,0.0001581725,0.000545385,0.00110992,0.0005027051,0.002027238,0.000638851,0.003048645,0.001791828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004375529,"about_ca_system_score_gemma":0.0008599116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001052449,"about_ca_topic_score_gemma":0.001692142,"domain_scores_codex":[0.9997453,0.00006660704,0.00004255855,0.00003856243,0.00008472888,0.00002219979],"domain_scores_gemma":[0.999432,0.0002533587,0.00006473886,0.0000114803,0.0001810908,0.00005730241],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000304414,0.00007038384,0.0002597774,0.02656296,0.0002024849,0.0002024955,0.0001079623,0.00008865765,0.0008486774,0.002896878,0.1577742,0.8106812],"study_design_scores_gemma":[0.00003461391,0.0001261963,0.0009525404,0.00781643,0.0001418138,0.0009139379,0.0001089906,0.00004286988,0.0001910354,0.001718281,0.9879346,0.00001882832],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0000683985,0.9953445,0.00003863934,0.002470539,0.001769545,0.000002062515,0.000009187024,0.000003617549,0.0002935636],"genre_scores_gemma":[0.0003810907,0.9953679,0.00008935472,0.001980659,0.001382638,0.000004524126,0.00001676252,0.000001848576,0.0007752278],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003141181,"threshold_uncertainty_score":0.01050836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03465948998415853,"score_gpt":0.3064208681804805,"score_spread":0.271761378196322,"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."}}