{"id":"W4383092669","doi":"10.1155/2023/9802235","title":"Modelling Skeletal Muscle Ageing and Repair In Vitro","year":2023,"lang":"en","type":"article","venue":"Journal of Tissue Engineering and Regenerative Medicine","topic":"Muscle Physiology and Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Biotechnology and Biological Sciences Research Council; Trent University; Nottingham Trent University","keywords":"Myogenesis; Skeletal muscle; Regeneration (biology); Cell biology; Myocyte; PI3K/AKT/mTOR pathway; Biology; C2C12; Ageing; Signal transduction; Anatomy; Genetics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002463944,0.00008129988,0.0001615213,0.0001053527,0.00002894912,0.000002116031,0.00003213828,0.00005548343,0.000001719606],"category_scores_gemma":[0.00008139868,0.00006213001,0.00002195354,0.00008517861,0.00005047474,0.00000470267,0.00002430286,0.0001099407,2.116241e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003647448,"about_ca_system_score_gemma":0.000009817013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009661377,"about_ca_topic_score_gemma":0.000001476632,"domain_scores_codex":[0.9995372,0.00002316247,0.0001712337,0.000103757,0.00005690531,0.0001077796],"domain_scores_gemma":[0.9997936,0.00002096154,0.0000487641,0.00005312476,0.00002839536,0.00005513741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002722883,0.000006350289,0.00002874358,0.00003475145,0.00002635793,0.00004273432,0.000295858,0.09371728,0.9035222,0.00003081935,0.0004438976,0.001823758],"study_design_scores_gemma":[0.006248868,0.003227234,0.01323595,0.0006563285,0.000112404,0.0003361766,0.001819535,0.5495065,0.3496959,0.0003872656,0.07396977,0.0008041087],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9853241,0.008059993,0.005981784,0.0004191271,0.0001505404,0.00003595404,0.000001210372,0.000007612549,0.00001968327],"genre_scores_gemma":[0.996955,0.001479034,0.0009920796,0.00003178026,0.0003737035,0.000001471865,0.00000728256,0.00000868959,0.0001509364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5538263,"threshold_uncertainty_score":0.2533588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01077343666245912,"score_gpt":0.2473497214505903,"score_spread":0.2365762847881311,"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."}}