{"id":"W4311326009","doi":"10.18632/aging.204435","title":"Single nuclei profiling identifies cell specific markers of skeletal muscle aging, frailty, and senescence","year":2022,"lang":"en","type":"article","venue":"Aging","topic":"Nutrition and Health in Aging","field":"Medicine","cited_by":101,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"National Institute on Aging; National Cancer Institute; National Institutes of Health; Astellas Foundation for Research on Metabolic Disorders; Canadian Institutes of Health Research; Astellas Pharma","keywords":"Sarcopenia; Skeletal muscle; Transcriptome; Senescence; Biology; Gene expression profiling; Gene expression; Population; Gene; Bioinformatics; Cell biology; Medicine; Genetics; Endocrinology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002449004,0.0002107643,0.0003162297,0.0005989675,0.0002592564,0.0006012961,0.0001665527,0.0003019183,0.00165431],"category_scores_gemma":[0.0002967655,0.0001168446,0.0001858814,0.0002447858,0.0002350417,0.0003146341,0.0003498097,0.0002813361,0.0007223971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002098065,"about_ca_system_score_gemma":0.0002187356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001194717,"about_ca_topic_score_gemma":0.004297373,"domain_scores_codex":[0.9998631,0.00001121383,0.00001083959,0.00005980895,0.00003563598,0.00001932013],"domain_scores_gemma":[0.9997943,0.00002983734,0.00004201255,0.00002148673,0.00007598152,0.00003638294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000152935,0.00001622324,0.0103436,0.00005711898,0.00001425533,0.00005096164,0.0001112857,0.00007923828,0.9825907,0.0001856626,0.0001558597,0.006242105],"study_design_scores_gemma":[0.0000405737,0.0008769572,0.4750966,0.00008357759,0.0001211741,0.002214187,0.0009671331,0.004885247,0.4981109,0.001386462,0.01616663,0.00005061644],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.961028,0.004573072,0.02583969,0.0002734874,0.0001031696,0.00007049346,0.002622444,0.00018932,0.00530032],"genre_scores_gemma":[0.9807795,0.001917417,0.009705647,0.0001852485,0.00004649188,0.0001056931,0.001737848,0.00004730795,0.005474776],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00165431,"threshold_uncertainty_score":0.005534172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03935164596638335,"score_gpt":0.2938969969305609,"score_spread":0.2545453509641776,"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."}}