{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004333699,0.0001063426,0.0002249084,0.000166481,0.000293685,0.00002502778,0.00007726144,0.00002262032,0.0003248506],"category_scores_gemma":[0.00001773306,0.0001193692,0.00005461925,0.0002220015,0.00008362174,0.00008896631,0.0001512198,0.0002721401,0.000005968129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007689365,"about_ca_system_score_gemma":0.00004047485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004835892,"about_ca_topic_score_gemma":0.000001813937,"domain_scores_codex":[0.9987751,0.0000592961,0.0003296104,0.000270525,0.0003016081,0.000263877],"domain_scores_gemma":[0.9994532,0.00006142049,0.000136476,0.0001964147,0.0000491233,0.0001033503],"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":[0.00007646624,0.0004486947,0.07336564,0.002540592,0.00002975284,0.0001887169,0.003204491,0.00001739079,0.8896633,0.0004842285,0.006236406,0.0237443],"study_design_scores_gemma":[0.009957804,0.001206004,0.2213829,0.002290249,0.0002384908,0.0006106814,0.04633664,0.004059704,0.3640043,0.001738917,0.3467635,0.001410717],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903572,0.002565754,0.000184156,0.001519431,0.0003716966,0.0002752394,0.00000858794,0.00008186737,0.004636077],"genre_scores_gemma":[0.9952981,0.0001457001,0.003200052,0.0005139689,0.0001121388,0.0000123805,0.00001527031,0.00002519129,0.0006772139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.525659,"threshold_uncertainty_score":0.4867733,"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."}}