{"id":"W4318819346","doi":"10.1038/s41467-023-36265-x","title":"Transcriptional reprogramming of skeletal muscle stem cells by the niche environment","year":2023,"lang":"en","type":"article","venue":"Nature Communications","topic":"Muscle Physiology and Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; McGill Genome Centre; Ottawa Hospital; McGill University; Jewish General Hospital","funders":"Lady Davis Institute for Medical Research; Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Jewish General Hospital; Stem Cell Network; Compute Canada; Government of Canada; McGill University","keywords":"Reprogramming; Niche; Stem cell; Cell biology; Skeletal muscle; Biology; Stem cell niche; Computational biology; Genetics; Cell; Progenitor cell; Anatomy; Biochemistry","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":[0.00009298664,0.0001268374,0.0001504732,0.00008693859,0.00005294209,0.0001906229,0.0001102564,0.00008584514,0.0006912829],"category_scores_gemma":[0.0001072637,0.00009127797,0.0001964162,0.0001066068,0.0001240995,0.00008953996,0.0001677621,0.0001326198,0.0001609317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001250677,"about_ca_system_score_gemma":0.0001309589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003475041,"about_ca_topic_score_gemma":0.0007424551,"domain_scores_codex":[0.9999539,0.000006624987,0.000001799247,0.00001604719,0.00001441965,0.000007237032],"domain_scores_gemma":[0.9999731,0.000007180563,0.000008136015,0.000004057955,0.000003065665,0.000004475848],"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":[0.00003946125,0.000007327322,0.0007447859,0.00003163241,0.000005761338,0.00001881553,0.00001290693,0.001659824,0.9923862,0.000344494,0.00002795762,0.004720741],"study_design_scores_gemma":[0.00001473115,0.0002152843,0.0171629,0.00001375094,0.00003390121,0.000127515,0.00004990008,0.04634256,0.9296126,0.0007818224,0.005631361,0.00001378768],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9639766,0.0006715615,0.03320958,0.00003340145,0.00002322403,0.00001022137,0.0003807016,0.0001814635,0.001513252],"genre_scores_gemma":[0.9870235,0.0006819527,0.01032041,0.00002952996,0.000008427218,0.00001650931,0.000431824,0.00005662844,0.001431246],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006912829,"threshold_uncertainty_score":0.002312601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01517829646730318,"score_gpt":0.2626035547145506,"score_spread":0.2474252582472474,"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."}}