{"id":"W4210686526","doi":"10.1002/jcsm.12903","title":"MicroRNA regulatory networks associated with abnormal muscle repair in survivors of critical illness","year":2022,"lang":"en","type":"article","venue":"Journal of Cachexia Sarcopenia and Muscle","topic":"Muscle Physiology and Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Canada Research Chairs; University Health Network; University of Toronto; St. Michael's Hospital","funders":"Canadian Institutes of Health Research; University of Alberta; Physicians' Services Incorporated Foundation; Canadian Thoracic Society","keywords":"Transcriptome; Wasting; microRNA; Muscle atrophy; Muscle weakness; Sarcopenia; Biology; Weakness; C2C12; Skeletal muscle; Gene expression; Internal medicine; Bioinformatics; Medicine; Gene; Endocrinology; Genetics; Anatomy; Myogenesis","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":[0.000738658,0.0001334288,0.0003013293,0.00008438858,0.0001302623,0.000005716291,0.0001814052,0.0001084655,0.00005907768],"category_scores_gemma":[0.0001951446,0.0001200144,0.0001211778,0.0001622501,0.0002303259,0.00001532483,0.000147039,0.0003034324,1.169544e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002271102,"about_ca_system_score_gemma":0.0001398366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007114519,"about_ca_topic_score_gemma":0.000189989,"domain_scores_codex":[0.9986891,0.0002873108,0.0004021791,0.0001932565,0.0001850179,0.0002431357],"domain_scores_gemma":[0.9992599,0.0001003181,0.000248675,0.0001757399,0.0001220341,0.00009325574],"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":[0.01027548,0.004240802,0.2036179,0.0003224464,0.0009592653,0.0003913846,0.002959257,0.03196234,0.7126034,0.0009571221,0.009173047,0.0225375],"study_design_scores_gemma":[0.00420438,0.002742153,0.975723,0.00008125183,0.0001212872,0.0001056809,0.002142314,0.0006168648,0.004948177,0.000297379,0.008521564,0.0004959879],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974031,0.001874115,0.0001369406,0.0001668738,0.0001538,0.00008692876,0.00002240997,0.000004433355,0.0001514276],"genre_scores_gemma":[0.9993752,0.00008938152,0.0001470422,0.0002481865,0.00006068185,0.00000692407,0.00001924612,0.0000181993,0.00003516582],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.772105,"threshold_uncertainty_score":0.4894047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006040797321139185,"score_gpt":0.2276659498484133,"score_spread":0.2216251525272741,"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."}}