{"id":"W2801392121","doi":"10.1016/j.stemcr.2018.04.009","title":"Direct Reprogramming of Mouse Fibroblasts into Functional Skeletal Muscle Progenitors","year":2018,"lang":"en","type":"article","venue":"Stem Cell Reports","topic":"Muscle Physiology and Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":103,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Arthritis and Musculoskeletal and Skin Diseases; National Institute of Diabetes and Digestive and Kidney Diseases; Glenn Foundation for Medical Research; EMBO; National Institute on Aging; Canadian Institutes of Health Research; National Institutes of Health; Muscular Dystrophy Association; Gruss-Lipper Family Foundation; Massachusetts General Hospital; National Institute of General Medical Sciences; National Institute of Environmental Health Sciences; Stem Cell Network","keywords":"Biology; Reprogramming; Skeletal muscle; Progenitor cell; Cell biology; Progenitor; Stem cell; Genetics; Anatomy; Gene","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":[0.0001646755,0.0001288372,0.0001383963,0.00003197668,0.0000930141,0.000006790521,0.00006356461,0.0001355898,0.00005265144],"category_scores_gemma":[0.00002448056,0.0001222893,0.0001239986,0.00007706739,0.0001937487,0.000004423595,0.00009034828,0.00004779344,0.000008891648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006910988,"about_ca_system_score_gemma":0.00007974284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003450269,"about_ca_topic_score_gemma":0.00002709144,"domain_scores_codex":[0.9989197,0.00004098618,0.0002954104,0.0004286847,0.0001201469,0.0001951326],"domain_scores_gemma":[0.9991478,0.000007770336,0.0002129107,0.0004416724,0.0001236286,0.00006616368],"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":[0.00005751183,0.0001015313,0.003066852,0.00004951448,0.00003654698,0.000009176551,0.00006424749,0.00002065001,0.9889112,0.000004952788,0.001719545,0.005958349],"study_design_scores_gemma":[0.0001324238,0.0004677064,0.002533312,0.000008103801,0.00001402039,0.00001874746,0.0001061005,0.000005403469,0.9655058,0.00004558807,0.03101125,0.0001515156],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991797,0.000313001,0.0001912837,0.000007794489,0.0003274569,0.0001608748,0.000001851916,0.00002224564,0.007178455],"genre_scores_gemma":[0.9970859,0.00001037308,0.000303528,0.00002417993,0.0002583329,0.0000241881,0.00006977871,0.00001881334,0.002204956],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02929171,"threshold_uncertainty_score":0.4986813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006988788353651912,"score_gpt":0.2216399984040326,"score_spread":0.2146512100503807,"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."}}