{"id":"W2891865027","doi":"10.1096/fj.201800622rr","title":"Genetic manipulation of CCN2/CTGF unveils cell‐specific ECM‐remodeling effects in injured skeletal muscle","year":2018,"lang":"en","type":"article","venue":"The FASEB Journal","topic":"Connective Tissue Growth Factor Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Institute of Arthritis and Musculoskeletal and Skin Diseases; National Institute of General Medical Sciences; National Heart, Lung, and Blood Institute; National Institutes of Health","keywords":"CTGF; Extracellular matrix; Fibrosis; Connective tissue; Skeletal muscle; Collagen VI; Muscular dystrophy; Myocyte; Matricellular protein; Cell biology; Biology; Regeneration (biology); Pathology; Growth factor; Endocrinology; Medicine; Genetics; Receptor","routes":{"ca_aff":true,"ca_fund":false,"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":[0.000216477,0.0004931166,0.000248826,0.000354895,0.0002583577,0.0002880943,0.0003216671,0.0004751296,0.001549963],"category_scores_gemma":[0.000139538,0.0002240189,0.0003057935,0.0001851562,0.0005509573,0.0002372205,0.0002564205,0.0009087017,0.0005563497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005424018,"about_ca_system_score_gemma":0.0003498863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00229667,"about_ca_topic_score_gemma":0.004013969,"domain_scores_codex":[0.9997537,0.00002923383,0.00004002724,0.00005358669,0.00007294388,0.00005056594],"domain_scores_gemma":[0.9997184,0.00004915506,0.00007180683,0.00003214437,0.00002289503,0.0001055775],"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":[0.00004163691,0.0000136025,0.00004224347,0.00001461048,0.000001695818,0.00001999324,0.000008460109,0.00002330037,0.9996156,0.00005448884,0.00001317234,0.0001512831],"study_design_scores_gemma":[0.00002490337,0.0001642927,0.001919649,0.000009151555,0.00001039879,0.0001250684,0.00002428222,0.0008196762,0.9950253,0.00002514935,0.001846953,0.000005072734],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9919525,0.0008310554,0.003821091,0.0001582356,0.00007566235,0.00006876998,0.0009687858,0.0001490977,0.001974816],"genre_scores_gemma":[0.9871501,0.0005887502,0.00481883,0.0001100028,0.00001824453,0.000122084,0.001185138,0.00009605333,0.005910734],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00229667,"threshold_uncertainty_score":0.005185127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02063330995120247,"score_gpt":0.2767612484431992,"score_spread":0.2561279384919967,"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."}}