{"id":"W3164042698","doi":"10.1002/jbm.a.37239","title":"Promoting endogenous repair of skeletal muscle using regenerative biomaterials","year":2021,"lang":"en","type":"review","venue":"Journal of Biomedical Materials Research Part A","topic":"Tissue Engineering and Regenerative Medicine","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Institute of Musculoskeletal Health and Arthritis; Canadian Institutes of Health Research","keywords":"Regeneration (biology); Biomaterial; Skeletal muscle; Tissue engineering; Materials science; Regenerative medicine; Biomedical engineering; In vivo; Structural integrity; Cell biology; Nanotechnology; Stem cell; Biology; Medicine; Anatomy; Engineering; Biotechnology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.007745042,0.0005037516,0.005212768,0.0012814,0.0001420482,0.00005998321,0.0003451722,0.0006107339,0.0008750805],"category_scores_gemma":[0.003509189,0.000312979,0.0008606867,0.001167411,0.0008224507,0.0000824597,0.0002657571,0.0006703185,0.00001328083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003504289,"about_ca_system_score_gemma":0.002583418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002572685,"about_ca_topic_score_gemma":2.762623e-7,"domain_scores_codex":[0.9911118,0.002282611,0.003165638,0.0004586652,0.002202223,0.0007790633],"domain_scores_gemma":[0.9954888,0.0004893353,0.001378776,0.0005259727,0.001411137,0.0007059828],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004432424,0.0006974222,4.400299e-7,0.04364124,0.001673431,0.005125166,0.0004918582,3.398127e-7,0.8047638,0.0000560906,0.002435962,0.1410699],"study_design_scores_gemma":[0.0008572652,0.002078544,0.000001155148,0.08297386,0.0009977801,0.006817051,0.0001076903,0.000009279518,0.05169745,0.000005128836,0.8542073,0.0002474981],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01885801,0.9772862,0.00009118716,0.0001090136,0.002537237,0.0009083652,0.0001642843,0.00003198212,0.00001376814],"genre_scores_gemma":[0.001059903,0.9865655,0.00420919,0.000004635113,0.007532596,0.00003173523,0.0001691679,0.0001217223,0.0003056024],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8517714,"threshold_uncertainty_score":0.9999322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2646562019684454,"score_gpt":0.4565923165811251,"score_spread":0.1919361146126797,"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."}}