{"id":"W3202203893","doi":"10.1002/adfm.202106548","title":"MEndR: An In Vitro Functional Assay to Predict In Vivo Muscle Stem Cell‐Mediated Repair","year":2021,"lang":"en","type":"article","venue":"Advanced Functional Materials","topic":"Muscle Physiology and Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Michael's Hospital; University of Toronto","funders":"University of Toronto; Ontario Institute for Regenerative Medicine; Connaught Fund; Stem Cell Network; Canada First Research Excellence Fund; Government of Ontario","keywords":"In vivo; Stem cell; Cell biology; Regeneration (biology); Regenerative medicine; Scaffold; In vitro; Mesenchymal stem cell; Myocyte; Biology; Tissue engineering; Skeletal muscle; Biomedical engineering; Materials science; Anatomy; Medicine; Biochemistry; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001330542,0.001285759,0.0006306334,0.001305306,0.0002866963,0.0007337491,0.000654507,0.0007636917,0.00298868],"category_scores_gemma":[0.0009396556,0.0004848089,0.0005298445,0.0003521498,0.0003810027,0.0004500315,0.0005337475,0.0007521466,0.001332218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004496846,"about_ca_system_score_gemma":0.0003444804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004231439,"about_ca_topic_score_gemma":0.0008000828,"domain_scores_codex":[0.9987724,0.0002269033,0.0001166815,0.0002259347,0.0005888113,0.00006924617],"domain_scores_gemma":[0.9989861,0.0003204031,0.0002848091,0.0001756893,0.0001458682,0.00008702414],"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":[0.00003362985,0.00002927851,0.0003147892,0.00004715172,0.000008482458,0.00002128524,0.000009385886,0.0002324602,0.9965262,0.0001079692,0.00005919551,0.002610286],"study_design_scores_gemma":[0.000003462346,0.0001508794,0.001690743,0.000007564061,0.00001282517,0.0001177636,0.000007718856,0.003339611,0.9935062,0.00005244439,0.001100148,0.00001071643],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4774604,0.003780866,0.5017072,0.0001866012,0.0002316284,0.0004666772,0.003160222,0.005603754,0.007402595],"genre_scores_gemma":[0.6396765,0.002160565,0.344568,0.0001258701,0.00005238622,0.0008581791,0.002883234,0.0005099481,0.00916538],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00298868,"threshold_uncertainty_score":0.009998083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009285657223405243,"score_gpt":0.2249906839392825,"score_spread":0.2157050267158772,"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."}}