{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002710334,0.000175675,0.0002147812,0.00007697164,0.00005534141,0.00001306118,0.00007734392,0.0001730885,0.0007352418],"category_scores_gemma":[0.00008655763,0.0001887876,0.00005779001,0.0001748186,0.00003415106,0.00001999306,0.00008818953,0.00007613535,0.00003589075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003619944,"about_ca_system_score_gemma":0.0001358776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001730475,"about_ca_topic_score_gemma":0.00009167855,"domain_scores_codex":[0.9984336,0.0002279828,0.000333217,0.0005736696,0.0001414887,0.0002900573],"domain_scores_gemma":[0.9994186,0.00004505429,0.00006351164,0.0002884193,0.00008699724,0.00009747858],"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":[0.001580043,0.00022841,0.0005186275,0.00001980375,0.00001536406,0.00001069044,0.00001836949,0.003470569,0.9928569,0.00005885867,0.0008962455,0.0003261601],"study_design_scores_gemma":[0.00129298,0.0001918264,0.03962009,0.00001123063,0.000005620412,0.000004785134,0.0001692931,0.0000237442,0.9497548,0.000198232,0.008510558,0.0002168697],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973424,0.0001522865,0.0004178212,0.0001119831,0.0009296844,0.0001923342,0.0002083474,0.00003568553,0.0006094262],"genre_scores_gemma":[0.9960756,0.00004101114,0.0005319041,0.000933375,0.000219191,0.0001696626,0.001413451,0.00002306403,0.0005927092],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04310209,"threshold_uncertainty_score":0.8050382,"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."}}