{"id":"W4298144072","doi":"10.3389/fbioe.2022.989888","title":"Engineering diabetic human skin equivalent for in vitro and in vivo applications","year":2022,"lang":"en","type":"article","venue":"Frontiers in Bioengineering and Biotechnology","topic":"Planarian Biology and Electrostimulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Canadian Institutes of Health Research; Réseau de Recherche en Santé Buccodentaire et Osseuse","keywords":"Keratinocyte; Skin equivalent; Diabetic foot; Diabetes mellitus; Basement membrane; Wound healing; Medicine; Fibroblast; In vivo; Human skin; Basal (medicine); Tissue engineering; Laminin; Extracellular matrix; In vitro; Chemistry; Endocrinology; Immunology; Cell biology; Pathology; Biology; Biomedical engineering; Biochemistry","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":[0.0001559041,0.0001011946,0.0001426151,0.0003405908,0.00004717925,0.000004236334,0.00008920406,0.0001986204,8.175286e-7],"category_scores_gemma":[0.00001804226,0.0001205469,0.00001545597,0.0001799861,0.00004270398,0.000002630561,0.00008722694,0.0001783724,4.37895e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004096043,"about_ca_system_score_gemma":0.000008104203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009315012,"about_ca_topic_score_gemma":0.00001216671,"domain_scores_codex":[0.9993011,0.00001307517,0.0001481778,0.0002724924,0.00002359783,0.0002415132],"domain_scores_gemma":[0.9998385,0.000009290396,0.00002180605,0.0001075239,0.000003509762,0.00001942702],"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":[0.00006763978,0.00003181288,0.008045282,0.00003122584,0.00001096917,0.000002122646,0.0000187351,0.00631062,0.9829774,0.0002256447,0.0001601579,0.002118382],"study_design_scores_gemma":[0.003547416,0.0006638883,0.01683888,0.00002969969,0.00001871348,0.00006248424,0.0002276699,0.09574519,0.8032206,0.0009554799,0.07788921,0.0008008006],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9658928,0.001985142,0.03090172,0.000715868,0.00009393795,0.0003460054,0.00003651941,0.00002333805,0.000004681173],"genre_scores_gemma":[0.9966074,0.0001702003,0.002745126,0.00004851165,0.00002079092,0.0002953971,0.00008042892,0.00001077522,0.00002133371],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1797568,"threshold_uncertainty_score":0.4915758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004063750563280038,"score_gpt":0.2022849093525825,"score_spread":0.1982211587893024,"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."}}