{"id":"W2794400808","doi":"10.1002/adhm.201701405","title":"Toward Immunocompetent 3D Skin Models","year":2018,"lang":"en","type":"review","venue":"Advanced Healthcare Materials","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fiducie de Recherche sur la Foret des Cantons-de-l'Est; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Commonwealth Scientific and Industrial Research Organisation","keywords":"Computer science; Scope (computer science); Induced pluripotent stem cell; Scaffold; Variety (cybernetics); Computational model; Immune system; Human skin; Nanotechnology; Risk analysis (engineering); Biochemical engineering; Biology; Engineering; Artificial intelligence; Immunology; Medicine; Materials science; Embryonic stem cell","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009250745,0.000704064,0.002385722,0.0003021836,0.0001085071,0.0001172005,0.000965394,0.0006888745,0.000413486],"category_scores_gemma":[0.0001253549,0.0006113615,0.000269365,0.0003818014,0.000141181,0.0001618247,0.0003737164,0.0006024506,0.001196049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006378866,"about_ca_system_score_gemma":0.0002972076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008285823,"about_ca_topic_score_gemma":0.000007255528,"domain_scores_codex":[0.9957036,0.0003543377,0.001483714,0.0006638379,0.0006154985,0.001178979],"domain_scores_gemma":[0.997951,0.0002515781,0.0002249207,0.001035283,0.0001661776,0.0003710535],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005467361,0.00001014384,1.29793e-8,0.07362016,0.00009286141,0.00001848516,0.00005978188,0.00002589295,0.00004954648,0.0003736508,0.0003747806,0.9253692],"study_design_scores_gemma":[0.0001358568,0.00006930757,3.558754e-7,0.01654095,0.00004889007,0.00003408542,0.000006936705,0.00005208954,0.0002944406,0.0008833965,0.981379,0.0005546433],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0000290567,0.9924065,0.0007967471,0.00005574353,0.003440951,0.001591878,0.0003606452,0.0007057388,0.0006127605],"genre_scores_gemma":[0.0001289333,0.9897314,0.007754252,0.00004479731,0.0008822237,0.0006998467,0.0003452034,0.0002860905,0.0001272276],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9810042,"threshold_uncertainty_score":0.9996338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1130973445926272,"score_gpt":0.3860809631048159,"score_spread":0.2729836185121887,"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."}}