{"id":"W4412651079","doi":"10.1016/j.mtbio.2025.102111","title":"A dermis-on-a-chip model for compound screening","year":2025,"lang":"en","type":"article","venue":"Materials Today Bio","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto General Hospital; University of Toronto; University Health Network; Canada Research Chairs","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canada Foundation for Innovation; Ontario Research Foundation","keywords":"Chip; Dermis; Computer science; Medicine; Pathology; Telecommunications","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":[0.0004775025,0.0001428685,0.0002083221,0.0001416979,0.0000866535,0.0001218612,0.0002627285,0.0001196001,0.0001127007],"category_scores_gemma":[0.0001862409,0.0001328864,0.00004435802,0.0001259795,0.00005269375,0.00003513283,0.00008145561,0.00008895757,0.00005459049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005061633,"about_ca_system_score_gemma":0.00003199593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001040302,"about_ca_topic_score_gemma":0.000002187121,"domain_scores_codex":[0.9989708,0.00002369598,0.0002522962,0.0001977861,0.0001746035,0.0003808073],"domain_scores_gemma":[0.9994246,0.0001931656,0.00001680257,0.0002548165,0.00003604414,0.00007458599],"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":[0.0001499568,0.00005556383,0.0001169198,0.0009243613,0.00013222,0.000008115119,0.0001342691,0.01420415,0.9270135,0.006891244,0.03507756,0.01529216],"study_design_scores_gemma":[0.0007672134,0.00003448135,0.0005067528,0.0002722115,0.00001498534,0.000001541176,0.00001090712,0.3384363,0.6367729,0.004600105,0.01831786,0.0002647303],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7435959,0.00009517563,0.246424,0.0008151753,0.001094908,0.0006094349,0.000123416,0.0005925123,0.00664951],"genre_scores_gemma":[0.9873325,0.0000141542,0.01089829,0.0002178223,0.0001273457,0.0001017963,0.00003088834,0.00003361559,0.001243621],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3242321,"threshold_uncertainty_score":0.541895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03773374683650549,"score_gpt":0.3088644523219961,"score_spread":0.2711307054854906,"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."}}