{"id":"W4380569357","doi":"10.1557/s43577-023-00551-2","title":"Recent advances in personalized 3D bioprinted tissue models","year":2023,"lang":"en","type":"article","venue":"MRS Bulletin","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Victoria","funders":"Institute of Neurosciences, Mental Health and Addiction; Materials Research Science and Engineering Center, Harvard University; Canada Research Chairs","keywords":"3D bioprinting; Regenerative medicine; Induced pluripotent stem cell; Biocompatible material; Personalized medicine; Drug discovery; Computer science; Tissue engineering; Nanotechnology; Biomedical engineering; Computational biology; Bioinformatics; Stem cell; Medicine; Materials science; Biology; Cell biology; Embryonic stem cell","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":[0.0009418933,0.0003816543,0.0003424173,0.000891196,0.0001449703,0.001310646,0.0005567715,0.0007103734,0.002534162],"category_scores_gemma":[0.0008929227,0.0003799484,0.0004405443,0.0007952152,0.0006170892,0.001026639,0.0006900511,0.0008940456,0.001025221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004662541,"about_ca_system_score_gemma":0.0002997806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004640245,"about_ca_topic_score_gemma":0.0006541851,"domain_scores_codex":[0.9995913,0.00008627548,0.00003380404,0.00006689799,0.0001955769,0.00002614257],"domain_scores_gemma":[0.9994129,0.0002975318,0.0000654635,0.00008354436,0.0001043162,0.00003623763],"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":[0.0001820108,0.0001144556,0.001013655,0.002903783,0.00006990092,0.0007227063,0.0004512028,0.0128186,0.1785258,0.03202202,0.01196767,0.7592083],"study_design_scores_gemma":[0.00001971682,0.0003495656,0.0022315,0.0004850151,0.0001059538,0.005017839,0.0001520118,0.02177128,0.1612808,0.009829536,0.7986554,0.0001014484],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.04656437,0.6054769,0.2863143,0.006238721,0.001230658,0.00009506582,0.0004567888,0.00163409,0.05198917],"genre_scores_gemma":[0.2032026,0.6009141,0.1727241,0.002531283,0.0009948132,0.0001454963,0.0007943302,0.0003204698,0.01837287],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002534162,"threshold_uncertainty_score":0.008477569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02609773283790226,"score_gpt":0.2973351319899182,"score_spread":0.2712373991520159,"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."}}