{"id":"W4388624449","doi":"10.1016/j.addr.2023.115142","title":"Engineered organoids for biomedical applications","year":2023,"lang":"en","type":"review","venue":"Advanced Drug Delivery Reviews","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":50,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"National Institutes of Health; Ministry of Science and ICT, South Korea; Nuclear Safety and Security Commission; Iran Telecommunication Research Center; Institute for Information and Communications Technology Promotion; Korea University; National Cancer Institute; National Research Foundation; National Heart, Lung, and Blood Institute; National Research Foundation of Korea; Korea University Guro Hospital; National Aeronautics and Space Administration","keywords":"Organoid; Personalized medicine; Drug discovery; Computer science; Regenerative medicine; Drug development; Precision medicine; Computational biology; Stem cell; Bioinformatics; Medicine; Biology; Drug; Neuroscience; Pathology; Cell biology; Pharmacology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0007032573,0.001326181,0.001553341,0.002764226,0.000207372,0.001322562,0.0007110826,0.001153823,0.006165137],"category_scores_gemma":[0.0005947792,0.0004524707,0.0006549637,0.002342606,0.0004257579,0.001335529,0.0008596265,0.001673976,0.003203199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005960717,"about_ca_system_score_gemma":0.0007552336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000930422,"about_ca_topic_score_gemma":0.001938156,"domain_scores_codex":[0.9997367,0.00003532055,0.00002856301,0.00003756284,0.0001306475,0.00003119669],"domain_scores_gemma":[0.9997844,0.0001161891,0.0000376496,0.000008540869,0.00003910763,0.00001415804],"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":[0.00008228236,0.0001081377,0.00004651042,0.01955835,0.00006697878,0.0001675596,0.00004535231,0.0007382717,0.01812208,0.004631324,0.01717437,0.9392588],"study_design_scores_gemma":[0.00003565826,0.0001493392,0.0003458275,0.003845077,0.0001506275,0.0006741943,0.00004165824,0.0002717531,0.006916299,0.001466416,0.9860701,0.00003317404],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003060937,0.9960116,0.0008154715,0.0001124931,0.0003098942,0.00001302271,0.00004392302,0.00001957367,0.002367969],"genre_scores_gemma":[0.001428514,0.9949288,0.0007885315,0.0001649977,0.0001122152,0.00001877251,0.0000665367,0.000005996555,0.002485651],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.006165137,"threshold_uncertainty_score":0.02062446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07115449051281655,"score_gpt":0.3734480775722105,"score_spread":0.302293587059394,"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."}}