{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001299889,0.0007003573,0.002666668,0.0004885,0.0001094361,0.00004765671,0.001149182,0.0004138534,0.000144377],"category_scores_gemma":[0.0007521852,0.0005835761,0.0009047581,0.001922223,0.0001323737,0.0001006299,0.0002199681,0.0007963417,0.008210866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00034648,"about_ca_system_score_gemma":0.0001853362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.986326e-7,"about_ca_topic_score_gemma":0.000001185124,"domain_scores_codex":[0.9962245,0.0001281098,0.001568438,0.0006924752,0.0004505929,0.000935949],"domain_scores_gemma":[0.9966703,0.001518162,0.000188747,0.001054511,0.0001039257,0.0004643575],"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":[6.086352e-7,0.00001722028,1.007585e-8,0.05969639,0.0001039932,0.000002844325,0.000006594937,0.000009359293,0.00001385273,0.00003586026,0.02709362,0.9130197],"study_design_scores_gemma":[0.0001442293,0.00001422168,2.42715e-8,0.01175763,0.0002778861,0.000006622345,0.000001976426,0.0005470631,0.000004159976,0.00009494936,0.9866117,0.0005395541],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[2.060394e-7,0.9781348,0.01388452,0.00001969849,0.0005106819,0.005700323,0.0003157329,0.001141844,0.0002921982],"genre_scores_gemma":[5.076329e-8,0.9748846,0.01101765,0.0000201282,0.0006221957,0.009893132,0.001201253,0.0003356597,0.002025367],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9595181,"threshold_uncertainty_score":0.9996616,"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."}}