{"id":"W3091842643","doi":"10.11159/nddte20.117","title":"Development of Organoid-on-a-chip Platform for Preclinical DrugScreening","year":2020,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Recent Advances in Nanotechnology","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Interreg; European Regional Development Fund","keywords":"Organoid; Computer science; Drug development; Drug; Chip; Organ-on-a-chip; System on a chip; Embedded system; Nanotechnology; Medicine; Pharmacology; Microfluidics; Materials science; Neuroscience; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009357521,0.0006717738,0.0007403232,0.0005729104,0.0002881849,0.0008485378,0.0009844721,0.001032524,0.002551803],"category_scores_gemma":[0.0006244977,0.0003058212,0.0006419013,0.0003265594,0.0003875193,0.0006137664,0.0006222679,0.001054653,0.001899795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005169346,"about_ca_system_score_gemma":0.0009753467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006113712,"about_ca_topic_score_gemma":0.001228957,"domain_scores_codex":[0.9994662,0.00007523041,0.00002899691,0.0001442199,0.000226933,0.00005838758],"domain_scores_gemma":[0.9995824,0.0001126913,0.00004929958,0.00008094014,0.0001076901,0.00006694781],"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":[0.00008470536,0.00008554836,0.0001959391,0.000282226,0.00003347238,0.0001401076,0.00005488101,0.002447071,0.965215,0.001569611,0.001485619,0.02840584],"study_design_scores_gemma":[0.00001949216,0.0004821311,0.000599275,0.00002405221,0.00003932462,0.0002247883,0.00002791039,0.01021442,0.9528017,0.0004928868,0.03502519,0.00004880135],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1210164,0.007905368,0.8427044,0.0007704471,0.001130756,0.001586537,0.00260761,0.005933028,0.01634554],"genre_scores_gemma":[0.3503956,0.004853936,0.6299332,0.0007219536,0.00008528458,0.001953641,0.002130835,0.0002633237,0.009662152],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002551803,"threshold_uncertainty_score":0.008536577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03687290334352892,"score_gpt":0.3160871412221518,"score_spread":0.2792142378786229,"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."}}