{"id":"W4392590210","doi":"10.1016/j.bprint.2024.e00337","title":"3D bioprinting of human iPSC-Derived kidney organoids using a low-cost, high-throughput customizable 3D bioprinting system","year":2024,"lang":"en","type":"article","venue":"Bioprinting","topic":"Renal and related cancers","field":"Biochemistry, Genetics and Molecular Biology","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; Canada Foundation for Innovation","keywords":"Organoid; Induced pluripotent stem cell; Nephron; 3D bioprinting; Cell biology; Kidney; Tissue engineering; Biology; Computational biology; Computer science; Embryonic stem cell; Biomedical engineering; Medicine; Biochemistry","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":[0.0004719479,0.0004921606,0.0003742681,0.0004259786,0.0002927126,0.0005918203,0.0003943216,0.0006425627,0.00129201],"category_scores_gemma":[0.0002755769,0.0004211032,0.0007198807,0.000237916,0.000258044,0.000234781,0.0004799498,0.000827652,0.0009022094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003948146,"about_ca_system_score_gemma":0.0002316842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000569085,"about_ca_topic_score_gemma":0.001330747,"domain_scores_codex":[0.9996769,0.00002427017,0.00002978085,0.00008222379,0.0001489794,0.00003785403],"domain_scores_gemma":[0.9997757,0.00007673458,0.00004329575,0.0000551367,0.00002765492,0.00002155204],"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":[0.0000116644,0.00001061801,0.00006985413,0.00003872662,0.00000472623,0.00006775105,0.00002478872,0.0004759859,0.9963313,0.0001228164,0.0001167794,0.002725004],"study_design_scores_gemma":[0.000004338895,0.00002857039,0.001178932,0.000007370193,0.00001400806,0.0002628783,0.00001167806,0.003809459,0.9896975,0.00007579304,0.004894603,0.0000147065],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5362723,0.00277451,0.4442398,0.0003410203,0.000287891,0.0004003533,0.001968056,0.002999048,0.01071703],"genre_scores_gemma":[0.6630494,0.00220576,0.3197376,0.0002567373,0.00004529181,0.0005930419,0.002165991,0.0005664904,0.01137967],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.00129201,"threshold_uncertainty_score":0.004322231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01071522136266464,"score_gpt":0.2537838746267929,"score_spread":0.2430686532641283,"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."}}