{"id":"W3093129325","doi":"10.1088/1758-5090/abc1be","title":"Toward a neurospheroid niche model: optimizing embedded 3D bioprinting for fabrication of neurospheroid brain-like co-culture constructs","year":2020,"lang":"en","type":"article","venue":"Biofabrication","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"National Institute of Biomedical Imaging and Bioengineering; National Center for Advancing Translational Sciences; National Institute of Arthritis and Musculoskeletal and Skin Diseases; National Institutes of Health; National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; Ministry of Science and Technology, Taiwan","keywords":"Fabrication; 3D bioprinting; Materials science; Systems engineering; Computer science; Manufacturing engineering; Biomedical engineering; Engineering; Tissue engineering; Medicine","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":[0.000251075,0.0005443619,0.0002227481,0.0003483685,0.0002424322,0.0005432123,0.0002845934,0.000595893,0.0005588759],"category_scores_gemma":[0.0002590718,0.0002298963,0.0002864567,0.000229422,0.0002757382,0.0003613084,0.0002846167,0.0004245496,0.000472994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004587548,"about_ca_system_score_gemma":0.0004536869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001179973,"about_ca_topic_score_gemma":0.002944106,"domain_scores_codex":[0.9998235,0.00001595733,0.00001362086,0.00003985866,0.00008437288,0.00002277287],"domain_scores_gemma":[0.9998366,0.00003901795,0.00004208061,0.0000233364,0.00003225184,0.00002665758],"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":[0.000005024727,0.00001287206,0.00005848684,0.00003372331,0.00000220651,0.00005576815,0.00002587013,0.001217882,0.9974457,0.0001820884,0.00003892561,0.0009213912],"study_design_scores_gemma":[0.000004737976,0.00003667926,0.0005789971,0.000005408988,0.000005738422,0.0001188944,0.00001746143,0.00920218,0.9880826,0.00009137902,0.001846377,0.000009501747],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8500748,0.001016051,0.1434615,0.000166,0.00005566479,0.0002101194,0.0006308344,0.0008448231,0.003540198],"genre_scores_gemma":[0.852084,0.001100059,0.143804,0.00004382079,0.000008850967,0.0002838755,0.0006125647,0.0001900802,0.00187275],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001179973,"threshold_uncertainty_score":0.003328562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04860859004477057,"score_gpt":0.2901150919910661,"score_spread":0.2415065019462955,"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."}}