{"id":"W2801546204","doi":"10.1002/adma.201800242","title":"Microfluidics‐Enabled Multimaterial Maskless Stereolithographic Bioprinting","year":2018,"lang":"en","type":"article","venue":"Advanced Materials","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":422,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Dental and Craniofacial Research; Office of Naval Research; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; National Cancer Institute; National Institutes of Health; Xunta de Galicia; National Institute of Biomedical Imaging and Bioengineering; Sharif University of Technology; Brigham and Women's Hospital","keywords":"Stereolithography; Biofabrication; Microfluidics; Materials science; Nanotechnology; Tissue engineering; 3D bioprinting; Self-healing hydrogels; Biomedical engineering; Fabrication; Regenerative medicine; Ethylene glycol; Engineering; Chemistry; Cell","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0002330145,0.0004704933,0.0002946165,0.0003505031,0.0001682385,0.0002986231,0.0005163043,0.0003902447,0.001077135],"category_scores_gemma":[0.0001938004,0.0003923093,0.0002823978,0.000166672,0.0002266299,0.0003302144,0.0003983038,0.000467475,0.0005239173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004430892,"about_ca_system_score_gemma":0.0002673877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002863606,"about_ca_topic_score_gemma":0.0006185799,"domain_scores_codex":[0.9997584,0.00001736213,0.0000187715,0.0000719923,0.0001037619,0.00002956904],"domain_scores_gemma":[0.9998392,0.00003966191,0.00006312518,0.00002316771,0.00001842091,0.00001630941],"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":[0.00001087498,0.000008352344,0.00002767121,0.00003621846,0.000001979754,0.0000194746,0.00000673975,0.000118055,0.995733,0.0001484608,0.00008355855,0.003805512],"study_design_scores_gemma":[0.000007910153,0.00005339743,0.0004368964,0.000002846656,0.000004633658,0.0001462774,0.000002251765,0.003576053,0.992299,0.00004984465,0.003409608,0.00001132845],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5258804,0.004707959,0.457454,0.0003319698,0.0006629095,0.0003483238,0.001171388,0.003979364,0.005463762],"genre_scores_gemma":[0.6376364,0.001666586,0.3542652,0.0001772567,0.0001149629,0.000290264,0.0005231089,0.000125716,0.005200545],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001077135,"threshold_uncertainty_score":0.003603399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01055765329167331,"score_gpt":0.2639201960442362,"score_spread":0.2533625427525629,"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."}}