{"id":"W1994521364","doi":"10.1089/ten.2006.0253","title":"Design and Fabrication of Sub-mm-Sized Modules Containing Encapsulated Cells for Modular Tissue Engineering","year":2007,"lang":"en","type":"article","venue":"Tissue Engineering","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institutes of Natural Sciences; Canadian Institutes of Health Research; National Institutes of Health","keywords":"Modular design; Scaffold; Tissue engineering; Umbilical vein; Fabrication; Biomedical engineering; Construct (python library); Process (computing); Self-healing hydrogels; Layer (electronics); Materials science; Nanotechnology; Computer science; Chemistry; Engineering; In vitro","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":[0.0003781251,0.0004704009,0.0002889974,0.0002743597,0.000135057,0.0002877119,0.000375444,0.000319519,0.0004052493],"category_scores_gemma":[0.0002751836,0.0002944222,0.0004640542,0.0001473512,0.0002007016,0.0002944789,0.0003186648,0.0004056183,0.0003678712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001490129,"about_ca_system_score_gemma":0.0001889947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001058025,"about_ca_topic_score_gemma":0.0002939902,"domain_scores_codex":[0.9998627,0.00002094195,0.00001565115,0.00002874001,0.00004617648,0.00002584322],"domain_scores_gemma":[0.9997556,0.0000430662,0.00007275359,0.00004142573,0.00003790361,0.00004932694],"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":[0.00001393749,0.00001671306,0.0002341806,0.0000447403,0.000007977642,0.00005486994,0.00002327165,0.0007085191,0.9950448,0.0002455142,0.00004358751,0.003561926],"study_design_scores_gemma":[0.00001212972,0.0003086025,0.001507293,0.000006952542,0.00002605127,0.000308816,0.00001278737,0.003445841,0.9907323,0.00009927532,0.003525567,0.00001437172],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7408219,0.001300843,0.2542706,0.0001212827,0.0001093069,0.0004105697,0.0003472889,0.0004568401,0.002161331],"genre_scores_gemma":[0.6986914,0.001013446,0.2976947,0.00007751507,0.00002910907,0.0003426629,0.0004224024,0.00007216708,0.001656593],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0004704009,"threshold_uncertainty_score":0.001999795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01500497618271345,"score_gpt":0.2555475989369388,"score_spread":0.2405426227542253,"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."}}