{"id":"W2765398719","doi":"10.1089/ten.tec.2017.0346","title":"UV-Assisted 3D Bioprinting of Nanoreinforced Hybrid Cardiac Patch for Myocardial Tissue Engineering","year":2017,"lang":"en","type":"article","venue":"Tissue Engineering Part C Methods","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":235,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; University Health Network","funders":"Canadian Institutes of Health Research; University of Saskatchewan; Saskatchewan Health Research Foundation; Heart and Stroke Foundation of Canada","keywords":"Biofabrication; Materials science; Biomedical engineering; Tissue engineering; Self-healing hydrogels; 3D bioprinting; Extracellular matrix; Cardiac muscle; Carbon nanotube; Viability assay; Nanotechnology; Chemistry; In vitro; Anatomy; Polymer chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003092678,0.0005592935,0.001068462,0.0003582014,0.000235261,0.0001521419,0.001094395,0.0003006958,0.0000782099],"category_scores_gemma":[0.004636091,0.0006283636,0.0002827835,0.0002605554,0.0001194025,0.0002530314,0.0003840467,0.0005991285,0.00003494216],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001487619,"about_ca_system_score_gemma":0.00005973893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008027798,"about_ca_topic_score_gemma":6.053519e-7,"domain_scores_codex":[0.996727,0.00007867596,0.0009088477,0.0005364493,0.0005722165,0.001176778],"domain_scores_gemma":[0.9965727,0.001136823,0.0001845931,0.001497658,0.0001882724,0.0004198985],"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":[0.00001791573,0.00001951452,0.0002798438,0.001751635,0.0004830931,0.00001939156,0.0001717659,0.07886878,0.6496201,0.0004504707,0.0009590341,0.2673584],"study_design_scores_gemma":[0.0004414585,0.00006928769,0.002261557,0.0002637503,0.00006743117,0.00001039904,0.000007076631,0.198708,0.6078395,0.00001396523,0.1897477,0.0005698503],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08574101,0.001116693,0.9034477,0.00007047695,0.005852617,0.001080081,0.00009865073,0.001131579,0.001461123],"genre_scores_gemma":[0.3521584,0.0001615035,0.6451474,0.000004894015,0.001269555,0.000328558,0.00004484337,0.0002881754,0.0005966148],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2667886,"threshold_uncertainty_score":0.9996167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03717872928252469,"score_gpt":0.361220425957408,"score_spread":0.3240416966748833,"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."}}