{"id":"W2891065887","doi":"10.1016/j.biomaterials.2018.09.026","title":"Rapid 3D bioprinting of decellularized extracellular matrix with regionally varied mechanical properties and biomimetic microarchitecture","year":2018,"lang":"en","type":"article","venue":"Biomaterials","topic":"Tissue Engineering and Regenerative Medicine","field":"Medicine","cited_by":273,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; National Science Foundation","keywords":"Decellularization; Extracellular matrix; Materials science; Biomedical engineering; 3D bioprinting; Hepatocellular carcinoma; Stromal cell; Tissue engineering; Cancer research; Cell biology; Medicine; Biology","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":[0.0002749649,0.0004482985,0.000244353,0.0002241296,0.0001682157,0.0004009589,0.000238554,0.000469084,0.0006322059],"category_scores_gemma":[0.0002264283,0.000309773,0.0002847641,0.0001507766,0.0003067158,0.000241625,0.0003724972,0.0004336092,0.0002667743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003121923,"about_ca_system_score_gemma":0.0002203636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003170357,"about_ca_topic_score_gemma":0.001086287,"domain_scores_codex":[0.9998372,0.00001500125,0.00001224764,0.00003954415,0.00005077811,0.00004516066],"domain_scores_gemma":[0.9998428,0.00003905158,0.00005114768,0.00003370251,0.00001703672,0.00001623343],"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":[0.00001129742,0.000005199789,0.00002237495,0.00001150734,0.000002026839,0.00001627556,0.00001470711,0.0001279882,0.9990875,0.00005606873,0.00002144552,0.0006236475],"study_design_scores_gemma":[0.000007790474,0.00003855327,0.0008250544,0.000002585274,0.000006024589,0.00008429205,0.000008719385,0.001351884,0.9967226,0.00003478835,0.0009116887,0.000005869151],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9663764,0.001287859,0.02784597,0.00008612071,0.0000666604,0.00008531265,0.0002102234,0.0003691464,0.003672301],"genre_scores_gemma":[0.9699075,0.0004634668,0.02657587,0.0001036583,0.00001593606,0.0001087096,0.0001934882,0.0001454355,0.002485913],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006322059,"threshold_uncertainty_score":0.002265155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02687705859088679,"score_gpt":0.2423333992012652,"score_spread":0.2154563406103784,"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."}}