{"id":"W2902499520","doi":"10.1021/acsbiomaterials.8b01235","title":"3D Printing of Neural Tissues Derived from Human Induced Pluripotent Stem Cells Using a Fibrin-Based Bioink","year":2018,"lang":"en","type":"article","venue":"ACS Biomaterials Science & Engineering","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":150,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Stem Cell Network; British Columbia Innovation Council","keywords":"3D bioprinting; Induced pluripotent stem cell; Tissue engineering; Neural tissue engineering; Neural stem cell; Biomedical engineering; Cell biology; Self-healing hydrogels; Materials science; Nanotechnology; Stem cell; Chemistry; Biology; Embryonic stem cell; Engineering; Biochemistry","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":[0.0002574921,0.0004001899,0.0001791227,0.0004699803,0.0002177418,0.000424341,0.0002731458,0.0004703886,0.001158745],"category_scores_gemma":[0.0002904143,0.0002830939,0.0004493368,0.0002760105,0.0002251171,0.0002797839,0.0003269821,0.0004744984,0.0007524517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002275483,"about_ca_system_score_gemma":0.0002510288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003184112,"about_ca_topic_score_gemma":0.0008936354,"domain_scores_codex":[0.9997502,0.00001649091,0.00003031911,0.00005586992,0.0001255121,0.00002164663],"domain_scores_gemma":[0.9998247,0.00005753809,0.00004774672,0.0000403884,0.00001830657,0.00001120568],"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":[0.00001274156,0.00001098555,0.0001191403,0.00006746445,0.000004027013,0.0002096296,0.00002909104,0.0007275193,0.9888038,0.0002758887,0.0001165893,0.009623159],"study_design_scores_gemma":[0.000002861732,0.00003196223,0.0005641734,0.000007381853,0.000005250551,0.0003712962,0.000006039447,0.001518319,0.9933982,0.00009052793,0.003994994,0.000009058738],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5878345,0.00371892,0.3799333,0.0003026541,0.000416876,0.0003146711,0.001872097,0.003704396,0.02190256],"genre_scores_gemma":[0.6214565,0.002220187,0.3672679,0.0001755546,0.00003253617,0.0001770439,0.0008837576,0.0003327824,0.007453744],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001158745,"threshold_uncertainty_score":0.003876388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0396416862865309,"score_gpt":0.288619573293052,"score_spread":0.2489778870065212,"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."}}