{"id":"W2956525133","doi":"10.3390/mi10070480","title":"The Applications of 3D Printing for Craniofacial Tissue Engineering","year":2019,"lang":"en","type":"review","venue":"Micromachines","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":92,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Scaffold; 3D printing; Tissue engineering; Selective laser sintering; Biomedical engineering; Materials science; Three dimensional printing; Rapid prototyping; Craniofacial; Dental alveolus; Stereolithography; 3d printed; Dentistry; Engineering; Medicine; Sintering; Composite material","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.0005041765,0.0002911791,0.0007663079,0.0001465573,0.00009681649,0.00005598257,0.0007590236,0.0002269254,0.0000134583],"category_scores_gemma":[0.0002734911,0.0002041803,0.0002321686,0.0003291996,0.00005972428,0.00002460104,0.0001537574,0.0004077374,0.00007060861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006060052,"about_ca_system_score_gemma":0.00006480423,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000712184,"about_ca_topic_score_gemma":0.000001717878,"domain_scores_codex":[0.9985921,0.00002398869,0.0005808053,0.0002292684,0.0001909555,0.0003828495],"domain_scores_gemma":[0.9981642,0.001130991,0.0001051658,0.0004790066,0.00006274158,0.00005785289],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[3.831083e-7,0.000005760406,0.000001515513,0.02888251,0.0001014711,1.791316e-7,0.00001195128,0.00005076681,0.0003035338,0.0001596558,0.0002242845,0.970258],"study_design_scores_gemma":[0.00006008629,0.000008621779,0.000003485824,0.001513683,0.00009952462,0.000005558935,0.000001095361,0.001272236,0.00007870723,0.00001480044,0.9967525,0.0001896854],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000008963029,0.9748005,0.02244831,0.000008493114,0.0004224125,0.001712976,0.00008935895,0.0001693862,0.0003396413],"genre_scores_gemma":[0.00001888559,0.9924625,0.005817289,0.000001257887,0.0004050041,0.0006932672,0.00005654203,0.0001264776,0.000418808],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9965282,"threshold_uncertainty_score":0.8326233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0278090054191582,"score_gpt":0.3440090114670218,"score_spread":0.3162000060478636,"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."}}