{"id":"W2793883971","doi":"10.1002/adhm.201870023","title":"Tissue Engineering: Silicon Carbide Nanoparticles as an Effective Bioadhesive to Bond Collagen Containing Composite Gel Layers for Tissue Engineering Applications (Adv. Healthcare Mater. 5/2018)","year":2018,"lang":"en","type":"article","venue":"Advanced Healthcare Materials","topic":"Electrospun Nanofibers in Biomedical Applications","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Bioadhesive; Materials science; Tissue engineering; Nanoparticle; Nanotechnology; Composite number; Silicon carbide; Lamination; Biomedical engineering; Adhesive; Drug delivery; Composite material; Engineering; Layer (electronics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017847,0.0004263582,0.0001129831,0.000292812,0.0001503893,0.0003145249,0.0001941015,0.0004181263,0.0005547056],"category_scores_gemma":[0.00008858022,0.000200912,0.0002176413,0.0001049958,0.0001840852,0.0002476738,0.000161185,0.0002606724,0.0002565807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002291014,"about_ca_system_score_gemma":0.0001702637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005820384,"about_ca_topic_score_gemma":0.001450275,"domain_scores_codex":[0.9998893,0.00001290146,0.00000716358,0.00002791564,0.00004890053,0.00001387361],"domain_scores_gemma":[0.9999481,0.00001045271,0.00001413564,0.000003332829,0.00001426577,0.000009548119],"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":[0.00001120465,0.0000125688,0.00003293851,0.00004148158,0.00000303179,0.00003645425,0.00001033461,0.00004932039,0.9976896,0.0000841221,0.00008329506,0.001945708],"study_design_scores_gemma":[0.000006508321,0.00008903336,0.0003098668,0.000003103956,0.000006389783,0.0001175777,0.000007361479,0.0007079203,0.9967396,0.00001518349,0.001994058,0.000003396133],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9493361,0.01604613,0.02613665,0.0005804525,0.0003766071,0.0001571645,0.0001617353,0.0003187209,0.006886529],"genre_scores_gemma":[0.9604099,0.005206948,0.02475808,0.0003563575,0.0000719245,0.00006993682,0.0002130673,0.00005646388,0.008857426],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005820384,"threshold_uncertainty_score":0.001855671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01058875473224032,"score_gpt":0.3185880162021229,"score_spread":0.3079992614698826,"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."}}