{"id":"W4384406238","doi":"10.1002/adtp.202300139","title":"Designing Regenerative Bioadhesives for Tissue Repair and Regeneration","year":2023,"lang":"en","type":"article","venue":"Advanced Therapeutics","topic":"Tendon Structure and Treatment","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; McGill University","keywords":"Regeneration (biology); Regenerative medicine; Bioadhesive; Tissue engineering; Biomedical engineering; Wound healing; Medicine; Surgery; Nanotechnology; Materials science; Drug delivery; Stem cell; Biology; Cell biology","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":[0.0004906052,0.0006111006,0.0003609459,0.0004959435,0.0003856384,0.0008818523,0.0004422701,0.0007659883,0.001744642],"category_scores_gemma":[0.0002969166,0.0003284756,0.0003096263,0.000230614,0.0003029098,0.0007733521,0.0006347056,0.0004981098,0.0009379301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003034163,"about_ca_system_score_gemma":0.0003600998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002339515,"about_ca_topic_score_gemma":0.0005336036,"domain_scores_codex":[0.999805,0.00004221096,0.00001796282,0.00002118977,0.00007139608,0.00004224285],"domain_scores_gemma":[0.9998691,0.00003056684,0.00003553845,0.000009504766,0.00003233592,0.00002296601],"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":[0.00004425612,0.000121734,0.0003485491,0.0008785439,0.00001810405,0.0004344668,0.000116541,0.002395308,0.9513696,0.009883167,0.0007165332,0.03367324],"study_design_scores_gemma":[0.00006229409,0.001076366,0.001656801,0.0003032642,0.00005510699,0.001170847,0.0003010869,0.01157973,0.8740053,0.005177569,0.1045449,0.00006680492],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6480426,0.07702112,0.2319356,0.002241469,0.00163444,0.000971459,0.0003957934,0.0006939077,0.03706357],"genre_scores_gemma":[0.8061925,0.02867819,0.1470589,0.0008955143,0.0002475064,0.0006702261,0.0002163029,0.00008165477,0.01595936],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001744642,"threshold_uncertainty_score":0.005836368,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04342197594645338,"score_gpt":0.3448809939769246,"score_spread":0.3014590180304713,"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."}}