{"id":"W4297495987","doi":"10.5772/intechopen.106966","title":"Advances in Biomaterials for Corneal Regeneration","year":2022,"lang":"en","type":"book-chapter","venue":"IntechOpen eBooks","topic":"Corneal Surgery and Treatments","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier de l’Université de Montréal; Université de Montréal; Hôpital Maisonneuve-Rosemont","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Fonds de Recherche du Québec - Santé; Vetenskapsrådet; Stem Cell Network","keywords":"Regeneration (biology); Economic shortage; Corneal transplantation; Medicine; Cornea; Corneal disease; Blindness; Transplantation; Corneal Diseases; Ophthalmology; Extracellular vesicle; Microvesicles; Surgery; Optometry; Biology; Cell biology; microRNA","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001900435,0.0002575477,0.0005431226,0.0002081234,0.00007193448,0.00002281146,0.00008968454,0.000184512,0.001555748],"category_scores_gemma":[0.00002786508,0.0002351364,0.0001685551,0.0000117016,0.00004634609,0.00006059928,0.00007626711,0.0001173033,0.000047107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002381578,"about_ca_system_score_gemma":0.0001241185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004019659,"about_ca_topic_score_gemma":0.0001352852,"domain_scores_codex":[0.9988142,0.00001522732,0.0004280266,0.000382907,0.0001786359,0.0001810485],"domain_scores_gemma":[0.9993215,0.0000843306,0.0001922224,0.0002842276,0.00005463088,0.00006308452],"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":[0.004368124,0.000143869,0.0001618289,0.0004378863,0.0002774052,0.001262501,0.0001841921,0.000002823185,0.01068224,0.09326579,0.002663715,0.8865497],"study_design_scores_gemma":[0.001230933,0.000482485,0.00001267455,0.0003803121,0.0001142373,0.0001036874,0.000007198062,0.000005013901,0.01384927,0.01350531,0.9700735,0.000235409],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001758319,0.0009326984,0.0000621436,0.0001153984,0.0009223528,0.002162712,0.0002384247,0.00008096404,0.993727],"genre_scores_gemma":[0.1196977,0.0005689423,0.0004119163,0.0004008416,0.0003857195,0.0009731805,0.001149615,0.0001295665,0.8762825],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9674097,"threshold_uncertainty_score":0.999357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03799112324999195,"score_gpt":0.3016121165037449,"score_spread":0.2636209932537529,"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."}}