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Record W4283821391 · doi:10.1097/ico.0000000000003094

Delivery of Cells to the Cornea Using Synthetic Biomaterials

2022· review· en· W4283821391 on OpenAlexaff
Mitchell Ross, Nicole Marie Amaral, Aftab Taiyab, Heather Sheardown

Bibliographic record

VenueCornea · 2022
Typereview
Languageen
FieldMedicine
TopicCorneal Surgery and Treatments
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCorneaSelf-healing hydrogelsRegenerative medicineStem cellCorneal DiseasesTissue engineeringBiomedical engineeringMaterials scienceOphthalmologyMedicineCell biologyBiology

Abstract

fetched live from OpenAlex

ABSTRACT: The cornea is subject to a myriad of ocular conditions often attributed to cell loss or cell dysfunction. Owing to the superficial positioning of tissues composing the anterior segment of the eye, particularly the cornea, regenerative medicine in this region is aided by accessibility as compared with the invasive delivery methods required to reach deep ocular tissues. As such, cell therapies employing the use of carrier substrates have been widely explored. This review covers recent advances made in the delivery of stem cells, corneal epithelial cells, and corneal endothelial cells. Particular focus is placed on the most popular forms of synthetic scaffolds currently being examined: contact lenses, electrospun substrates, polymeric films, and hydrogels.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.176
GPT teacher head0.361
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2022
Admission routes1
Has abstractyes

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