Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: To review the development of artificial corneas (prostheses and tissue equivalents) for transplantation, and to provide recent updates on our tissue-engineered replacement corneas. METHODS: Modified natural polymers and synthetic polymers were screened for their potential to replace damaged portions of the human cornea or the entire corneal thickness. These polymers, combined with cells derived from each of the three main corneal layers or stem cells, were used to develop artificial corneas. Functional testing was performed in vitro. Trials of biocompatibility and immune and inflammatory reactions were performed by implanting the most promising polymers into rabbit corneas. RESULTS: Collagen-based biopolymers, combined with synthetic crosslinkers or copolymers, formed effective scaffolds for developing prototype artificial corneas that could be used as tissue replacements in the future. We have previously developed an artificial cornea that mimicked key morphologic and functional properties of the human cornea. The addition of synthetic polymers increased its toughness as it retained transparency and low light scattering, making the matrix scaffold more suitable for transplantation. These new composites were implanted into rabbits without causing any acute inflammation or immune response. We have also fabricated full-thickness composites that can be fully sutured. However, the long-term effects of these artificial corneas need to be evaluated. CONCLUSIONS: Novel tissue-engineered corneas that comprise composites of natural and synthetic biopolymers together with corneal cell lines or stem cells will, in the future, replace portions of the cornea that are damaged. Our results provide a basis for the development of both implantable temporary and permanent corneal replacements.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.005 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it