Review of Corneal Graft Registries
Bibliographic record
Abstract
PURPOSE: Corneal graft registries are organized systems that collect and analyze outcome data (such as long-term graft survival and visual outcomes) after keratoplasty procedures. The aim of this review was to identify existing corneal graft registries and to describe their characteristics. METHODS: A search of the PubMed database was performed on June 1, 2021, for articles pertaining to corneal graft registries. RESULTS: The PubMed literature search yielded 958 publications, of which 116 met all the inclusion and exclusion criteria. Among these articles, 15 corneal graft registries were identified, including 6 regional registries, 8 national registries, and 1 multinational registry. This article provides an overview of their characteristics and discusses the main advantages and pitfalls of clinical registries. CONCLUSIONS: Clinical registry data are increasingly recognized as a valuable tool to monitor corneal transplant outcomes to improve health care services and optimize resource management.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.007 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".