META-ANALYSIS ON THE PREVALENCE OF CORNEAL ULCER IN BRAZIL (2021-2024)
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
Objective: This meta-analysis aimed to synthesize the prevalence of corneal ulcer in Brazil between 2021 and 2024, addressing regional variability, methodological heterogeneity, and data scarcity. Methods: Following PRISMA 2020 and MOOSE guidelines, a comprehensive search across PubMed, Scopus, Embase, Web of Science, and Google Scholar was conducted for observational studies reporting prevalence data on corneal ulcer in Brazilian populations. Two reviewers extracted data independently and assessed methodological quality using the Newcastle Ottawa Scale. Random-effects models were used to pool prevalence estimates, and heterogeneity was assessed via Cochrans Q and Istatistics. Conclusions: Corneal ulcer remains a significant ocular public health issue in Brazil. The findings underscore the need for standardized diagnostic protocols and continuous epidemiological surveillance to reduce blindness burden.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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 it