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
In recent years, noteworthy gains have been made in unravelling the genetic contribution to some complex ocular diseases, principally age-related macular degeneration. Yet, a relatively poor understanding of the genetic aetiology for many other heritable blinding diseases, such as glaucoma, keratoconus and myopia, remains. Genetic isolates, populations with varying degrees of geographical or cultural seclusion, provide an effective means for investigating the molecular mechanisms involved in human diseases. This is particularly true for rare diseases in which founded alleles can be rapidly driven to a high frequency due to restriction of gene flow in the population. Recent success in complex gene mapping has resulted from the widened linkage disequilibrium (LD) in the genome of genetically isolated populations. An improved understanding of the predisposing genetic risk factors allows for enhanced screening modalities and paves the foundations for the translation of genomic technology into the clinic. This review focuses on the role population isolates have had in the investigation of genes underlying complex eye diseases and discusses their likely usefulness given the expansion of large-scale case-control association studies.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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