Genetic Isolates in Ophthalmic Diseases
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".