ADAPTIVE OPTICS IN RETINITIS PIGMENTOSA
Bibliographic record
Abstract
PURPOSE: To provide a comprehensive overview of quantitative adaptive optics imaging (AOI) photoreceptor parameters in retinitis pigmentosa (RP). METHODS: A systematic literature search was conducted on Ovid Medline, Embase, and Cochrane Library from January 2000 to June 2023 for articles reporting on quantitative photoreceptor measurements from AOI systems in RP. Our primary outcomes were cone density, regularity, and spacing measurements at various eccentricities. RESULTS: Twenty-six studies reporting on 299 eyes with various forms of RP that underwent AOI were included. Seventeen studies reported on cone density parameters in RP, which mostly decreased with increasing eccentricity from the fovea and were reduced in RP eyes relative to normal control eyes. Four studies reported on cone regularity in RP, which was reduced relative to normal control eyes. Twelve studies reported on cone spacing parameters in RP, which were often increased relative to normal control eyes. CONCLUSION: RP eyes showed a reduced cone density, reduced cone regularity, and increased cone spacing relative to control eyes. There is considerable variability in the reporting of AOI parameters in this setting, a paucity of data comparing AOI parameters in RP eyes to age-matched controls, and best practices of AOI use have yet to be established.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.009 | 0.006 |
| 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) | 0.004 | 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 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".