THREE-DIMENSIONAL OPTICAL COHERENCE TOMOGRAPHY FOR RHEGMATOGENOUS RETINAL DETACHMENT IN POSTERIOR STAPHYLOMA
Bibliographic record
Abstract
In Brief Purpose: The detection of microretinal breaks in posterior staphyloma is frequently challenging. We evaluated the ability of three-dimensional optical coherence tomography to detect retinal breaks in posterior staphyloma. Patients: We prospectively examined two highly myopic eyes of two patients with rhegmatogenous retinal detachment in posterior staphyloma. Results: Retinal breaks could not be detected in any of the two eyes by conventional fundus examination; however, these breaks were easily detected on the series of B-scan optical coherence tomography images. The location of retinal breaks was registered in the color fundus photographs, and it corresponded well with the findings during vitrectomy. Conclusion: Three-dimensional optical coherence tomography seems to be an effective tool for detecting microretinal breaks and is useful in vitrectomy for rhegmatogenous retinal detachment in the area with posterior staphyloma. The authors evaluated two cases of rhegmatogenous retinal detachment in posterior staphyloma by using three-dimensional OCT. Three-dimensional OCT is useful for detecting retinal breaks and evaluating the three-dimensional structure of the vitreo-retinal interface in myopic foveal detachment.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".