Descemet's Stripping With Endothelial Keratoplasty in Iridocorneal Endothelial Syndrome
Bibliographic record
Abstract
An interventional case is described to report on the clinical outcome of Descemet's stripping automated endothelial keratoplasty performed for iridocorneal endothelial syndrome. A Descemet's stripping automated endothelial keratoplasty was performed in the eye of a 53-year-old woman with decompensated cornea secondary to iridocorneal endothelial syndrome. The transplant and the angle were evaluated with optical coherence tomography. Within 10 months postoperatively, the graft was clear and best-corrected visual acuity improved from 20/400 to 20/30. Descemet's stripping automated endothelial keratoplasty appears to be an effective measure to treat corneal decompensation, improve vision, and facilitate the examination of the optic disc and retina in patients with iridocorneal endothelial syndrome.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".