Histopathological trabecular meshwork remodeling after cataract surgery detected with an advanced image analyzer
Bibliographic record
Abstract
PURPOSE: To compare the histopathological morphometry of the trabecular meshwork and ciliary processes in pseudophakic eyes and phakic eyes using advanced image analyzer technology. SETTING: McGill University, Montreal, Quebec, Canada. DESIGN: Retrospective case series. METHODS: Thirty-five pseudophakic eyes and 25 phakic eyes were sectioned and converted into digital slides. The total trabecular meshwork area and the ciliary body stroma were demarcated. The area of the trabecular meshwork, cellular and noncellular trabecular meshwork compartments, trabecular space, distance from scleral spur to inner uveal trabecular portion, and degree of fibrosis of the ciliary processes were evaluated. RESULTS: The trabecular meshwork area was larger in the pseudophakic group than the phakic group (P = .03). Furthermore, a trend of larger trabecular space recorded was seen in the pseudophakic group than the phakic group (P = .14). No differences in the proportion of cellular (P = .88) and noncellular trabecular meshwork compartments (P = .4) were seen between groups. The scleral spur to inner uveal trabecular portion distance was longer in the pseudophakic group than the phakic group (P = .008) and correlate with the trabecular meshwork area (P = .0001, r = 0.56). In the ciliary processes, a higher degree of fibrosis was measured in the pseudophakic group than the phakic group (P = .02). CONCLUSIONS: There were significant histopathological changes in the trabecular meshwork and higher fibrosis in the ciliary processes in pseudophakic eyes compared with phakic eyes. These findings support the hypothesis that trabecular meshwork remodeling after cataract surgery is involved in lowering intraocular pressure.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".