Effect of varying microkeratome parameters on laser in situ keratomileusis interface surfaces
Bibliographic record
Abstract
PURPOSE: To evaluate the effect of altering microkeratome parameters (oscillation rates and head-advance speeds) and repeated blade use on human and porcine laser in situ keratomileusis interface surface quality and to evaluate correlations between human and porcine interface surface quality. SETTING: Emory Vision, Atlanta, Georgia, USA. METHODS: Corneal flaps were created in porcine eyes and human cadaver eyes with an Amadeus I microkeratome using varying head-advance speeds and oscillation rates. Microkeratome blades were used once in 18 porcine eyes, twice in 18 human eyes (simulating clinical use), and 5 times in 15 porcine eyes. The interface surface was imaged with electron microscopy, with overall bed quality and surface smoothness graded from 1 to 5 (smoothest to roughest) by 5 masked corneal specialists using the same grading criteria for porcine eyes and human eyes. RESULTS: Neither oscillation rates nor head-advance speeds consistently influenced bed smoothness in any group. There were no differences in bed quality between first cuts and second cuts in human eyes or between porcine eyes with multiple blade use. Porcine eyes had statistically significantly smoother stromal beds than human eyes (P<.01); there was no correlation between porcine eye scores and human eye scores (r = -0.1). CONCLUSIONS: Neither alterations in microkeratome parameters nor repeated blade use consistently influenced stromal bed quality in human or porcine eyes. No subjective correlation existed between stromal bed qualities of porcine corneas and human corneas; therefore, future studies evaluating corneal stromal bed quality should be performed in human corneas only.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".