Canadian Opinions on Refractive Surgery and Approaches to Presbyopia Correction
Bibliographic record
Abstract
PURPOSE: To explore the opinions of Canadian ophthalmologists on refractive and presbyopia-correcting surgeries. METHODS: We distributed an online survey to the Canadian Ophthalmological Society members, covering laser refractive surgery (LRS), femtosecond laser-assisted cataract surgery (FLACS), lenticular refractive surgery (lenRS) that includes cataract refractive surgery (CRS) with premium intraocular lens (IOL) implantation, and presbyopia correction. RESULTS: There were 68 (7.6%) total respondents. Most respondents would not consider LRS (62.5%) nor FLACS (73.9%) for themselves. Male sex and performance of LRS or FLACS was significantly associated with consideration of these procedures for self. Most respondents (59.3%) would consider lenRS for themselves. The top method of personal presbyopia correction was spectacles, chosen by 52.5%. CONCLUSIONS: When surveying the wide body of Canadian ophthalmologists, most respondents preferred spectacle correction of presbyopia and would consider lenRS, but not LRS or FLACS for themselves. Surgeons performing these procedures were more likely to consider them for self.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".