Trends in Radiation Practices for Female Ocular Oncologists in North America: A Collaborative Study of the International Society of Ocular Oncology
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to determine the known radiation exposure, attitudes, and consequent risk modifications among female ocular oncologists in North America who routinely administer radioactive plaque brachytherapy treatment and are members of the International Society of Ocular Oncology. METHODS: Nineteen female ocular oncologists completed an anonymous 17-question radiation exposure survey. RESULTS: Eleven of the participants chose to routinely wear lead protection during surgery; 8 did not. Fifteen of 19 participants reported using an unloaded "nonactive" template to prepare for plaque implantation. During pregnancy, 11 of 13 participants continued to perform plaque brachytherapy. Eight of these 11 undertook measures to decrease radiation exposure self-reported as lead wear and other. The average reported anxiety regarding fertility was 2.1 (SD, 2.2) on a scale from 1 to 10. CONCLUSION: This study corroborates prior literature that surgeons' exposure to radiation during plaque brachytherapy is minimal. Nonetheless, there remains some anxiety regarding exposure risk to women, due to potential effects on fertility and fetal health. We found variability in exposure monitoring, required training, and precautions during pregnancy amongst this group of surgeons. Improved education and clearer pregnancy guidelines may equip female ocular oncologists with optimal knowledge regarding risk of radiation exposure.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".