Calculation of beta‐ray dose distributions from ophthalmic applicators and comparison with measurements in a model eye
Bibliographic record
Abstract
Dose distributions throughout the eye, from three types of beta-ray ophthalmic applicators, were calculated using the EGS4, ACCEPT 3.0, and other Monte Carlo codes. The applicators were those for which doses were measured in a recent international intercomparison [Med. Phys. 28, 1373 (2001)], planar applicators of 106Ru-106Rh and 90Sr-90Y and a concave 106Ru-106Rh applicator. The main purpose was to compare the results of the various codes with average experimental values. For the planar applicators, calculated and measured doses on the source axis agreed within the experimental errors (<10%) to a depth of 7 mm for 106Ru-106Rh and 5 mm for 90Sr-90Y. At greater distances the measured values are larger than those calculated. For the concave 106Ru-106Rh applicator, there was poor agreement among available calculations and only those calculated by ACCEPT 3.0 agreed with measured values. In the past, attempts have been made to derive such dose distributions simply, by integrating the appropriate point-source dose function over the source. Here, we investigated the accuracy of this procedure for encapsulated sources, by comparing such results with values calculated by Monte Carlo. An attempt was made to allow for the effects of the silver source window but no corrections were made for scattering from the source backing. In these circumstances, at 6 mm depth, the difference in the results of the two calculations was 14%-18% for a planar 106Ru-l06Rh applicator and up to 30% for the concave applicator. It becomes worse at greater depths. These errors are probably caused mainly by differences between the spectrum of beta particles transmitted by the silver window and those transmitted by a thickness of water having the same attenuation properties.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".