WE‐C‐108‐12: Accounting for Intrinsic Energy Dependence of TLDs When Establishing Dose Rate Constants for Brachytherapy Seeds
Bibliographic record
Abstract
Purpose: To retrospectively account for the intrinsic energy dependence of TLDs when used to measure dose rate constants (DRC) for I–125 and Pd‐103 brachytherapy seeds, to establish new measured values for all seeds and compare the new values with Monte Carlo (MC) values and consensus values published by TG‐43U1. Methods: To calculate the relative absorbed‐dose energy dependence, f^rel, the ratio D(TLD)/D(w) at brachytherapy energies relative to Co‐60 is calculated using the EGSnrc BrachyDose code for TLD sized voxels at 1 cm from the seed centered in a water phantom. A similar geometry is used at high energy with the detector at 5 cm depth and DOSXYZnrc code. The original energy dependence applied to DRC measurements is replaced by the calculated f^rel values. By comparing the revised measured DRCs to the MC values, one can determine an appropriate relative intrinsic energy dependence, k^rel. The new relative absorbed‐dose sensitivity, S^rel, calculated as the product of f^rel and k^rel, is to give the measured DRC for comparison with Monte Carlo calculated values and TG‐43U1 consensus values. Results: The calculated f^rel values are 1.389 and 1.354 and the deduced k^rel values are 1.067 and 1.066 for I‐125 and Pd‐103 seed models, respectively. Using these new values with the literature DRC measurements, differences between calculated and revised measured DRCs are within 5% (typical measurement uncertainty) and the average discrepancy is 0.5%. The average of both DRC sets are on average 3.4% lower than the the consensus values reported in TG‐43U1. Conclusion: This work demonstrates that the energy response dependence, measured 25 years ago, applied to recent DRC measurements of I–125 and Pd‐103 brachytherapy seeds needs to be updated, thereby leading to a revision of the DRC consensus values reported by TG‐43U1.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".