Dose Equivalent Rate Constants and Barrier Transmission Data for Nuclear Medicine Facility Dose Calculations and Shielding Design
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Bibliographic record
Abstract
A primary goal of nuclear medicine facility design is to keep public and worker radiation doses As Low As Reasonably Achievable (ALARA). To estimate dose and shielding requirements, one needs to know both the dose equivalent rate constants for soft tissue and barrier transmission factors (TFs) for all radionuclides of interest. Dose equivalent rate constants are most commonly calculated using published air kerma or exposure rate constants, while transmission factors are most commonly calculated using published tenth-value layers (TVLs). Values can be calculated more accurately using the radionuclide's photon emission spectrum and the physical properties of lead, concrete, and/or tissue at these energies. These calculations may be non-trivial due to the polyenergetic nature of the radionuclides used in nuclear medicine. In this paper, the effects of dose equivalent rate constant and transmission factor on nuclear medicine dose and shielding calculations are investigated, and new values based on up-to-date nuclear data and thresholds specific to nuclear medicine are proposed. To facilitate practical use, transmission curves were fitted to the three-parameter Archer equation. Finally, the results of this work were applied to the design of a sample nuclear medicine facility and compared to doses calculated using common methods to investigate the effects of these values on dose estimates and shielding decisions. Dose equivalent rate constants generally agreed well with those derived from the literature with the exception of those from NCRP 124. Depending on the situation, Archer fit TFs could be significantly more accurate than TVL-based TFs. These results were reflected in the sample shielding problem, with unshielded dose estimates agreeing well, with the exception of those based on NCRP 124, and Archer fit TFs providing a more accurate alternative to TVL TFs and a simpler alternative to full spectral-based calculations. The data provided by this paper should assist in improving the accuracy and tractability of dose and shielding calculations for nuclear medicine facility design.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.000 | 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 it