Encapsulated Gamma Source Contact Dose Conversion Factors: Updating NCRP-40 Guidance
Bibliographic record
Abstract
ABSTRACT: Secondary electron generation on the surface of encapsulated gamma sources can play a large role in the dose measured near the surface of the encapsulation. The National Council on Radiation Protection and Measurements Report No. 40 contains contact dose rate conversion factors for encapsulated gamma sources, along with recommended secondary electron correction factors. However, secondary electron correction factors were based on experiments performed in the 1930s and 1940s with encapsulated radium sources, and the correction factors for the other sources listed in the report were estimated based on these radium source measurements. Monte Carlo simulations were performed using the Particle and Heavy Ion Transport code System (PHITS) to calculate the contact dose rate conversion factors for each encapsulated gamma source presented in NCRP-40, taking into account the dose from both gamma rays and secondary electrons. These simulations showed that the contact dose rate conversion factors are much lower than those presented in NCRP-40, and the secondary electron contribution was much greater than the values proposed by NCRP-40. The original research used results from encapsulated 226Ra experiments to determine the secondary electron correction factors for NCRP-40. To support the current Monte Carlo calculations, experiments were conducted using an encapsulated 137Cs source, rare earth magnet, and ion chamber detector to show that the secondary electron correction factors presented in NCRP-40 were not applicable to the geometry of tissue in direct contact with the encapsulation. In this work, contact dose conversion factors for common encapsulated radionuclide sources are presented.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".