Intercomparison of Monte Carlo radiation transport codes to model TEPC response in low-energy neutron and gamma-ray fields
Bibliographic record
Abstract
Tissue-equivalent proportional counters (TEPC) can potentially be used as a portable and personal dosemeter in mixed neutron and gamma-ray fields, but what hinders this use is their typically large physical size. To formulate compact TEPC designs, the use of a Monte Carlo transport code is necessary to predict the performance of compact designs in these fields. To perform this modelling, three candidate codes were assessed: MCNPX 2.7.E, FLUKA 2011.2 and PHITS 2.24. In each code, benchmark simulations were performed involving the irradiation of a 5-in. TEPC with monoenergetic neutron fields and a 4-in. wall-less TEPC with monoenergetic gamma-ray fields. The frequency and dose mean lineal energies and dose distributions calculated from each code were compared with experimentally determined data. For the neutron benchmark simulations, PHITS produces data closest to the experimental values and for the gamma-ray benchmark simulations, FLUKA yields data closest to the experimentally determined quantities.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".