Relative biological effectiveness of 31 meV thermal neutrons in peripheral blood lymphocytes
Bibliographic record
Abstract
The reported relative biological effectiveness (RBE) for thermal neutrons has a large range (5-51, for cytogenetic endpoints), which can confound radiation protection decision-making. To determine whether thermal neutron spectra can influence RBE, the RBE of reactor-derived thermal neutrons of average energy 31 meV was evaluated in human peripheral blood lymphocytes using two classical DNA double-strand break endpoints: the dicentric chromosome assay (DCA) and the cytokinesis-block micronucleus assay. Dose-response curves for 41 to 408 mGy revealed a preference for linear regression. Maximum RBE (RBEM) values of 6.7 ± 0.9 and 4.4 ± 0.7 were calculated for the DCA and the micronucleus assay, respectively. These 31 meV RBEM values were significantly lower than our prior results for 64 meV thermal neutrons, which yielded a DCA RBEM of 11.3 ± 1.6 and a micronucleus RBEM of 9.0 ± 1.1. Dose-specific RBE values decreased with increasing dose for both assays. Microdosimetry simulations demonstrated similar quality factor values for both thermal neutron spectra. Dose deposition differences on the cellular scale, the difference in dose rate between irradiation configurations, or a not-yet understood phenomenon may be responsible for the RBE difference between the 31 and 64 meV thermal spectra. These findings indicate that the currently accepted radiation weighting factor wR value of 2.5 for thermal neutrons may underestimate the radiation detriment to small or shallow tissue targets including the lens of the eye.
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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 | 0.002 |
| 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) | 0.001 | 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".