DOSE TO THE CELL NUCLEUS FROM EXPOSURE TO TRITIATED PUMP OIL OR FORMALDEHYDE
Bibliographic record
Abstract
A Monte Carlo simulation of tritium decays in a cell composed of two parts, a nucleus and surrounding cytoplasm, was developed to evaluate the beta-radiation dose to the nucleus. A dose modifying factor (DMF), which is a ratio of the average nuclear dose to the whole-tissue dose, after skin-contact exposure of rats to tritiated pump oil or tritiated formaldehyde was estimated. Biokinetic data characterizing the retention of tritium in liver were available in the form of tritium-specific activities and biological half-times for tritiated water and five macromolecular species (DNA, RNA, acid-soluble fraction, acid-insoluble protein, and lipids). The spatial distribution of tissue-free water and macromolecular species in the nucleus and cytoplasm of rat liver cells was based on published data. In the case of exposure to tritiated pump oil, tritium incorporated into lipids provides the largest percentage (60%) of the absorbed dose to the nucleus. For the tritiated-formaldehyde exposure, the tritium dose to the nucleus is overwhelmingly contributed by tritiated water (58%) and in acid-insoluble proteins (40%). For both these tritiated organic exposures, the tritium-labeled DNA has a negligible effect on the DMF. The DMF for the tritiated pump oil and formaldehyde exposures was estimated as 0.81 and 1.05, respectively: the DMF of both exposures was close to unity. Given the other uncertainties in tritium dosimetry, our results suggest that for these skin-contact exposures a uniform distribution of tritium in tissue is an adequate assumption for dosimetry.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".