Internal organ dose rate conversion coefficients of Japanese macaques to 134Cs,137Cs and 131I
Bibliographic record
Abstract
The purpose of this study was to estimate the internal dose of radiation in Japanese macaques (aka Nihonzaru or snow monkey) due to the Fukushima nuclear power plant accident. Images of a male Japanese macaque weighing ~10 kg were acquired using a multi-slice computed tomography (CT) scan with a 64-row segment detector. The CT images were used to create voxel phantoms of the bones, bone marrow, brain, eyes, heart, lungs, stomach, liver, spleen, pancreas, kidneys, intestines, bladder, testes, thyroid and miscellaneous tissue. The Particle and Heavy Ion Transport System (PHITS) Monte Carlo code was used to calculate the internal exposure rate conversion factors for 134Cs, 137Cs and 131I isotopes for the created voxel phantoms with a statistical precision higher than 1%. The PHITS-calculated energy deposits were compared with those for rhesus monkeys. The results showed that the fractions of energy deposits for β-radiation in different organs were almost identical between the two species. For γ-radiation, there was excellent agreement in the self-absorption rate with the approximate curve of the Japanese macaque, with an average deviation of 2%. The maximum deviation of 12% was for the kidney, which has two organs, so the error with the approximate curve is slightly larger due to the energy loss created between organs.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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".