Environmental microdosimetry: microdosimetric characterisation of low-dose exposures
Bibliographic record
Abstract
A number of researchers, as well as the International Commission on Radiation Units and Measurements, have described how concepts and quantities used in microdosimetry best capture the stochastic nature of low-level exposures in terms of cell hits and the fraction of cells affected within a tissue. However, the concepts of microdosimetry are not generally intuitive to the public or indeed to health physicists. In this article, the methods of conventional internal dosimetry was applied to different forms of radioactive iodine to derive cell-hit numbers and cell fractions affected by low-level exposures, and it is shown that microdosimetric analysis is compatible with conventional dosimetry but has the advantage of underscoring the stochastic nature of ionising radiation at low dose. The microdosimetric description of low-dose exposures derived in this work could be improved with the use of Monte Carlo track structure codes and more realistic models of different tissues and their cellular structure.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 0.001 |
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".