Radiobiology of Accidental, Public, and Occupational Exposures
Bibliographic record
Abstract
Abstract This chapter describes situations where individuals may be potentially exposed to ionizing radiation in accidental, occupational, or public exposures excluding those from clinical radiotherapy. Each exposure type can have very specific characteristics ranging in radiation quality, dose, dose rate, length of exposures, and proportion of the body acute exposure. As such, some long-term health effects of low-dose exposures are described including effects on the embryo and fetus, heritable diseases, cataracts, and cardiovascular effects. Special focus on exposure to radon is included along with the health effects specific to this exposure situation. Accidental and malicious exposures can also include high-dose scenarios that can lead to the development of acute radiation syndrome (ARS). Details of ARS are described along with how it can be diagnosed. In some exposure scenarios, large numbers of individuals are exposed such that triage is required to quickly identify those needing medical intervention to mitigate ARS. Strategies for triage for treatment are described with respect to trauma, contamination, and exposure along with a discussion of suggested countermeasures for internal exposure and medical follow-up after exposure. In order to assist with determining the dose of radiation an individual has been exposed to, several biodosimetry techniques are described. The final section focuses on the radiation protection system including definitions of quantities commonly used and the limits of exposure.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.015 | 0.005 |
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".