Case study on occupational exposures to radiation with possible co-exposure to heavy metals
Bibliographic record
Abstract
Biodosimetry is a valuable tool for determining the ionising radiation dose received by exposed individuals. The dicentric chromosome assay and translocation analysis are both standardised methods of biodosimetry which analyse chromosome damage. The dicentric chromosome assay is most suitable for acute exposures in the recent past as the dicentric frequency decreases with time after exposure. Translocation analysis is more appropriate for chronic exposures and older exposures as the translocations are considered stable and long-lasting. For both, analysis of low doses is difficult due to the stochastic nature of the damage and high levels of uncertainty. Complicating matters, confounding factors, such as medical exposures or exposures to heavy metals, have been shown to have an additive or synergistic effect to damage from radiation. For the situation described here, the individuals were welders who were also potentially exposed to both radiation and heavy metals. Biodosimetry was performed on 8 welders who were potentially exposed to ionising radiation during an industrial radiographic procedure using 192 Ir for non-destructive testing. Analysis was performed 4–6 years after the suspected exposures and chromosome damage above expected background levels was detected. Here we discuss the analysis performed, the methods used to estimate whole-body doses and the involvement of confounding factors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".