Radiation Biology and Its Role in the Canadian Radiation Protection Framework
Bibliographic record
Abstract
The linear no-threshold (linear-non-threshold) model is a dose-response model that has long served as the foundation of the international radiation protection framework, which includes the Canadian regulatory framework. Its purpose is to inform the choice of appropriate dose limits and subsequent as low as reasonably achievable requirements, social and economic factors taken into account. The linear no-threshold model assumes that the risk of developing cancer increases proportionately with increasing radiation dose. The linear no-threshold model has historically been applied by extrapolating the risk of cancer at high doses (>1,000 mSv) down to low doses in a linear manner. As the health effects of radiation exposure at low doses remain ambiguous, reducing uncertainties found in cancer risk dose-response models can be achieved through in vitro and animal-based studies. The purpose of this critical review is to analyze whether the linear no-threshold model is still applicable for use by modern nuclear regulators for radiation protection purposes, or if there is sufficient scientific evidence supporting an alternate model from which to derive regulatory dose limits.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".