Ensuring robust radiological risk assessment for wildlife: insights from the International Atomic Energy Agency EMRAS and MODARIA programmes
Bibliographic record
Abstract
In response to changing international recommendations and national requirements, a number of assessment approaches, and associated tools and models, have been developed over the last circa 20 years to assess radiological risk to wildlife. In this paper, we summarise international intercomparison exercises and scenario applications of available radiological assessment models for wildlife to aid future model users and those such as regulators who interpret assessments. Through our studies, we have assessed the fitness for purpose of various models and tools, identified the major sources of uncertainty and made recommendations on how the models and tools can best be applied to suit the purposes of an assessment. We conclude that the commonly used tiered or graded assessment tools are generally fit for purpose for conducting screening-level assessments of radiological impacts to wildlife. Radiological protection of the environment (or wildlife) is still a relatively new development within the overall system of radiation protection and environmental assessment approaches are continuing to develop. Given that some new/developing approaches differ considerably from the more established models/tools and there is an increasing international interest in developing approaches that support the effective regulation of multiple stressors (including radiation), we recommend the continuation of coordinated international programmes for model development, intercomparison and scenario testing.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".