Models and approaches available to estimate the exposure of non-human biota: an international comparison of predictions
Bibliographic record
Abstract
Over the last decade, there have been a number of models and approaches proposed to estimate the exposure of non-human biota to ionising radiations. Some countries are now using these within their national regulatory frameworks for nuclear and other sites which may be releasing radioactivity to the environment. To date validation of these approaches has been limited and there has been little attempt to compare the outputs of the different models being applied. To address this gap, a new Biota Working Group (BWG) has been formed by the IAEA as part of the EMRAS (Environmental Modelling for Radiation Safety) programme. The primary objective of the EMRAS BWG, as set by its participants, is: ‘to compare and validate models being used and developed by Member States for biota dose assessment (that may be used) as part of regulatory process of licensing and compliance monitoring of authorised releases of radionuclides in order to improve Member State’s capabilities for protection of the environment’. Initial exercises are directed at the comparison and validation of screening level models.\nIn this paper, we will report on a recently conducted comparison of predicted activity concentrations in a range of non-human biota assuming a simple scenario. Unweighted internal and external dose conversion coefficients will also be compared for a selection of reference organism geometries, as currently being proposed by the ICRP, in environmentally relevant media. The models and approaches used encompass those being developed and applied in the USA, Canada, France, Belgium and the UK, as well as the outputs from international collaborative programmes. The results of this work will be discussed in the context of the longer term objectives of the EMRAS Biota Working Group.
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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 | 0.000 | 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 | 0.000 | 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) | 0.001 | 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".