Evolutionary approach for pollution study: The case of ionizing radiation
Bibliographic record
Abstract
Estimating the consequences of environmental changes, specifically in a global change context, is essential for conservation issues. In the case of pollutants, the interest in using an evolutionary approach to investigate their consequences has been emphasized since the 2000s, but these studies remain rare compared to the characterization of direct effects on individual features. We focused on the study case of anthropogenic ionizing radiation because, despite its potential strong impact on evolution, the scarcity of evolutionary approaches to study the biological consequences of this stressor is particularly true. In this study, by investigating some particular features of the biological effects of this stressor, and by reviewing existing studies on evolution under ionizing radiation, we suggest that evolutionary approach may help provide an integrative view on the biological consequences of ionizing radiation. We focused on three topics: (i) the mutagenic properties of ionizing radiation and its disruption of evolutionary processes, (ii) exposures at different time scales, leading to an interaction between past and contemporary evolution, and (iii) the special features of contaminated areas called exclusion zones and how evolution could match field and laboratory observed effects. This approach can contribute to answering several key issues in radioecology: to explain species differences in the sensitivity to ionizing radiation, to improve our estimation of the impacts of ionizing radiation on populations, and to help identify the environmental features impacting organisms (e.g., interaction with other pollution, migration of populations, anthropogenic environmental changes). Evolutionary approach would benefit from being integrated to the ecological risk assessment process.
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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) | 0.000 | 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".