Behavioural toxicity of organic chemical contaminants in fish: application to ecological risk assessments (ERAs)
Bibliographic record
Abstract
Chemical pollutants rarely attain acutely lethal concentrations in nature; thus the majority of their effects are expected to be sublethal. Estimation of the likelihood of effects from exposures to sublethal concentrations of contaminants in effluent plumes downstream of point sources poses a challenge when conducting ecological risk assessments (ERAs). This is an issue for regulatory agencies worldwide. This paper reviews the importance and availability of information on behavioural toxicity and identifies opportunities for its inclusion in ERAs. One of the major advantages of using data on behavioural effects is that they are more sensitive indicators of potential for impacts on survival in the field than are measures of lethality. Indications from available data for fish suggest that behavioural effects of organic contaminants often occur at concentrations 1 to 2 orders of magnitude lower than those found to elicit mortality. As a result, it is believed that the use of data on behavioural toxicity in ERAs could benefit the assessment process a great deal, allowing for the consideration of more ecologically significant and protective hazard and exposure scenarios.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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".