Uncertainties Associated with Assessing the Risk of an Endocrine Active Substance in the Canadian Environment
Bibliographic record
Abstract
Abstract A number of biological responses and multigenerational effects, mediated through the disruption of endocrine systems, have been observed in biota exposed to relatively low concentrations of environmental contaminants. These types of responses need to be considered within a weight of evidence approach in our risk assessment and risk management frameworks. However, including endocrine responses in an environmental risk assessment introduces a number of uncertainties that must be considered. A risk assessment of nonylphenol and nonylphenol polyethoxylates (NP/NPE) is used as a case study to demonstrate the sources and magnitude of some of the uncertainties associated with using endocrine disruption as an assessment endpoint. Even with this relatively well studied group of substances, there are substantial knowledge gaps which contribute to the overall uncertainties, limiting the interpretation within the risk assessment. The uncertainty of extrapolating from in vitro or biochemical responses to higher levels of organization or across species is not well understood. The endocrine system is very complex and chemicals can interact or interfere with the normal function of endocrine systems in a number of ways (e.g., receptors, hormones) which may or may not result in an adverse responses in the whole organism. Using endocrine responses can lead to different conclusions than traditional endpoints due to a variety of factors, such as differences in relative potencies of chemicals for specific endpoints (e.g., receptor binding versus chronic toxicity). The uncertainties can also be considerably larger and the desirability of using endocrine endpoints should be carefully evaluated. Endocrine disruption is a mode of action and not a functional endpoint and this needs to be considered carefully in the problem formulation stage and the interpretation of the weight of evidence.
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 | 0.009 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".