Assessment of the Effects of Endocrine Disrupting Substances in the Canadian Environment
Bibliographic record
Abstract
Abstract Endocrine disruptors are a complex issue that continues to evolve. From a government perspective, the issue of endocrine disruptors is complicated by the inclusion of several related issues, making it difficult to deal with in an effective manner. The sub-issues probably need to be dealt with through different regulatory mechanisms. The endocrine disruptor issues can be divided into three main categories: a) issues associated with subtle responses to compounds that are persistent, lipophilic and capable of biomagnification; b) issues associated primarily with non-persistent and relatively hydrophilic substances in industrial and municipal effluents; and c) issues associated with screening existing and new chemicals for their capability of interacting with the endocrine system in an adverse manner. This paper discusses options for dealing with chemicals found in complex mixtures such as pulp mill effluents, sewage effluents and in-use agricultural chemicals. When studies documented potential concerns about the potential for pulp mill effluents to cause reproductive and endocrine changes in fish, the Government of Canada developed an Environmental Effects Monitoring program as part of the new regulatory package. The EEM program is designed to provide information on whether effects are present in the environment when industry complies with their regulated discharge requirements. Endocrine disruptors have the potential to cause environmental effects with other regulated effluents, and an EEM-type of approach would be capable of identifying situations where effects are present and need to be dealt with.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".