Polycyclic aromatic compounds (PACs) in the Canadian environment: Exposure and effects on wildlife
Bibliographic record
Abstract
Polycyclic aromatic compounds (PACs) are ubiquitous in the environment. Wildlife (including fish) are chronically exposed to PACs through air, water, sediment, soil, and/or dietary routes. Exposures are highest near industrial or urban sites, such as aluminum smelters and oil sands mines, or near natural sources such as forest fires. This review assesses the exposure and toxicity of PACs to wildlife, with a focus on the Canadian environment. Most published field studies measured PAC concentrations in tissues of invertebrates, fish, and birds, with fewer studies of amphibians and mammals. In general, PAC concentrations measured in Canadian wildlife tissues were under the benzo[a]pyrene (BaP) guideline for human consumption. Health effects of PAC exposure include embryotoxicity, deformities, cardiotoxicity, DNA damage, changes to DNA methylation, oxidative stress, endocrine disruption, and impaired reproduction. Much of the toxicity of PACs can be attributed to their bioavailability, and the extent to which certain PACs are transformed into more toxic metabolites by cytochrome P450 enzymes. As most mechanistic studies are limited to individual polycyclic aromatic hydrocarbons (PAHs), particularly BaP, research on other PACs and PAC-containing complex mixtures is required to understand the environmental significance of PAC exposure and toxicity. Additional work on responses to PACs in amphibians, reptiles, and semi-aquatic mammals, and development of molecular markers for early detection of biological responses to PACs would provide a stronger biological and ecological justification for regulating PAC emissions to protect Canadian wildlife.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".