Co-exposures to trace elements and polycyclic aromatic compounds (PACs) impacts North American river otter (Lontra canadensis) baculum
Bibliographic record
Abstract
Environmental loadings of polycyclic aromatic compounds (PACs) and trace elements are increasing in areas with marked oil and gas extraction, such as in the Athabasca oil sands region, Alberta, Canada. Some of these chemicals are recognized as potent endocrine disrupting compounds (EDCs). The impacts of co-exposure to PACs and metals on free-ranging wildlife is of considerable concern. River otters (Lontra canadensis) are sentinel species of aquatic ecosystem health. The baculum (penile bone) is an important part of the reproductive system in otters that ensures successful copulation. Although baculum health is critical to male reproductive success and is sensitive to exposure to EDCs, there is no information available regarding the impact of PAC and metal exposures on measures of baculum health. River otter baculum and livers were dissected from carcasses obtained from the fur trade. Trace element and PAC analyses were carried out in liver with matching baculums subjected to dimensional analysis, bone mineral density (BMD) and mechanical loading testing. Trace elements and select PACs exhibited both protective and deleterious effects on baculum bone health metrics. Alkylated four ring PACs were negatively associated with baculum bone material properties (ex: C4-Chrysene and C4-pyrene). The same compounds have been shown to exhibit strong anti-androgenic activities. Few comparable studies exist related to contamination and adverse effects of PACs in wild terrestrial mammals. Baculum health metrics may be an important tool to include in biomonitoring studies as to date, there are limited means to assess male reproductive performance in wildlife biomonitoring programs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".