Comparative toxicity of two diluted bitumens to developing yellow perch (Perca flavescens)
Bibliographic record
Abstract
Increasing demand for diluted bitumen (dilbit) has led to the development of the oil sands industry and the expansion of transcontinental pipelines. Dilbit is an unresolved complex mixture with variable diluent and bitumen composition. Thus, it is important to understand the effects of the two most transported dilbits in Canada, Access Western Blend (AWB) and Cold Lake Blend (CLB) on a North America native and freshwater fish species, the yellow perch (Perca flavescens). Fertilized embryos were exposed to both dilbits for 16 days, from <24 h post-fertilization until hatch. The treatment regime was a static daily renewal of water accommodated fractions (WAF) and chemically-enhanced water accommodated fractions (CEWAF) at concentrations ranging from 0.01 to 21.3 μg/L of total polycyclic aromatic compounds (TPACs). Hatched embryos were assessed for malformations and changes in the expression of genes associated with phase I and II detoxification and oxidative stress. The prevalence of developmental malformations increased significantly at the highest concentrations of all treatments, with WAF treatments yielding a higher prevalence than CEWAF. The EC50s for AWB and CLB WAF and CEWAF solutions ranged from 9.8 to 24 μg/L TPACs, with the CEWAF of AWB being the least toxic. Relative mRNA levels of cyp1a showed induction by up to 18-fold in WAF and 50-fold in CEWAF treatments at similar concentrations of measured dilbit in solution. Complementary DNA methylation analysis was assessed and fish embryos exposed to AWB CEWAF and CLB WAF showed decreased DNA methylation profiles with increasing exposure to dilbit, suggesting that global gene expression is increasing in these treatments. With recent approvals of pipelines in North America, these data will support site-specific risk assessments and monitoring of Canadian ecosystems should a pipeline spill occur.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 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".