Resilience of larval wood frogs (Rana sylvatica) to hydrocarbons and other compounds released from naturally weathered diluted bitumen in a boreal lake
Bibliographic record
Abstract
The risks to aquatic wildlife from spills of diluted bitumen (dilbit) into inland waters are poorly understood. In this paper, we describe the response of larval wood frogs (Rana sylvatica) to hydrocarbons and other compounds released from experimental spills of dilbit in a temperate boreal lake. To simulate a wide range of environmentally relevant oil spill scenarios, different volumes of Cold Lake Winter Blend dilbit (0, 1.5, 2.9, 5.5, 18, 42, 82, and 180 L) were added to 10 m diameter in-lake limnocorrals. Larvae (n = 360) were reared (from Gosner Stage (GS) 25 to ∼42) in land-based aquatic microcosms, where they were first exposed to clean water during a 2-week baseline phase, and then (at GS ∼30), to contaminated water withdrawn from the limnocorrals for 3 weeks. We observed no statistically significant trends in survival, growth, or development of larvae as a consequence of exposure to the chemical compounds released from naturally weathered dilbit. Likewise, neither cytochrome P450 1A biomarkers nor levels of thyroid hormones in wood frogs near metamorphic climax were significantly related to volume of the oil spills. However, there was a modest statistically significant decrease in larval activity (up to 8.7% relative to the control), but no change in other behavioral metrics (i.e., sociality or space use). Our work adds to the limited body of literature on the effects of unconventional oils on aquatic wildlife and helps to inform risk assessments regarding pipeline projects.
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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".