Amphibians as indicators of wetland quality in wetlands formed from oil sands effluent
Bibliographic record
Abstract
Abstract Fort McMurray, Alberta, Canada, is home to the largest oil sands mining operation in the world. Two of the companies currently mining the oil sands hope to use wetlands formed from oil sands effluent as part of their reclamation strategy required at mine closure. To evaluate the ability of these created wetlands to sustain amphibians, one population of Bufo boreas tadpoles and three different populations of Rana sylvatica tadpoles were exposed to oil sands process-affected water representative of a range of effluents expected to occur on the oil sands lease site at mine closure. Endpoints used to assess the response of the tadpoles to the process-affected waters included survival, growth, rate of development, and frequency of physical deformities. Bufo boreas held in process-affected waters displayed significantly reduced growth and prolonged developmental time (days to metamorphosis) as compared to those held in reference waters. The response of the three separate populations of R. sylvatica were population dependent. Two of the three populations responded similarly, demonstrating decreased survival and significantly reduced rates of growth when held in process-affected waters as compared to reference waters; the third was highly sensitive, displaying no growth and extremely poor survival in all exposures, suggesting different tolerances to the process-affected waters among different R. sylvatica tadpole populations. Amphibians such as B. boreas and R. sylvatica were sensitive indicators of effluent quality. Based on the effluents used in this study, wetlands formed from oil sands effluent will not support viable amphibian populations.
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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 | 0.000 | 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".