Wild Amphibian and Wetland Health and Contaminants, Oil Sands Region
Bibliographic record
Abstract
Water chemistry, 26 different metals, and polycyclic aromatic compounds (PACs) were measured at 21 wetland sites where studies of amphibian health are being conducted. The water chemistry measurements (pH, conductivity, total dissolved solids, etc.) are used to further assess water quality, characterize the wetlands studied, and allow for comparisons among the different types of boreal wetlands being monitored. The data show low concentrations of metals, with many of the individual metals at undetectable levels. Two water quality samples, one from 2011 (with an arsenic concentration of 8.27 µg/L) and one from 2012 (arsenic at 6.47 µg/L) from Galoot Lake, located in the Peace-Athabasca Delta, exceeded the guideline for arsenic established for the protection of aquatic life by the Canadian Council of Ministers of the Environment (5.0 µg/L; CCME). However, samples collected from this same location in 2013 (1.29 and 0.78 µg/L) and 2014 (2.21 µg/L) were below the CCME guideline. Passive sampling techniques, such as the deployment of semipermeable membrane devices (SPMDs), are being used in this monitoring program to monitor PACs in boreal wetlands. The highest concentrations of PACs were detected in SPMDs deployed within a 25 km radius of surface mining activity, consistent with the pattern revealed by snow deposition studies of PACs in the region. Field investigations continue to evaluate the health of wild amphibian populations at varying distance from oil sands operations.
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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".