Chemical characteristics and acid sensitivity of boreal headwater lakes
Bibliographic record
Abstract
Boreal ecosystems in northwest Saskatchewan may be threatened by acidification as this area is downwind of atmospheric emissions sources from regional oil sands mining operations. To evaluate the status of lakes in this region, a survey of 259 headwater lakes was conducted during 2007–2008 within ~300 km of Fort McMurray, Alberta. Acid sensitivity by ecoregion increased from Mid-Boreal Upland to Churchill River Upland to Athabasca Plain, with 60 % of lakes classified as sensitive (50–200 μeq L–1 acid neutralizing capacity (ANC)), and 8 % as very sensitive (<50 μeq L–1 ANC) to acid deposition. Organic anions dominated the acidity balance in most lakes, but non-marine sulphate varied positively with lake elevation and % upland cover (r2 = 0.24). Base cation concentrations (Ca, Mg, K, Na) were correlated with % deciduous forest in the catchment area (r2 = 0.33), while dissolved organic carbon (DOC) was related most strongly to % bog and lake flushing variables (r2 = 0.53). Variation in runoff coefficients derived by isotope mass balance corresponded with catchment area attributes that proxy controls on evaporation, infiltration and storage, and showed some ecoregional differences. The findings have implications for assignment of runoff values required to calculate critical loads of acidity. Although acidification appears not to be significantly advanced, many dilute oligotrophic lakes with pH 6.0 to pH 6.5 are vulnerable to acid deposition.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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".