Assessing annual trends, monthly fluctuations and between‐station relationship of sulphate deposition in the Turkey Lakes Watershed
Bibliographic record
Abstract
Water deposition of pollutants can be a good indicator of both air and water quality in a region of interest. In this paper, we study sulphate deposition change over time in a network of multiple monitoring stations in the Turkey Lakes Watershed in Sault Ste. Marie, Ontario, Canada. As there is generally substantial correlation among sulphate deposition observed over time and space, we incorporate temporally correlated multivariate random effects into Gamma regression models to account for the temporal dependence within each station and between‐station dependence in space. We applied our new approach to analyse monthly average sulphate depositions between 1983 and 2003. We found the observed increase of sulphate deposition between 1994 and 2003 was not significant, that is, annual trends in sulphate deposition had stabilized since 1994. Our analysis also quantified increasing sulphate deposition from upstream to downstream and its monthly fluctuations from higher in winter to lower in summer. Understanding of these sulphate deposition trends is of great policy relevance to environmental conservation. Copyright © 2016 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".