Cause of pH decline in stream water during spring melt runoff in northern Sweden
Bibliographic record
Abstract
This study has sought to distinguish the anthropogenic and natural factors that drive episodic pH decline in northern Sweden. Approximately 600 stream water chemistry samples from 12 streams during the spring melt runoff of 1997 and 1998 were collected. Although the acid deposition levels of the region are relatively low (2-4 kg SO 4 2- -S·ha -1 ·year -1 ), the pH decline in all of the almost two dozen spring melt events ranged from nearly 1 to 3 pH units. By using the sum of base cation concentration as a dilution index and an organic acid pH model, the sources contributing to the pH decrease were quantified. For a majority of the spring melt events, organic acids contributed over 75% of the acidity at peak runoff (minimum pH). In only three of the monitored events was the anthropogenic SO 4 2- contribution as high as that from natural sources. NO 3 - did not contribute to the pH decline during spring melt in this study. An interannual variation was observed that was probably due to a larger anthropogenic deposition load during the winter of 1997-1998 and a more rapid snowmelt during the spring of 1998.
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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 | 0.000 | 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) | 0.000 | 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".