Long-Term Effects of Ecological Factors on Nonpoint Source Pollution in the Upper Reach of the Yangtze River
Why this work is in the frame
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Bibliographic record
Abstract
Nowadays, nonpoint source pollution has been a dominant cause of water quality deterioration and eutrophication. For large basins, long-term effects of ecological factors on nonpoint source pollution are significant and have gained worldwide attention. Yangtze River is the largest river in China, and water environment protection of its upper reach is crucial to maintain the whole river health and the Three Gorges Project successful operation. The objective of this study is to reveal the effects of ecological factors on nonpoint source pollution in the upper reach of the Yangtze River during the period from 1960 through 2003 by the Improved Export Coefficient Model and the Nutrient Losses Empirical Model. The results indicated that during those decades the effects of ecological factors on dissolved pollutants were constant whereas those on sediment as well as absorbed pollutants changed slightly and decreased obviously after 2000. Comparing to anthropogenic factors, ecological ones had a dominant influence on sediment and absorbed pollutants. As for load intensities, long-term effects of ecological factors on dissolved pollutants hadn’t changed much, while those on sediment as well as absorbed pollutants was increasingly significant and then reached an ultimate in 1980. Atmospheric deposition, grassland as well as forest were important sources of dissolved nitrogen export, nevertheless, grassland and forest were the main export areas of dissolved phosphorus, sediment as well as absorbed pollutants. The study would facilitate the source identification and nonpoint source pollution control in the upper reach of the Yangtze River to improve water quality.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it