Identification and Evaluation of Factors Affecting the Eutrophication of Wuxing Lake
Bibliographic record
Abstract
Lake eutrophication is a major problem with water environment around the world.It is of great ecological significance to identify and control the inducing factors of lake eutrophication.This paper explores the causes of the eutrophication of Wuxing Lake from external conditions, sources of nutrients, and the relationship between nutrients and eutrophication.The influencing factors of lake eutrophication were subject to correlation analysis, revealing how much each factor affects the degree of eutrophication.The results show that temperature has the greatest impact on the eutrophication of Wuxing Lake, followed by total phosphorus (TP); current speed is the weakest impact factor.Hence, external conditions have a significant effect on the eutrophication of Wuxing Lake.Nitrogen and phosphorus, as nutrients for algae and other phytoplankton, also contribute greatly to the eutrophication of Wuxing Lake.The research results contribute greatly to the healthy development of Wuxing Lake and the sustainable economic growth of the surrounding regions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 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".