Three Gorges Dam: Influence of water quality on the density of schistosome-transmitting Oncomelania hupensis in the Dongting Lake Area, China
Bibliographic record
Abstract
Abstract Schistosomiasis is a severe infectious disease and snails contribute to its transmission. Many factors, including water quality, affect the distribution of snails. This study collected the data on snails and indicators related to water quality in the Dongting Lake area from the period of 1998–2014. Water quality indexes such as permanganate index (CODMn), five-day biochemical oxygen demand (BOD5), total nitrogen (TN) and total phosphorus (TP) in correction with snail density were first examined using the Mann-Kendall (M-K) test. And then a Bayesian spatial-temporal model was constructed to evaluate the effect of water quality on snail density adjusting for meteorological factors and spatial-temporal variations. The results showed that the density of snails in the Dongting Lake area was influenced by water quality. The growth and reproduction of snails were promoted at a low pollution concentration, while inhibited at a high pollution concentration. These findings might provide valuable insights for relevant authorities to monitor the quality of water environment through investigating snail density.
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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 | 0.001 |
| 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 | 0.000 | 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".