Algal production and trihalomethane formation potential: an experimental assessment and inter-river comparison
Bibliographic record
Abstract
Trihalomethanes (THMs) are byproducts produced during the disinfection of drinking water. We combined survey and experimental approaches to identify factors that influence THM formation potential (THMFP) in the Ohio River drainage basin. Two surveys of the Ohio River and its five principal tributaries were conducted to characterize spatial variation in THMFP in relation to algal abundance and suspended organic matter. We performed three experiments by placing Ohio River water in 2000-L outdoor mesocosms and manipulating algal senescence and bloom development by shading. Increases in THMFP among high- and low-light and dark tanks suggest that algal production, algal senescence, and possibly photolysis increased THMFP by as much as 50% over 36 days. Comparable yields of THMs (per unit of chlorophyll) were observed in both survey and experimental settings. Comparison of input waters with outputs indicates that the Ohio River at times acts to attenuate downstream transport of THM precursors. Our findings suggest that both watershed-scale and internal processes regulating THMFP should be considered as utilities develop strategies to meet new drinking water guidelines.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".