Evaluation of Surface Water Quality with Biochemical Assays
Bibliographic record
Abstract
The increasing demands on our water resources require the rapid evaluation of water quality of surface waters near urban areas. The purpose of this study was to examine urban surface waters by rapid and cheap two biochemical-based assays: the peroxidase toxicity (Perotox) test and the prebiotic pyruvate-glyoxalate (pyr-glyox) pathway for malate synthesis. Surface waters samples were extracted on C18 solid phase cartridge and eluted with ethanol. The evaluation of plastic polymers was also determined as a proxy of water pollution. The data revealed that plastic materials were found in both small and large urban areas and were lower downstream a municipal treated effluent. The prebiotic assay for malate production was significantly blocked by water extracts for the most populated city (1.8 million population) and in the corresponding municipal effluent dispersion plume. For the Perotox assay, the same results were obtained for the surface water extracts. An add-on of the Perotox assay included a DNA protection index for the detection of potential genotoxic compounds. The DNA protection index was significantly increased at the most populated city and was lost in the treated municipal effluent dispersion plume. In conclusion, two highly sensitive biochemical assays are presented to quickly monitor changes in water quality from urban pollution where stronger impacts were found from highly populated cities and in some case in the corresponding wastewater dispersion plume.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".