Use of β-<scp>D</scp>-galactosidase and β-<scp>D</scp>-glucuronidase activities for quantitative detection of total and fecal coliforms in wastewater
Bibliographic record
Abstract
Two enzymatic methods based on the measurement of the β-D-galactosidase activity of total coliforms and the β-D-glucuronidase activity of Escherichia coli were used to assess coliform levels in wastewater alongside traditional culture-based techniques, which can be biased by the aggregation of bacteria or their attachment to particles. Enzymatic methods were precise (i.e., coefficients of variation were 9%15%), rapid (response in 20 min), and correlated well (in log units) with traditional techniques for raw and treated sewage (r2> 0.75). They were used for rapid assessment of coliform removal efficiency in two different wastewater treatments. These methods could be useful for the estimation of the abundance of coliforms in domestic sewage and their removal by wastewater treatment processes.Key Words: wastewater, total coliforms, fecal coliforms, β-D-galactosidase activity, β-D-glucuronidase activity.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".