Measurement of potential activity of fixed nitrifying bacteria in biological filters used in drinking water production
Bibliographic record
Abstract
Nitrification during biological filtration is being used more and more in drinking water production to remove ammonia, which can be the source of several water quality problems during distribution. In this process, ammonia is converted into nitrite and then into nitrate by fixed autotrophic nitrifying bacteria. The purpose of this work was to develop a technique to estimate fixed nitrifying biomass (sum of ammonia- and nitrite-oxidizing populations). The quantification of autotrophic nitrifying biomass was determined by potential nitrifying activity measurement. The production of oxidized forms of inorganic nitrogen (nitrates and nitrites) was measured after an incubation of 2 cm3 of colonized solid support in the presence of a 5-ml nitrifier medium containing 10 mg N-NH4 L−1 for 30 min at 32°C. The production rate of oxidized nitrogen in optimal conditions was measured and converted into nitrifying biomass by using the maximum specific oxidizing activity. This technique was shown to be appropriate for conditions encountered in the biological filters used in drinking water production and sufficiently simple to be used for routine measurements. Journal of Industrial Microbiology & Biotechnology (2000) 24, 161–166.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".