Kinetic analysis of attached growth nitrification in cold climates
Bibliographic record
Abstract
The rate of nitrification within a laboratory-scale Biological Aerated Filtration treatment system at 4 degrees C was investigated during an exposure time of approximately four months (acclimatized experiments). In addition, shock experiments from 20 degrees C to 4 degrees C and from 4 degrees C to 20 degrees C were performed. The acclimatized experiments demonstrated that the exposure time the system remained at low temperature strongly affects the rates of nitrification. Nevertheless, the experiments showed that significant nitrification rates are maintained for up to 115 days at 4 degrees C. The rate of ammonia removal after an exposure time of 115 days at 4 degrees C was shown to be as high as 16% of the rate of removal observed at 20 degrees C. The 20 degrees C to 4 degrees C shock experiment demonstrated a 56% decrease in the rate of ammonia removal. On the other hand, the 4 degrees C to 20 degrees C shock experiment demonstrated an increase in the relative rates of ammonia removal of up to 300% when compared to rates of removal measured after 115 days at 4 degrees C. Thus, although the rates of nitrification have been shown to decrease significantly as a function of exposure time at 4 degrees C, the process has demonstrated important rates of ammonia removal at 4 degrees C for the approximate span of the North American winter.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".