Effects of Long Exposure to Low Temperatures on Nitrifying Biofilm and Biomass in Wastewater Treatment
Bibliographic record
Abstract
Attached growth biological treatment systems are a promising solution to ammonia removal in cold-temperature climates. Environmental scanning electron microscopy (ESEM) and confocal laser scanning microscopy in combination with fluorescent in situ hybridization (FISH) was used to investigate the effects of 4 months of exposure to 4 degrees C on nitrifying biofilm and biomass. These molecular and microscopic methods were modified to minimize loss of mass and distortion of in situ perspectives. Environmental scanning electron microscopy revealed that nitrifying biofilm did not exhibit significant changes in volume with exposure to 4 degrees C. Confocal laser scanning microscopy in combination with FISH showed that the number of ammonia-oxidizing bacteria (AOB) cells present in the biofilm was statistically consistent during exposure to 4 degrees C. The RNA content of AOB cells remained sufficient for FISH enumeration. The number of nitrite-oxidizing bacteria cells remained steady during exposure to 4 degrees C; however, the RNA content of the cells appeared to decrease with exposure to 4 degrees C, thereby preventing their enumeration using FISH.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".