Should activated sludge models consider influent seeding of nitrifiers? Field characterization of nitrifying bacteria
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study revealed the presence of nitrifying bacteria in influent municipal wastewaters reaching full-scale biological wastewater treatment plants. Respirometric assays showed that the influent nitrifiers were active following a 5- to 8-hour period of metabolic induction. Diversity analyses by pyrosequencing of functional gene PCR (polymerase chain reaction) amplicon suggested that the nitrifiers in the influent stream likely seeded activated sludge bioreactors since the most abundant operational taxonomic units in the influent and mixed liquor were the same. Based on the estimated seeding intensity of 0.3 g of nitrifiers per day per gram of nitrifiers already present, the absolute minimum solids retention time (SRT) was reduced by approximately 56% at 5 °C as compared to non-seeding conditions. This can have important repercussions on the design and sizing of bioreactors operating in cold climates and calls for a need to fine-tune process modelling by considering the contribution of autotrophic nitrifying biomass from municipal influent streams.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it