Modeling bioaugmentation with nitrifiers in membrane bioreactors
Bibliographic record
Abstract
Bioaugmentation with nitrifiers was studied using two pilot-scale membrane bioreactors, with the purpose of assessing the suitability of state-of-the-art activated sludge models (ASMs) in predicting the efficiency of bioaugmentation as a function of operating conditions. It was demonstrated that the temperature difference between seeding and seeded reactors (ΔT) affects bioaugmentation efficiency. Experimental data were accurately predicted when ΔT was within a range of up to 10 °C at the higher range, and when the temperature was significantly lower in the seeded reactor compared to the seeding one, standard ASMs overestimated the efficiency of bioaugmentation. A modified ASM, capable of accurately representing the behavior of seeded nitrifying biomass in the presence of high ΔT, would require the inclusion of the effect of temperature time gradients on nitrifiers. A simple linear correlation between ΔT and the Arrhenius coefficient was proposed as a preliminary step.
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.
How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".