A distillery by-product as an external carbon source for enhancing denitrification in mainstream and sidestream treatment processes
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
The use of fusel oil as an 'alternative' carbon source for denitrification in the mainstream and sidestream treatment processes was studied. Research comprised two kinds of batch experiments as well as acclimation of process biomass to external carbon sources. In the conventional nitrate utilization rate (NUR) measurements (one-phase experiments with non-acclimated biomass), the NUR with fusel oil was 1.4-1.7 g N/(kg VSS·h which was comparable to NUR with ethanol and with slowly biodegradable fraction of the settled wastewater. When fusel oil was added at the beginning of the anoxic phase, preceded by an anaerobic phase (in two-phase experiments with non-acclimated biomass), the NURs of 2.5-2.9 g N/(kg VSS·h) were comparable to the tests without the addition of any external carbon sources. The addition of fusel oil and ethanol resulted in a significant enhancement of the denitrification efficiency in lab-scale sequencing batch reactors treating sludge reject water. The NURs continuously increased from below 1 g N/(kg VSS·h) to over 10 g N/(kg VSS·h) over the entire 4-week operational period, indicating gradual acclimation to the substrate. The overall total N removal efficiency reached ∼90%.
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 | 0.000 |
| 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 it