Modeling aerobic carbon source degradation processes using titrimetric data and combined respirometric–titrimetric data: Experimental data and model structure
Bibliographic record
Abstract
Experimental data are presented that resulted from aerobic batch degradation experiments in activated sludge with simple carbon sources (acetate and dextrose) as substrates. Data collection was done using combined respirometric-titrimetric measurements. The respirometer consists of an open aerated vessel and a closed non-aerated respiration chamber for monitoring the oxygen uptake rate related to substrate degradation. The respirometer is combined with a titrimetric unit that keeps the pH of the activated sludge sample at a constant value by addition of acid and/or base. The experimental data clearly showed that the activated sludge bacteria react with consumption or production of protons during aerobic degradation of the two carbon sources under study. Thus, the cumulative amount of added acid and/or base could serve as a complementary information source on the degradation processes. For acetate, protons were consumed during aerobic degradation, whereas for dextrose protons were produced. For both carbon sources, a linear relationship was found between the amount of carbon source added and the amount of protons consumed (in case of acetate: 0.38 meq/mmol) or produced (in case of dextrose: 1.33 meq/mmol) during substrate degradation. A model taking into account substrate uptake, CO(2) production, and NH(3) uptake for biomass growth is proposed to describe the aerobic degradation of a C(x)H(y)O(z)-type carbon source. Theoretical evaluation of this model for reference parameters showed that the proton effect due to aerobic substrate degradation is a function of the pH of the liquid phase. The proposed model could describe the experimental observations with both carbon sources.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".