Specificity and potential applications of the biochemical acidogenic potential method for the anaerobic characterization of wastewater
Bibliographic record
Abstract
The biochemical acidogenic potential (BAP) testis an anaerobic characterization method for wastewater. Fermentable organic fractions are obtained through modeling BAP test results. This method was compared to more common fractionation methods such as settling, coagulation, and respirometry, but no direct relationship was found. Biochemical acidogenic potential testing was thus considered to bring new and complementary information. The settleable matter accounted for approximately 50% of the fermentable matter, with a rate comparable to that of aerobic hydrolysis, suggesting a potential assimilable carbon source that could be liberated in sewers or in anaerobic processes. It was also observed that respirometry could underestimate the amount of fermentable substrates while overestimating that of hydrolyzable matter and of heterotrophic biomass involved in anaerobic processes. The BAP fractions are related to the wastewater capacity to produce volatile fatty acids, which are the main substrates of the microorganisms responsible for enhanced biological phosphorus removal (EBPR). The potential contribution of the BAP fractionation to assist the design, operation, and modeling of the activated-sludge EBPR processes was discussed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".