Biodegradation of spent pulping liquor lignins under mesophilic and thermophilic anaerobic conditions
Bibliographic record
Abstract
We conducted a laboratory scale feasibility study on the anaerobic treatment of spent pulping liquor effluent in upflow anaerobic sludge bed reactors. Tests showed that, in spite of high levels of sodiuk and lignin in the liquor, up to 80% of CODs can be successfully removed at a specific removal rate of 0.22 g and 0.57 g COD g⁻¹ VSS d⁻¹ for mesophilic and thermophilic conditions, respectively. Throughout the experiment, lignin accumulation occurred in the mesophilic, but not in the thermophilic reactor. Lignin measurements confirmed that up to 59% of lignin was degraded under thermophilic conditions. Higher activity of thermophilic biomass coupled with higher solubility, and therefore bioavailability of lignin under thermophilic conditions, contributed to the observed lignin removal.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 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".