Impact of furfural on the sugar analysis of prehydrolysis liquor of kraft-based dissolving pulp production process using the HPAEC technique
Bibliographic record
Abstract
High performance anion-exchange chromatography with pulse ampero-metric detector (HPAEC-PAD) is a reliable method to systematically determine the sugar contents in pulp and paper waste streams, including bleaching and extraction liquors. We used the same method to determine the sugar content of industrially produced pre-hydrolysis liquor (PHL) from a kraft-based dissolving pulp production process. The analysis showed that the traditional method cannot be applied for sugar analysis, and an improvement on the method was required. In fact, the presence of furfural in the PHL sample was the reason for the required modification. It was noted that the removal of furfural via evaporation could improve the reliability of the HPAEC technique for sugar assessments. If the concentration of furfural was higher than 0.045% (wt.) in the PHL, the error introduced in the sugar analysis was profound. Also, the industrially produced PHL contained more furfural than the laboratory produced PHL under the same hydrolysis conditions. Consequently, the concentration of furfural in the PHL should be taken into account for sugar analysis using the HPAEC technique.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".