Chlorine and ash removal from salt-laden woody biomass by washing and pressing
Bibliographic record
Abstract
Over 11 million cubic meters of timber were harvested from the coastal forests of British Columbia in 2017. For transport, the logs are usually floated in the water and towed along the coastal waters along Fraser River to sawmills. The submerged timber’s chlorine content is up to 100 times higher than the timber harvested from inland. The sawmill residues leftover from cutting the salt-laden timber are unsuitable to be burned in boilers. In this study, ground sawdust, bark, and wood chips of three species from the Lower Mainland: Douglas fir, hemlock, and western red cedar, as well as spruce-pine-fir (SPF) from Vancouver Island, were washed for 5 min using tap water under constant stirring and pressed on a flat metal bed for 30 s using a mechanical hydraulic press. The chlorine content dropped from 2,000-24,000 ppm to below 700 ppm db (dry basis). The low salt biomass meets the ISO 17225-2 quality standard for wood pellets. The chlorine removal efficiency of this treatment method was 88-95%. The reduction in ash content of the washed and pressed samples ranged was 45-85% of the ash in the untreated biomass.
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.
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) | 0.001 | 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".