Evaluating the Use of Humidification Systems During Heat Treatment of MPB Lumber
Bibliographic record
Abstract
Lumber produced from lodgepole pine logs attacked by the mountain pine beetle (MPB) infestation in British Columbia, Canada, exhibits very low initial moisture content (MC). Depending on the time elapsed since attack, the initial MC can be significantly lower than the fiber saturation point (FSP ∼30%). Lumber exhibiting 19% MC or less is considered ready for the dimension lumber market and does not necessarily need to be kiln dried. However, phytosanitary regulations require that lumber products be heat treated before delivery to customers. For lumber already quite dry, the Canadian Food Inspection Agency (CFIA) kiln drying/heat treatment schedules may be too long and can result in overdrying. For the significant volume of MPB lumber with an initial MC below 19%, the use of low-pressure steam or cold water spray could allow this lumber to be heat treated without causing further drying. This approach should result in improved lumber quality because overdrying would certainly be minimized and probably eliminated. In this study, two sorts (dry and wet sort) of MPB lumber were dried in a pilot laboratory kiln humidified with low-pressure steam or cold water spray. Twelve drying runs were carried out. The experimental results indicated that the times to reach the temperature of 56°C in the core of the lumber were shortened and warp for the dry-sort lumber group was reduced when the low-pressure steam or cold water spray system was used. Thus, for MPB lumber with a low initial MC, the utilization of lower pressure steam or cold water spray during heat treatment represents an attractive alternative to reduce kiln residence time, minimize or eliminate overdrying, and improve lumber quality.
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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) | 0.001 | 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".