ISSN online 0718-221X COMPATIBILITY OF FOUR EASTERN CANADIAN WOODS WITH GYPSUM AND GYPSUM-CEMENT BINDERS BY ISOTHERMAL CALORI-
Bibliographic record
Abstract
In order to determine the feasibility of manufacturing wood-gypsum and wood-gypsum-cement particleboards, the hydration reactions of four Eastern Canadian wood species with gypsum and Port-land cement were studied. The compatibility of hot water extracted and raw wood particles with both gypsum and a gypsum-Portland cement mixture were determined for jack pine, balsam fi r, aspen and white birch by isothermal calorimetry. The four species were found to be compatible and suitable for the manufacturing of inorganic-bonded wood composite boards on the basis of the compatibility factor. The hot water extractive content was low in the four species and did not have a consistent impact on the compatibility factor. Nevertheless, hot water soluble extractives did have an impact on the time required to reach the maximum heat fl ux, delaying it to undesirable levels particularly in the case of balsam fi r mixed with neat gypsum. However, the effect of balsam fi r on neat gypsum hydration was markedly reduced by the addition of 30 % Portland cement. Hot water extraction of the wood particles and the addition of Portland cement to the wood-gypsum mixture signifi cantly reduced the time requi-red to reach the maximum heat fl ux. The gypsum-cement mixture was less sensitive to the inhibitory effect of wood than neat gypsum.
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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 | 0.001 | 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) | 0.005 | 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".