Envelope protection of preservative-treated pine decking with modified low molecular weight phenol formaldehyde resin
Bibliographic record
Abstract
Preservative-treated pine is commonly used for outdoor decking in Canada and the United States, but its attractive appearance is lost when it is exposed to the weather. Wood can be protected from ‘weathering’ using low molecular weight phenol formaldehyde (LMW PF) resin. In this thesis, I combine preservative treatments and modification of wood with PF resin to try to develop wood decking with superior resistance to weathering. My hypothesis is that shallow ‘envelope’ modification of treated wood with LMW PF resin containing photostabilizers and wax additives will protect the appearance of preservative-treated pine decking exposed to natural weathering. I first screened different additives for their ability to protect wood from the adverse effects of weathering. The best additives were selected for further testing. Preservative-treated Scots and southern pine boards were modified by dipping or vacuum impregnation with modified PF resins, and modified and treated boards were exposed to the weather. Envelope modification restricted checking of untreated pine boards weathered for two years. Degradation of modified boards was shallow and easily cleaned off. Underneath the weathered grey layer, the colour of PF-modified wood was retained. Envelope modification with different PF resin formulations also protected treated boards weathered for six months. Ferric chloride was a more effective additive than a lignin stabilizer for most substrates (treated or untreated). The dark colour of PF/ferric-modified wood masked mould. The different PF resins I tested improved the performance of treated wood to varying degrees, but their effectiveness depended on the substrate they were applied to. I conclude that: (1) envelope modification with PF and modified PF resins is able to protect treated decking from the adverse effects of weathering; (2) vacuum impregnation with PF resin is a better method than dipping at creating an effective weather-resistant envelope at the surface of treated wood decking; (3) PF and additives need to be tailored to suit different preservative-treated woods; (4) PF modification shows promise as a finishing process to enhance weathering resistance of treated wood.
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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".