The Search for Durable Exterior Clear Coatings for Wood
Bibliographic record
Abstract
The goal of a durable exterior clear coating has eluded generations of coatings technologists, despite long-standing desire amongst the public for such a coating. The journey towards this goal initially focused on modifications to coating formulation, but took a completely different direction when it was found that a UV-transparent silicone clear coating on wood modified with chromic acid met consumer expectations of coating durability. This finding sparked world-wide interest in wood pre-treatments as a way of enhancing the durability of clear coatings. This interest initially focused on transition metal compounds, but has now shifted in the direction of organic and inorganic photostabilizers or even more drastic pre-treatments. Pre-treatments that dimensionally stabilize wood, protect it from microbial degradation and photostabilize lignin, when combined with flexible, photostable, coatings provide the next way-stop on the journey towards achieving the goal of durable exterior clear coatings for wood. This paper reviews this journey, drawing upon our research and that of other groups who have focused on this elusive goal.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".