Aboveground Decay Resistance of Selected Canadian Softwoods at Four Test Sites after 10 Years of Exposure
Bibliographic record
Abstract
Abstract Aboveground field performance data are needed to help users select appropriate materials, assist in the development of evidence-based codes and standards, and support the development of new export markets. A review of the literature in the early 2000s revealed that there was very little hard data on the performance of North American naturally durable wood species, particularly for aboveground applications. Field tests of six Canadian wood species reputed to have moderate to high natural durability were therefore installed in test out-of-ground contact in the autumn of 2004 and spring of 2005 at two test sites in Canada and two in the United States. Decay results are reported after 10 years. The test site with the fastest aboveground decay rate was in Hawaii. Above ground, yellow cedar (Callitropsis nootkatensis) and western red cedar (Thuja plicata) were the most consistently durable at all four test sites. However, it would not have been possible to predict the relative performance of naturally durable species in one climate and location from their relative performance in another climate and location. The presence of sapwood was associated with more severe decay, although it was unclear whether the presence of sapwood increased the risk of decay in the adjacent heartwood. There was no substantial difference between decay in old-growth and second-growth samples above ground. The presence of a coating applied to decking had some protective effect against decay at the less aggressive test sites.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".