Characterization of the diffusion of organic fungicides with amine oxides in white pine and white spruce
Bibliographic record
Abstract
Wood products, especially those used in outdoor conditions, can be damaged by dimensional changes and decay fungi. It is therefore advised to use impregnation treatments to mitigate these hazards. While the potency of the chemicals employed in the treatments is important, characterization of the treatments is also crucial to ensure deep and durable protection. In this study, eastern white pine (Pinus strobus L.) and white spruce (Picea glauca (Moench) Voss) were impregnated with propiconazole and 3-iodo-2-propynyl butylcarbamate (IPBC) through diffusion. Instead of using pressure treatments, the samples were dipped in solutions containing amine oxides, which can diffuse into the wood. The treatments were characterized by the mass of fungicide impregnated, fungicide leaching, and the impregnation depths of both the fungicides and the amine oxides. It was found that the treatment impregnated slightly more than 0.040 kg/m3 of both fungicides, meeting EU standards. It was also shown that the presence of amine oxides slightly prevented the leaching of the fungicides in white pine. The penetration of the amine oxides was several millimeters deep in all directions, but the penetrations of the fungicides were much shorter and only longitudinal.
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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) | 0.000 | 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".