Evaluating Wood Preservatives for Use with OSB. Part 1: Compatibility with Typical Resin Systems
Bibliographic record
Abstract
Termites cause significant damage to wood-based structures in the Southeastern Unites States of America and Hawaii. Commonly used composites, such as waferboard must contain wood preservatives when used in these areas. In-line addition during blending of the furnish is the preferred approach for incorporating biocides into such composites.The effects on resin behaviour when adding three fungicides and two termiticides in different quantities to eight commonly used phenol-formaldehyde (PF) based resin and one polymeric diphenylmethane diisocyanate (pMDI) resin typically used for OSB and other composite manufacture, was assessed by monitoring the changes in viscosity and gelation time. The biocides were provided by Dr. Wolman GmbH, Germany. The termiticides were organics solutions based on bifenthrin, chlorfenapyr, and 5-amino-1-[2,6-dichloro-4-(trifluoromethyl)phenyl]-4-[(1R,S)-(trifluoromethyl)sulfinyl]-1H-pyrazol-3-carbonitrile (ATTC), while the fungicides were aqueous solutions based on K-HDO (N-cyclohexyldiazeniumdioxy potassium) or K-HDO and fenpropimorph.The fungicides were generally less compatible with the resins than the termiticides, in that they would likely to require some modification to the process used to manufacture the OSB with PF resin, and were found to be incompatible with the pMDI-resin. The bifenthrin based termiticide was compatible with 6 of the 8 PF-resins tested at the concentrations examined. The chlorfenapyr based termiticide was less compatible, (only 3 of the PF-resins) while the remaining 5 PF-resins were incompatible at any concentration. The ATTC based termiticide was compatible with only three of the PF-resins.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".