FUNGI COLONIZING DOUGLAS-FIR IN COOLING TOWERS: IDENTIFICATION AND THEIR DECAY CAPABILITIES
Bibliographic record
Abstract
This study was performed to identify microfungi isolated from chromated copper arsenate (CCA) treated-Douglas-fir members in cooling towers, and to test for their capacities to cause weight loss, anatomical damage, and strength losses in Douglas-fir and Keruing heartwood. Among 26 fungal species isolated, Acremonium sp., Fusarium spp., Trichoderma spp., Phialophora spp., and Alternaria alternata were most frequently isolated, constituting approximately 75% of all isolates. Half of the fungi, representing about 60% of all isolates, caused soft-rot damage. Microscopic examination revealed that most of the fungi eroded the cell wall (Type 2 damage), and soft-rot types did not differ with wood species. Strength reductions by fungal attack were not significant compared to controls although one fungal species (Monocillium sp. KUC 3016) produced significant strength loss on Douglas-fir, and three species (Gonabotrys simplex, Phialophora mutabilis KUC 3022, and Phialophora mutabilis KUC 3039) caused significant strength loss on Keruing. The results indicate that some soft-rot fungi can affect wood properties significantly, and their potential to affect the service life of wood members in cooling towers must be considered.
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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".