Bibliographic record
Abstract
Wood-inhabiting fungi include many molds, wood-staining fungi, and decay fungi. Most of these fungal species can result in economic losses to wood users. Studies on molds, staining fungi, and decay fungi are necessary to be able to control their growth on wood and wood products. In this study, wood-inhabiting fungi were isolated from logs of 3 major Canadian hardwood species: sugar maple, white birch, and yellow birch. Two media were used for isolation. From these 3 wood species, a total of 1198 fungal cultures were obtained from summer- and winter-harvested logs in dry storage and under water sprinkling. The results showed that most fungal species were not host specific and affected all of the wood species tested. Frequently isolated molds were Alternaria alternata, Trichoderma species, and Mucor/Rhizopus (Zygomycota) species, frequently isolated staining fungi were Ophiostoma piceae and Ophiostoma piliferum, a frequently isolated bark saprophyte was Nectria cinnabarina, and frequently isolated decay fungi were taxa of the phylum Basidiomycota. More fungal species were isolated from summer-harvested logs than from winter-harvested logs. Fewer fungal cultures, especially decay fungi, were isolated from logs in early storage than from logs in late storage.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.000 | 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".