Susceptibility of winter cut red pine (<i>P. resinosa</i>) stumps to heterobasidion root disease (HRD) infection
Bibliographic record
Abstract
Heterobasidion root disease (HRD), a destructive disease of conifers, is a growing management concern. Infection by HRD fungus ( Heterobasidion irregulare) most often occurs when spores, usually produced when temperature is between 5 and 32 °C, land and germinate on freshly cut surfaces. Older stump surfaces are generally unsuitable for colonization, likely due to changes in chemical and physical properties of wood and competitor fungi that limit HRD infection. Stump protectants are effective but not used or recommended in subfreezing temperatures during winter when spores are less common. This study evaluated the potential for older cut stump infection following snowmelt in spring via inoculation of disks collected 7 weeks following initial thinning and exposed to extensive subfreezing temperatures. We found that a surprising number of disks (40%) were successfully colonized with H. irregulare. More research on potential for winter cut conifer HRD infection is warranted as are steps to limit this potential.
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) | 0.000 | 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".