Mountain pine beetle associated blue-stain fungi cause lesions on jack pine, lodgepole pine, and lodgepole × jack pine hybrids in Alberta
Bibliographic record
Abstract
Mountain pine beetles ( Dendroctonus ponderosae Hopkins; (MPB)) have spread into lodgepole × jack pine hybrid ( Pinus contorta Douglas × Pinus banksiana Lambert) forests in Alberta and are predicted to spread into jack pine forests. Their success in these forests is uncertain but will be influenced by multiple factors, including the ability of their associated blue-stain fungi to colonize the trees and the health of the encountered trees. Healthy and dwarf mistletoe infected pines at three sites across Alberta (one site per pine species) were inoculated with three isolates each of Grosmannia clavigera (Robinson-Jeffrey and Davidson) Zipfel, de Beer and Wingfield and Ophiostoma montium (Rumbold) von Arx. Both fungi grew and caused lesions on all hosts, suggesting that MPB will not be limited by a lack of fungal growth. Both fungi caused longer lesions in jack and hybrid pines than in lodgepole pines, indicating that susceptibility varies among hosts and is greater in the novel systems than in the co-evolved one. G. clavigera caused longer lesions than O. montium in hybrids and lodgepole pines, while the two species caused similar-sized lesions on jack pine. Intraspecific variation was high in G. clavigera, with one isolate producing much shorter lesions than the other two. Dwarf mistletoe infestation had little effect on infection lesion length.
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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 | 0.001 | 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) | 0.000 | 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".