Nutrient Consumption and Pigmentation of Deep and Surface Colonizing Sapstaining Fungi in Pinus contorta
Bibliographic record
Abstract
Summary In this paper, we examined the ability of deep and surface staining fungi to utilize wood tissue nutrients. Fungal isolates were inoculated onto fresh billets and γ-sterilised sawnwood, both from Pinus contorta, and also onto defined nutrient media. The wood samples were assessed for host viability, fungal growth and nutrient status. The results indicated that the most aggressive sapstain species on fresh logs was Ceratocystis coerulescens, followed consecutively by Leptographium spp., Ophiostoma minus, O. piliferum, O. piceae, O. setosum, O. pluriannulatum and Aureobasidium pullulans. HPLC analysis of soluble sugars in fungal-infected wood indicated that mannose was the most depleted sugar, followed by glucose. Lipid analysis of infected wood indicated that Leptographium spp. and C. coerulescens greatly reduced the triglyceride fraction and that there was a wide spectrum of consumption of triglyceridederived fatty acids between the fungi. On defined media, the carbon source mannose led to the darkest pigmentation for all tested fungi. For C. coerulescens, the order of pigmentation intensity for the remaining tested carbon sources was reversed when compared to the other fungal species.
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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 | 0.000 |
| 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".