Development of blue stain in mechanically harvested Scots pine (<i>Pinus sylvestris</i>) logs during storage
Bibliographic record
Abstract
Blue stain is a type of discoloration that considerably lowers the aesthetic qualities of wood. During harvesting, fungal inoculum finds its way into the wood through places of cutting, delimbing, and damage to the tree stem. The development of peripheral blue stain in the logs of Scots pine (Pinus sylvestris L.) due to damage by a harvester head was investigated, using logs felled and delimbed with a chainsaw as reference. The development of blue stain was related to the age class of the stand, the date of felling, and the microclimatic conditions of the wood storage place. The mean surface area of blue stain in logs produced with the harvester was almost 35 cm2, approximately 30% larger than that of the reference logs. In stands of the fourth age class (diameter at breast height 32 cm), the surface of blue stain was more than two times larger than that of stands of the third age class (diameter at breast height 24 cm). The mean area of blue stain in wood stored after spring felling (19.3 cm2) was about 50% of that after summer felling (38.2 cm2). In particular, the development of blue stain in logs obtained with a harvester was visible between weeks 6 and 9 after spring felling and between weeks 3 and 6 after summer felling. For both felling dates, the range of blue stain depended less on air temperature around the wood stack and depended more on the duration of 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) | 0.000 | 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".