Evaluation of decay resistance for steam-heat-treated wood
Bibliographic record
Abstract
The objective of this research was to evaluate the influence of steam-heat treatment on the decay resistance of Chinese white poplar and Chinese fir wood against the wood-rotting fungi Gloeophyllum trabeum (Pers.:Fr.) Murrill. The Chinese white poplar and Chinese fir specimens were obtained from Shandong and Hunan provinces, respectively. They were steam-heat-treated at 170, 185, 200, 215, or 230 oC with time duration of 1, 2, 3, 4, and 5 hrs in an air-tight chamber that comprised less than 2 per cent oxygen. According to the standard GB/T 13942.1-92, the decay resistance experiments were completed with the wood-rotting fungi G. trabeum on an agar block test with 12-week incubation. The results of steam-heat treatment indicated that, compared to a weight loss of 56% for untreated samples, a weight loss of 45% decreased to just 2% for Chinese white poplar with an increase in temperature from 170 to 230℃. No weight loss was observed in the steam-heat-treated China-fir heartwood, sapwood, and untreated sapwood specimens, while only a weight loss of 4.739% in untreated China-fir heartwood specimens was found.
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".