Bibliographic record
Abstract
The utilization of mountain pine beetle (MPB) killed wood and the diversification of the global trading market have been issues in the British Columbia’s forest industry. Currently, almost half of the lodgepole pines in BC are attacked by MPB. The infestation of lodgpole pines is not only losing economic values but also damaging ecosystems and environments. MPB killed wood appears as blue stain in sapwood. However, the wood remains unaffected on the mechanical property, so it can be still used for producing many types of value-added products. The major challenges of using MPB killed wood are the extreme dryness, short shelf life, and limited markets. The Canada’s forest industry has relied heavily on the U.S. market. The reliance of one country has shown serious problems by experiencing the recent global economic crisis. China’s forest industry has become the most important client to the BC’s forest industry by offsetting the decreased exports to U.S. Many markets have been examined to discover the potential markets for the MPB killed wood products. As a result, there should be markets specially aimed to utilize the MPB killed wood. However, there are uncertainties in optimizing processing wood products from MPB-killed wood and the long term fibre supply.
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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 | 0.003 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.061 | 0.004 |
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".