Evaluation of <i>Cryptomeria japonica</i> forest management based on wood production and carbon emission reduction in Yamagata Prefecture, Japan
Bibliographic record
Abstract
With respect to carbon emissions in the context of climate change, a trade-off occurs between the carbon fixation and timber production functions of forests. Through this study, we aimed to clarify the relationship between the two functions by comparing harvesting plans for maximising timber production and carbon emission reduction effects at a privately owned sugi ( Cryptomeria japonica) forest in Tsuruoka City, Yamagata Prefecture, Japan. When formulating the harvesting plans, we included unreforested clearcuts as an option and assumed the natural regeneration of broadleaf forests in unreforested clearcuts. Reduction of carbon emission effects was evaluated based on carbon stocks in forest biomass, harvested wood products, and substitution effects, which we evaluated using static and dynamic substitution effect approaches. The results showed that even when the dynamic substitution effect was used, no trade-off occurred between timber production and carbon emission reduction until 2050; however, a trade-off was impending in the long run. This result supports Japan’s timber utilisation promotion policy to achieve carbon neutrality by 2050.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".