Financial and Economic Analyses of Conventional and Reduced Impact Harvesting Systems
Bibliographic record
Abstract
This paper examines the various committed new technology and improve logging activities ascribed in the ‘Logfisher’ Practice (LP) rather than Conventional Practice (CP). The result of cost analysis shows that the cost constitutes under LP is higher than under CP. Incremental average per ha total cost rose by 46.86% to RM13,576/ha. While the incremental average per m3 total cost increased by 57.41% to RM267.80/m3. Hence, CP was slightly more profitable and exceeds the Net Present Value (NPV) of LP. Similarly, the Benefit-Cost Ration (BCR) for CP is better than LP. On the other hand, the result of the economic analysis of 40-year period showed that the LP system (NPV = RM9302/ha) provided a higher level of overalls benefits and welfare to the society as a whole as opposed to CP (NPV = RM8497/ha).
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".