Harvesting Productivity and Cost of Clearcut and Partial Cut in Interior British Columbia, Canada
Bibliographic record
Abstract
ABSTRACT: Clearcutting has been the dominant harvesting method i n British Columbia (representing 95% of the total areaharvested annually). However forest managers are increasingly recommending the use of alternative silvicultural systems andharvest methods, including various types of partial cutting, to m eet ecological and social objectives. In this study we comparedharvesting productivity and harvesting costs between treatments th rough detailed and shift level time studies in 300-350 year-oldInterior Cedar-Hemlock stands in British Columbia, Canada. Recommendations for improving operational planning/layout and theimplementation of clearcut and partial cutting silvicultural systems were made. Harvesting costs varied in the ground-based clearcuttreatments from $10.95/m 3 - $15.96/m 3 and $16.09/m 3 - $16.93/m 3 in the group selection treatments. The ground-based groupretention treatment had a cost of $13.39/m 3 , while the cable clearcut had a cost of $15.70/m 3 . An understanding of the traditionaland alternative wood products that could be derived from the ha rvested timber was imperative to increasing the amount ofmerchantable volume and reducing the corresponding harvesting cos ts. Stand damage was greatest in t he group selection treatments;however, mechanized felling showed an increase in stand damage over manual felling while grapple skidding showed a decreasein skidding damage compared to line skidding.Keywords: Alternative harvesting, Clearcutting, Partial cutting, Western red cedar, Stand damageJournal of Forest ScienceVol. 24, No. 1, pp. 1~14, April 2008
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".