Residual Tree Damage Along Forwarder Trails from Cut-to-Length Thinning in Maine Spruce Stands
Bibliographic record
Abstract
Abstract In Maine and adjacent eastern Canadian provinces, cut-to-length harvesting has emerged as an ecologically attractive method of thinning conifer plantations and natural stands. Yet regional information on the extent of residual stand damage associated with this system is lacking. Eight naturally regenerated red spruce (Picea rubens) stands in northern Maine were studied; all stands were thinned in 1997–1998 with a processor and forwarder combination. Field methods consisted of examining individual trees near forwarder trails for bole damage and measuring the size and aboveground height of individual wounds. The frequency of trees damaged in each stand ranged from 25–46%. The four sites with the highest pre- and post-cut tree densities generally had the greatest number of damaged trees. Trees located along forwarder trails were more frequently damaged than nontrailside trees. The average individual wound size ranged from 2.6–8.7 in.2; 82–98% of the wounds in each stand were less than or equal to 10 in.2 in size. Usually, wounds on trailside trees were not significantly larger than wounds on nontrailside trees. Regardless of tree location, most wounds were located 3–6 ft above ground level.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".