Fates of live trees retained in forest cutting units, western Cascade Range, Oregon
Bibliographic record
Abstract
Live trees, standing dead trees, and downed logs have been retained in some forest harvest sites in the Pacific Northwest to fulfill various ecological objectives. To assess the fates of retained trees following partial cutting of mature forests in the central western Cascade Range in Oregon, we inventoried standing live and dead trees and toppled trees in 21 cutting units in 1993 and 2001. In 1993, 1–10 years after cutting, an average of 65% of the initially retained trees (average of counts for all sites) were alive and standing, 12% had been toppled or topped by wind, 13% had become snags by natural processes, and 10% were converted to snags by management action, including cutting, blasting, girdling, and inoculation with fungi. By 2001, when cutting-unit ages ranged from 9 to 18 years, 54% of the retained trees were alive and standing, 10%–21% had been toppled or topped by wind, 11%–22% had become snags by natural processes, and 14% had been converted to snags by management action. The highest levels of mortality occurred at sites with abundant intentional snag creation and (or) prescribed fire following harvest. The rate of mortality due to windthrow declined over time, possibly because the remaining trees were more windfirm.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".