Negligible structural development and edge influence on the understorey at 16–17‐yr‐old clear‐cut edges in black spruce forest
Bibliographic record
Abstract
Abstract Questions What is the distance of edge influence on the structure and understorey composition at 16–17‐yr‐old cut edges in black spruce boreal forest? How do these edges compare with more recent 2–5‐yr‐old cut edges in the same region? Location Northwestern Quebec, Canada. Methods Forest structure and understorey composition were sampled along transects perpendicular to ten 16–17‐yr‐old clear‐cut edges, and compared to published results from 2–5‐yr‐old cut edges. We used randomization tests to assess the magnitude and distance of edge influence, and to compare edge influence between different edge ages. Results Black spruce forest next to the 16–17‐yr‐old cut edges was structurally and compositionally very similar to interior forest, with little edge influence from harvesting beyond 5 m into the forest. Edge influence on the understorey was weak (low magnitude) and not very extensive (short distance) at these edges, with no significant edge influence on the abundance of individual species. Logs peaked in abundance on the forest side of the edge, with values higher than in either adjacent ecosystem. Conclusions Overall, 16–17‐yr‐old cut edges in black spruce forest showed little evidence of further structural change compared to the 2–5‐yr‐old cut edges. Structural development of these edges as well as regeneration of the disturbed areas also resulted in reduced edge influence on the understorey. Instead, clear‐cut edges in black spruce forest may experience more forest influence on the regenerating disturbed area.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".