Short-term use of different residual forest structures by three sciurid species in a clear-cut boreal landscape
Bibliographic record
Abstract
We compared the abundance of red squirrel (Tamiasciurus hudsonicus Erxleben), northern flying squirrel (Glaucomys sabrinus Shaw), and eastern chipmunk (Tamias striatus L.) in three types of black spruce (Picea mariana (Mill.) BSP) residual forest 3 to 5 years after logging (upland strips, riparian strips, and forest blocks) in central Quebec, Canada. Controls consisted of mature forest undisturbed by forestry practices. Despite their sporadic occurrence, northern flying squirrels and eastern chipmunks were captured in the three residual forest types as well as in control sites. Red squirrels inhabited all types of residual forest and no differences in densities were found between residual forest treatments and controls. Juvenile recruitment, return rate (survival), and body mass were also similar for red squirrels in all treatments. However, midden abundance was higher in controls and blocks than in strips. In the short term, red squirrel populations maintain themselves in all types of residual black spruce forests after logging. The northern flying squirrel and the eastern chipmunk appear to tolerate the presence of logging disturbances and are present at low density in the different types of residual forests.
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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) | 0.000 | 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".