A PRELIMINARY ASSESSMENT ON THE INFLUENCE OF HABITAT COMPOSITION AND STRUCTURE ON MOOSE DENSITY IN CLEAR- CUTS OF NORTH-WESTERN QUÉBEC
Bibliographic record
Abstract
Aerial survey data were used to describe moose density changes in relation to habitat composition and structure in clear-cut areas, and to infer the impact of these variables on limiting factors. We hypothesized that moose density would be lower in cut areas due to increased hunting and predation. Four habitat types (food and cover stands, cover stands, cuts, and other habitats) and 7 fragmentation indices were used in our analyses. Aerial surveys conducted in seven 35-112- km 2 blocks showed that moose density was related to the proportion of deciduous and mixed (food and cover) stands within each block and edge between food and cover and resinous stands (cover). Density, productivity, and harvest rate were not significantly influenced by clear-cuts. Our results suggest that habitat models should consider food and food-cover border over other habitat components.
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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 | 0.002 |
| 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) | 0.002 | 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".