Browse occurrence, biomass, and use by white-tailed deer in a northern New Brunswick deer yard
Bibliographic record
Abstract
Winter browse abundance influences population growth of white-tailed deer (Odocoileus virginianus) in northeastern North America, where they regularly experience harsh winter conditions. We surveyed browse biomass and abundance among vegetation types and determined the extent of browse species selection and avoidance in a northeastern deer yard. Deer browsed 19 species but only red and striped maples (Acer rubrum L. and Acer pensylvanicum L.) were consistently selected. Regenerating, mature mixedwood, and mature sprucefir stands were most likely to have high amounts of browse cover. Mature mixedwood stands had greater total browse biomass than submature hardwood and mature cedar stands. It is possible that our observed selection and avoidance of browse species reflects changes in availability as snow depth increased in middle to late winter. Thus, browse availability and use should be interpreted with respect to known patterns of deer habitat use during varying degrees of winter severity. We recommend that mixedwood stands be recognized as important part of winter habitat for deer. We underscore their importance for wintering deer, because they allow them to access shelter and browse simultaneously.
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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 | 0.000 | 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".