The ecology of Canada Yew (<i>Taxus canadensis</i>Marsh.): A review
Bibliographic record
Abstract
Canada yew (Taxus canadensis Marsh.) is a shade-tolerant evergreen shrub native to the understories of the boreal and deciduous forests of northeastern North America. Canada yew has a relatively unique growth form, with low sprawling branches capable of forming dense clusters of stems. Historic accounts suggest that before Euro-American settlement, Canada yew was a common plant across its range in many forest types and that it was locally abundant or dominant in 5%–20% of forest stands in the northern part of its range. Canada yew’s range has declined during the last century as a result of browsing by native ungulates, fire, intensive forest management, and clearing of land for agriculture and other development. It is considered uncommon throughout most of its present North American range, except for often isolated populations in areas that remain free from heavy browsing pressure by moose and deer (e.g., islands, areas with heavy snow cover, or areas naturally low in ungulate abundance). Its decline has likely resulted in changes to abiotic and biotic conditions, including structure and composition of understory vegetation and concomitant effects on understory vertebrates. Increasing white-tailed deer populations and reduced snowfall as a result of climate change in eastern North America threaten to extirpate this species from additional parts of its range in the next century. Suggestions for future research are discussed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".