Evidence of Arboreal Lichen Use in Peatlands by White-tailed Deer, <em>Odocoileus virginianus</em>, in Northeastern Alberta
Bibliographic record
Abstract
Within the past 10 to 15 years, White-tailed Deer (Odocoileus virginianus) have extended their geographical range to include most of northern Alberta. In the boreal forest they are most abundant in well-drained upland habitat. We report the occurrence of unusually large numbers of deer seen in a large fen complex in the west side of the Athabasca River Caribou range in northeastern Alberta. Further, we report an observation that suggests that deer may be using arboreal lichen (old man’s beard; Bryoria spp. and Usnea spp.) as a winter food in this region. We discuss the potential ecological ramifications of this observation for Woodland Caribou (Rangifer tarandus caribou) in northeastern Alberta.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 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 teacher head, 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".