Climate change effects on deer and moose in the Midwest
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT Climate change is an increasing concern for wildlife managers across the United States and Canada. Because climate change may alter populations and harvest dynamics of key species in the region, midwestern states have identified the effects of climate change on ungulates as a priority research area. We conducted a literature review of projected climate change in the Midwest and the potential effects on white‐tailed deer ( Odocoileus virginianus ) and moose ( Alces alces ). Warmer temperatures and decreasing snowpack in the region favor survival of white‐tailed deer. In contrast, moose may become physiologically stressed in response to warming, and increasing deer populations spreading disease will exacerbate the problem. Although there is some uncertainty about exactly how the climate will change, and to what degree, robust projections suggest that deer populations will increase in response to climate change and moose populations will decrease. Managers can begin preparing for these changes by proactively creating management plans that take this into account. Published 2019. This article is a U.S. Government work and is in the public domain in the USA. The Journal of Wildlife Management published by Wiley Periodicals, Inc. on behalf of The Wildlife Society
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 it