Short-term response of Gray Wolves, Canis lupus, to wildfire in northwestern Alaska
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
There is a paucity of data concerning the effects of wildfires on large carnivores.During summer 1988 a wildfire burned 845 km? of taiga forest within the territory of two radiocollared Gray Wolf (Canis lupus) packs in northwest Alaska.We contrasted their use of areas that were burned with areas that were not burned before, during, and after fire.Wolves used the area that was later burned disproportionately more than expected before the fire.During and after (i.e., remainder of summer) the fire, they used the burned area more than expected during summer, but as expected during winter.Three years after the fire wolves began using the burned area similarly to their use before the fire; up until that time, wolves used the burned area less than it had been used prior to the burn.We attributed the changes in wolf distribution to changes in ungulate availability which were probably caused by the wildfire.
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it