Feeding site selection by woodland caribou in north-central British Columbia
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
We examined the foraging habits of the northern woodland caribou ecotype {Rangifer tarandus caribou) at the scale of the individual feeding site. Field data were collected in north-central British Columbia over two winters (Dec 1996-Apr 1998). We trailed caribou and measured vegetation characteristics (species composition and percent cover), snow conditions (depth, density, and hardness), and canopy closure at terrestrial and arboreal feeding sites, and at random sites where feeding had not occurred. Logistic regression was used to determine the attributes of feeding sites that were important to predicting fine scale habitat selection in forested and alpine areas. In the forest, caribou selected feeding sites that had a greater percent cover of Cladina mitis and Cladonia spp, lower snow depths, and a lower percentage of debris and moss. Biomass of Bryoria spp. at the 1-2 m stratum above the snow significantly contributed to predicting what trees caribou chose as arboreal feeding sites. In the alpine, caribou selected feeding sites with a greater percent cover of Cladina mitis, Cladina rangiferina, Cetraria cucullata, Cetraria nivalis, Thamnolia spp., and Stereocaulon alpinum as well as lower snow depths.
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 | 0.000 | 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) | 0.013 | 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