Effects of geophagy on food intake, body mass, and nutrient dynamics of snowshoe hares (<i>Lepus</i> <i>americanus</i>)
Bibliographic record
Abstract
Geophagy is thought to have several physiological benefits to animals, including mineral supplementation and adsorption of toxins. However, these benefits have rarely been demonstrated experimentally. Using soil from a known lick in northern Alaska, we investigated the effect of geophagy on food intake and mass loss in captive snowshoe hares (Lepus americanus Erxleben, 1777) fed a formulated ration of feltleaf willow leaves (Salix alaxensis (Andersson) Coville), a preferred forage of snowshoe hares. Lick soil contained 4.8% clay, 12.5% carbonates, and had more available Na (72.7 mg·kg−1) than willow leaves. Hares fed willow leaves consumed more soil (15.2 ± 2.0 g·kg–0.75·d−1) than those fed formulated ration (9.3 ± 1.3 g·kg–0.75·d−1). Hares had higher willow intake when offered soil (45.8 ± 2.0 g·kg–0.75·d−1) than those without soil (35.0 ± 2.1 g·kg–0.75·d−1), and willow-fed hares offered soil lost less body mass (P < 0.001) than those without soil. Soil availability resulted in higher digestible intakes of N, Ca, Mg, Na, and K, but not P. These results suggest that the availability of mineral licks may alter forage use and functional response of this generalist herbivore in interior Alaska.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".