Does quality of winter food affect spring condition and breeding in female bank voles (<i>Clethrionomys glareolus</i>)?
Bibliographic record
Abstract
:We studied the effects of food supplementation on 16 bank vole populations in spring. We manipulated food quantity and quality in eight populations that were enclosed and eight other populations that were free-ranging on forest grids. The enclosed populations received large amounts of sunflower seeds, as high-quality food (four enclosures) or barley seeds, as low-quality food (four enclosures). Four of the open populations were supplemented with small amounts of spruce seeds, and four served as non-supplemented controls. Effects of differential food quantity and quality on overwintering weight of individual females and on spring litters were monitored by live-trapping. Pregnant females were removed to the laboratory for parturition and to record pup number and weight. Female body mass at the onset of breeding was highest in enclosures with high-quality food. Females from both enclosure treatments with a large quantity of food were heavier than females from open grids. The litters from enclosures supplemented with high-quality food tended to be one pup larger and grew faster than those from the low-quality food enclosures. Litter size of females of the non-supplemented forest plots did not differ from that of the spruce-seed-supplemented plots or from the enclosure females. In general, quantity of winter food may affect female body weight in spring, but quality of food appeared to have a positive effect on litter size and early growth of pups.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".