Nest attendance of lactating red squirrels (<i>Tamiasciurus hudsonicus</i>): influences of biological and environmental correlates
Bibliographic record
Abstract
Time allocation by lactating mammals is a reconciliation of often opposing nutritional and thermal demands of both the offspring and mother. Here we test the hypothesis that nest attendance patterns of lactating red squirrels ( Tamiasciurus hudsonicus ) vary with environmental and biological traits that relate to the thermoregulation of mothers and their offspring. We used temperature dataloggers to continuously record nest attendance and activity of free-ranging females with neonatal ( n = 45) and preemergent ( n = 53) litters. Lactating red squirrels concentrated activity out of the nest around the warmest parts of winter days and the coldest parts of summer days. Both younger and lighter litters had mothers that spent more time in the nest and shorter periods of time out of the nest. Females matched timing of activity within a day to the hourly air temperatures closest to their thermal neutral zone, serving to reduce individual and offspring thermoregulatory costs associated with activity. Nest attendance patterns appear to be constrained by the thermal, and possibly nutritional, requirements of the litter with females fine-tuning behavior to match constantly changing environmental and biological conditions, consistent with reduced energetic costs.
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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".