Influence of winter ticks (<i>Dermacentor albipictus</i>) and temperature on recumbent behaviour of moose (<i>Alces alces</i>) calves
Bibliographic record
Abstract
Heavy infestations with winter ticks ( Dermacentor albipictus (Packard, 1869)) have been associated with mortality of moose ( Alces alces (Linnaeus, 1758)). Recumbency is an obligate behaviour for moose when ruminating and when conserving core body heat in cold weather. Recumbent behaviours were used to establish impacts of ticks and ambient temperatures on moose calves during the winter. Calves ( n = 12) were evenly divided into no-tick, low-tick, and high-tick groups. Recumbency bout duration increased over the winter but was independent of the tick group. The probability of ruminating decreased during warm temperatures for infested moose in the early stages of infestation. Legs tucked tightly decreased with increasing ambient temperature for all groups, and all groups had a higher probability of head down when ambient conditions were colder. The greatest differences in behaviour were between moose of the high-tick group and other moose. During the most active tick phases when ambient conditions dropped below −10 °C, moose of the high-tick group had a higher probability of being recumbent with their head down and legs tucked tight to the body. Energy conservation, irritation from ticks, and the impact of body condition are the three primary stimuli that most likely influenced recumbent postures of moose calves in this study.
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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".