Variation in body condition of moose calves in regions with contrasted winter conditions and tick loads
Bibliographic record
Abstract
For many mammals living at higher latitudes, food scarcity and snow-hindered movements associated with their first winter are synonymous of trying months. In addition, most wild animals have to cope with parasites. Many studies have been conducted on captive animals to assess consequences parasitism on health over winter, but comparable studies on wild populations are scarce for large mammals. Here, we performed winter tick ( Dermacentor albipictus Packard, 1869) counts and collected body condition data (mass and hematological parameters) on 15 moose ( Alces alces (Linnaeus, 1758)) calves from two distinct climatic regions in northern and southern New Brunswick (Canada) in January. The same calves were recaptured 3 months later to observe variation in body condition parameters. Higher tick loads and more drastic changes of hematological parameters, such as hematocrit and creatinine in southern individuals, suggested that this population might be suffering more from the consequences of winter tick infestation than the northernmost population. However, other parameters that were not measured in our study, such as quantity and quality of food, could influence moose calves body condition at the southeastern limit of their range.
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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 | 0.001 | 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".