Stress level, parasite load, and movement pattern in a small-mammal reservoir host for Lyme disease
Bibliographic record
Abstract
Occurrence of Lyme disease has increased rapidly in Canada in the past 5 years. The emergence of Lyme disease coincides with the range expansion of the primary host, the white-footed mouse (Peromyscus leucopus (Rafinesque, 1818)), in the region. We evaluated the effects of stress level, parasite load, and forest-patch characteristics on P. leucopus movement pattern. We found negative relations between on the one hand the adrenal gland size, a proxy for stress level, and population density, and on the other hand, home-range area and movement rate of mouse individuals, suggesting that stressed mice cannot maintain a large home range. Population density was also related with excursion (outside the forest patch) and exploration (outside the home range) rates, either directly or through its effect on home-range area and movement rate. Finally, movement rate and excursion rate were lower in individuals infested with more black-legged ticks (Ixodes scapularis Say, 1821). Our results have implication for the mechanism of Lyme disease emergence in the region: individual hosts that carry more ticks and are thus more likely to be spreading the bacterium responsible for Lyme disease are dispersing less than tick-free individuals. Monitoring of Lyme disease should thus consider how the characteristics of host communities modulate the spread of the disease across the landscape.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".