Ixodid tick effects on deer mice (Peromyscus maniculatus) hematology and ectop
Bibliographic record
Abstract
The ranges of the blacklegged tick (Ixodes scapularis) and the wood tick (Dermacentor variabilis) are expanding northward in Ontario, Canada in response to climate warming, reaching naïve or inexperienced host populations of deer mice (Peromyscus maniculatus) in more northern areas. As hematophagous parasites, ticks can affect their host’s hematology and differing levels of hemoglobin in mice populations where tick exposure varies, may be due to the difference in exposure to ticks. If a naïve mouse population does not cohabitate with an established tick population, the mice should then have higher hemoglobin levels since they are not being affected by ticks. The parasite community structures of deer mouse hosts should also differ when ticks are prevalent at varying exposure levels, as the prevalence of these ticks is expected to decrease the likelihood of other ectoparasite species co-occurring with them on the host. Blood samples were collected from individual mice from populations where: 1) both blacklegged ticks and wood ticks were prevalent, 2) only wood ticks were prevalent, or 3) where both tick species were absent in order to assess hemoglobin levels. Ectoparasites were collected from these same mice to determine parasite loads and species co-occurrences. Both my hypotheses were supported as hemoglobin levels were found to be higher in naïve mice compared to infested mice, particularly those with high tick infestations, and heterospecific parasite prevalence appeared to be higher when ticks were absent. As the ticks’ ranges expand, it is important to understand the differences between naïve and experienced hosts when the prevalence of these ticks can potentially alter the physiology and community assemblages of naïve mice.
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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) | 0.002 | 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".