Limited detection of shared zoonotic pathogens in deer keds and blacklegged ticks co‐parasitizing white‐tailed deer in the eastern United States
Bibliographic record
Abstract
Deer keds, such as Lipoptena cervi Linnaeus (Diptera: Hippoboscidae), are blood-feeding flies from which several human and animal pathogens have been detected, including Borrelia burgdorferi sensu lato Johnson (Spirochaetales: Borreliaceae), the causative agent of Lyme disease. Cervids (Artiodactyla: Cervidae), which are the primary hosts of deer keds, are not natural reservoirs of B. burgdorferi sl, and it has been suggested that deer keds may acquire bacterial pathogens via co-feeding near infected ticks. We screened L. cervi (n = 306) and Ixodes scapularis Say (Ixodida: Ixodidae) (n = 315) collected from 38 white-tailed deer in Pennsylvania for the family Anaplasmataceae, Bartonella spp. (Hyphomicrobiales: Bartonellaceae), Borrelia spp., and Rickettsia spp. (Rickettsiales: Rickettsiaceae). Limited similarity in the bacterial DNA detected between these ectoparasites per host suggested that co-feeding may not be a mechanism by which deer keds acquire these bacteria. The feeding biology and life history of deer keds may impact the observed results, as could the season when specimens were collected. We separately screened L. cervi (n = 410), L. mazamae Róndani (n = 13), L. depressa Say (n = 10), and Neolipoptena ferrisi Bequaert (n = 14) collections from locations within the United States and Canada for the same pathogens. These results highlight the need to further study deer ked-host and deer ked-tick relationships.
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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 | 0.001 | 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".