Gaps and opportunities in on‐host winter tick (<i>Dermacentor albipictus</i>) surveillance in North America
Bibliographic record
Abstract
Abstract The investigation and management of the impacts of winter tick (Dermacentor albipictus) infestations on moose (Alces alces) in North America necessitates coordinated surveillance and intervention efforts. However, variations in parasite surveillance methods and potential biases towards sampling specific host species for this generalist parasite can impede attempts to standardize observed disease patterns across vast regions and into the future. We collected and classified records of winter tick surveillance on ungulate hosts throughout North America to identify trends and biases in species, space, and time, with the aim of identifying gaps and suggesting improvements to existing practices. We conducted a literature review spanning a century of winter tick reports on free‐roaming or wild ungulate hosts in North America, resulting in 125 relevant records. From this sample, we compiled information on host species and surveillance method details and categorized winter tick quantification techniques based on their perceived insight for analyses and interventions, assigned as an ecological information value (Eco‐IV) ranging from 0 to 3. We examined variations in Eco‐IV among free‐roaming ungulates based on species, literature type, and data source. Among the 18 identified ungulate hosts, moose, white‐tailed deer (Odocoileus virginianus), and elk (Cervus canadensis) were most frequently reported. We observed a higher Eco‐IV for moose, indicating an abundance of species‐specific information, and a lower Eco‐IV (less information available) for methods focusing on white‐tailed deer. Limited sample sizes prevented the identification of patterns of knowledge acquisition for elk. Eco‐IVs in other ungulate species were consistently lower than moose, white‐tailed deer, and elk, regardless of literature type or data source. Exotic and invasive species systematically lacked detailed methods (Eco‐IV = 0). These findings highlight significant information gaps that impede the ability to compare winter tick infestation rates across studies, geographic regions, and host species, thus hindering coordinated management actions. We recommend standardizing winter tick quantification methods for all ungulate host species, specifically other common winter tick hosts such as white‐tailed deer and elk, and increased communication among groups working on tick–host systems to address these gaps.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| 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".