Risky business: relating probability of direct contact to risk of chronic wasting disease
Bibliographic record
Abstract
Chronic wasting disease (CWD) is a fatal, prion disease of cervids that was first detected in Alberta in 2005. Transmission of CWD by direct contact with infected individuals plays a major role in the early phases of an outbreak. Mule deer ( Odocoileus hemionus ) comprise 85% of CWD-infected animals in the province, and we investigated the seasonal effects of grouping patterns and landscape heterogeneity on direct, pair-wise contacts (distance of 3 m) within and between sex-specific (same or mixed sex) groups of mule deer in east-central Alberta. We determined seasonal contacts of mule deer based on proximity loggers that alter GPS schedules to record contact locations. We modeled the relative risk of contact between sex-specific dyads both within and between social groups based on landscape characteristics at the location of contact. We then assessed the support for 5 hypotheses that linked locations of seasonal contacts to occurrence of CWD on the landscape. Disease occurrence on the landscape was derived by comparing locations of CWD-infected and CWD-uninfected deer collected as part of the Alberta’s CWD hunter-harvest surveillance program. We found that contacts in winter occurred in areas where deer use was concentrated, whereas in summer, contact locations were less constrained in space where patterns of landscape characteristics at contact locations varied between sex-specific dyads. Contact probabilities of within and between-group male dyads in winter and between-group female dyads in summer were the best predictors of CWD risk in east-central Alberta. Our results relate habitat specific, social behaviors between conspecific mule deer to potential routes of CWD transmission and contribute to CWD research that guides management strategies for an emergent wildlife disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".