Modeling the role of songbirds and rodents in the ecology of Lyme disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Small rodents such as the white-footed mouse (Peromyscus leucopus) and the eastern chipmunk (Tamias striatus) efficiently transmit Borrelia burgdorferi, the etiologic agent of Lyme disease, to feeding ticks, whereas other hosts of ticks are less efficient reservoirs of B. burgdorferi. We examined the roles of ground-foraging and ground-nesting songbirds as alternative hosts for ticks, focusing on their potential to dilute the infection prevalence of ticks (Ixodes scapularis, the black-legged tick) with B. burgdorferi. We developed a mathematical model based on the relative use by ticks of rodent and bird hosts across varying host densities. We parameterized the model for sites in southeastern New York State using original data and for the northeastern United States using published values. Our results indicate that American robins (Turdus migratorius), ovenbirds (Seiurus aurocapillus), veeries (Catharus fuscescens), and wood thrushes (Hylocichla mustelina) have a low capacity to dilute the prevalence of tick infection, particularly when rodents are at moderate to high densities. We attribute this result to low use by ticks of birds and a low density of birds relative to that of rodents. Only when rodents constitute less than ca. 10-20% of the combined rodent and songbird host community are birds capable of substantially reducing the infection prevalence of ticks. In years or habitat types in which the density of rodents is low but that of ground-dwelling songbirds is high, the risk of human exposure to Lyme disease may reduced because birds dilute the infection prevalence of tick vectors.
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.
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 | 0.000 |
| 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) | 0.001 | 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 it