Map simulator of tick abundance in heterogeneous agricultural landscapes
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
Abstract Among vector-borne diseases, tick-borne diseases (TBD) are a major concern for human health. Mapping the distribution of important tick species is thus a major challenge for efficient prevention. Due to its specific ecological requirements, Ixodes ricinus , the main tick species in Europe responsible for TBD transmission, lives mostly in woodlands but also at the interface between woodlands and pastures or crops and along hedgerows. At the landscape scale, extensive variations in tick densities are observed but remain poorly understood. In that aim, we built a statistical model to identify the landscape variables influencing the abundance of questing I. ricinus nymphs, using GLMM approaches and MCMC estimates. This model was fitted on a data set based on a field sampling of ticks conducted during 3 years in 2 different agricultural landscapes in northwest and southwest France, for a total of 5390 sampling units. Among 12 variables investigated, 4 were finally kept in the model: woodland perimeter, woodland distance, road distance and building perimeter. Then, we developed a R package that simulates the abundance of questing nymphs within a given agricultural landscape, taking into account the influence of the different habitats as determined by the above statistical model. The maps obtained as an output from this simulator will be a useful tool for visualizing TBD risk, notably for stake-holders involved in landscape management and public health decisions. Graphical abstract Highlights Ixodes ricinus abondance is influenced by landscape characteristics Tick sampling was carried out in heterogeneous agricultural landscapes Informative variables related to habitats were identified by statistical analysis Woodlands, roads and buildings influence tick densities The resulting model was used to build a simulator of tick at-risk zones
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) | 0.001 | 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 | 0.001 | 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 it