Predicting the potential distribution of<i>Vexillata</i>(Nematoda: Ornithostrongylidae) and its hosts (Mammalia: Rodentia) within America
Bibliographic record
Abstract
Species distribution modelling has been a powerful tool to explore the potential distribution of parasites in wildlife, being the basis of studies on biogeography. Vexillata spp. are intestinal nematodes found in several species of mammalian hosts, such as rodents (Geomyoidea) and hares (Leporidae) in the Nearctic and northern Neotropical regions. In the present study, we modelled the potential distribution of Vexillata spp. and their hosts, using exclusively species from the Geomyidae and Heteromyidae families, in order to identify their distributional patterns. Bioclimatic and topographic variables were used to identify and predict suitable habitats for Vexillata and its hosts. Using these models, we identified that temperature seasonality is a significant environmental factor that influences the distribution of the parasite genus and its host. In particular, the geographical distribution is estimated to be larger than that predicted for its hosts. This suggests that the nematode has the potential to extend its geographical range and also its spectrum of host species. Increasing sample size and geographical coverage will contribute to recommendations for conservation of this host-parasite system.
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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 | 0.001 | 0.001 |
| 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".