Parasite species co-occurrence patterns on North American red squirrels (<i>Tamiasciurus hudsonicus</i>)
Bibliographic record
Abstract
Abstract Parasite species interactions, host biology traits, and external environmental factors can drive co-occurrence patterns between parasite species. We investigated co-occurrence patterns between three ectoparasite species (mite (Neotrombicula harperi), and fleas (Orchopeas caedens and Ceratophyllus vison)) of North American red squirrels (Tamiasciurus hudsonicus). We evaluated (1) whether ectoparasites of red squirrels exhibit non-random co-occurrence patterns, and (2) the contribution of host and external environmental factors to parasite co-occurrence. Bayesian ordination and regression analysis (boral) revealed random associations between parasite species pairs when accounting for host and external environmental factors. However, the mite N. harperi exhibited a negative association with the flea O. caedens and positive association with the flea C. vison linked to temporal patterns of occurrence. Our data suggests that parasites of the investigated population of red squirrels tend to form associations based on temporal trends in infestation rather than species interactions. Further experimentation should investigate the role of additional factors on parasite co-occurrence patterns, such as temperature, precipitation, and humidity.
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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 | 0.000 |
| 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 | 0.000 | 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 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".