Relationships between gregarine infection in damselflies, wetland type, and landscape characteristics
Bibliographic record
Abstract
Abstract Although human-modified landscapes are characterized by the loss of natural habitats, new habitats also can be created and exploited by many species. The importance of landscape change to invertebrate associations (particularly host-parasite associations) is understudied. Our objective was to determine whether prevalence and intensity of gregarine parasitism in the damselfly Ischnura verticalis (Say) (Odonata: Coenagrionidae) differed between 17 artificial and 7 natural wetlands in landscapes that varied in amount of forest and wetland cover and road density determined at spatial extents of 500m and 1km from each wetland. Wetlands were located in and around Ottawa, Ontario, and Gatineau, Quebec, Canada. Wetland type did not account for significant variation in principal components based on forest and wetland cover and road density at either spatial extent. Gregarine prevalence was higher in damselflies collected from natural wetlands than in those collected from artificial wetlands and was positively associated with increasing forest cover. In contrast, gregarine intensity was inversely related to road density. Our results suggest that parasitism of damselflies by gregarines is associated with wetland type and landscape characteristics, although the mechanisms producing such relationships are unknown.
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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 | 0.000 | 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".