The Effects of Road De-Icing Salts on Two Amphibian Species, Rana Sylvatica and Rana Pipiens, and Their Trematode Parasites
Bibliographic record
Abstract
With ongoing amphibian declines, it is essential to determine possible contributors such as diseases and environmental contaminants that may increase susceptibility. A potential contaminant is road salt (mainly NaCl), which leaches into aquatic environments. I examined whether road salts make larval amphibians (tadpoles) more susceptible to trematode parasite infection, and also how these affect free-living trematode infectious stages (cercariae). I exposed Rana sylvatica (wood frogs) and R. pipiens (northern leopard frogs) to control, medium (400 mg/L), and high salt (800 mg/L) treatments, and then to trematodes. High salt tended to reduce wood frog anti-parasite behaviour and resistance to infection but the opposite was seen for R. pipiens, although these tadpoles had elevated lymphocyte counts in high salinity. Trematodes were differentially affected by increased salinities. The results suggest that host-parasite-environment interactions are complex, with species differentially affected by contaminants, which may lead to community shifts in predominant hosts and parasite species.
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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 | 0.000 | 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) | 0.002 | 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".