Effects of sub-zero temperatures on the intraerythrocytic parasite, Hepatozoon catesbianae, infecting freeze-tolerant wood frog, Rana sylvatica
Bibliographic record
Abstract
Hepatozoon catesbianae is a malaria-like parasite that commonly infects the erythrocytes of frogs of Eastern Canada. Although green frogs (Rana clamitans) and bullfrogs (Rana catesbeiana) are commonly infected with Hepatozoon species, these parasites have a low prevalence and intensity in wood frogs, Rana sylvatica. These observations may be explained by the inability of parasites to survive when wood frogs freeze during the winter. The objective of this study is to determine if freezing of experimentally infected wood frogs affects the prevalence and parasitaemia, which is defined as the percentage of blood cells infected with a parasite, of H. catesbianae. Tadpoles hatching from egg masses collected in April 2012 were raised to adulthood by summer 2013. Mosquito larvae, and green frogs that served as a source of infection, were collected in summer 2013. A total of 20 wood frogs were fed mosquitoes with infections of H. catesbianae, and 13 became infected with H. catesbianae. Five infected wood frogs were assigned to the experimental group, five other infected wood frogs remained unfrozen as controls, and the infections in three frogs were not mature. The experimental group was acclimated at 4 C for a period of 4 weeks, after which the frogs were frozen at -3 C for 48 hr, and subsequently thawed at 4 C for a period of 6 days. Following the post-freezing recovery period, blood samples were taken from the experimental and control groups and were examined for H. catesbianae. Data from this study were combined with that of Hammer (2012) and McGee (2013) and were subjected to statistical analysis to test if sub-zero temperatures reduces the parasitaemia of H. catesbianae in wood frogs. Although there was a significant difference in the decrease of parasitaemia levels of H. catesbianae over time, this decrease was not attributed to freezing.
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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 | 0.001 |
| 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".