On parasite fauna of the European beaver
Bibliographic record
Abstract
The purpose of the research is identification of the current parasitological situation for Eurasian beavers inhabiting the Central Russia. Materials and methods. The work was carried out on hunting farms and in specially protected areas of the Central Russia. Potentially infective material was collected, recorded and preserved from animals during 2015–2021. The age of the animals was determined by their weight and physiological state of the rodents’ teeth and internal organs, and the sex was determined by their genitals. The animals were examined according to the method of complete and partial helminthological dissection per Skryabin. Results and discussion. A total of 41 animals were examined. Three forms of parasitism on animals were identified in natural habitat, namely, the trematode Stichorchis subtriquetrus, the nematode Travassosius rufus, and the ectoparasite Platypsyllus castoris. The stichorchosis causative agent localized in the animal’s large intestine was diagnosed in 35 rodents (85.4%). The helminth infection was 96% in the Eurasian beaver and 68.7% in the Canadian beaver. The nematode infection in stomach was detected in 31 animals (75.6%). The infection by T. rufus was 88% in the Eurasian beaver, and 56.3% in the Canadian beaver. The infected animals were delivered from the Vladimir, Moscow, Ryazan, Tula and Yaroslavl Regions. The beaver beetle P. castoris was found in 6 animals (14.6%). The infection rate was 8% in the Eurasian beaver, and 25% in the Canadian beaver. Animals with wingless arthropods have been identified in the Moscow and Ryazan Regions.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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".