Metazoan and protozoan pathology of wild opossums (Didelphis virginiana) in Mexico
Bibliographic record
Abstract
ABSTRACT: The aim was to describe the incidence and lesions caused by metazoan and protozoan parasites in Didelphis virginiana opossums in Mexico. From 2019 to 2021, twenty D. virginiana were collected from the state of Colima, Mexico. Post mortem, parasitological, and histopathological studies were performed to identify and describe their lesions and findings. All opossums(20/20) presented at least one type of parasite of the twelve found; the most abundant were nematodes 58.33% (7/12) Didelphostrongylus hayesi, Turgida turgida, Cruzia sp., Viannaia sp., Trichuris didelphis, Trichostrongylidae and Gnathostoma sp. Protozoa 25% (3/12), including Sarcocystis sp., Besnoitia sp., and Sarcocystis sp. A single specimen of Mathevotaenia sp., 8.3% (1/12), and Paragonimus mexicanus 8.3%, were identified (1/12). The most affected systems were the digestive, respiratory, and musculoskeletal. The most abundant parasites were Turgida turgida (20/20) 100%, Cruzia sp., (16/20) 80%, and Viannaia sp. (6/20) 30%, followed by Sarcocystis sp. cysts, (6/20) 30%. The associated parasitic lesions were: D. hayesi produce eosinophilic granulomatous bronchopneumonia, P. mexicanus eosinophilic focal granulomatous pneumonia, and Besnoitia sp., focal eosinophilic lymphoplasmacytic interstitial pneumonia. Gnathostoma and T. turgida caused severe eosinophilic granulomatous focal gastritis. Viannaia sp., Sarcocystis sp., Mathevotaenia sp., and Trichostrongylidae; caused diffuse eosinophilic mucosal enteritis. Cruzia sp., and T. didelphis, induced diffuse eosinophilic mucosal typhlitis. Sarcocystis sp. cysts were detected in the cytoplasm of muscle fibers without histological changes.
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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".