An investigation of the role of wild rats in transmitting <i>Leptospira</i> spp. to stray cats and dogs in Malaysia
Bibliographic record
Abstract
Stray cats and dogs have been reported to shed Leptospira spp., and wild rats are speculated to be involved. We aimed to elucidate the role of wild rats in transmitting Leptospira to stray cats and dogs in Malaysia. We tested sera from 124 wild rats with the microscopic agglutination test (MAT): 88 of 122 (72%) sera were positive (titer ≥1:100), with the predominant serovars Icterohaemorrhagiae, Bataviae, Ballum, Javanica, Lai, and Pomona. With a Leptospira -specific PCR assay, we detected pathogenic Leptospira spp. in 33 of 124 (27%) kidney samples and 13 of 79 (16%) urine samples. Isolates obtained by culture of rat kidney and urine were identified to the species level with MAT using hyperimmune sera and the PCR assay. From 29 isolates, 2 pathogenic species were identified: L. interrogans serovar Bataviae and L. borgpetersenii serovar Javanica. Phylogenetic analysis using partial 16S rDNA sequences of the Leptospira spp. from the wild rats indicated that the species were similar to isolates from stray cats and dogs in previous studies. We confirmed that wild rats carried pathogenic Leptospira spp. and were a potential source of leptospiral infection of stray cats and dogs in Malaysia.
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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) | 0.000 | 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".