Comparative studies on seroepidemiology of canine leptospirosis by micro agglutination test (MAT) and recombinant Lip L32 ELISA.
Bibliographic record
Abstract
Dogs (806) of 17 breeds were examined serologically by microscopic agglutination test (MAT) for the presence of different serovars of Leptospira organism. An overall seroprevalence of 7.07% was observed by MAT. Serovar Canicola was the predominant followed by lcterohaemorrhagiae, Australis, Autumnalis, Tarassovi, Ballum and others. Male dogs were more sero positive (8.31%) than females (5.41%). The highest seropositivity was observed in 3–5 year age group and lowest in under 1 year of age. Breed-wise more number of positive samples were from large sized breed of dogs like Labrador, German shepherd and Doberman. However, Spitz had maximum (26.31%) seroprevalence among all breeds. Sera samples collected from Chennai, Tamil Nadu showed highest seroprevalence (15.21%) with maximum number of serovars (28). The efficacy of recombinant leptospiral lipoprotein 32 (rLipL32) as an antigen was evaluated using enzyme-linked immunosorbent assay (ELISA) for serodiagnosis of canine leptospirosis. A seropositivity of 10.29% was observed. The relative sensitivity and specificity of ELISA as compared to MAT, was calculated as 100 and 96.52%, respectively. The concordance percentage between MAT and ELISA was 96.77, and the kappa statistics showed a substantial amount of agreement between MAT and ELISA. Results suggested that rLipL32 protein antigen based ELISA could be used as a serodiagnostic test for serodiagnosis of canine leptospirosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| 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 | 0.002 |
| 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 teacher head, 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".