Retrospective Study of Ascites in Canines of North Gujarat Region
Bibliographic record
Abstract
The present work was conducted to evaluate the trend of ascites in canines of the North Gujarat region, India during 2017−2020. A total of 5094 dogs were presented for diverse clinical history at Veterinary Clinical Complex Deesa and Dantiwada. Amongst the dogs evaluated with clinical approach supported by ultrasonographic investigation in ascites suspected cases, total 91 were found affected. A thorough evaluation was conducted on all the dogs for various clinical signs. In most cases, the prominent clinical signs were abdominal distension, abnormal heart sound, and lethargy. History of no deworming was noticeable feedback from dog owners. Year wise prevalence of ascites was noted as 1.12% (2017), 1.12% (2018), 1.38% (2019) and 3.25% (2020) irrespective of etiologies. An increasing trend of ascites cases was observed over the years under evaluation. Female dogs were found more prone to ascites condition. Higher prevalence was observed in dogs one to the 5-year age group. Maximum numbers were reported from non-descript breed (n=19), labrador (n=13) and German shepherd (n=10). Anechoic fluid and fibrin in the abdominal cavity were consistent findings in most cases during ultrasonographic evaluation. Ascites can be prevented by regular deworming and by diet management.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".