Incidence of canine reproductive cases presented to veterinary college Gadag, during 2021-2023
Bibliographic record
Abstract
A study on the incidence of gynaecological cases in canines was presented between April 2021andMarch 2023 at the Department of Veterinary Gynaecology and Obstetrics, Veterinary College Gadag. A total of 374 gynaecological cases were presented. The highest incidence was found to be Exfoliative Vaginal Cytology (36.10%), followed by Pregnancy Diagnosis (26.74%), Birth control (7.49%), Tumour (7.22%), Assisted mating and AI (7.22%), Pyometra (6.15%), Anoestrous (4.28%), Mismating (2.41%), Dystocia (1.34%) and Retention of Fetal Membranes (1.07%). Breed-wisepredilection indicated that Labrador Retriever(32.89%), Golden Retriever (10.70%), German Shepherd (10.70%), Rottweiler (9.63%) and others(36.10%).The majority of cases were presented during Winter (29.94%), followed by Monsoon (25.94%), Autumn (22.73%) and Summer (21.39%).
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".