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%).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 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".