Bibliographic record
Abstract
The present study was aimed to record the occurrence of acute kidney diseases in dogs.Overall occurrence of acute kidney diseases was 01.18 % (32/2696).Out of 148 suspected dogs 21.62% (32/148) suffered with acute kidney disease.The age wise occurrence of acute kidney disease was found to be higher in dogs aged between 4-8 years 28.12% (18/64), followed by dogs above 8 years 25.00% (12/48) of age and was less in dogs 1-4 years age 10.52% (02/19).Breed wise occurrence was higher in Labrador retriever 26.82% (11/41). HIGHLIGHTSm Overall occurrence of acute kidney diseases was 01.18 %. m The age wise occurrence of acute kidney disease was found to be higher in dogs aged between 4-8 years of age.
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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 | 0.013 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".