European Network for Optimization of Veterinary Antimicrobial Therapy (ENOVAT) guidelines for antimicrobial use in canine acute diarrhoea
Bibliographic record
Abstract
Acute diarrhoea is a common presentation in dogs, and a common reason for antimicrobial prescription and nutraceutical use. This evidence-based guideline provides recommendations for antimicrobial and probiotic treatment of canine acute diarrhoea (CAD). A multidisciplinary panel developed the recommendations by adhering to the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework. The opinions of stakeholders (general veterinary practitioners and dog owners) were collected and incorporated to ensure the applicability of this guideline. Four strong recommendations informed by high certainty evidence, and three conditional recommendations informed by very low or low certainty evidence, were drafted by the panel, along with an ungraded section on diagnostic work-up of dogs with acute diarrhoea. The ENOVAT guidelines initiative encourages national or regional guideline makers to use the evidence presented in this document, and the supporting systematic review, to draft national or local guidance documents.
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 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 | 0.028 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".