Guide to Antimicrobial Use in Animals
Bibliographic record
Abstract
Foreword: David Lloyd (Royal Veterinary College). Preface. Table of Contents. List of contributors. 1. Principles of Prudent and Rational Antimicrobial Use in Animals: Luca Guardabassi (University of Copenhagen) and Hilde Kruse (National Veterinary Institute Norway). 2. Human Health Risks Associated with Antimicrobial Use in Animals: Lars B. Jensen (Technical University of Denmark), Frederick J. Angulo (Centers for Disease Control and Prevention, USA), Kare Molbak (Statens Serum Institut) and Henrik C. Wegener (Technical University of Denmark). 3. Antimicrobial Resistance Risk Assessment: Emma Snary (Veterinary Laboratories Agency, UK) and Scott McEwen (University of Guelph). 4. Clinical Importance of Antimicrobial Drugs in Human Medicine: Peter Collignon (Australian National University), Patrice Courvalin (Institut Pasteur) and Awa Aidara-Kane (World Health Organization). 5. Geographical Differences in Market Availability, Regulation and Use of Antimicrobial Products: Angelo A. Valois (Australian Government Department of Agriculture Fisheries and Forestry), Yuuko S. Endoh (Ministry of Agriculture, Forestry and Fisheries (MAFF), Tokyo, Japan), Kornelia Grein (European Medicines Agency) and Linda Tollefson (US Food and Drug Administration). 6. Strategies to Minimize the Impact of Antimicrobial Treatment on the Selection of Resistant Bacteria: Peter Lees (Royal Veterinary College), Ove Svendsen (University of Copenhagen) and Camilla Wiuff (Health Protection Scotland). 7. Guidelines for Antimicrobial Use in Swine: David G. S. Burch (Octagon Services Ltd), C. Oliver Duran (Moss Veterinary Partners) and Frank M. Aarestrup (Technical University of Denmark). 8. Guidelines for Antimicrobial Use in Poultry: Ulrich Loehren (Lohmann & Co.), Antonia Ricci (Istituto Zooprofilattico Sperimentale delle Venezie) and Timothy S. Cummings (Mississippi State University). 9. Guidelines for Antimicrobial Use in Ruminants: Peter D. Constable (Purdue University), Satu Pyorala (University of Helsinki) and Geoffrey W. Smith (North Carolina State University). 10. Guidelines for Antimicrobial Use in Horses: J. Scott Weese (University of Guelph), Keith Edward Baptiste (University of Copenhagen), Viveca Baverud (National Veterinary Institute Sweden) and Pierre-Louis Toutain (Ecole Nationale Veterinaire). 11. Guidelines for Antimicrobial Use in Dogs and Cats: Luca Guardabassi (University of Copenhagen), G. Houser (University of Copenhagen), L. A. Frank (University of Tennessee) and M. G. Papich (North Carolina State University). 12. Guidelines for Antimicrobial Use in Aquaculture: Peter R. Smith (National University of Ireland, Galway), Alain Le Breton (Fish Consultant), Tor Einar Horsberg (Norwegian School of Veterinary Science) and Flavio Corsin (Ministry of Fisheries, Vietnam). Acknowledgements
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.112 | 0.130 |
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".