Developing an Open-Access Antimicrobial Resistance Learning Site for Veterinary Medical Students
Bibliographic record
Abstract
Recognizing the crucial role of veterinarians in mitigating antimicrobial resistance (AMR), the Centers for Disease Control and Prevention (CDC) has funded the development of a suite of educational materials to promote the responsible veterinary medical use of antimicrobials. An open-access, Web-based multimedia curriculum regarding antimicrobial resistance in veterinary practice was thus created. The antimicrobial-resistance learning site (AMRLS) for veterinary medical students was completed and made available for use in January 2011 (http://amrls.cvm.msu.edu/). Designed for integration into existing veterinary medical courses, the AMRLS is also a resource for continuing education for practicing veterinarians, animal scientists, and food-animal industry specialists. This Web site emphasizes the mechanisms by which AMR emerges and spreads, the significant role of veterinarians in mitigating AMR, and the need to preserve the efficacy of antibiotics for future generations.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.104 | 0.042 |
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".