Bibliographic record
Abstract
The American public is concerned about food safety, and there is a growing realization that we are ill equipped to handle major food-borne illness outbreaks and bioterrorism. Since veterinary medicine plays an important role in assuring the safety of our nation's food supply, we would like to present to veterinary and public health educators a newly emerging resource for food-safety educational materials. This article describes an integrative collaborative approach for the creation and dissemination of engaging food-safety teaching resources for veterinary faculty. This USDA-funded project, Design to Dissemination: Developing Materials and Repository for Integrative Veterinary Food Safety Education, involves expert teachers in diverse fields and from many veterinary schools. The purpose of the project is to create materials that teach students food safety from farm to fork, and it offers teachers clinically relevant teaching resources that are difficult to create or locate. The educational materials are being created as smaller "building blocks" of content, commonly referred to as "learning objects" (LOs), focused on individual learning objectives. These learning objects are placed in the Veterinary Food Safety Education Learning Object Repository, where they are catalogued, stored, and kept accessible and where faculty can search, evaluate, and download teaching materials to use in their courses. In this way the learning objects can be more easily shared and reused or repurposed for other courses and applications. With this article we hope to excite faculty in veterinary schools and public-health programs and encourage them to use the repository and participate in piloting the educational materials.
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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".