Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Pork meat is in high demand worldwide and this is expected to increase. Pork is often raised in intensive conditions, which is conducive to the spread of infectious diseases. Vaccines, antibiotics, and other biosafety measures help mitigate the impact of infectious diseases. However, bacterial strains resistant to antibiotics are more and more frequently found in pig farms, animals, and the environment. It is now recognized that a holistic perspective is needed to sustainably fight antibiotic resistance, and that an integrated One Health approach is essential. With this in mind, this review tackles antibiotic resistance throughout the pork raising process, including their microbiome; many factors of their environment (agricultural workers, farms, rivers, etc.); and an overview of the impact of antibiotic resistance on pork meat, which is the end product available to consumers. Antibiotic resistance, while a natural process, is a public health concern. If we react, and act, collectively, it is expected to be, at least partially, reversible with judicious antibiotic usage and the development of innovative strategies and tools to foster animal health.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.010 |
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 it