Bio- and Agroterror: The Role of the Veterinary Academy
Bibliographic record
Abstract
ith the events of September 11, 2001, and the anthrax attacks that followed, a somber realization is emerging that we have entered an era of international terrorism that, for years to come, will threaten the quality of life worldwide. This new form of attack, known as “asymmetric warfare,” is predicted to supplant traditional military endeavors and is aimed at provoking economic, social, and political chaos and destabilization and, ultimately, at undermining confidence in government. Targets of these so-called asymmetric threats may not be restricted to human beings, but increasingly may include any arena in which destruction or damage could undermine economic, social, environmental, or political values.1 Among the arsenals available to achieve these goals is intentional dissemination of harmful biological organisms, including many agents aimed at causing human illness or contaminating the food supply (bioterror) and also many agricultural diseases (agroterror). The resulting economic devastation and collapse of animal industries would initiate a cascade of events through multiple sectors of the economy. It will be of paramount importance to the well-being of society that new visionary curricula be developed to prepare veterinarians for these new challenges, which are now a reality for our profession.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".