Crossing the Interspecies Barrier: Opening the Door to Zoonotic Pathogens
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
The number of pathogens known to infect humans is ever increasing. Whether such increase reflects improved surveillance and detection or actual emergence of novel pathogens is unclear. Nonetheless, infectious diseases are the second leading cause of human mortality and disability-adjusted life years lost worldwide [1,2]. On average, three to four new pathogen species are detected in the human population every year [3]. Most of these emerging pathogens originate from nonhuman animal species. Zoonotic pathogens represent approximately 60% of all known pathogens able to infect humans [4]. Their occurrence in humans relies on the human-animal interface, defined as the continuum of contacts between humans and animals, their environments, or their products. The human-animal interface has existed since the first footsteps of the human species and its hominin ancestors 6–7 million years ago, promoting the prehistoric emergence of now wellestablished human pathogens [5]. These presumably include pathogens with roles in the origin of chronic diseases, such as human T-lymphotropic viruses and Helicobacter pylori, as well as pathogens causing major crowd diseases, such as the smallpox and measles viruses and Bordetella pertussis [5,6]. Since prehistory, the humananimal interface has continued to evolve and expand, ever allowing new pathogens to access the human host and cross species barriers [5].
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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 | 0.002 |
| 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 | 0.000 |
| 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 it