One What? Why GI Researchers Should Know and Care About the One Health Initiative
Bibliographic record
Abstract
The One Health Initiative is an international movement that began in 2006 and is supported by, among others, the American Medical Association and the US Centers for Disease Control.1 Its goal is both laudable and logical: to bring together animal, human, and environmental health practitioners for collaborations that enhance health and well being, broadly and globally. Sadly, although One Health (and the related concept of Zoobiquity2) are widely appreciated in the veterinary community, they are generally unknown in the human medical community, especially among subspecialists such as gastroenterologists.
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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 | 0.035 | 0.153 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.010 | 0.023 |
| Scholarly communication | 0.027 | 0.040 |
| Open science | 0.005 | 0.014 |
| Research integrity | 0.033 | 0.035 |
| Insufficient payload (model declined to judge) | 0.046 | 0.025 |
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".