Celebrating three years of Science in One Health: shaping a transdisciplinary community
Bibliographic record
Abstract
(SOH) has served as a platform for advancing One Health knowledge and practice since 2022. Guided by the vision of "One World, One Health", SOH is committed to exploring health issues at the human-animal-environment interface. Over the past three years, SOH has built an ambitious and dynamic editorial board across diverse disciplines, expanding its global influence and establishing itself as a global One Health community of authors and readers. So far, SOH has published 4 volumes, featuring 90 influential articles. Among them, 11 articles have garnered 17-82 citations, and 10 have achieved 2700-12,000 downloads. The third anniversary is considered a significant milestone, which marks a solid foundation for sustained growth. Moving forward, we expect to shape the future of One Health in collaboration with authors, readers, reviewers, and editorial board members of SOH.
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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 | 0.014 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.012 | 0.007 |
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".