Research on Selected Wildlife Infections in the Circumpolar Arctic—A Bibliometric Review
Bibliographic record
Abstract
One Health, a multidisciplinary approach to public health, which integrates human, animal, and environmental studies, is prudent for circumpolar Arctic health research. The objective of our bibliometric review was to identify and compare research in select infectious diseases in Arctic wildlife species with importance to human health indexed in English language databases (PubMed, Scopus) and the Russian database eLibrary.ru. Included articles (in English and Russian languages) needed to meet the following criteria: (1) data comes from the Arctic, (2) articles report original research or surveillance reports, (3) articles were published between 1990 and 2018, and (4) research relates to naturally occurring infections. Of the included articles (total n = 352), most were from Russia (n = 131, 37%), Norway (n = 58, 16%), Canada (n = 39, 11%), and Alaska (n = 39, 11%). Frequently reported infectious agents among selected mammals were Trichinella spp. (n = 39), Brucella spp. (n = 25), rabies virus (n = 11), Echinococcus spp. (n = 10), and Francisella tularensis (n = 9). There were 25 articles on anthrax in eLibrary.ru, while there were none in the other two databases. We identified future directions where opportunities for further research, collaboration, systematic reviews, or monitoring programs are possible and needed.
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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 | 0.010 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.136 | 0.128 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".