The First One Health Model (Deliverable 2.1)
Bibliographic record
Abstract
The Arctic is undergoing large disruptions. Multiple stressors such as climate change, and biodiversity loss in combination with infectious diseases and pollution from numerous sources, are affecting humans, wildlife and the environment in the Arctic. The ArcSolution project will provide comprehensive knowledge on these pressing challenges and will propose corresponding and accurate mitigating solutions for pollution, co-created with the people of the Arctic, all within a One Health framework. ArcSolution project produces a new locally anchored and integrated One Health framework, which is based on different knowledge sources that consider local concerns, priorities, and needs in the context of pollution at the ArcSolution study locations in Northern Finland, Northern Norway, Greenland, Svalbard, and MacKenzie delta area, Canada. In addition, Faroese Islands have been added to the study locations in the beginning of March 2025. The study sites represent a diversity of Arctic communities with different geographies, population structures, livelihoods, lifestyles, pollution sources and effects of climate change. The project uses a community-based participatory approach, which started already in the project application writing period. The members of the communities have been involved in the process from early on by communicating their priorities and concerns. The ArcSolution One Health framework is developed in WP2 (ArcSolution One Health framework) in collaboration with other WPs 3, 4, 5 and 6, over the course of the four-year study frame. In WP3 (Arctic pollution in a climate change context), pollutants in the environment are measured and modelled. Pollutant effects on ecosystems and humans are studied in WP4 (Impacts under different scenarios), and solution strategies from technological approaches to chemicals management are proposed in WP5 (Solutions: Resilience, adaptation, mitigation). In collaboration with the lead of WP6 (Exploitation, Dissemination and Communication), citizen science projects and communication and dissemination activities are planned and conducted together with local schools and municipalities. The results and knowledge produced in work packages will be feed back into the One Health Framework, and the knowledge will be synthetized and updated annually throughout the project stages. This deliverable presents the first step for the ArcSolution One Health framework/model, regarding all dimensions of animal, environmental and human health. The framework is based on different types of knowledges and information gathered and combined during the first months of the ArcSolution project. The model includes reports and findings in natural sciences, health sciences, engineering, and social science, together with local, traditional ecological knowledge, and Indigenous knowledge, as well as citizen science knowledge.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.201 | 0.061 |
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".