Bibliographic record
Abstract
The Arctic health was the main topic at an expert meeting of the Arctic Council held in Oulu this May. The need for drawing attention to health issues was recognized as an impor tant par t of the international Arctic co-operation. Environmental pollutants in the Arctic as health risk factors will be discussed during the AMAP-collaboration. Also climatic physical factors in the Arctic as health risks are in focus as regards the Arctic Climatic Impact Assessment (ACIA). Global surveillance of HIV and tuberculosis in the Arctic has also star ted. A similar kind of surveillance should also find its place as regards injuries, infectious and chronic diseases. This basic information on nor thern health is vital so that proper health care practices could be established. To promote these activities co-operation with health and well-being professionals and officials in different countries is important; active participation at the grass-root level is also valuable when setting priorities concerning health and well-being in the entire circumpolar area. This Journal offers a forum for well grounded opinions when it comes to the needs and practices of the future cooperation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.015 | 0.027 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".