Skin diseases in the world`s indigenous peoples – with special focus on Greenland’s Inuit`s population
Bibliographic record
Abstract
Providing health care in Greenland is a major challenge. Spanning 2,600 km from north to south and 1,050 km from east to west, Greenland is the largest island in the world and has the lowest population density on the globe. The geographical situation combined with, at times, extreme weather conditions make providing healthcare a logistical challenge in Greenland. Most Doctors working in Greenland are used to perform a very broad range of medical duties including various dermatological conditions. But not a single certified Dermato-venereologist at work in Greenland. Dermatological care at specialist level is provided by tele-dermatology. In this article we will describe some of the problems with skin diseases in Greenland with special focus on the Inuit population – based on challenges with access to care and challenges associated with diagnosis based on differences in baseline patient characteristics and correct treatment due to cultural differences influencing treatment preferences. Key words: Arctic dermatology, Inuits, Atopic dermatitis, Psoriasis, Hidradenitis Suppurativa
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".