The Inuit cancer pattern—The influence of migration
Bibliographic record
Abstract
The Inuit cancer pattern is characterized by high frequencies of Epstein-Barr Virus (EBV)-associated carcinomas of the nasopharynx and salivary glands. The reasons are unknown, but genetic and environmental factors are believed to be involved. Using data from the well-defined Inuit population in Greenland we investigated whether migration to Denmark influenced their risk of cancer. Greenland is part of the Danish Kingdom, and population-based registries cover both countries. Using rates for Denmark as reference, sex-specific standardized incidence ratios (SIR) were calculated for Inuit who never lived in Denmark and for those who at least once were registered with a Danish address. During 1973-2003, we observed 3,567 cancers in a cohort of 77,888 persons. Of these, 862 among 26,214 Inuit ever living in Denmark, and 2,705 among 51,674 nonmigrating Inuit. High SIRs for cancers of the nasopharynx [31.7 (CI 22.0-45.5)] and salivary glands [3.1 (CI 1.4-6.9)] observed among Inuit migrating to Denmark were comparable to those observed among Inuit never living in Denmark. Significant higher risk of cancer of the bladder, breast, prostate gland, skin, brain and stomach was observed among Inuit following migration to Denmark. The SIR was not generally influenced by duration of stay. The high risk of carcinoma of the nasopharynx and salivary glands observed in Inuit populations is maintained after migration to a low incidence area. This indicates that genetic factors or environmental factors acting early in life are etiologically important for these cancers.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".