Aspects of the epidemiology of nasopharyngeal carcinoma and Epstein-Barr virus infection in Greenland
Bibliographic record
Abstract
Objectives. The Inuit traditionally exhibit a distinctive cancer pattern characterised by high frequencies of nasopharyngeal (NPC) and salivary gland carcinomas, and low frequencies of tumours common in Western populations. Both NPC and salivary gland carcinomas are closely associated with Epstein-Barr virus (EBV), a nearly ubiquitous infection in all populations, and infection among Inuit is characterised by a particular pattern with early primary infection and high antibody titres. NPC is believed to be the result of environmental factors, especially EBV, acting on genetically susceptible individuals. However, knowledge is sparse on the extent and importance of the individual susceptibility and the interaction with EBV. During the second half of the twentieth century considerable changes in living conditions and lifestyle have occurred in the Inuit population of Greenland, and the effects on the patterns of malignant disease and EBV acquisition are unknown.The present thesis explores different aspects of the EBV-associated carcinomas among Inuit, with emphasis on the individual susceptibility of NPC and the epidemiology of EBV infection.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".