Incidence, persistence, and determinants of human papillomavirus (HPV) infection in a population of Inuit women in Nunavik, Québec
Bibliographic record
Abstract
Objectives: To study the incidence, persistence, and determinants of human papillomavirus (HPV) infection in a population of Inuit women from Nunavik, Quebec by HPV type, Alpha-papillomavirus species, and oncogenic risk grouping. Methods: We recruited a cohort of Inuit women living in communities in Nunavik when they presented for routine care. Baseline sociodemographic and lifestyle characteristics were collected and cervical specimens collected throughout the follow-up period were tested for HPV-DNA using the PGMY Line-blot assay. Results: Almost 40% of women acquired a new any-type HPV infection, at a rate of 14.44 infections per 1000 women-months (WM). High-risk (HR) HPV infections were acquired at a higher rate than low-risk (LR) infections. HPV-31 was the type with the highest incidence rate, while species alpha-9 had the highest species-specific incidence rate. Multivariate logistic regression found age and marital status to be the most important predictors of infection acquisition across infection categorizations. Only 36.1% of women cleared their incident infections. No predictors of clearance were found. Conclusions: Incidence and persistence of HPV infections were comparable to a population of Canadian university students but are elevated compared to a cohort of randomly selected women in Ontario. Age and markers of sexual activity appear to be risk factors for infection acquisition.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".