The natural history of typespecific human papillomavirus infections in female university students. Cancer Epidemiol Biomarkers Prev 2003;12(6):485–90
Bibliographic record
Abstract
Little is known about the average duration of type-specific human papillomavirus (HPV) infections and their patterns of persistence. The objectives of this study were to evaluate the rate of acquisition and clearance of specific HPV types in young women. Female university students (n 621) in Montreal were followed for 24 months at 6-month intervals. At each visit, a cervical specimen was collected. HPV DNA was detected using the MY09/MY11 PCR protocol followed by typing for 27 HPV genotypes by a line blot assay. The Kaplan-Meier technique was used to estimate the cumulative probability of acquiring or clearing a HPV infection considering types individually or in high-risk (HR) or low-risk (LR) groups defined by oncogenic potential. Incidence rates were 14.0 cases/1000 women-months (95 % confidence interval, 11.4–16.3) and 12.4 cases/1000 women-months (95 % confidence interval, 10.4–14.8) for acquiring HR and LR HPV infections, respectively. The 24-month cumulative rates of acquisition were highest for HPV-16
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".