Betapapillomavirus natural history and co‐detection with alphapapillomavirus in cervical samples of adult women
Bibliographic record
Abstract
Human papillomaviruses (HPV) of the genus Betapapillomavirus can infect both cutaneous and mucosal sites, but research on their natural history at mucosal sites remains scarce. We examined the risk factors and co-detection patterns of HPVs of the Betapapillomavirus and Alphapapillomavirus genera in cervical samples of the Ludwig-McGill cohort study. We assessed a subset of 505 women from the Ludwig-McGill cohort study from São Paulo, Brazil. Cervical samples over the first year of follow-up were tested for DNA of over 40 alphapapillomavirus types and 43 betapapillomavirus types using a type-specific multiplex genotyping polymerase chain reaction assay. We assessed the risk factors for prevalent and incident betapapillomavirus type detection, and whether types were detected more frequently together than expected assuming independence using permutation tests, logistic regression, and Cox regression. We observed significant within-genus clustering but not cross-genus clustering. Multiple betapapillomavirus types were co-detected in the same sample 2.24 (95% confidence interval [CI]: 1.65-3.29) times more frequently than expected. Conversely, co-detections of alphapapillomavirus and betapapillomavirus types in the same sample occurred only 0.64 (95% CI: 0.51-0.83) times as often as expected under independence. In prospective analyses, positivity to one HPV genus was associated with a nonsignificant lower incidence of detection of types in the other genus. Lifetime number of sex partners and new sex partner acquisition were associated with lower risks of prevalent and incident betapapillomavirus detection. Betapapillomaviruses are commonly found in the cervicovaginal tract. Results suggest potentially different mechanisms of transmission for betapapillomavirus genital infections other than vaginal sex.
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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 | 0.000 |
| 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".