Determinants of baseline seroreactivity to human papillomavirus type 16 in the Ludwig-McGill cohort study
Bibliographic record
Abstract
BACKGROUND: Immunity plays an important role in controlling human papillomavirus (HPV) infection and associated lesions. Unlike infections caused by other viruses, natural HPV infection does not always result in a protective antibody response. Therefore, HPV antibodies are also considered markers of cumulative exposure. The aim of this study was to identify determinants of HPV16 seroreactivity at enrollment among women from the Ludwig-McGill cohort, a natural history study of HPV infection and risk of cervical neoplasia. METHODS: HPV16 serology was assessed by ELISA for L1 and L2 capsid antigens, while HPV typing and viral load measurements were performed by PCR-based methods. The associations were analyzed by unconditional logistic regression. RESULTS: Of 2049 subjects, 425 (20.7%) were strongly seropositive for HPV16. In multivariate analysis, seroreactivity was positively correlated with age, lifetime number of sexual partners, frequency of sex, and HPV16 viral load, and negatively associated with duration of smoking. CONCLUSIONS: HPV16 seroreactivity is determined by factors that reflect viral exposure.
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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".