Human papillomavirus testing for primary screening of cervical cancer precursors.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Our objective was to determine whether the addition of human papillomavirus (HPV) testing to screening cytology improves the detection of cervical cancer precursors. Women of ages 18-69 years underwent conventional Pap cytology and HPV DNA testing in a multicenter study in Newfoundland, Canada. Those with positive cytology and/or HPV and a random sample of those with dual negative results were referred for colposcopy. The study enrolled 2098 women. The relative sensitivity of HPV testing was significantly higher than cytology for all-grade squamous intraepithelial lesions [SILs; 73%; 95% confidence interval (CI), 62-82] and high grade SILs (HSILs; 90%; 95% CI, 74-97) but had lower relative specificity (62% for all-grade SILs and 51% for HSILs) than most cytological cutpoints. The rate of combined correct results for all-grade lesions was higher for HPV testing (68.8%) than for any cytological cutpoint (equivocal, 52.3%; LSILs, 51.6%; HSILs, 44.5%). The combination of HPV and an LSIL cutpoint had a negative predictive value of 68% (95% CI, 52-80) for all SILs and 100% (95% CI, 91-100) for HSILs, while referring for colposcopy only 12% of the women. We concluded that HPV testing in conjunction with cytology improved the screening efficacy of cytology alone and may allow for a more effective and safe primary screening program with increased screening intervals.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.003 | 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 it