Prevalence and type distribution of human papillomavirus in 5,000 British Columbia women—implications for vaccination
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
BACKGROUND: Human papilloma virus (HPV) prevalence studies performed in different regions and population groups across Canada would inform public health decisions regarding implementation of anti-HPV vaccines. METHODS: A total of 8,700 liquid-based specimens from 8,660 women aged 13-86 from throughout British Columbia were collected. DNA was isolated from 4,980 of these samples and assessed for HPV prevalence and type distribution. HPV was detected by PCR analysis using tagged GP5+/6+ consensus primers to amplify the L1 region of HPV; typing was done by bi-directional sequencing of PCR products. RESULTS: Overall HPV prevalence was 16.8% (age adjusted 15.5%). Prevalence of high-risk HPV was 13.9, and 10.7% of samples contained HPV16. HPV prevalence was highest in the youngest group of women (<20 years). One-third of HPV positive samples contained more than one HPV type. Percentages of low-grade (LGIL) and high-grade intraepithelial lesions (HGIL) containing high-risk HPV are 52.3 and 79.4%, respectively. CONCLUSIONS: Overall HPV prevalence in this study is within the range of estimates from other studies. The prevalence of HPV16 is higher than what is found in other Canadian and international studies. HPV16 and HPV18 compose a majority of the high-risk virus in this study. Use of current HPV vaccines could considerably reduce HPV-related conditions including cervical cancer and procedures such as colposcopy.
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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) | 0.001 | 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 it