High grade cervical lesions are caused preferentially by non‐European variants of HPVs 16 and 18
Bibliographic record
Abstract
The intratypic variability of HPVs 16 and 18 has been extensively studied and has been used as an important tool in epidemiological studies of viral transmission, persistence and progression to clinically relevant cervical lesions. Infections by non-European variants of HPVs 16 and 18 are associated with an increased risk for the development of high grade squamous intraepithelial lesions (HSIL). Our aim was to correlate the intratypic molecular variability of both HPV types and risk of persistent infection and lesion outcome in a cohort study conducted in Brazil. We characterized molecular variants of HPV types 16 and 18 by sequencing a fragment of the LCR, and of the E6 and L1 genes, for HPV-16 variants only. For both types, European variants composed the most prevalent and diverse group. Persistent infections with HPV-18 were associated with continuous detection of European variants. However, risk for simultaneous detection of HSIL and HPV DNA was higher in women harboring non-European variants of HPV-16. The same trend was observed with HSIL detected during follow-up. Our study confirms the association between non-European variants and risk of cervical neoplasia, and highlights the importance of their geographic distribution for cervical cancer risk assessment.
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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 | 0.000 | 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 | 0.000 | 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 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".