Human papillomaviruses-related cancers
Bibliographic record
Abstract
Human papillomavirus (HPV) infections are estimated to be the most common sexually transmitted infections worldwide. Meanwhile, it is well established that infection by high-risk HPVs is considered the major cause of cervical cancer since more than 96% of these cancers are positive for high-risk HPVs, especially types 16 and 18. Moreover, during the last 2 decades, numerous studies pointed-out the possible involvement of high-risk HPV in several human carcinomas including head and neck, colorectal and breast cancers. The association between high-risk HPVs and cervical cancer and potentially other human malignancies would necessitate the introduction of vaccines which were generated against the 2 most frequent high-risk HPVs (types 16 and 18) worldwide, including the Middle East (ME) as well as North African countries. The presence of high-risk HPVs in the pathogenesis of human cancers in the ME, which is essential in order to evaluate the importance of vaccination against HPVs, has not been fully investigated yet. In this review, we present an overview of the existing epidemiological evidence regarding the presence of HPV in human cancers in the ME and the potential impact of vaccination against HPV infections and its outcome on human health in this region.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".