Human Papillomavirus Genomics: Past, Present and Future
Bibliographic record
Abstract
Human papillomaviruses (HPV) are a group of divergent DNA viruses, of which a select few evolutionarily related HPVs have emerged to be highly oncogenic and of significant medical importance. Essentially all cases of cervical cancer, as well as a subset of other anogenital and oral cancers are caused by this limited set of HPV types. At present, over 150 HPV types have been identified and may be classified into genera, species and types based upon comparison of the viral genome. Established nucleotide phylogenies sort the highly pathogenic HPV types to the genus Alphapapillomavirus (α-PV). A species group includes viral types with 60-70% genomic nucleotide similarity that share a most-recent common ancestor; for example the species group's alpha-9 (HPV16-related) and alpha-7 (HPV18-related), contain the majority of known oncogenic HPV types. Genomes from the same HPV type with 1-10% nucleotide differences designate HPV variant lineages. The established nucleotide variations observed in extant HPV genomes have been fixed through evolutionary processes prior to human population expansion and global dissemination. To characterize viral types and variants associated with pathology for clinical applications (e.g. screening), molecular epidemiological studies have proven essential for identifying links between HPV natural history and carcinogenicity. This chapter presents a historical account of HPV genomics in the context of major discoveries and advances over the past 2 thousand years.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".