Human papillomavirus genotypes in invasive cervical squamous cell carcinoma in Trinidad
Bibliographic record
Abstract
OBJECTIVE: To determine the relative contribution of known high-risk human papillomavirus (HPV) genotypes to the occurrence of cervical cancers in Trinidad. METHODS: The distribution of HPV genotypes in cases of invasive cervical squamous cell carcinoma in Trinidad was investigated. This study was a follow-up to an investigation of HPV genotypes in 310 nonsymptomatic women in Trinidad. The latter study showed that cervical HPV prevalence and heterogeneity of genotypes were high in the study population; notably, the genotypes targeted by the available HPV prophylactic vaccines were not the most common types. RESULTS: The current study of 85 cases of invasive cervical squamous cell carcinomas demonstrated that the previously observed heterogeneity in HPV genotype distribution is lost in cases of invasive cervical cancer, with the vaccine-targeted HPV types HPV 16 and HPV 18 becoming the most prevalent. CONCLUSIONS: HPV 16 and HPV 18 were the primary HPV genotypes associated with cases of invasive squamous cell carcinoma in the current Trinidad study. This strong association leads us to conclude that the HPV vaccines targeting HPV 16 and HPV 18 may contribute to reducing the cervical cancer burden in Trinidad.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".