VOYAGER: an international consortium investigating the role of human papilloma virus and genetics in oral and oropharyngeal cancer risk and survival
Bibliographic record
Abstract
Abstract Head and neck cancer (HNC) is the sixth most common cancer globally. Incidence and survival rates vary significantly across geographic regions and HNC tumor subsites. This is partly due to differences in risk factor exposure, including tobacco smoking, alcohol consumption and human papillomavirus (HPV) infection, alongside detection and treatment strategies. The VOYAGER (human papillomaVirus, Oral and oropharYngeal cAncer GEnomic Research) consortium is a collaboration between five large North American and European studies which generated data on more than 10,000 participants (7,233 cases and 3,297 controls). The primary goal of the collaboration was to improve understanding of the role of HPV and genetic factors in oral cavity and oropharyngeal cancer risk and outcome. Demographic and clinical data collected by the five studies were harmonized, and HPV status was determined for the majority of cases. In addition, almost 1,000 tumors were sequenced to characterize somatic alterations. The resulting comprehensive biomedical resource can be utilized to answer critical outstanding research questions to help improve HNC prevention, early detection, treatment, and surveillance. Highlights VOYAGER is a large harmonized international resource for advancing head and neck cancer research. Comprehensive demographic, clinical and genetic data to support studies of head and neck cancer risk and survival. Standardized data harmonization to enable robust analyses across multiple populations. Long-term follow-up to facilitate the development of prognostic and predictive biomarkers.
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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 | 0.043 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.006 |
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".