An analysis of clustering of betapapillomavirus antibodies.
Bibliographic record
Abstract
Betapapillomaviruses (betaPVs) may contribute to the aetiology of cutaneous squamous cell carcinoma. However, no high-risk types have yet been identified, possibly because the high frequency of co-infection prevents a straightforward analysis of the independent effects of individual viruses. This study aimed to determine whether specific virus types were more likely to co-occur than others, thereby reducing the number of parameters needed in statistical models. Antibody data were analysed from controls who participated in case-control studies in The Netherlands, Italy and Australia and from participants in the German Nutrition Survey. Cluster analysis and two ordination techniques were used to identify patterns. Evidence of clustering was found only according to the number of viruses to which antibodies were detected. The lack of clustering of specific viral types identified suggests that if there are betaPV types that are independently related to skin carcinogenesis, they are unlikely to be identified using standard epidemiological methods.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".