Bibliographic record
Abstract
Human papilloma virus (HPV) has many known strains, two of the most well studied perhaps being the high-risk types 16 and 18. These strains have attracted more interest because they are known to disrupt tumour-suppressor genes that control the cell cycle, rendering those genes less effective at keeping cell division in check.Within the last decade, an increase in oral hpv-linked cancers of the throat and tongue has been attributed to exposure and contraction of hpv through oral sex, most notably in younger people. An understudied and arguably equal contributor to oral hpv infection might be indirect contact with an infected person. Presented here is a brief but important perspective on the relationship between cannabis use and oral cancer. The development of oral cancer is not a result of smoking cannabis per se; rather, it is hypothesized to be a result of contracting hpv through various forms of sharing and passing joints and other smoking apparatuses. Therefore, it is hypothesized that bogarting (and not passing) joints might decrease oral hpv among cannabis smokers. Future research should therefore investigate the prevalence of oral hpv in cannabis smokers to better understand its epidemiology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".