Bibliographic record
Abstract
Cervical cancer screening has reduced morbidity and mortality in many countries, but efforts to optimize screening modalities and schedules are ongoing. Using data from a randomized trial conducted in British Columbia, Canada, in conjunction with a provincial screening registry, Gottschlich and colleagues demonstrated that the estimated risk for precancerous disease (cervical intraepithelial neoplasia grades 2 or worse) at 8 years following a negative human papillomavirus (HPV) test was similar to the current standard of care (Pap testing after 3 years). The study supports extending screening intervals for those with a negative HPV test beyond currently recommended 5-year intervals. In an ideal world, the resources saved through less frequent routine cervical screening could be redirected to increasing screening uptake and follow-up of abnormalities to improve equity in cervical cancer prevention. However, implementation of extending screening intervals remains less than straightforward in settings with fragmented healthcare systems that lack information systems to support patient call/recall, such as the United States. To achieve the full promise of primary HPV testing, stakeholders at every level must commit to identifying and addressing the diverse spectrum of barriers that undergird existing inequities in care access, appropriately resource implementation strategies, and improve health information systems. See related article by Gottschlich et al., p. 904.
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 | 0.058 | 0.123 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.006 | 0.014 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".