Counterpoint: Cervical Cancer Screening Guidelines--Approaching the Golden Age
Bibliographic record
Abstract
Changes in screening guidelines that imply suppression of procedures once recommended are always controversial because of the perception that benefits are being curtailed. Prior to 2012, cervical cancer screening guidelines issued by US-based expert bodies differed in several decision areas, making clinicians essentially cherry-pick among recommendations. To some extent, this approach to screening practices also served to shield clinicians from litigation. It implied starting screening earlier, doing it more frequently, and stopping later in life than necessary. This state of affairs changed in 2012, when the most influential professional groups updated their cervical screening guidelines, and recommendations became essentially unified. All groups recommended that women older than 65 years of age discontinue cervical cancer screening on the basis of evidence that screening benefits in this age group were minor and far outweighed by harms. The guidelines are very specific about the exceptions, which ensure acceptable safety. It is expected that the new guidelines will permit less wasteful cervical screening, while fostering the opportunity to direct resources towards ensuring adequate coverage of high-risk women.
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 | 0.005 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.059 | 0.042 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".