Office of NHS cancer screening programme misrepresents Nordic work in breast screening row
Bibliographic record
Abstract
EDITOR—In Mayor's news story in the issue of 27 October the office of the NHS cancer screening programme in the United Kingdom misrepresents our research entirely.1 The office says that our findings of more aggressive treatment of breast cancer among screened women are based on only two studies, classified as poor quality. They are not. Numbers of mastectomies as well as numbers of tumourectomies increase when women are screened. This finding is consistent and is based on all four of the seven screening trials that have published data on this, including the two medium quality trials from Canada and Malmo.2 The office …
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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 | 0.013 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.056 | 0.059 |
| Insufficient payload (model declined to judge) | 0.013 | 0.015 |
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".