The Authors Reply
Bibliographic record
Abstract
We thank Dr. Weiss for his comments (1). However, we feel that Dr. Weiss is in error over several issues. First, for women aged 40–49 years, the “noninferiority” of the control arm in the Canadian National Breast Screening Study must be interpreted with a recognition that these participants received only an initial breast examination and were taught breast self-examination (2). Thus, after the first screen, the comparison was between mammography and usual care in the community, not regular clinical breast examinations. Second, the numbers of breast cancer deaths had increased since our previous reports (3, 4), thus substantially narrowing the confidence interval of the estimate of a null effect of mammography. In fact, the main results presented in our recent report (2) relate to the cancers diagnosed during the 5-year screening period. Compared with the previous reports (3, 4), the numbers of breast cancer deaths increased from 138 in the mammography arm and 128 in the control arm to 180 and 171, respectively, in our recent report (2). Further, for all breast cancer deaths, the numbers increased from 212 and 213 in the previous reports to 500 and 505 for the mammography and control arms, respectively. This refutes the claim that nothing has changed in our current report. There was always the possibility that a difference might emerge with long-term follow-up from mammography-detected cancers with a very long natural history. Our extended follow-up conclusively discounts this possibility. Third, the extended follow-up enabled us to estimate the extent of overdiagnosis from mammography with a precision that was not possible before, thus facilitating a more accurate recognition of the harms associated with mammography screening. We are not alone in pointing out how important it is to include overdiagnosis in estimates of potential benefits of mammography screening versus harms (5–7). In his letter (1), Dr. Weiss criticizes us for not reviewing the results of other breast screening trials. In fact, we did mention some of them but felt that it was not up to us to conduct a complete re-review of those findings at this time. Thus, in our view it is very important that the results of our study, with its unique design, demonstrating no beneficial effect of mammography screening (2), be reemphasized, and it seems that others agree with us (8, 9). Indeed, many investigators have failed to recognize the competing effects of screening and improved treatment of breast cancer (10–12). Thus, we renew our call for a reassessment of the value of mammography screening. Conflict of interest: none declared.
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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 | 0.007 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.133 | 0.097 |
| Insufficient payload (model declined to judge) | 0.011 | 0.011 |
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".