THE AUTHORS REPLY
Bibliographic record
Abstract
We thank O'Carroll et al. for their comments (1) and reiterate our opinion that our analysis provides little support for the hypothesis that nighttime extremely low frequency electromagnetic field exposure explains the association between magnetic field exposure and childhood leukemia risk (2). Following the initial pooled analysis (3), a subsequent German analysis demonstrated a strong association with nighttime exposure and a linear dose-response relation (4, 5), irrespective of the high correlation between daytime and nighttime exposure. This led to the suggestion that nighttime exposure might be a better exposure metric than the widely used 24-/48-hour average exposure, due either to reduced exposure misclassification or, in light of the melatonin hypothesis, to the exposure occurring in a biologically more meaningful time window. Had this been confirmed using the pooled data set, it would have supported the suggestion that the association between magnetic fields and childhood leukemia is actually stronger than previously described (3). Instead, however, our main finding was that the 24-/48-hour average exposure and nighttime exposure metrics gave virtually the same results (2).
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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 | 0.006 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.030 | 0.039 |
| Insufficient payload (model declined to judge) | 0.016 | 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".