Do studies of wire code and childhood leukemia point towards or away from magnetic fields as the causal agent?
Bibliographic record
Abstract
A long-standing point of controversy in the epidemiologic literature concerns the meaning of a wire code-childhood leukemia association for assessing the role of magnetic field exposure. Six studies of wire codes and childhood leukemia in North America were examined, three of which reported positive associations and all of which found some relation between wire codes and measured magnetic fields. Supporting magnetic fields as the basis for the wire code associations are the correspondence between those wire code levels which predict distinct magnetic fields and those which predict leukemia risk in the positive studies. Geographic locations and methods that refine wire codes as magnetic fields predictors also tend to strengthen the association with leukemia. Opposing arguments are based on the failure of the wire code-magnetic field association to predict the strength of association across studies, including the unexplained lack of association between wire codes and leukemia in the Midwest and in Canada. Alternatives to magnetic fields are less supported; residential mobility, social class, and neighborhood characteristics are unlikely to explain a wire code effect. Ambiguity persists because of the modest strength of the wire code-leukemia association, the complexity of the relation between wire codes and magnetic fields, lack of knowledge of risk factors for childhood leukemia, and the limited evaluation of wire code correlates other than magnetic fields.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".