Parental exposure to medical radiation and neuroblastoma in offspring
Bibliographic record
Abstract
Previous studies have suggested an association between parental medical radiation exposure and increased incidence of certain childhood cancers. We investigated the relationship between medical radiation and risk of neuroblastoma in offspring using data from a North American case-control study. Cases were children diagnosed with neuroblastoma from 1 May 1992, to 30 April 1994, at Children's Cancer Group and Pediatric Oncology Group institutions throughout the United States and Canada. One matched control per case was selected using random-digit dialling. Telephone interviews were conducted with parents to collect data on any medical radiation examinations and treatments in the 2 years before conception or during pregnancy. We included 500 maternal and 339 paternal matched pairs. Overall, no association was found between maternal exposure to radiation and neuroblastoma risk (odds ratio [OR] = 1.0; 95% confidence interval [CI]: 0.7, 1.3). Analysis of maternal exposure by specific anatomical site showed no association for gonadal sites [OR = 1.0; 95% CI = 0.5, 2.0]. Little association was found with paternal radiation exposure [OR = 1.2; 95% CI = 0.8, 1.8]. No consistent exposure-response gradient was found based upon the number of maternal or paternal medical radiation examinations. The data presented here, coupled with the lower radiation doses currently used, indicate that any further study of this question will require larger studies with improved exposure assessment.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".