Childhood leukaemia risks: from unexplained findings near nuclear installations to recommendations for future research
Bibliographic record
Abstract
Recent findings related to childhood leukaemia incidence near nuclear installations have raised questions which can be answered neither by current knowledge on radiation risk nor by other established risk factors. In 2012, a workshop was organised on this topic with two objectives: (a) review of results and discussion of methodological limitations of studies near nuclear installations; (b) identification of directions for future research into the causes and pathogenesis of childhood leukaemia. The workshop gathered 42 participants from different disciplines, extending widely outside of the radiation protection field. Regarding the proximity of nuclear installations, the need for continuous surveillance of childhood leukaemia incidence was highlighted, including a better characterisation of the local population. The creation of collaborative working groups was recommended for consistency in methodologies and the possibility of combining data for future analyses. Regarding the causes of childhood leukaemia, major fields of research were discussed (environmental risk factors, genetics, infections, immunity, stem cells, experimental research). The need for multidisciplinary collaboration in developing research activities was underlined, including the prevalence of potential predisposition markers and investigating further the infectious aetiology hypothesis. Animal studies and genetic/epigenetic approaches appear of great interest. Routes for future research were pointed out.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".