Data Supplement from Occupational Exposure to Extremely Low-Frequency Magnetic Fields and Brain Tumor Risks in the INTEROCC Study
Bibliographic record
Abstract
<p>Supplementary Table S1. Description of ELF levels in the most frequent jobs in low (<0.12 microT), medium (0.12 -< 0.15 microT), and high ({greater than or equal to} 0.15 microT) ELF categories based on the 33rd, and 66th percentile of jobs among study participants. Supplementary Table S2. Distribution of cumulative (uT-years) and average (uT) occupational ELF exposure levels, INTEROCC study, 2000-2004, Australia, Canada, France, Germany, Israel, New Zealand, and United Kingdom. Supplementary Table S3. Correlation between cumulative ELF in the three exposure time windows, 1-4, 5-9, and 10+ years prior to the date of diagnosis/reference date, INTEROCC study, 2000-2004, Australia, Canada, France, Germany, Israel, New Zealand, and United Kingdom. Supplementary Table S4. Adjusted ORs (95% CIs)a for high- and low-grade glioma in relation to categorical indicators of cumulative occupational ELF exposure, overall and in selected separate exposure time windows, 1-4, 5-9, and 10+ years prior to the date of diagnosis/reference date, INTEROCC study, 2000-2004, Australia, Canada, France, Germany, Israel, New Zealand, and United Kingdom. Supplementary Table S5. Adjusted ORs (95% CIs)a for glioma and meningioma in relation to categorical indicators of time-weighted average occupational ELF exposure in three separate exposure time windows, 1-4, 5-9, and 10+ years prior to the date of diagnosis/reference date, INTEROCC study, 2000-2004, Australia, Canada, France, Germany, Israel, New Zealand, and United Kingdom. Supplementary Table S6. Adjusted ORs (95% CIs)a for glioma and meningioma in relation to categorical indicators of maximum ELF exposed job in three separate exposure time windows, 1-4, 5-9, and 10+ years prior to the date of diagnosis/reference date, INTEROCC study, 2000-2004, Australia, Canada, France, Germany, Israel, New Zealand, and United Kingdom. Supplementary Table S7. Adjusted ORs (95% CIs)a for glioma in relation to categorical indicators of cumulative occupational ELF exposure in the 1-4 year time window prior to the date of diagnosis/reference date, adjusting for occupational BAP and PAH chemical exposure, INTEROCC study, 2000-2004, Australia, Canada, France, Germany, Israel, New Zealand, and United Kingdom.</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".