Experimental validation of a statistical model for evaluating the past or future magnetic field exposures of a population living near power lines
Bibliographic record
Abstract
This study was designed to provide an experimental validation for a statistical model predicting past or future exposures to magnetic fields (MF) from power lines. The model estimates exposure, combining the distribution of ambient MF in the absence of power lines with the distribution of past or future MF produced by power lines. In the study, validation is carried out by comparing exposures predicted by the model with the actual measurements obtained from a large-scale epidemiological study. The comparison was made for a group of 220 women living near a 735 kV power line. Knowing that the individual arithmetic means of MF exposures follow a log-normal distribution, the Pearson correlation between the log-transformed measured means and the calculated ones was determined and found to be 0.77. Predicted values of MF exposures were slightly lower than measured values. The calculated geometric mean of the group was 0.33 microT, compared to 0.38 microT for the measured geometric mean. The present study shows good agreement between the measured MF exposure of an individual inside a house near a 735 kV line and the MF exposure calculated using a statistical model.
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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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".