Bibliographic record
Abstract
Dosimetry is evaluated for live-line workers exposed to 50 Hz non-uniform magnetic fields from typical high-voltage transmission lines in the United Kingdom. The configurations involve twin-, triple- and quadruple-conductor transmission line bundles. Scenarios include three worker postures for the twin and triple bundles, and four postures for the quadruple bundle. The postures are selected to simulate worst case scenarios representative of work practices and result in highest values of dosimetric measures in critical organs. Only single-phase bundles are considered, as adjacent bundles of differing phase result only in a small reduction of the dosimetric measures. Reported data include various measures of the electric field and current density induced in tissues, as well as of the current density averaged over 1 cm2 areas normal to the current flow. A value of this latter quantity of 10 mA m(-2) is suggested as a threshold for neural tissue in the UK and international regulations. Critical tissues considered in this study include the retina, spinal cord, brain and cerebrospinal fluid. Some discussion is devoted to problems associated with the concept of current-density averaging, and two algorithms are considered. For a nominal load of 1 kA per subconductor, averaged current densities exceed the guideline bounds, only for a small number of postures and bundle configurations, in the brain, retina and cerebrospinal fluid. Non-averaged current densities in the cerebrospinal fluid exceed the suggested bound for all scenarios modelled, as well as in the retina for three postures involving a quadruple bundle.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".