Bibliographic record
Abstract
In 1980, Tell and Mantiply published a study of radiofrequency (RF) fields measured across 15 major metropolitan areas in the USA. They required a van fully equipped with instrumentation and computing capability for their measurements. This study aimed to assess whether and how hand-held instrumentation available today would facilitate and enhance the efficiency of large-scale surveys of ambient RF fields. In addition, the data would provide a suggestion as to how the profile of ambient RF fields has changed with respect to frequency content and magnitude. Not unexpectedly, the relative power densities were orders of magnitude lower than the Federal Communications Commission's (FCC) maximum permissible exposure (MPE) for the general public, with a maximum time-averaged value across the VHF-FM-UHF-cellular bands of 0.12 % of the MPE (AM's contribution was negligible). In both the 1980 and the present study, the power density in the FM band was a major contributor to overall power density, but over time, power densities in the VHF and UHF band decreased and increased, respectively. From the perspective of absolute power density, the wideband values in the 1980 study, this study and any number of assessments conducted in European nations are not generally different from one another.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".