Dynamic Control of the Shielding Effectiveness of Optically Transparent Screens
Bibliographic record
Abstract
This article presents the design, fabrication, and characterization of an active electromagnetic shield intended to dynamically protect optical and electromagnetic sensors against high intensity radiated fields. The shield exhibits high and constant optical transparency level over the entire visible light spectrum thanks to a micrometric mesh metal thin film printed on a glass substrate. The central micrometric mesh area is separated from the peripheral ground plane of the shield by a peripheral slot. This slot is fitted out with p-i-n diodes and resistors, connecting electrically the central micrometric mesh area and the ground plane. The aim of these components is to dynamically control the shielding effectiveness of the screen, by using the conducting (on) or blocking (off) states of the p-i-n diodes. Accordingly, the shielding effectiveness can be set at high level to protect the system against high intensity radiated fields, and conversely at low level to both prevent system electromagnetic self-perturbation and increase the sensitivity of the internal electromagnetic sensors. Dynamic control of the shielding effectiveness of the fabricated screen, whose optical transparency is close to 85% over the entire visible light spectrum, is fully demonstrated. A shielding effectiveness contrast ranging from 5 dB to 24 dB between theonandoffdiode states was measured in the 2–10.5 GHz frequency range in a reverberation chamber.
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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 | 0.000 | 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 | 0.001 | 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".