Scalp EEG Acquisition in a Low-Noise Environment: A Quantitative Assessment
Bibliographic record
Abstract
This pilot study investigates effects of an ultra shielded capsule at the low-noise underground laboratory (LSBB), Rustrel, France, when used to acquire scalp electroencephalogram (EEG). Analysis of EEG recordings from three volunteers confirms that clean EEG signals can be acquired in the LSBB capsule without the need for notch filtering. In addition, using different setups for acquiring EEG in the capsule, statistical analysis of power spectral densities based on a geodesic distance measure reveals that the laptop computer and patient module do not introduce any noise on recorded signals. Moreover, the current study shows that the backward counting task as a mental activity can be better detected using the EEG acquired in the capsule due to the higher level of â-band activities. The counting-relaxed â-band energy ratio is calculated using the S transform and compared between the hospital and capsule, revealing significantly higher values in the capsule (p < 0.05). Exploring the relative â-band energy (ratio of â-band energy to that of 0-12 Hz in counting state) reveals that the average of this measure is higher in the capsule for all subjects. Those results demonstrate the potential of the LSBB capsule for novel EEG studies, including establishing novel low-noise EEG benchmarks.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| 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".