Bibliographic record
Abstract
The main limiting factor of EEG monitoring in the critical/intensive care environments is, and always has been, the recording electrode. The electrode and its application to the scalp has changed very little since EEG was first discovered and developed as a clinical tool. However, the evolution of amplifiers and data acquisition systems have made tremendous strides. Modern-day EEG recording systems now have the capability to record for days and weeks with little intervention, whereas the EEG electrode requires constant attention and skilled adjustment every 10 to 24 hours. If one surveys the vast array of electrodes used now and in the past, the only electrode that, once placed, never needed any further adjustment for days and weeks on end, was the chronic silver-silver/chloride (Ag-Ag/Cl) sphenoidal (Sp) electrode. This Sp electrode has now been modified to permit it to be placed subdermally, similar to that of a subdermal needle electrode, but now the needle is removed to leave in place a fine, flexible, durable, chronic Ag-Ag/Cl electrode. Once placed, this subdermal wire electrode (SWE, patent pending) starts to record immediately with a low impedance of 3 to 4 Komega. This electrode can record any biopotential, in humans and in animals, and in most recording environments; it never needs adjustment, and records high-quality biopotential signals for as long as it is left in place. The SWE is also MRI and computed-tomography compatible. It takes less than half the time to place the SWE, and placement can now be performed by any medically trained personnel to obtain a low-maintenance, high-quality EEG recording.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".