Editorial: Advances in bioelectronics and stimulation strategies for next generation neuroprosthetics
Bibliographic record
Abstract
is Research Topic, contributed to by electrophysiologists, biomedical engineers, computational neuroscientists, and neuropsychologists, provides a state-of-the-art overview of advances in neural stimulation technologies, ranging from recent progress in functional electrical stimulation (FES) to new understanding of how weak electric eld (EF) stimulation affects cellular properties.e submissions to this Research Topic can be grouped into four key areas: (A) non-invasive stimulation, (B) optimal implantation location, (C) advances in stimulus parameter identi cation, and (D) the in uence of neural ultrastructures under EF.It is helpful to provide four quotes from Sun Tzu's e Art of War 1 to represent the theme of each section:1 The Art of War is an ancient Chinese military treatise written in 5th century BC.It remains the most influential strategy text used in military thinking, business tactics, legal strategy, politics, sports, lifestyles and beyond.
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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.029 | 0.021 |
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".