Multimaterial and multifunctional neural interfaces: from surface-type and implantable electrodes to fiber-based devices
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Neural interfaces have enabled significant advancements in neuroscience and paved the way for clinical applications in the diagnosis, treatment, and prevention of neurological disorders. A variety of device modalities, such as electrical, chemical and optical neural interfacing, are required for the comprehensive monitoring and modulation of neural activity. The development of recent devices with multimodal functionalities has been driven by innovations in materials engineering, especially the utilization of organic soft materials such as polymers, carbon allotropes, and hydrogels. A transition from rigid to soft materials has improved device performance through enhanced biocompatibility and flexibility to realize stable long-term performance. This article provides a comprehensive review of a variety of neural probes ranging from surface-type and implantable electrodes to fiber-based devices. We also highlight the influence of materials on the development of these neural interfaces and their effects on device performance and lifetime.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it