Implanted intracortical electrodes as chronic neural interfaces to the central nervous system
Bibliographic record
Abstract
Recent developments in neural interfaces show that it is possible to have fine control of a robotic prosthetic by interfacing with the motor cortex of the human brain. Development of long term systems for this purpose is a challenging task with many different possibilities. Intracortical implants have shown the most promise in providing enough signal selectivity and throughput for complex control systems with many degrees of freedom. Intracortical systems generally fall into two categories: MEMS devices and bundle of wire systems. While both show promise, MEMS systems have been greatly popularized due to their reproducibility. In particular, the Michigan probe and Utah microarray are often used as a base for construction of more complex intracortical systems. However, these systems still carry many downsides. Their long-term viability is questionable, with mixed results. The effects of damage from implantation are still inconclusive and immune responses remain a problem for long-term use. While there is some promising research in the use of bioactive molecules and biocompatible materials to prevent immune responses, more controlled study is needed before intracortical systems become widespread.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".