Analysis of the Selective Nature of Sensory Nerve Stimulation Using Different Sinusoidal Frequencies
Bibliographic record
Abstract
This study examines the ability to selectively activate different nerve fibers in a finger by using different sinusoidal stimulation frequencies. Specifically, the stimulation of A-beta, A-delta, and C-fibers is looked into, and responses from each of three different stimuli (5 Hz, 250 Hz, and 2000 Hz) are compared. Action potential (AP) responses from the different nerve fibers are simulated. Activation thresholds are determined for each fiber type. The resulting firing frequencies are compared with thresholds found in the literature to determine the stimulating signal amplitude at which sensations begin to be perceived for each stimulation frequency. Results indicate that while selective stimulation of C-fibers and A-beta fibers appears to be possible with 5 Hz and 2000 Hz, respectively, selective stimulation of A-delta fibers may not be possible due to them requiring a higher stimulating signal amplitude to cause the nerve to reach the physiological threshold than A-beta fibers for 250 Hz. Thus, selective stimulation of the three types of nerve fibers may not be possible for all three examined frequencies.
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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) | 0.000 | 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) | 0.001 | 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 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".