The Treatment of Orofacial Pain by Using Transcranial Direct Current Stimulation
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
Neurostimulation methods are used in the treatment of chronic pain, although mainly for pharmacology resistant pain. Transcranial Direct Current Stimulation (tDCS) is a non-invasive neurostimulation method using low direct current (0.029-0.08 mA/cm2) applied to a cathode and anode, which directly stimulates the cranial surface. The applied current causes the most significant changes directly under the electrodes: the cathode reduces the excitability of cortical neurons, whereas the anode increases excitability. The effect of stimulation usually lasts a few hours up to a few days. We observed 19 patients with chronic orofacial pain. Inclusion criteria for the study were the following: orofacial pain, stable analgesic medication for at least one week before the beginning of stimulation and during its course, and age 18-75 years old. Patients with severe organic brain damage or seizure disease (epilepsy) were not included. The most common diagnosis was secondary trigeminal neuralgia after dental surgery. We measured thermal and tactile stimulation on the face before and after tDCS, then at 14 days. The total follow-up period lasted six months. We evaluated pain on a numerical scale (0-10) at each follow-up. We used sets of inventories focused on the examination of pain (a short form of McGill inventory), depression, anxiety, and pain interference with daily activities. tDCS is a non-invasive stimulation technique that is affordable and can be easily administered, especially when compared to other neurostimulation techniques. Only 15 patients out of the total number of 19 responded to the questionnaires.
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 | 0.001 | 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) | 0.000 | 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