Bibliographic record
Abstract
Repetitive Transcranial Magnetic Stimulation (rTMS) uses a magnetic coil to induce an electric field in brain tissue, which has been shown to have excitatory effects at frequencies >5 Hz. The use of a novel rTMS protocol is tested on various measures of cognitive ability in volunteers at various stages of Alzheimer's disease. Nine volunteers were each given real and sham treatments, with the order of treatments randomly determined. Each treatment block consisted of 13 sessions spread out over 4 weeks with 10 of those in the first 2 weeks. During each session, 2000 TMS pulses at 90-100% of resting motor threshold were applied to each side of the dorsolateral prefrontal cortex, in 50 pulse trains of 2 second duration at 20 Hz. In between the pulse trains, volunteers were given short object or action naming tasks to ensure their alertness. Volunteers were also encouraged to practice our online mental exercises at home during both sham and real treatments. Evaluation was performed each week using the Montreal Cognitive Assessment (MOCA) test. The extensive Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-Cog) evaluation was also done at the beginning and end of the 4 week treatment block. A 4 week washout period was enforced between the two treatment blocks. The individuals with more advanced symptoms (based on their ADAS-Cog scores) did not show a significant difference between sham and real treatments, while the 6 individuals at early stages of Alzheimer's showed a noticeably stronger improvement during the real treatment as compared to the sham treatment (Fig. 1). No significant effect was seen in the ADAS-Cog assessments. After 4 weeks, a greater improvement was seen for the mental exercises being practiced at home during the real sessions than that of the sham sessions.
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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 | 0.000 |
| 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) | 0.009 | 0.002 |
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".