Magnetic stimulation of the central and peripheral nervous systems
Bibliographic record
Abstract
Since 1985, when the technique of transcranial magnetic stimulation (TMS) was first developed, a wide range of applications in healthy and diseased subjects has been described. Comprehension of the physiological basis of motor control and cortical function has been improved. Modifications of the basic technique of measuring central motor conduction time (CMCT) have included measurement of the cortical silent period, paired stimulation in a conditioning test paradigm, repetitive transcranial magnetic stimulation (rTMS), and peristimulus time histograms (PSTH). These methods allow dissection of central motor excitatory versus inhibitory interplay on the cortical motor neuron and its presynaptic connections at the spinal cord, and have proven to be powerful investigational techniques. TMS can be used to assess upper and lower motor neuron dysfunction, monitor the effects of many pharmacological agents, predict stroke outcome, document the plasticity of the motor system, and assess its maturation and the effects of aging, as well as perform intraoperative monitoring. The recent use of rTMS in the treatment of depression and movement disorders is novel, and opens the way for other potential therapeutic applications.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.004 | 0.003 |
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".