Tactile temporal thresholds detect relapse-related changes in multiple sclerosis: a preliminary study
Bibliographic record
Abstract
BACKGROUND: Tactile temporal thresholds, which represent the time separating the onset of two tactile stimuli when they are judged as simultaneous, can differentiate a group of people with multiple sclerosis (MS) from normal controls. Demyelination, axonal injury and loss, and altered information processing all occur in MS and may cause these increased thresholds. Thus, tactile temporal thresholds may be a useful outcome measure in MS. Our objective was to assess whether tactile temporal thresholds reflect change during a MS relapse. METHODS: During a study to evaluate the stability of tactile temporal thresholds in people with MS, two participants suffered relapses. Both events were associated with prolonged thresholds (i.e., significantly increased thresholds). CONCLUSIONS: Tactile temporal thresholds can detect neurologic worsening and thus warrant further evaluation as a useful method to facilitate in the monitoring of disease change in people with MS.
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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 | 0.002 | 0.004 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".