Invisible and Visible Symptoms of Multiple Sclerosis
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
The purpose of this study was to examine whether it is the invisible or the visible symptoms or signs of multiple sclerosis (MS) that are associated with greater health distress. Visible symptoms include the use of assistive devices, problems with balance, and speech difficulties, while invisible symptoms include fatigue, pain, depression, and anxiety. In a sample of 145 adults with MS, participants reported on these symptoms and their current level of self-reported health distress. Hierarchical regression analyses were used to determine whether invisible or visible symptoms were more predictive of health distress. When visible symptoms were added as the first step in the regression, 18% of the variance in health distress was explained. When invisible symptoms were added as the first step, 53% of the variance was accounted for. The invisible symptoms of pain and depression were the most significant predictors of distress. For a subset of the sample that had had MS for more than 11 years, pain and depression continued to be important predictors, but assistive-device use and fatigue were also important. Nurses should be aware that invisible symptoms may be more troubling to patients than visible symptoms and should ensure that adequate screening and treatment are provided for those with MS.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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