Recognizing and Treating Common Psychiatric Disorders in 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
BACKGROUND: The rate of depression and other psychiatric disorders is greater in multiple sclerosis (MS) than in other chronic conditions or neurologic diseases. This means that clinical neurologists seeing MS patients will frequently be engaged in the diagnosis and treatment of psychiatric distress. REVIEW SUMMARY: This review provides a summary of what is known about psychiatric dysfunction in MS. It offers information about the current views on the link between various psychiatric disorders and MS. More important, it offers suggestions on how the knowledge from existing research can be integrated into real-world practice. CONCLUSION: Clinicians need to understand the factors that influence the development of psychiatric disorders in MS, the relationship between disease-modifying therapies and psychiatric distress, and the issues surrounding the treatment of psychiatric conditions in MS. Thorough knowledge of psychiatric dysfunction and MS will allow the clinician to design an effective treatment regimen that helps patients cope with their disease.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 |
| 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