Human herpesvirus 6 infection as a trigger of multiple sclerosis: an update of recent literature
Bibliographic record
Abstract
BACKGROUND: This is an update on the existing evidence regarding a relationship between infection with human herpesvirus 6 (HHV-6) and multiple sclerosis (MS) in order to contribute on the attempt to define the nature and strength of that relationship. RESULTS: Study quality was assessed using the criteria proposed by Moore and Wolfson and by the classification criteria used by the Canadian Task Force on the Periodic Health Examination. Studies were categorized both by experimental technique and by quality (high [A], intermediate [B], and low [C]) as determined by the Moore and Wolfson criteria. Overall, 27 (90%) of 30 studies, 18 (86%) of which were classified as A quality, reached a statistically significant result. According to the Canadian Task Force classification, all studies were categorized as evidence of qualityII-1. Limitations of the available experimental techniques and perspectives for future research are discussed. CONCLUSIONS: The current review continues to emphasize the need for further, objective, evidence-based examination of the relationship between HHV-6 infection and multiple sclerosis.
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.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".