Bibliographic record
Abstract
Multiple sclerosis (MS) is an inflammatory autoimmune demyelinating disease of the central nervous system (CNS) [1]. Its debilitating effects on sensory, motor, autonomic, and neurocognitive functions affect primarily young adults, especially women (two to three times more frequent than in men), and is most frequent in northern countries, affecting more than 150 individuals of every 100,000 inhabitants e.g. in Canada and the Scandinavian countries. The development of this often initially relapsing/remitting and later progressive disease is associated with genetic and environmental risk factors [1, 3]. The major histocompatibility complex (MHC) class II gene locus is by far the most prominent genetic risk factor, and altered immune responses to the Epstein Barr virus (EBV), the causative infectious agent of most cases of infectious mononucleosis or "kissing disease", have in recent years emerged as the most prominent environment induced risk factors for MS [1]. Interestingly, particularly infectious mononucleosis as symptomatic primary EBV infection, caused by a lymphocytosis of mainly lytic EBV antigen specific CD8 + T cells, and elevated antibody responses against EBV have been found to synergize with the MS associated MHC class II molecule HLA-DRB1*1501 to increase MS risk seven- to fifteen-fold, respectively [1]. Moreover, EBV infection seems to precede MS onset by several years in nearly all patients. Thus, EBV infection currently appears as a prerequisite for MS development that increases the risk for this autoimmune disease in genetically susceptible individuals.
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How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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; both teacher heads agree on what is shown here.
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".