Bibliographic record
Abstract
Geographically MS describes three frequency zones. High frequency areas (prevalence 30+ per 100 000) now comprise most of Europe, Israel, Canada, northern US, southeastern Australia, New Zealand, and easternmost Russia. Medium frequency areas include southern US, most of Australia, South Africa, the southern Mediterranean basin, Russia into Siberia, the Ukraine and parts of Latin America. Prevalence rates under 5 per 100 000 are found in the rest of Asia, Africa and northern South America. Migrants from high to lower risk areas retain the MS risk of their birth place only if they are at least age 15 at migration. Those from low to high increase their risk even beyond that of the natives, with susceptibility extending from about age 11 to 45. Thus MS is ordinarily acquired in early adolescence with a lengthy latency before symptom onset. MS occurred in epidemic form in North Atlantic islands: probably in Iceland and the Shetland-Orkneys; clearly in the Faroe Islands. In the Faroes first symptom onset was in 1943, heralding the first of four successive epidemics at 13 year intervals. The disease was presumably introduced by occupying British troops during World War II, with the postwar occurrences representing later transmissions to and from consecutive cohorts of Faroese. What was transmitted is thought to be a specific, widespread, persistent infection called PMSA (the primary multiple sclerosis affection) which only rarely leads years later to clinical MS. Search for PMSA is best attempted on the Faroes where there are regions still free of MS after 50 years.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".