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Record W2040358703 · doi:10.1159/000151514

The Prevalence of Multiple Sclerosis in the Middle East

2008· review· en· W2040358703 on OpenAlexaff
Jasem Al–Hashel, Aaron D. Besterman, Christina Wolfson

Bibliographic record

VenueNeuroepidemiology · 2008
Typereview
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsMiddle EastMedicineEpidemiologyMultiple sclerosisNorth eastDemographyPopulationAssertionSouth eastEnvironmental healthPathologyPsychiatryGeographySocioeconomics

Abstract

fetched live from OpenAlex

BACKGROUND: The prevalence of multiple sclerosis (MS) in the Middle East has been reported to be low to medium. METHODS: To verify this assertion we conducted a review of published data on the occurrence of MS in the Middle East. RESULTS: Fourteen studies reporting on the prevalence of MS in the Middle East were initially identified, 5 of which were excluded due to inadequate data or serious methodological limitations. The data from the 9 included studies suggested that the prevalence of MS may vary widely within the Middle East, from low to high. However, these 9 studies were inconsistent in case ascertainment, inclusion criteria and methods of prevalence calculation, and most did not include age/sex standardization. CONCLUSION: Methodological inconsistencies among studies make it difficult to be confident in drawing conclusions about the prevalence of MS in the Middle East. Nevertheless, there is little evidence to support the assertion that the prevalence of MS in the Middle East is low to medium. Rather, the prevalence of MS in the Middle East may range from low to high, depending on the specific population and environment of study. However, to confirm these findings, further epidemiological research is needed.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.029
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.951
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.473
GPT teacher head0.404
Teacher spread0.069 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations44
Published2008
Admission routes1
Has abstractyes

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