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Record W2955282209

Multiple sclerosis: Prevalence and impact.

2018· article· en· W2955282209 on OpenAlexaffabout
Heather Gilmour, Pamela L Ramage-Morin, Suzy L Wong

Bibliographic record

VenuePubMed · 2018
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsPublic Health Agency of CanadaStatistics Canada
Fundersnot available
KeywordsMultiple sclerosisMedicinePopulationDemographyPediatricsGerontologyEnvironmental healthPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

This article provides new information about multiple sclerosis (MS) using the 2010/2011 Neurological Conditions Prevalence File, the 2011/2012 Survey of Neurological Conditions in Institutions in Canada, and the 2011 Survey on Living with Neurological Conditions in Canada. An estimated 93,500 Canadians living in private households and 3,800 residents of long-term care institutions had been diagnosed with MS. Prevalence estimates were 159 and 418 cases per 100,000 population for men and women, respectively; 2.6 women reported MS for every man with the condition. Among the household population, MS was generally diagnosed between the ages of 20 and 49 (82%). For the majority (68%), MS was their only neurological condition. The impact of MS included pain that prevented activities, impairments in mobility, cognition or sleep, and limitations in social functioning. Almost two-thirds (64%) stated that MS affected their lives at least moderately.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.094
Threshold uncertainty score0.188

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0080.012
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.107
GPT teacher head0.311
Teacher spread0.204 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations77
Published2018
Admission routes2
Has abstractyes

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