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Record W2558465982

Epilepsy in Canada: Prevalence and impact.

2016· article· en· W2558465982 on OpenAlexaffabout
Heather Gilmour, Pamela L Ramage-Morin, Suzy L Wong

Bibliographic record

VenuePubMed · 2016
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsStatistics Canada
Fundersnot available
KeywordsEpilepsyMoodPopulationMedicinePsychiatryEnvironmental health
DOInot available

Abstract

fetched live from OpenAlex

This article provides information about the prevalence and impact of epilepsy, based on the 2010 and 2011 Canadian Community Health Surveys, the 2011/2012 Survey of Neurological Conditions in Institutions in Canada, and the 2011 Survey on Living with Neurological Conditions in Canada. An estimated 139,200 Canadians had epilepsy. Among the household population, epilepsy was generally diagnosed before age 30 (75%). For the majority of these people (64%), epilepsy was their only neurological condition. People with epilepsy were more than twice as likely to have been diagnosed with a mood disorder, compared with the general population (17% versus 7%), and eight times as likely to experience incontinence (34% versus 4%). Overall, an estimated 18% reported that their life was affected quite a bit or extremely by epilepsy; 44% felt that their life was impacted a little bit or moderately; and 39% felt that their life was not impacted at all. This study examined the impact of epilepsy on interactions with others, sleep, driving, education, and employment.

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)0.000
metaresearch head score (Gemma)0.002
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: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.192

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0060.013
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.021
GPT teacher head0.257
Teacher spread0.236 · 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

Citations18
Published2016
Admission routes2
Has abstractyes

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