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Data Sheet 1_The Canadian collaborative project on genetic susceptibility to multiple sclerosis cohort population structure and disease etiology.pdf

2025· dataset· en· W6946746425 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2025
Typedataset
Languageen
FieldChemistry
TopicWood and Agarwood Research
Canadian institutionsnot available
Fundersnot available
KeywordsDiseaseEpidemiologyMultiple sclerosisProbandGenetic predispositionCohortPopulationGenetic epidemiology

Abstract

fetched live from OpenAlex

Background Previous genetic and epidemiological studies have examined subpopulations from the Canadian Collaborative Project on Genetic Susceptibility to Multiple Sclerosis (CCPGSMS) patient cohort, but an encompassing analysis of the study population has not yet been carried out. Objective This retrospective study examines patterns of multiple sclerosis (MS) prevalence in 13,663 cohort members, including 4,821 persons with MS or suspected MS and 8,842 family members. Methods We grouped participants into epidemiologic subgroups based on age of MS onset, clinical stage at diagnosis, symptom type at disease onset, sex, proband status, disability as measured by the EDSS, and ancestry based on reported ethnicity. Results We observed a 2.7:1 MS prevalence ratio of women to men, though disease severity was greater for male patients. Variation in the age of disease onset between patients was only slightly associated with sex and strongly associated with disease type. Specific types of clinical symptoms at disease onset were associated with the prognosis. Regional residence did not correlate with disease onset, type, or severity. Conclusion Population trends, as presented here, are not explained by environmental factors alone, highlighting the need for a comprehensive genetic analysis to understand disease variance across families.

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)0.000
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.357
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0920.000

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 head0.060
GPT teacher head0.312
Teacher spread0.252 · 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
GenreDataset

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

Citations0
Published2025
Admission routes1
Has abstractyes

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