MétaCan
Menu
Back to cohort
Record W4393931160 · doi:10.1016/j.msard.2024.105599

Assessment of dietary intake and its inflammatory potential in persons with pediatric-onset multiple sclerosis

2024· article· en· W4393931160 on OpenAlexafffund
Sama Bitarafan, Feng Zhu, Ali Mirza, Çharles N. Bernstein, Gary Van Domselaar, Ruth Ann Marrie, E. Ann Yeh, Yinshan Zhao, Brenda Banwell, Emmanuelle Waubant, Helen Tremlett

Bibliographic record

VenueMultiple Sclerosis and Related Disorders · 2024
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of TorontoSickKids FoundationPublic Health Agency of CanadaUniversity of ManitobaUniversity of British Columbia
FundersHospital for Sick ChildrenUniversity of TorontoMultiple Sclerosis Society of CanadaMcGill UniversityUniversity of Pennsylvania
KeywordsMultiple sclerosisMedicinePediatricsImmunology

Abstract

fetched live from OpenAlex

OBJECTIVE: To compare diet and the modified dietary inflammatory index (mDII) between individuals with pediatric-onset multiple sclerosis (PoMS), monophasic acquired demyelinating syndromes (monoADS), and controls. METHODS: The association between diet, mDII, and disease status was examined in 131 individuals with PoMS/monoADS/controls (38/45/48) using logistic regression. RESULTS: The associations between diet and PoMS were modest, reaching significance for whole grain intake (adjusted odds ratio, aOR=0.964, 95 % confidence intervals, CI:0.934-0.995) but not mDII (aOR=1.20, 95 %CI:0.995-1.46) versus controls. No findings for monoADS reached significance versus controls. CONCLUSIONS: Individuals with PoMS, but not monoADS, had lower dietary whole grain intake than controls.

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)0.002
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.269
Teacher spread0.237 · 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

Citations3
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueMultiple Sclerosis and Related DisordersSame topicMultiple Sclerosis Research StudiesFrench-language works237,207