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Record W2105413352 · doi:10.1093/occmed/kql104

University of Toronto case-control study of multiple chemical sensitivity-3: intra-erythrocytic mineral levels

2006· article· en· W2105413352 on OpenAlexaffabout
Cornelia J. Baines, Gail McKeown‐Eyssen, Nicholas Riley, Lynn M. Marshall, V. Jazmaji

Bibliographic record

VenueOccupational Medicine · 2006
Typearticle
Languageen
FieldMedicine
TopicFibromyalgia and Chronic Fatigue Syndrome Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineDetoxicationMultiple chemical sensitivityCase-control studyInternal medicineGastroenterologyChemistryBiochemistry

Abstract

fetched live from OpenAlex

BACKGROUND: Multiple chemical sensitivity (MCS) has an estimated American prevalence of 15%, and no consistently abnormal laboratory tests are available to assist in its diagnosis. Some physicians treating MCS patients have observed changes in intra-erythrocytic minerals (IEMs). As co-factors, minerals could influence detoxication of xenobiotics. AIM: To test whether IEM differed comparing MCS cases with controls. METHODS: A total of 408 women meeting validated inclusion and exclusion criteria for MCS participated in this case-control study. RESULTS: No statistically significant differences were observed. However, for copper, chromium, magnesium, molybdenum, sulphur and zinc, mean detectable levels were all lower in cases. No dose-response relationships were found. CONCLUSION: IEM measurements do not appear to provide useful diagnostic markers for MCS.

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)0.003
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 score0.235
Threshold uncertainty score0.468

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.028
GPT teacher head0.293
Teacher spread0.265 · 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

Citations5
Published2006
Admission routes2
Has abstractyes

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