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Record W2238766692

Approach to patients with unexplained multimorbidity with sensitivities.

2014· article· en· W2238766692 on OpenAlexaff
Stephen J. Genuis, Marko G. Tymchak

Bibliographic record

VenuePubMed · 2014
Typearticle
Languageen
FieldMedicine
TopicFibromyalgia and Chronic Fatigue Syndrome Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCausationMedicineToxicantMEDLINEMultiple chemical sensitivityIntensive care medicinePsychiatryInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To explore the underlying causation of unexplained multimorbidity with sensitivities and to discuss the management of patients who present with this perplexing condition. SOURCES OF INFORMATION: Medical and scientific literature was used from MEDLINE (PubMed), several books, toxicology and allergy journals, conference proceedings, government publications, and environmental health periodicals. MAIN MESSAGE: Multimorbidity with sensitivities has become an increasingly common and confusing primary care dilemma. Escalating numbers of debilitated individuals are now presenting to family physicians and specialists with multisystem health complaints, including sensitivities and fatigue, with no obvious causation, a paucity of laboratory findings, and a lack of straightforward solutions. In the recent scientific literature, there is discussion of sensitivity-related illness, an immune-mediated disorder that frequently manifests with multisystem symptoms, commonly including sensitivities and fatigue. This condition appears to be originally caused by adverse environmental exposures and toxicant bioaccumulation-an increasingly prevalent and well-documented problem in contemporary culture. CONCLUSION: Various toxic exposures and their bioaccumulation within the body frequently manifest as sensitivity-related illness. In clinical settings, patients with this disorder often present with otherwise unexplained multimorbidity and sensitivities. The health status of patients with this condition can be ameliorated by removing triggers (eg, scented products), optimizing biochemistry, removing further sources of toxicant exposures, and eliminating the internal dose of persistent toxicants.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.019
GPT teacher head0.220
Teacher spread0.201 · 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 designNot applicable
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

Citations7
Published2014
Admission routes1
Has abstractyes

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