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Record W2028523557 · doi:10.1159/000084255

Clustering of Allergic Outcomes within Families and Households in Areas Endemic for Helminth Infections

2005· article· en· W2028523557 on OpenAlexaff
Sitti Wahyuni, Erliyani Sartono, Taniawati Supali, Jaring S. van der Zee, Andarias Mangali, Ronald van Ree, Jeanine J. Houwing‐Duistermaat, Maria Yazdanbakhsh

Bibliographic record

VenueInternational Archives of Allergy and Immunology · 2005
Typearticle
Languageen
FieldImmunology and Microbiology
TopicParasites and Host Interactions
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsImmunologyAllergyImmunoglobulin EAllergenBiologyHelminth infectionsPopulationHelminthsEnvironmental healthMedicineAntibody

Abstract

fetched live from OpenAlex

BACKGROUND: Allergy and helminth infections share key immunological features in terms of Th2 responses. Although in industrialized countries clustering of allergic disorders within families has been frequently reported, such information is lacking from areas where helminth infections are endemic. METHODS: A total of 466 subjects from 29 families and 112 households participated in this study. Filarial infection, skin test reactivity and IgE to mite as well as total IgE were measured in all samples. Clustering of the allergy-related outcomes due to genetic and household factors was tested. RESULTS: Genetic factors contributed significantly to the clustering of total IgE and allergen-specific IgE, whereas only household factors contributed to the clustering of SPT positivity. CONCLUSION: Similar to several studies conducted in western populations, total IgE and allergen-specific IgE are influenced by genetic factors in a population resident in a helminth endemic area. However, clustering of SPT positivity due to genetic factors was not significant in the current study raising the question of whether the presence of helminth infections may override genes that are associated with the expression of tissue reactivity to allergens in the west.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.715
Threshold uncertainty score0.420

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.272
Teacher spread0.260 · 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.

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

Citations9
Published2005
Admission routes1
Has abstractyes

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