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Record W2431198678 · doi:10.1002/gepi.2001.21.s1.s154

Sex‐ and Age‐of‐Onset‐Based Locus Heterogeneity in Asthma

2001· article· en· W2431198678 on OpenAlexaff
Anil Srivastava, Cecilia A. Cotton, Andrew D. Paterson

Bibliographic record

VenueGenetic Epidemiology · 2001
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of TorontoUniversity of WaterlooQueen's University
Fundersnot available
KeywordsLocus (genetics)AsthmaAge of onsetGeneticsBiologyMedicineDemographyInternal medicineGeneDiseaseSociology

Abstract

fetched live from OpenAlex

Asthma is a complex disease with a genetic component. The results of genome-wide linkage studies imply that locus heterogeneity is likely to be an important feature of the genetics of asthma. To attempt to reduce locus heterogeneity, we hypothesized that the following may form the bases for locus heterogeneity at some asthma susceptibility loci: sex of affected individuals, parental origin of alleles shared by affected sib pairs, and age of onset of wheeze. Analysis of such strata may assist in the identification of novel susceptibility loci, or reveal the basis for locus heterogeneity at previously identified loci. Genotype and phenotype data from genome-wide linkage searches for asthma susceptibility loci from three populations were analyzed. Some regions demonstrated evidence for linkage to affected individuals of a particular sex. There was evidence for excess maternal allele sharing at regions on chromosomes 9 and 11. Regions on chromosomes 2 and 6 were linked to late and early age at onset of wheeze in asthma, respectively. These analyses suggest that the bases that we selected for stratification may be appropriate at certain susceptibility loci for asthma, and may therefore assist in the fine mapping of such loci. Differences in such variables between studies may explain apparent nonreplication of linkage results.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.060
Threshold uncertainty score0.711

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.034
GPT teacher head0.317
Teacher spread0.283 · 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

Citations6
Published2001
Admission routes1
Has abstractyes

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