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Record W2058195847 · doi:10.1177/0961203308089326

Neurocognitive abnormalities in offspring of mothers with systemic lupus erythematosus

2008· article· en· W2058195847 on OpenAlexaff
Murray B. Urowitz, Gladman Dd, Anne Mackinnon, Dominique Ibañez, V Bruto, Joanne Rovet, Earl D. Silverman

Bibliographic record

VenueLupus · 2008
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsHealth Sciences CentreHospital for Sick ChildrenHamilton Health SciencesToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsOffspringMcNemar's testMedicineNeurocognitiveNeuropsychologySystemic lupus erythematosusLogistic regressionInternal medicineLupus erythematosusPregnancyDiseaseImmunologyCognitionPsychiatryBiology

Abstract

fetched live from OpenAlex

Offspring of systemic lupus erythematosus (SLE) patients delivered during follow-up in the lupus clinic from 1973 to 1998 were assessed for SLE and by age-appropriate neurocognitive tests. Nine domains were evaluated. Controls, matched for age, sex, race and socio-economic status, underwent the same neurodevelopmental/neuropsychological evaluation. A domain was considered 'abnormal' if at least one of the tests in the domain yielded abnormal results. The number of offspring with normal/abnormal results was compared in each of the nine domains using McNemar test for matched analysis. In addition, an unmatched analysis using chi-square tests was performed. Logistic regression was run on both the matched pairs and unmatched groups to adjust for possible gender differences. A total of 106 children, 49 pairs of SLE offspring and matched controls (20 male and 29 female) and an extra eight offspring (three male and five female) of SLE patients without a control match were included. Of the 57 SLE offspring, none were diagnosed with SLE. The matched analyses of the neuropsychological domains revealed impairment in SLE children compared with matched controls in two of the nine domains: learning and memory and behaviour.

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 score0.973
Threshold uncertainty score0.853

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.263
Teacher spread0.238 · 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

Citations33
Published2008
Admission routes1
Has abstractyes

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