Neurocognitive abnormalities in offspring of mothers with systemic lupus erythematosus
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".