Bibliographic record
Abstract
Maternal antibody transfer in pregnancy and breastmilk is implicated in the development of allergen-specific responses in children. Human studies investigating the effect of maternal allergen-specific IgG (sIgG) on allergic diseases in offspring are limited. Maternal sIgG in breastmilk and serum was measured in a subset of the CHILD birth cohort using an allergen macroarray and compared against sIgE of the child at 12-months (n=266). Hierarchical clustering of breastmilk sIgG was used to analyze the impact on atopic outcomes via multivariable logistic regression models. Breastmilk sIgG did not directly correlate with 12-month outcomes regardless of maternal atopic status. Higher breastmilk sIgG was a significant risk factor for skin prick test positivity at 12-months to food (OR 1.90 [1.07-3.41], p=0.030). Mean breastmilk/serum sIgG were significantly lower among IgE-sensitized children for cashew and Ara h 2, and higher for almond and ovalbumin. Relative abundance of breastmilk/serum sIgG may affect IgE-sensitization in offspring.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".