Antibodies Against SARS-CoV-2 Do Not Cross-React with Endemic Coronaviruses in a Pediatric Population: Data from a Bangladesh Cohort
Bibliographic record
Abstract
There is a limited understanding of the immunological differences between children and adults that protect children from developing severe coronavirus disease 2019 (COVID-19) following SARS-CoV-2 infection. Previous infection with endemic human coronaviruses (HCoVs) has been suggested as a factor. In this study, we used 100 paired residual samples collected before and during the COVID-19 pandemic from children in Bangladesh. We compared the changes in their sero-status (no COVID-19 vs. COVID-19) and quantified antibody levels to HCoVs. We found that although 45% of the children seroconverted for IgG antibodies against SARS-CoV-2, there was no correlation between evidence of previous infection with HCoVs and the magnitude of SARS-CoV-2 antibody responses post-infection. Moreover, no differences in the anti-HCoV antibody levels were found pre- and post-SARS-CoV-2 infection.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".