A case for vaccinating adolescent girls for protection against COVID-19 during pregnancy and childbirth in resource-limited settings
Bibliographic record
Abstract
<ns3:p>The coronavirus disease 2019 (COVID-19) pandemic has had severe implications worldwide, including increased adverse maternal and neonatal health outcomes. Vaccination is one way of protecting against these adverse health outcomes. However, in some low-resource settings, vaccine inequity has led to poor uptake of COVID-19 vaccination. There are very high rates of adolescent pregnancy in low-resource settings, which are likely to become even higher as we begin to see the full effects of COVID-19 lockdown measures, including school closures. Although the benefits of COVID-19 vaccination in adolescents are debated, we propose that adolescent girls should be prioritised in COVID vaccination roll out in low-resource settings. This is to provide protection from severe COVID-19 disease in pregnancy, preventing adverse maternal and neonatal health outcomes.</ns3:p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".