Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Pregnant women are at increased risk for severe morbidity and mortality following infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), leading some countries to recommend vaccination of pregnant women against coronavirus disease 2019 (COVID-19). These recommendations are based on studies conducted early in the pandemic, and thus, the pregnant women in these studies most likely did not have pre-existing immunity to SARS-CoV-2 at the time of infection. The susceptibility of pregnant women and their infants to SARS-CoV-2 and the severity of infection may be attenuated as the pandemic progresses and an increasing number of women will have pre-existing immunity (following natural infection or vaccination prior to pregnancy) during pregnancy. The reactogenicity, immunogenicity and efficacy of COVID-19 vaccines administered in pregnancy may also be affected by the pre-existing immunity of pregnant women. Maternal vaccine trials should be evaluated in the context of their timing in the pandemic and interpreted based on the pre-existing immunity of pregnant women.
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.
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 | 0.001 | 0.004 |
| 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) | 0.001 | 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 it