Group B Streptococcus: Trials and Tribulations
Bibliographic record
Abstract
Group B Streptococcus (GBS) is estimated to have caused 319,000 cases of neonatal disease resulting in 90,000 infant deaths globally in 2015. It is also associated with maternal sepsis, preterm births, stillbirths and neonatal encephalopathy. There is a significant burden of neurologic impairment among survivors of infant GBS disease. Intrapartum antibiotic prophylaxis strategies have reduced the incidence of newborn early-onset GBS (occurring days 0-6) in some settings, but they are not feasible in many low and middle-income countries. A maternal vaccine given to pregnant women to stimulate passive transplacental transfer of protective antibodies has the potential to reduce maternal disease, adverse pregnancy outcomes and newborn disease. Phase I and II vaccine studies are occurring, but conducting phase III efficacy studies of a GBS vaccine candidate would require very large numbers due to the relatively low incidence of invasive GBS disease. It has therefore been proposed that alternative pathways to vaccine licensure should be explored, for example, through use of a regulatory approved correlate of protection and safety evaluation in mothers, fetuses and infants. These studies would then be followed-up with post-licensure phase IV studies in which vaccine effectiveness is evaluated.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".