NEW DNA-BASED PCR APPROACHES FOR RAPID REAL-TIME DETECTION AND PREVENTION OF GROUP B STREPTOCOCCAL INFECTIONS IN NEWBORNS AND PREGNANT WOMEN
Bibliographic record
Abstract
Group B streptococci (GBS), Streptococcus agalactiae, are Gram-positive bacteria occurring in pairs and short chains. S. agalactiae was originally investigated as a frequent cause of bovine mastitis; before the widespread use of penicillin, it accounted for as much as 90% of all bovine mastitis. It was first isolated from parturient women in 1935. Since the 1970s, GBS have emerged as important human pathogens and have remained the major cause of bacterial diseases in newborns in the western world. In 1990, there were approximately 7600 neonatal cases of invasive GBS disease in the USA. Since then, intense intrapartum use of antibiotics has decreased the incidence of neonatal early-onset GBS disease, to 2200 cases in 1998. Babies can be exposed to GBS during labour and delivery, when they swallow or inhale the bacteria while passing through the birth canal of the colonized mothers. Babies can also be exposed in utero. GBS infection in infants causes sepsis and meningitis, which can result not only in illness and death but also in long-term disabilities such as hearing loss, impaired vision, developmental problems and cerebral palsy. The direct costs of neonatal disease alone in the USA have been estimated at 300 million dollars annually. GBS is also an important cause of maternal illness and a risk factor for preterm delivery.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".