International Quality Assurance Study for Characterization of<i>Streptococcus pyogenes</i>
Bibliographic record
Abstract
Surveillance of group A streptococcal (GAS) infections was undertaken as a major component of the European Commission-funded project on severe GAS disease in Europe (strep-EURO). One aim of strep-EURO was to improve the quality of GAS characterization by standardization of methods. An external quality assurance study (EQA) was therefore carried out to evaluate current global performance. Eleven strep-EURO and seven other streptococcal reference centers received a panel of 20 coded GAS isolates for typing. Conventional phenotypic typing (based on cell surface T and M protein antigens and opacity factor [OF] production) and molecular methods (emm gene typing) were used either as single or combined approaches to GAS typing. T typing was performed by 16 centers; 12 centers found one or more of the 20 strains nontypeable (typeability, 89%), and 11 centers reported at least one incorrect result (concordance, 93%). The 10 centers that tested for OF production achieved 96% concordance. Limited availability of antisera resulted in poor typeability values from the four centers that performed phenotypic M typing (41%), three of which also performed anti-OF typing (typeability, 63%); however, concordance was high for both M (100%) and anti-OF (94%) typing. In contrast, the 15 centers that performed emm gene sequencing achieved excellent typeability (97%) and concordance (98%), although comparison of the performance between centers yielded typeability rates from 65 to 100% and concordance values from 83 to 100%. With the rapid expansion and use of molecular genotypic methods to characterize GAS, continuation of EQA is essential in order to achieve international standardization and comparison of type distributions.
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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 | 0.043 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".