Evolution of an International External Quality Assurance Model To Support Laboratory Investigation of <i>Streptococcus pneumoniae</i> , Developed for the SIREVA Project in Latin America, from 1993 to 2005
Bibliographic record
Abstract
In 1993 the Pan American Health Organization initiated a laboratory-based surveillance system, called the SIREVA project, to learn about Streptococcus pneumoniae invasive disease in Latin American children. In 1994, National Laboratories in six countries were trained to perform serotyping and antibiotic susceptibility testing using broth microdilution to determine the MIC for specified antibiotics. An international External Quality Assurance (EQA) program was developed to monitor and support ongoing laboratory performance. The EQA program was coordinated by the National Centre for Streptococcus (NCS), Edmonton, Canada, and included external proficiency testing (EPT) and a validation process requiring regular submission of a sample of isolates from each laboratory to the NCS for verification of the serotype and MIC. In 1999, the EQA program was decentralized to use three of the original laboratories as regional quality control centers to address operational concerns and to accommodate the growth of the laboratory network to more than 20 countries including the Caribbean region. The overall EPT serotyping accuracies for phase I (1993 to 1998) and phase II (1999 to 2005) were 88.0 and 93.8%, respectively; the MIC correlations within +/-1 log(2) dilution of the expected result were 83.0 and 91.0% and the interpretive category agreements were 89.1 and 95.3%. Overall, the validation process serotyping accuracies for phases I and II were 81.9 and 88.1%, respectively, 80.4 and 90.5% for MIC agreement, and 85.8 and 94.3% for category agreement. These results indicate a high level of testing accuracy in participating National Laboratories and a sustained increase in EQA participation in Latin America and the Caribbean.
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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 | 0.075 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".