Pooling Cervical Swabs and Testing by Ligase Chain Reaction Are Accurate and Cost-Saving Strategies for Diagnosis of <i>Chlamydia trachomatis</i>
Bibliographic record
Abstract
Specimen pooling to achieve efficiency when testing urine specimens for Chlamydia trachomatis nucleic acids has been suggested. We pooled endocervical swabs from 1,288 women and also tested individual swabs by ligase chain reaction (LCR). Out of 53 positive specimens, pools of 4 or 8 specimens missed two positives, providing 96.2% accuracy compared to individual test results. Dilution and positive-control spiking experiments showed that negative specimens with inhibitors of LCR in the pool reduced the signal. Conversely, two extra positives, detected only through pooling, were negative by individual testing but became positive after storage, suggesting that fresh positive specimens with labile inhibitors may be positive in a pool because of dilution of inhibitors. For this population of women with a 4% prevalence of C. trachomatis infection, substantial savings in cost of reagents (55 to 63%) and technologist time (50 to 63%) made pooling strategies a desirable alternative to individual testing.
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How this classification was reachedexpand
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".