Comparison of the BD Viper System With XTR Technology to the Gen-Probe APTIMA COMBO 2 Assay Using the TIGRIS DTS System for the Detection of Chlamydia trachomatis and Neisseria gonorrhoeae in Urine Specimens
Bibliographic record
Abstract
BACKGROUND: Performances of the BD ProbeTec Chlamydia trachomatis (CT)/Neisseria Gonorrhoeae (GC) Q(x) Amplified DNA Assay reagents on a BD Viper System with XTR Technology and APTIMA COMBO 2 Assay reagents on a TIGRIS DTS platform, for detection of both CT and GC were compared. METHODS: A total of 1018 first-void urine specimens were tested for the presence of CT and GC DNA using the 2 assays. RESULTS: CT was detected in 143 specimens (14%). Eight specimens exhibited discordant results, and they were divided equally between the 2 assays. Based on the original results, the overall agreement for CT was 99.2%, with 97.1% and 99.5% in agreement with positive and negative specimens, respectively. Cohen's Kappa was 0.967. GC was detected in 27 specimens (2.6%). Two specimens exhibited discordant results, and they were divided equally between the 2 assays. Based on the original results, the overall agreement was 99.8%, with 96.2% and 99.9% in agreement for positive and negative specimens, respectively. Cohen's Kappa was 0.961. CONCLUSIONS: There was a high level of agreement between the systems for both CT and GC detection.
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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 | 0.016 | 0.020 |
| 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 | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".