Molecular Diagnosis of Chlamydia trachomatis Infections by Probe Hybridization, PCR, LCR, TMA, and Q-β Replicase
Bibliographic record
Abstract
The use of cell cultures for the laboratory diagnosis of Chlamydia trachomatis infections was popularized during the 1970s and 80s (1-4). The techniques required live organisms and were restricted to specialized laboratories. During the 1980s the detection of chlamydia-specific antigens was extensively used and compared to cell culture, provided a less stringent transportation of clinical specimens. Both direct fluorescent antibodies (DFA) and enzyme immunoassay (EIA) systems were commercialized (5-7) and algorithms for confirming false positives were popularized (8,9). The first nucleic acid detection assay for C.trachomatis was evaluated during this time frame with comparisons to culture and antigen detection (10-14). In the early 1990s, the following amplified nucleic acid assays detecting C. trachomatis gene fragments were developed: polymerase chain reaction (PCR), ligase-chain reaction (LCR), Q-β replicase-amplified hybridization (QBRAH), transcription-mediated amplification (TMA), and nucleic acid sequence-based amplification (NASBA). Extensive evaluations of PCR and LCR have shown, through discordant analysis and expansion of the reference standard for positives, that these amplified assays are 20-30% more sensitive than culture, antigen, or nonamplified nucleic-acid detection methods (15-29). This range in sensitivity (for PCR and/or LCR) is influenced by the rate of inhibitors of amplification found in clinical specimens.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".