Validation and in-field testing of a new on-site qPCR system for quantification of <i>Legionella pneumophila</i> according to ISO/TS 12869:2012 in HVAC cooling towers
Bibliographic record
Abstract
Legionella pneumophila, found in engineered water systems such as HVAC cooling towers, poses a significant public health risk. Culture, though routinely used to quantify L. pneumophila, has several disadvantages including long turnaround time, low sensitivity, and inter-laboratory variability. In this study, we validated the performance of an on-site quantitative polymerase chain reaction (qPCR) detection system for L. pneumophila in accordance with International Standards Organization Technical Specification 12869:2012. We evaluated specificity, limit of detection and quantification, and calibration curve linearity. Additionally, we evaluated whole system recovery and robustness using samples taken from taps and evaporative cooling towers. We then compared the system's performance against laboratory culture and laboratory qPCR across 53 cooling towers in a 12-week in-field study. We found that concordance between on-site qPCR and culture was both laboratory- and site/sample-dependent. Comparison of laboratory qPCR with on-site qPCR revealed that laboratory results were highly variable and showed little concordance. Some discordance may be explained by time delay between sample collection and testing ('shipping effect') which may lead to inaccurate reporting. Overall, our study highlights the value of on-site qPCR detection of L. pneumophila, demonstrates that laboratories are prone to misreporting results due to shipping effects, and reveals significant discordance between laboratory qPCR and culture.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".