Multicenter Evaluation of a Commercial Cytomegalovirus Quantitative Standard: Effects of Commutability on Interlaboratory Concordance
Bibliographic record
Abstract
Commutability of quantitative reference materials has proven important for reliable and accurate results in clinical chemistry. As international reference standards and commercially produced calibration material have become available to address the variability of viral load assays, the degree to which such materials are commutable and the effect of commutability on assay concordance have been questioned. To investigate this, 60 archived clinical plasma samples, which previously tested positive for cytomegalovirus (CMV), were retested by five different laboratories, each using a different quantitative CMV PCR assay. Results from each laboratory were calibrated both with lab-specific quantitative CMV standards ("lab standards") and with common, commercially available standards ("CMV panel"). Pairwise analyses among laboratories were performed using mean results from each clinical sample, calibrated first with lab standards and then with the CMV panel. Commutability of the CMV panel was determined based on difference plots for each laboratory pair showing plotted values of standards that were within the 95% prediction intervals for the clinical specimens. Commutability was demonstrated for 6 of 10 laboratory pairs using the CMV panel. In half of these pairs, use of the CMV panel improved quantitative agreement compared to use of lab standards. Two of four laboratory pairs for which the CMV panel was noncommutable showed reduced quantitative agreement when that panel was used as a common calibrator. Commutability of calibration material varies across different quantitative PCR methods. Use of a common, commutable quantitative standard can improve agreement across different assays; use of a noncommutable calibrator can reduce agreement among laboratories.
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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 | 0.084 | 0.083 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".