Trueness and precision of the real-time RT-PCR method for quantifying the chronic bee paralysis virus genome in bee homogenates evaluated by a comparative inter-laboratory study
Bibliographic record
Abstract
The Chronic bee paralysis virus (CBPV) is the aetiological agent of chronic bee paralysis, a contagious disease associated with nervous disorders in adult honeybees leading to massive mortalities in front of the hives. Some of the clinical signs frequently reported, such as trembling, may be confused with intoxication syndromes. Therefore, laboratory diagnosis using real-time PCR to quantify CBPV loads is used to confirm disease. Clinical signs of chronic paralysis are usually associated with viral loads higher than 10 8 copies of CBPV genome copies per bee (8 log 10 CBPV/bee). This threshold is used by the European Union Reference Laboratory for Bee Health to diagnose the disease. In 2015, the accuracy of measurements of three CBPV loads (5, 8 and 9 log 10 CBPV/bee) was assessed through an inter-laboratory study. Twenty-one participants, including 16 European National Reference Laboratories, received 13 homogenates of CBPV-infected bees adjusted to the three loads. Participants were requested to use the method usually employed for routine diagnosis. The quantitative results (n = 270) were analysed according to international standards NF ISO 13528 (2015) and NF ISO 5725-2 (1994) . The standard deviations of measurement reproducibility ( S R ) were 0.83, 1.06 and 1.16 at viral loads 5, 8 and 9 log 10 CBPV/bee, respectively. The inter-laboratory confidence of viral quantification (+/− 1.96 S R ) at the diagnostic threshold (8 log 10 CBPV/bee) was +/− 2.08 log 10 CBPV/bee. These results highlight the need to take into account the confidence of measurements in epidemiological studies using results from different laboratories. Considering this confidence, viral loads over 6 log 10 CBPV/bee may be considered to indicate probable cases of chronic paralysis.
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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 | 0.012 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".