Performance characteristics of polymerase chain reaction and histological methods for the detection of <i>Haplosporidium nelsoni</i> in the eastern oyster ( <i>Crassostrea virginica</i> )
Bibliographic record
Abstract
Fitness for purpose and validation are increasingly becoming a benchmark in the development of test methods for the diagnosis of infectious diseases in aquatic animals. The design of the evaluation and the analysis of data are critical to demonstrate test method performance characteristics and fitness for purpose, as stated in the World Organization for Animal Health pathway for test validation. Three test methods for the detection of the oyster parasite Haplosporidium nelsoni were selected for the validation study described herein: histology, end-point polymerase chain reaction (PCR), and real-time PCR (qPCR). Preliminary work evaluated the analytical sensitivity and specificity of the PCR and qPCR assay in development. The following stage used test results on 100 oysters in 3 different laboratories to assess diagnostic sensitivity (DSe), diagnostic specificity (DSp), repeatability, and reproducibility. Repeatability and reproducibility were within 68-95%. The final part of the project evaluated DSe and DSp using test results on 400 oysters and results from the first 100 oysters tested. In the absence of a 100% gold standard test, latent class modeling methods were explored to characterize the tests (i.e., Bayesian analyses). For both PCR methods, DSe was >90%, and in the 60% range for histology, whereas DSp was >90% for all methods. Based on the results of this validation, a threshold cycle value of 30 for qPCR corresponds to the limit of sensitivity for histology where unreliable detection becomes more frequent, thus providing a threshold helpful in diagnostic settings where both histology and qPCR are used.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| 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".