Estimation of specificity and sensitivity of three diagnostic tests for infectious salmon anaemia virus in the absence of a gold standard
Bibliographic record
Abstract
Reverse transcriptase-polymerase chain reaction (RT-PCR), virus isolation (VI) and indirect fluorescent antibody test (IFAT) are three tests currently used by the salmon industry to identify fish infected with the infectious salmon anaemia virus (ISAV). However, very limited information is available on the sensitivity and specificity of these methods. In order to evaluate these tests in fish representing a range of farmed Atlantic salmon populations, five laboratories participated in a blind study of 400 kidney samples from four groups of fish with different prevalences of ISAV. Each laboratory used its own testing protocols. Estimates of the specificity of each test were determined directly from a population assumed to be free of infection. Indirect estimates of the sensitivity and specificity of each test were obtained using maximum likelihood estimation of a latent class model (i.e. no gold standard test result available). There was a substantial difference in sensitivity and specificity of RT-PCR among the three laboratories using this test. If only the best results for the RT-PCR tests are taken into account, the maximum likelihood estimates obtained from this study suggest RT-PCR and VI are of similar high sensitivity (range 92-100%), IFAT is the least sensitive method (range 65-76%) while the three tests have similar high specificities (range 96-100%). The results of the study suggest: (1) RT-PCR tests should be standardized before they are used as a diagnostic test for prevention and control of ISAV, (2) the sensitivity of VI was higher than expected and (3) IFAT has a low sensitivity but might be a good screening test because of its low cost.
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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 | 0.000 |
| 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".