Development and validation of an RNA- and DNA-based quantitative PCR assay for determination of Kudoa thyrsites infection levels in Atlantic salmon Salmo salar
Bibliographic record
Abstract
Quantitative PCR (QPCR) methods targeting the 18S rDNA gene (DNA QPCR) and cathepsin L mRNA (RNA QPCR) from Kudoa thyrsites (Gilchrist) were developed and compared with histology for determination of K. thyrsites infection levels in Atlantic salmon Salmo salar L. Both QPCR tests were specific, reproducible and sensitive down to 3 copies. DNA QPCR was able to detect lower K. thyrsites infection levels than those detected by RNA QPCR and histology. The higher sensitivity of the DNA-based test compared with the RNA-based test appeared to be biological in nature and suggested that when infection levels were low, there were fewer copies of cathepsin L mRNA than 18S rDNA genes. However, all 3 diagnostic methods were highly correlated. Regression analyses comparing DNA QPCR and histology data from 2 distinct groups of fish showed that the relationship between these 2 diagnostic methods was reproducible. A logistic regression analysis comparing diagnostic data with a visual assessment of post-mortem flesh quality indicated that histology was the single best predictor of flesh quality, followed by DNA QPCR and then RNA QPCR.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".