Use of RT-PCR for diagnosis of infectious salmon anaemia virus (ISAV) in carrier sea trout Salmo trutta after experimental infection
Bibliographic record
Abstract
The emergence of infectious salmon anaemia virus (ISAV) in Canada and Scotland and frequent new outbreaks of the disease in Norway strongly suggest that there are natural reservoirs for the virus. The main host for the ISA virus is probably a fish occurring in the coastal area, most likely a salmonid fish. Since sea trout is an abundant species along the Norwegian coast, common in areas where ISA outbreaks occur, and possibly a life-long carrier of the ISA virus, a study was initiated to evaluate reverse transcriptase polymerase chain reaction (RT-PCR) for diagnosis of the virus in experimentally infected trout. Several tissues (kidney, spleen, heart and skin) were collected from the trout during a 135 d period. The following diagnostic methods for detection of the ISA virus were compared: cell culture (Atlantic Salmon Kidney, ASK cells), challenge of disease-free salmon with blood from the infected trout, and RT-PCR. The RT-PCR was the most sensitive of these methods. With the help of this technique it was possible to pick out positive individuals throughout the experimental period of 135 d. Challenge of disease-free salmon were more sensitive than cell culture (ASK cells). These 2 latter methods require use of the immunofluorescent antibody test (IFAT) or RT-PCR for verification of presence of ISA virus.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".