Detection of Viral Hemorrhagic Septicemia Virus by Quantitative Reverse Transcription Polymerase Chain Reaction from Two Fish Species at Two Sites in Lake Superior
Bibliographic record
Abstract
Viral hemorrhagic septicemia virus (VHSV) was first detected in the Laurentian Great Lakes in 2005 during a mortality event in the Bay of Quinte, Lake Ontario. Subsequent analysis of archived samples determined that the first known isolation of VHSV in the Laurentian Great Lakes was from a muskellunge Esox masquinongy collected in Lake St. Clair in 2003. By the end of 2008, mortality events and viral isolations had occurred in all of the Laurentian Great Lakes except Lake Superior. In 2009, a focused disease surveillance program was designed to determine whether VHSV was also present in Lake Superior. In this survey, 874 fish from 7 sites along the U.S. shoreline of Lake Superior were collected during June 2009. Collections were focused on nearshore species known to be susceptible to VHSV. All fish were dissected individually by using aseptic techniques and were tested for the presence of VHSV genetic material by use of a quantitative reverse transcription (qRT) polymerase chain reaction (PCR) targeting the viral nucleoprotein gene. Seventeen fish from two host species at two different sites tested positive at low levels for VHSV. All attempts to isolate virus in cell culture were unsuccessful. However, the presence of viral RNA was confirmed independently in five fish by using a nested PCR that targeted the glycoprotein (G) gene. Partial G gene sequences obtained from three fish were identical to the corresponding sequence from the original 2003 VHSV isolate (MI03) from muskellunge. These detections represent the earliest evidence for the presence of VHSV in Lake Superior and illustrate the utility of the highly sensitive qRT-PCR assay for disease surveillance in aquatic animals.
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 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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".