Prevalence of PcaFV in Apostichopus californicus specimens collected in Southeast Alaska from Jun to Nov 2021
Bibliographic record
Abstract
Understanding the prevalence and load of aquatic invertebrate flaviviruses is essential to estimating risk to fisheries. We surveyed the prevalence of the Apostichopus californicus (urn:lsid:marinespecies.org:taxname:529363) associated flavivirus (PcaFV) using two approaches: Loop-mediated isothermal amplification (LAMP) and quantitative reverse transcriptase PCR. We targeted this survey around populations of A. californicus: specimens collected from Sitka Sound, Sitka, Alaska (Baranof Island), Southeast Alaska, and Nanoose, British Columbia, Canada. We found that LAMP detected PcaFV in 21% of tested specimens, and qRT-PCR in 88% of tested specimens. The mean load of PcaFV in copies per ng RNA extracted was significantly higher in specimens that were positive by LAMP compared to those in which LAMP did not detect PcaFV. This dataset contains PcaFV prevalence determined by RT-LAMP and qRT-PCR, as well as associated collection metadata.
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".