Development and Evaluation of Methods To Detect Nucleopolyhedroviruses in Larvae of the Douglas-Fir Tussock Moth, <i>Orgyia pseudotsugata</i> (McDunnough)
Bibliographic record
Abstract
Various molecular methods are used to detect pathogenic microorganisms and viruses within their hosts, but these methods are rarely validated by direct comparison. Southern hybridization, enzyme-linked immunosorbent assay (ELISA), and a novel DNA extraction/PCR assay were used to detect Orgyia pseudotsugata multiple nucleopolyhedrovirus (OpMNPV) in Douglas-fir tussock moth larvae. PCR was more sensitive than Southern hybridization and ELISA at detecting semipurified virus. ELISA, however, was the most accurate method for detecting virus within larvae, given that Southern hybridization and PCR produced false-negative results (31% and 2.5%, respectively). ELISA may be preferable in some applications because virus infections can be quantified (r(2) = 0.995). These results may be applicable to both applied and academic research that seeks to accurately identify the incidence of viruses and microorganisms that regulate insect populations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".