Cabbage Looper Resistance to a Nucleopolyhedrovirus Confers Cross-Resistance to Two Granuloviruses: Table 1.
Bibliographic record
Abstract
Previously, we showed that cabbage loopers (Trichoplusia ni Hübner) can evolve >20X resistance to the single (S) nucleocapsid nucleopolyhedrovirus (NPV) of Trichoplusia ni (TnSNPV). In this study, we investigate one potential cost that resistant cabbage loopers may incur, increased susceptibility to other mortality agents. Contrary to expectation, no such cost was observed with any of the six mortality agents tested. In fact, the LD50 of selected larvae was always greater than that of control caterpillars for each agent tested. However, the differences were never significant for permethrin or Bacillus thuringiensis subsp kurstaki (Berliner). The differences in the LD50 of control and selected T. ni for the wild-type multiple (M) nucleocapsid NPV of Autographa californica Speyer (AcMNPV, clone C6) and the recombinant AcMNPV (AcMNPV-AaIT) were small (≈2X) and significant in only one of three generations. Surprisingly, the highest level of cross-resistance was to the granuloviruses of Pieris rapae L. (4–5X; significant in two of three generations) and T. ni (20–30X; significant in three of three generations). This suggests that the infection pathway of TnSNPV may be more similar to TnGV than to that of AcMNPV.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".