The influences of host plant and genetic resistance to <i>Bacillus thuringiensis</i> on trade‐offs between offspring number and growth rate in cabbage loopers, <i>Trichoplusia ni</i>
Bibliographic record
Abstract
Abstract. 1. Variation in progeny size and quality is common among insects and this variation can strongly influence individual fitness. Larger progeny typically survive better and develop faster under adverse conditions and may have higher fecundity. Due to resource limitations, however, trade‐offs may arise between having fewer large offspring or more smaller ones. 2. For cabbage loopers, Trichoplusia ni , pepper leaves are a poorer larval host than cucumber or tomato leaves as indicated by survival, development rate, and body size. Moths reared on cucumber produced more slower growing offspring than those that had been reared on pepper, which produced fewer, faster growing progeny. 3. Traits conferring resistance to Bacillus thuringiensis ( Bt ) generally are associated with strong deleterious effects that may influence resource allocation and reproductive trade‐offs between progeny size and number. 4. Unlike the host‐plant related trade‐off between progeny size and fecundity observed among susceptible control moths, Bt ‐resistant parents had both the lowest fecundity and smallest progeny size on all host plants. This finding suggests that the progeny size–number relationship is constrained in resistant individuals.
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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 | 0.000 | 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) | 0.001 | 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".