Factors influencing aestivation in<i>Laricobius nigrinus</i>(Coleoptera: Derodontidae), a predator of<i>Adelges tsugae</i>(Hemiptera: Adelgidae)
Bibliographic record
Abstract
Abstract Laricobius nigrinusFender is being reared for release as a biological control agent for hemlock woolly adelgid (HWA),Adelges tsugaeAnnand. HWA is an introduced insect lethal to hemlock trees (Tsuga canadensis(L.) Carr. andT. carolinianaEngelm.) in the eastern United States. In nature, the predator (Laricobius nigrinus) and its prey (HWA) undergo a dormant period in the summer (aestivation). In the laboratory, the aestivation ofL. nigrinushas not been synchronized with that of HWA, resulting in significant predator mortality. Four factors (genetics, temperature, photoperiod, and moisture) were investigated for their effects on aestivation inL. nigrinus. Both the number of individuals and the time at which they emerged from aestivation were measured in response to these factors. Temperature was the most important cue for termination of aestivation, and photoperiod was a modifying factor. High temperature and long day length delayed emergence and high moisture levels resulted in greater emergence but did not affect emergence time. Genetics, as represented by broods, was not a major factor in aestivation termination. These results have led to improvement in rearingL. nigrinus, since emergence from aestivation can now be synchronized with the active period of HWA. Increased success in rearing has expedited field releases ofL. nigrinusin the eastern United States.
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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".