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Record W2104929970 · doi:10.4039/n06-110

Factors influencing aestivation in<i>Laricobius nigrinus</i>(Coleoptera: Derodontidae), a predator of<i>Adelges tsugae</i>(Hemiptera: Adelgidae)

2007· article· en· W2104929970 on OpenAlexfundno aff
Ashley Lamb, Scott M. Salom, Loke T. Kok

Bibliographic record

VenueThe Canadian Entomologist · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsnot available
FundersCanadian Forest Service
KeywordsAestivationBiologyTsugaPredatorEcologyPredationBiological pest controlBotany

Abstract

fetched live from OpenAlex

Abstract Laricobius nigrinus Fender is being reared for release as a biological control agent for hemlock woolly adelgid (HWA), Adelges tsugae Annand. HWA is an introduced insect lethal to hemlock trees ( Tsuga canadensis (L.) Carr. and T. caroliniana Engelm.) 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 of L. nigrinus has 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 in L. 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 rearing L. nigrinus , since emergence from aestivation can now be synchronized with the active period of HWA. Increased success in rearing has expedited field releases of L. nigrinus in the eastern United States.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.548
Threshold uncertainty score0.685

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.017
GPT teacher head0.228
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations26
Published2007
Admission routes1
Has abstractyes

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