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Record W2068296951 · doi:10.1673/031.013.5901

Monoterpenes from Larval Frass of Two Cerambycids as Chemical Cues for a Parasitoid,<i>Dastarcus helophoroides</i>

2013· article· en· W2068296951 on OpenAlexfundno aff
Jian‐Rong Wei, Xiping Lu, Li Jiang

Bibliographic record

VenueJournal of insect science/Journal of Insect Science · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsnot available
FundersU.S. Forest ServiceNatural Science Foundation of Shandong ProvinceChinese Academy of ForestryCanadian Forest ServiceNational Natural Science Foundation of China
KeywordsBiologyLonghorn beetleFrassParasitoidPantropicalEcologyPopulationParasitismHost (biology)LarvaBotany

Abstract

fetched live from OpenAlex

Anopiophora glabripennis (Motsch.) (Coleoptera: Cerambycidae) is a destructive woodborer, attacking many species of deciduous hardwood trees. Apriona swainsoni (Hope) (Coleoptera: Cerambycidae) is a woodborer of Sophora japonica L. (Angiospermae: Fabaceae). Dastarcus helophoroides (Fairmaire) (Coleoptera: Bothrideridae) is an important natural enemy of both Cerambycid species in China. Kairomones for two populations of D. helophoroides that parasitize A. glabripennis and A. swainsoni respectively were studied. Based on identification and quantification of volatiles from larval frass produced by A. glabripennis and A. swainsoni, monoterpenes were selected to test their kairomonal activity to both populations of D. helophoroides adults using a Y-tube olfactometer. The results indicated that (S)-(-)-limonene served as a kairomone for the population of D. helophoroides parasitized A. glabripennis. α-pinene, (IR)-(+)-αpinene and (+)-β-pinene were attractive to the population of D. helophoroides parasitized A. swainsoni. The results provide information about the co-evolution of D. helophoroides, its host, and host-food trees.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.012
GPT teacher head0.262
Teacher spread0.250 · 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 source (direct Gemma or distilled Codex), 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

Citations22
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueJournal of insect science/Journal of Insect ScienceSame topicForest Insect Ecology and ManagementFrench-language works237,207