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Insect growth‐reducing and antifeedant activity in Eastern North America hardwood species and bioassay‐guided isolation of active principles from <i>Prunus serotina</i>

2000· article· en· W2017430918 on OpenAlexaff
Samia S. Omar, Michel Lalonde, Meghan E Marcotte, Margaret Cook, Jérôme Proulx, K. Goel, Tony Durst, Bernard J. R. Philogène, John T. Arnason

Bibliographic record

VenueAgricultural and Forest Entomology · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Pest Control Strategies
Canadian institutionsDomtar (Canada)University of Ottawa
Fundersnot available
KeywordsBiologyBioassayBark (sound)SitophilusPyralidaeBotanyEuropean corn borerEriodictyolHorticulturePrunusRice weevilOstriniaPEST analysisNaringeninEcology

Abstract

fetched live from OpenAlex

Abstract 1 Thirty extracts of wood and bark of hardwood trees from Eastern North America were examined for insect growth‐reducing activity in a bioassay with European corn borer, Ostrinia nubilalis , and an antifeedant bioassay with the rice weevil, Sitophilus oryzae . 2 Nine of the bark extracts and four of the wood extracts showed significant growth reducing effects at 0.5% in meridic diets, whereas only two bark extracts and one wood extract showed significant antifeedant effect at the same concentration. 3 Slower growing tree species were more biologically active than fast growing ones. Isolation of the bioactive compounds in one of the active species, Prunus serotina , showed that naringenin, its derivative methoxynaringenin, and eriodictyol were responsible for the antifeedant effects.

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 score0.004
Threshold uncertainty score0.009

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 head0.023
GPT teacher head0.201
Teacher spread0.179 · 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

Citations13
Published2000
Admission routes1
Has abstractyes

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