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Record W2168755664 · doi:10.4039/n05-023

Effect of pea flour and pea flour extracts on<i>Sitophilus oryzae</i>

2006· article· en· W2168755664 on OpenAlexafffund
Xingwei Hou, Wes Taylor, Paul G. Fields

Bibliographic record

VenueThe Canadian Entomologist · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Pest Control Strategies
Canadian institutionsAgriculture and Agri-Food Canada
FundersUniversity of Manitoba
KeywordsSitophilusRice weevilFood scienceBiologyWheat flourRed flour beetleMidgutInsectBotanyLarva

Abstract

fetched live from OpenAlex

Abstract Protein-rich pea flour is an antifeedant and a repellent and is toxic to the rice weevil,Sitophilus oryzae(L.), but its mode of action is not known. Results showed that protein-rich pea flour had no fumigant effect on adult survival or offspring production ofS. oryzae. In a contact experiment, immobilized weevils were fed every other day and had their abdomens brushed with protein-rich pea flour or wheat flour on the alternate days. Insects treated with protein-rich pea flour had an average longevity of 9.6 days, which was significantly shorter than that for insects treated with wheat flour (11.3 days) or brushed controls (17.6 days). These results suggest that toxins from the protein-rich pea flour may be able to penetrate the insect cuticle. Midguts from weevils fed protein-rich pea flour, a pea flour extract, or a mixture of pea peptides contained numerous bubbles. Midgut tissues in these treated adults were injured, as shown by dual staining with the fluorescent dyes calcein AM and propidium iodide. The volume of the bubbles increased rapidly when insects were fed protein-rich pea flour or pea flour extract. There were no bubbles found in the midguts ofS. oryzaethat fed on wheat kernels or wheat flour.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

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 head0.007
GPT teacher head0.198
Teacher spread0.191 · 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 designBench or experimental
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

Citations7
Published2006
Admission routes2
Has abstractyes

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