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Record W4411543331 · doi:10.1139/cjps-2024-0259

Effects of kaolin clay on flea beetles and other pests and non-target insects on tatsoi

2025· article· en· W4411543331 on OpenAlexafffundvenue
Iniya Rajan, G. Christopher Cutler

Bibliographic record

VenueCanadian Journal of Plant Science · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMollusks and Parasites Studies
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyInsectFleaAgronomyEcology

Abstract

fetched live from OpenAlex

Kaolin is a natural aluminium silicate clay material of interest for insect pest management. We conducted field and laboratory experiments to assess effects of kaolin (Surround WP ® ) on pest and beneficial insects. In a field experiment with tatsoi greens ( Brassica rapa subsp. narinosa), kaolin applications, particularly at high rate (50 g AI L −1 ) reduced shot hole damage, as well as captures of crucifer flea beetles, striped flea beetles, aphids, and leafhoppers on sticky cards to levels comparable to an insecticide industry standard, while maintaining plant vigour. In the same field experiment, some kaolin treatments reduced captures of carabid beetles on some dates, but parasitic wasp captures on sticky cards were unaffected. In laboratory experiments, kaolin treatments did not cause mortality of two-spotted spider mite, green peach aphid, or diamondback moth larvae, but diamondback moth larvae avoided and consumed less cabbage foliage treated with kaolin. Our results suggest that kaolin can reduce crucifer and striped flea beetle damage on Brassicaceae crops like tatsoi and may provide similar protection against diamondback moth on Brassicaceae crops, while posing low hazard to non-target beneficial insects.

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)0.000
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 score0.428
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.009
GPT teacher head0.212
Teacher spread0.203 · 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

Citations1
Published2025
Admission routes3
Has abstractyes

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