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Record W2147079447 · doi:10.4039/tce.2014.42

Interactions between <i>Camelina sativa</i> (Brassicaceae) and insect pests of canola

2014· article· en· W2147079447 on OpenAlexaffabout
Juliana J. Soroka, Chrystel Olivier, Larry Grenkow, G. Séguin-Swartz

Bibliographic record

VenueThe Canadian Entomologist · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBiologyDiamondback mothPlutellidaeCamelina sativaPlutellaBrassicaBotanyMedicago sativaLepidoptera genitaliaBrassicaceaeNoctuidaeCanolaAgronomyCrop

Abstract

fetched live from OpenAlex

Abstract In an investigation of Camelina sativa (Linnaeus) Crantz (Brassicaceae) and five common insect pests of canola ( Brassica napus Linnaeus) (Brassicaceae), little feeding damage to the plant was inflicted by crucifer-feeding specialist flea beetles ( Phyllotreta Chevrolat species) (Coleoptera: Chrysomelidae), Delia Robineau-Desvoidy (Diptera: Anthomyiidae) root maggots, or diamondback moth ( Plutella xylostella Linnaeus (Lepidoptera: Plutellidae)). In choice tests, diamondback moths laid fewer eggs on C. sativa than on B. napus leaves. Diamondback moth larvae consumed less C. sativa leaf tissue, and tended to have a longer developmental period on C. sativa . Larvae of the polyphagous bertha armyworm ( Mamestra configurata Walker (Lepidoptera: Noctuidae)) had similar feeding levels on C. sativa and B. napus plants. However, there was a longer developmental period from larval to pupal stage and pupae weighed less when fed on C. sativa foliage, suggesting that C. sativa contains antibiosis factors against bertha armyworm. Two strains of aster yellows phytoplasma, 16SrI-A and 16SrI-B, were identified in C. sativa and in Macrosteles quadrilineatus (Forbes) (Hemiptera: Cicadellidae). Differences in incidence of aster yellows and abundance of M. quadrilineatus were observed among lines of C. sativa . The findings confirm that C. sativa is unlikely to support high populations of these insect pests on the Canadian prairies.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.544
Threshold uncertainty score0.525

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 head0.021
GPT teacher head0.224
Teacher spread0.204 · 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

Citations28
Published2014
Admission routes2
Has abstractyes

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