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Record W2095792431 · doi:10.1673/031.011.12901

Solid-Stemmed Wheat Does Not Affect Overwintering Mortality of the Wheat Stem Sawfly,<i>Cephus cinctus</i>

2011· article· en· W2095792431 on OpenAlexafffund
Héctor A. Cárcamo, Brian L. Beres, C. E. Herle, H. D. J. McLean, Sean McGinne

Bibliographic record

VenueJournal of Insect Science · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaWestern Grains Research Foundation
KeywordsSawflyBiologyOverwinteringCultivarAgronomyHardiness (plants)PEST analysisPopulationBotanyLarva

Abstract

fetched live from OpenAlex

The wheat stem sawfly, Cephus cinctus Norton (Hymenoptera: Cephidae), is a key pest of wheat in the northern Great Plains of North America. Host plant resistance in the form of solid-stemmed wheat cultivars is the main control strategy for C. cinctus. This study investigated the effect of novel and traditional solid wheat hosts on the overwintering mortality and cold-hardiness of C. cinctus. Field conditions from 2003-2005 showed that overwintering mortality in various wheat cultivars averaged 8% and was not related to the type of wheat cultivar. Similarly, supercooling points (-22° C) were not influenced by wheat host type. C. cintus are cold-hardy; up to 80% survive 10 days at -20° C and 10% survive 40 days. Its overwintering microhabitat near the crown area of the plant is well insulated for temperatures above -10° C and remains ~ 20° C above ambient minima. These data suggest that winter mortality is a minor factor in the population dynamics of wheat stem sawfly, and despite clear detrimental effects on larval weight and adult fitness, solid-stemmed cultivars do not reduce the ability of larvae to survive winters.

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 score0.004

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 head0.041
GPT teacher head0.262
Teacher spread0.221 · 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

Citations16
Published2011
Admission routes2
Has abstractyes

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