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Record W2995238993 · doi:10.1093/jee/toz331

Assessment of the Systems Approach for the Phytosanitary Treatment of Wood Infested With Wood-Boring Insects

2019· article· en· W2995238993 on OpenAlexafffund
Chris J.K. MacQuarrie, Meghan Gray, Robert Lavallée, Meghan K. Noseworthy, Marc E. Savard, Leland M. Humble

Bibliographic record

VenueJournal of Economic Entomology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsFPInnovationsNatural Resources CanadaCanadian Forest Service
FundersNatural Resources CanadaCanadian Food Inspection Agency
KeywordsEmerald ash borerAgrilusBuprestidaeFraxinusBiologyPhytosanitary certificationPEST analysisIntegrated pest managementPest controlAgroforestryAgronomyToxicologyHorticultureEcology

Abstract

fetched live from OpenAlex

Addressing the risk from pests present in wood and wood products destined for international trade is an essential step towards minimizing the movement, introduction and establishment of invasive species. One method of managing the pest risk associated with wood commodities is the use of a systems approach that incorporates multiple independent measures applied along a production pathway. However, quantifying the reduction of risk can be difficult because the approach requires raw material infested with the pest of interest at a sufficient density to be able to quantify changes in pest abundance. We tested a systems approach for the production of sawn wood using green ash, Fraxinus pennsylvanica Marshall (Lamiales: Oleaceae), infested with emerald ash borer, Agrilus planipennis Fairmaire (Coleoptera: Buprestidae), by quantifying the change in pest density during the milling process and the precise effect of heat treatment on insects in situ. Greater than 90% of emerald ash borer were removed at the first step of the milling process (debarking) and >99% were removed before the production of green sawn wood. No insects survived kilning or heat treatment. All life stages of emerald ash borer were killed at 56°C and above. Heat, however, had no sublethal effect on emerald ash borer performance. These results show that the application of a systems approach to mitigate emerald ash borer in heat-treated, sawn wood is effective. Moreover, the model-system approach developed in this study can be a template for investigating the effect of systems approaches for other phloem-feeding 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 score0.389
Threshold uncertainty score0.220

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 head0.015
GPT teacher head0.243
Teacher spread0.228 · 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

Citations14
Published2019
Admission routes2
Has abstractyes

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