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Reducing pest risk in birch wood products - The effective heat treatment for bronze birch borer Agrilus anxius (Coleoptera: Buprestidae) prepupae

2024· dataset· en· W6944920445 on OpenAlexaffabout

Bibliographic record

VenueGEOSCAN · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsAgrilusPhytosanitary certificationPEST analysisPest controlIntegrated pest managementKiln

Abstract

fetched live from OpenAlex

PURPOSE: Determine the time and temperature combinations that result in partial and complete mortality of larvae of the Bronze birch borer DESCRIPTION: The protection of forest resources and the safe trade of forest products require phytosanitary measures which reduce the risk of pest movement to novel environments. Technically sound science to develop measures are required to support safe trade policies. Heat treatment is a widely available, efficient and effective method to produce phytosanitary wood products destined for trade. Defining the optimal heat treatment dose needed to kill insects in wood products reduces the risk of spreading exotic species to new environments with the lowest possible energy cost which in turn reduces environmental impacts and provides confidence in current guidelines for heat treatment regulations. The minimum effective heat treatment dose (time and temperature) for Agrilus anxius (bronze birch borer) prepupae was determined using the Humble water bath applying heat in vitro. Heat treatment was assessed using a controlled increase in temperature to simulate the heat ramp applied to wood in industrial kilns and conventional heat chamber operations. Target temperatures between 51 and 56 °C for exposure durations of 15 and 30 min were tested to determine the minimum effective dose. Prepupal A. anxius did not survive exposure to 53, 54, 55 or 56 °C for 30 min or 54 and 56 °C for 15 min. Chronic mortality was observed at 53 °C for 15 min treatments. Evaluating the effect of specific heat treatment parameters for other forest pests is recommended to identify and validate the minimum temperature and time required to kill wood pests in order to avoid introducing exotic species with wood products and limit pest movement. Data was collected at the following sites: Insects for these experiments were collected from trees harvested in Victoria, British Columbia and the Valcartier Research Forestry Research Station, Valcartier, Quebec. Experiments were conducted at the Pacific Forestry Centre in Victoria, British Columbia and the Laurentian Forestry Centre in Ste Foy, Quebec.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.051
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.006

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 head0.014
GPT teacher head0.278
Teacher spread0.264 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2024
Admission routes2
Has abstractyes

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