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Record W166852427

INSECT REARING - A TOOL FOR DETECTING NON-INDIGENOUS WOOD BORING INSECTS

2009· article· en· W166852427 on OpenAlexaboutno aff
Troy Kimoto, Lee M. Humble

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousBroodGeographyBark (sound)Bark beetleForestryEcologyBiology
DOInot available

Abstract

fetched live from OpenAlex

Since 1998, the Canadian Food Inspection Agency (CFIA) has been using Lindgren funnel traps baited with the exotic bark beetle lure, ultra high release (UHR) ethanol, and UHR ethanol/UHR alpha-pinene to detect non-indigenous wood boring insects. However, several insects either do not respond to the lures used in this survey or do not rely on long-range chemicals to locate mates or host trees. Although effective at detecting some target species, this type of survey limits the spectrum of potentially detectable insects. Rearing insects from infested logs is a more generalized approach to detection because it does not exclude insects that do not respond to specific lures. As long as brood production of a given species occurs under the bark or within the wood of any tree, this survey has the capability to detect that insect. The CFIA, in partnership with the Canadian Forest Service, City of Surrey, City of Toronto, City of Montreal, Halifax Regional Municipality, and Vancouver Parks Board, is rearing infested logs as a tool for detecting established populations of non-indigenous wood boring insects. Steel marine transport containers (40 feet long) were modified into climate-controlled rearing facilities and placed in pre-selected locations in each of the cities (Surrey, Toronto, Montreal, Dartmouth). Logs that meet specific criteria (e.g., proximity to high risk sites, state of decline, signs of insect activity, etc.) are obtained through a city’s hazard tree removal program. Logs are placed in sleeve cages suspended from an overhead racking system or placed in modified sonotubes/building forms and held for insect emergence. To date, ambrosia beetles, weevils, bark beetles, longhorn beetles, and metallic wood borers have been reared from a variety of softwood and hardwood species. Although a few naturalized non-indigenous species have been collected, most of the reared insects are native. To date, there have not been any new records of introduced species.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.012
GPT teacher head0.222
Teacher spread0.211 · 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 designBench or experimental
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

Citations2
Published2009
Admission routes1
Has abstractyes

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