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Record W626226248

Progress toward developing trapping techniques for the emerald ash borer

2005· article· en· W626226248 on OpenAlexaboutno aff
Therese M. Poland, Deborah G. McCullough, Peter de Groot, G. G. Grant, Linda MacDonald, David Cappaert

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsnot available
Fundersnot available
KeywordsEmerald ash borerAgrilusBuprestidaeQuarantineGeographyInfestationEcologyBiologyForestryFraxinusAgronomy
DOInot available

Abstract

fetched live from OpenAlex

Since the 2002 discovery of emerald ash borer (EAB), Agrilus planipennis Fairmaire (Coleoptera: Buprestidae), in southeastern Michigan and Windsor, Ontario, the distribution of this exotic insect has continued to expand. The primary infestation in Michigan currently includes 13 counties, with small isolated pockets in at least 13 other counties. Accurate delimitation of the infested area and detection of new outlier infestations is critical for regulatory officials who must establish the quarantine boundaries and implement eradication and control measures. Trapping and detection techniques would greatly enhance survey efforts to delineate the distribution of EAB and locate new infestations.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.802
Threshold uncertainty score1.000

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)0.0010.000

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 head0.020
GPT teacher head0.265
Teacher spread0.245 · 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.

Study designNot applicable
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

Citations23
Published2005
Admission routes1
Has abstractyes

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