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Record W4399538187 · doi:10.1079/20240228432

Emerald Ash Borer, Agrilus planipennis (Fairmaire)

2023· report· en· W4399538187 on OpenAlexaboutno aff
Neil Audsley, Gonzalo Avila, Claudio Ioratti, Valérie Caron, Chiara Ferracini, Tibor Bukovinszki, Marc Kenis, Panagiotis Milonas, Annette Herz, Stanislav Trdan, Ana-Christina Fatu, Giuseppino Sabbatini-Peverieri, Vincent Lesieur, Nicolas Borowiec, Jana Collatz, Rob Tanner, Conor McGee

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsnot available
Fundersnot available
KeywordsEmerald ash borerAgrilusBuprestidaeFraxinusBiologyBotany

Abstract

fetched live from OpenAlex

The emerald ash borer (EAB), Agrilus planipennis, is a highly destructive pest native to Asia, first detected in North America in 2002 and in European Russia in 2003. EAB has caused extensive damage to ash trees in North America and Europe, leading to severe ecological and economic consequences. To combat this pest, several hymenopteran parasitoids from the native range of EAB were imported to the USA and Canada for biological control. Key parasitoids include Tetrastichus planipennisi, Spathius galinae and Oobius agrili, which have established in many areas and shown significant success in reducing EAB populations. T. planipennisi and S. galinae are particularly effective, while the impact of O. agrili is still being evaluated. O. agrili has not established well in the USA or Canada. Other potential biological control agents, such as Atanycolus nigriventris, Oobius primorskensis and Spathius polonicus, show promise but face challenges in host specificity and rearing. Continued research and monitoring are essential for effective EAB management.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.105
Threshold uncertainty score0.208

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.048
GPT teacher head0.294
Teacher spread0.246 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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