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Record W38013985

Population biology of emerald ash borer and its natural enemies in China

2008· article· en· W38013985 on OpenAlexaboutno aff
Houping Liu, Leah S. Bauer, Tonghai Zhao, Ruitong Gao

Bibliographic record

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

Abstract

fetched live from OpenAlex

Agrilus planipennis Fairmaire (Coleoptera: Buprestidae), also known as emerald ash borer (EAB), was first discovered in Michigan and Ontario, Canada, in 2002 following investigations of declining and dying ash trees (Fraxinus spp.). Agrilus planipennis has also spread to Ohio, Indiana, Maryland, Virginia, Illinois, Pennsylvania, and West Virginia by natural dispersal and transport of infested ash materials. As of 2007, over 25 million ash trees have been killed by this pest in Michigan alone. The adverse effects of A. planipennis on forest biodiversity, ash resources, and urban areas in North America are high as ash trees are widely distributed and planted throughout North America. In its native country of China, A. planipennis was considered only a minor and periodic pest of ash trees?presumably due the presence of natural enemies and host resistance. The introduction of North America ash species in recent decades, however, elevated A. planipennis to pest status in some areas and increased its distribution to additional locations in northern China.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.064

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 studies0.0000.000
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 head0.006
GPT teacher head0.215
Teacher spread0.209 · 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 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

Citations0
Published2008
Admission routes1
Has abstractyes

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