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Record W2209346199 · doi:10.1111/afe.12140

The life cycle of the emerald ash borer <i>Agrilus planipennis</i> in European Russia and comparisons with its life cycles in Asia and North America

2015· article· en· W2209346199 on OpenAlexaboutno aff
Marina J. Orlova‐Bienkowskaja, Andrzej O. Bieńkowski

Bibliographic record

VenueAgricultural and Forest Entomology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsnot available
FundersRussian Foundation for Basic Research
KeywordsAgrilusEmerald ash borerBuprestidaeFraxinusBiologyPEST analysisEcologyInstarLarvaGeographyBotany

Abstract

fetched live from OpenAlex

Agrilus planipennis Fairmaire (Coleoptera: Buprestidae), native to Asia, is a destructive invasive pest of ash Fraxinus spp. in U.S.A. , Canada and European Russia. It is spreading quickly and will probably soon be detected in other European countries. Information about the life cycle of the pest is needed for detection and survey efforts, development of control options and predicting the potential range in Europe. The life cycle has been studied in North America and Asia, although it has not previously been studied in European Russia. The number of larval instars and the duration of development of A. planipennis in European Russia were determined. Distributions of width of epistome and length of urogomphi indicated four larval instars. The number of excretory ducts and the presence of ledges did not provide a clear differentiation between instars. Development in most of the specimens took 2 years. Generation time is flexible. In warmer regions (Tianjin), most individuals finish development in 1 year, whereas, in colder regions (Moscow, Changchun, Harbin), it takes 2 years. In intermediate climatic regions (Michigan), the ratio of 1 : 2‐year life cycles depends on additional factors. The flexibility of the life cycle allows A. planipennis to establish in regions with different climates.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.967

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.189
Teacher spread0.179 · 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.

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

Citations53
Published2015
Admission routes1
Has abstractyes

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