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Record W4241803621 · doi:10.1079/cpc.3780.20210102619

Agrilus planipennis (emerald ash borer).

2021· preprint· en· W4241803621 on OpenAlexaboutno aff
Marc Kenis

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsnot available
Fundersnot available
KeywordsEmerald ash borerAgrilusFraxinusBiodiversityGeographyFirewoodAgroforestryForestryEcologyBiologyArchaeology

Abstract

fetched live from OpenAlex

Abstract The emerald ash borer, A. planipennis is an East Asian wood-boring beetle that is presently causing dramatic damage to ash (Fraxinus spp.) in the USA and Canada. Since its discovery in 2002 in Michigan, the beetle has quickly spread to at least 15 US States and Canadian Provinces, mainly through the transport of infested firewood and other wood products. In about 10 years, it is estimated that the beetle has killed over 30 million forest and ornamental trees, causing significant economic damage as well as serious concern for the survival of several ash species and related biodiversity and ecosystems in North America. The beetle has recently been discovered in the region of Moscow, from where it could invade the whole of Europe. Given its enormous impact in North America, the beetle is now on the alert list of many global, regional and national plant protection and environment protection organizations worldwide.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

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)0.0110.006

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 head0.009
GPT teacher head0.215
Teacher spread0.205 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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