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Record W1541487537 · doi:10.1111/afe.12090

Goldspotted oak borer effects on tree health and colonization patterns at six newly‐established sites

2014· article· en· W1541487537 on OpenAlexaff
Laurel J. Haavik, Mary Louise Flint, Tom W. Coleman, Robert C. Venette, Steven J. Seybold

Bibliographic record

VenueAgricultural and Forest Entomology · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsOntario Forest Research Institute
Fundersnot available
KeywordsBiologyBuprestidaeBroodInfestationPopulationEcologyTree healthForagingColonizationPEST analysisBotany

Abstract

fetched live from OpenAlex

Abstract Newly‐established populations of invasive wood‐inhabiting insects provide an opportunity for the study of invasion dynamics and for collecting information to improve management options for these cryptic species. From 2011 to 2013, we studied the dynamics of the goldspotted oak borer A grilus auroguttatus S chaeffer ( C oleoptera: B uprestidae), a new pest of oaks in southern C alifornia, at six sites that had been colonized recently. At all sites, the percentage of coast live oaks Q uercus agrifolia N ée, colonized by A . auroguttatus increased between 2011 (6–33%) and 2013 (23–40%), although beetle densities did not grow rapidly at most sites. From 2011 to 2013, there were minor changes in signs and symptoms of A . auroguttatus infestation (adult emergence holes, bark staining, and evidence of woodpecker foraging), except at one site where an outbreak occurred. At some sites, noticeable negative changes in oak crown health occurred 1 year prior to positive A . auroguttatus population growth. Among sites, most of the A . auroguttatus population density (66–93%) was produced by a small number of heavily‐infested trees (= brood trees). Early identification and removal of brood trees in newly‐invaded areas could slow the growth of A . auroguttatus populations.

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 score0.027
Threshold uncertainty score0.700

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)0.0000.000

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 head0.004
GPT teacher head0.194
Teacher spread0.190 · 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

Citations11
Published2014
Admission routes1
Has abstractyes

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