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Record W2981211737 · doi:10.30843/nzpp.2009.62.4869

Would St Johns wort beetles have been introduced to New Zealand nowadays

2009· article· en· W2981211737 on OpenAlexaboutno aff
Ronny Groenteman, Simon V. Fowler, Jon J. Sullivan

Bibliographic record

VenueProceedings of the New Zealand Weed Control Conference · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBiological Control of Invasive Species
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyHypericum perforatumBiological pest controlMidgeIndigenousWeedToxicologyGallBotanyEcology

Abstract

fetched live from OpenAlex

The classical biological control programme against St Johns wort (hereafter SJW) Hypericum perforatum is considered one of the greatest success stories in New Zealands history of weed biocontrol The first biocontrol agent the lesser SJW beetle Chrysolina hyperici (Coleoptera Chrysomelidae) was introduced to New Zealand in 1943 following hostrange testing in Australia which as an acceptable standard at the time did not include indigenous plant species No further hostrange testing was carried out in New Zealand Introduction of the greater SJW beetle C quadrigemina and the gall midge Zeuxidiplosis giardi followed in the 1960s The introduction of SJW beetles was re examined in the light of current hostrange testing standards In host specificity testing SJW beetle larval feeding and adult oviposition took place on indigenous Hypericum spp in both nochoice and choice tests clearly suggesting that these highly effective agents would have been considered unsafe for introduction to New Zealand under current standards Preliminary field observations suggest however that the risk to indigenous Hypericum spp is minimal raising an inevitable dilemma while safety in current host range testing is extremely high are we more likely to reject potentially effective agents through falsepositives expressed in our artificial testing arenas

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)0.001
metaresearch head score (Gemma)0.001
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 score0.115
Threshold uncertainty score0.228

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.001

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 head0.020
GPT teacher head0.217
Teacher spread0.197 · 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
Published2009
Admission routes1
Has abstractyes

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Same venueProceedings of the New Zealand Weed Control ConferenceSame topicBiological Control of Invasive SpeciesFrench-language works237,207