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Record W1861380621 · doi:10.1002/ps.3714

Field type, trap type and field‐edge characteristics affect <i>Rhagoletis mendax</i> captures in lowbush blueberries

2013· article· en· W1861380621 on OpenAlexafffund
Justin M. Renkema, G. Christopher Cutler, Sonia O. Gaul

Bibliographic record

VenuePest Management Science · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect behavior and control techniques
Canadian institutionsNova Scotia Department of AgricultureAgriculture and Agri-Food CanadaUniversity of GuelphDalhousie University
FundersDepartment of Agriculture, Nova Scotia
KeywordsTephritidaeBiologyInfestationEricaceaeMaggotHorticultureVacciniumBotanyPEST analysis

Abstract

fetched live from OpenAlex

BACKGROUND: Blueberry maggot, Rhagoletis mendax Curran (Diptera: Tephritidae), is the most important pest of blueberries in eastern North America. Insecticide use in fruit-bearing lowbush blueberry fields could be reduced with management strategies focused on vegetative fields. Fly distribution and fruit infestation levels were assessed where fruit-bearing and vegetative fields adjoin and along forested edges of vegetative fields. RESULTS: Along adjoining edges, immature female flies were captured in fruiting fields and mature females in vegetative fields throughout the season. Male fly captures and fruit infestation levels were greater at 5 m than at 30 m from the edge. Along forested edges, fly captures were best predicted by densities of ripe lowbush blueberries and large coniferous trees. Maggot infestation level in lowbush blueberries was best predicted by blueberry density and small deciduous trees. Bunchberry, Cornus canadensis L., was the only non-crop host in which blueberry maggot was found. CONCLUSIONS: We have shown that relatively high numbers of flies occur in vegetative fields and at edges of fruiting fields. Ripe blueberries and certain vegetation in forested edges affect fly distribution and probably maintain populations. These results may help to predict where controls for blueberry maggot should be targeted and suggest that management strategies focused on vegetative fields and field edges may be worthwhile.

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 score0.008
Threshold uncertainty score0.016

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)0.0020.000

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 head0.011
GPT teacher head0.231
Teacher spread0.220 · 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

Citations7
Published2013
Admission routes2
Has abstractyes

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