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Record W2065605879 · doi:10.1017/s0007485315000218

Using comparative genomics to develop a molecular diagnostic for the identification of an emerging pest <i>Drosophila suzukii</i>

2015· article· en· W2065605879 on OpenAlexaboutno aff
Katherine A. Murphy, Thomas R. Unruh, Lin Zhou, Frank G. Zalom, Peter W. Shearer, E. H. Beers, Vaughn M. Walton, Betsey Miller, Joanna C. Chiu

Bibliographic record

VenueBulletin of Entomological Research · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect behavior and control techniques
Canadian institutionsnot available
FundersUniversity of California, DavisWashington Tree Fruit Research Commission
KeywordsDrosophila suzukiiBiologyPEST analysisDrosophila (subgenus)QuarantineAgricultural pestIdentification (biology)Plant quarantineEntomologyDrosophilidaeBiotechnologyEcologyBotanyDrosophila melanogasterGenetics

Abstract

fetched live from OpenAlex

Drosophila suzukii (Spotted Wing Drosophila) has recently become a serious invasive pest of fruit crops in the USA, Canada, and Europe, leading to substantial economic losses. D. suzukii is a direct pest, ovipositing directly into ripe or ripening fruits; in contrast, other Drosophilids utilize decaying or blemished fruits and are nuisance pests at worst. Immature stages of D. suzukii are difficult to differentiate from other Drosophilids, posing problems for research and for meeting quarantine restrictions designed to prevent the spread of this pest in fruit exports. Here we used a combined phylogenetic and bioinformatic approach to discover genetic markers suitable for a species diagnostic protocol of this agricultural pest. We describe a molecular diagnostic for rapid identification of single D. suzukii larva using multiplex polymerase chain reaction. Our molecular diagnostic was validated using nine different species of Drosophila for specificity and 19 populations of D. suzukii from different geographical regions to ensure utility within species.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.307
GPT teacher head0.433
Teacher spread0.126 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations14
Published2015
Admission routes1
Has abstractyes

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