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Record W1905689073 · doi:10.1139/x2012-058

Distinguishing isolates of <i>Deladenus siricidicola</i>, a biological control agent of <i>Sirex noctilio</i>, from North America and the Southern Hemisphere using PCR–RFLP

2012· article· en· W1905689073 on OpenAlexafffundvenue
Isabel Leal, B. Foord, C. Davis, Peter de Groot, X. Osmond Mlonyeni, Bernard Slippers

Bibliographic record

VenueCanadian Journal of Forest Research · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsNatural Resources CanadaCanadian Forest Service
FundersAnimal and Plant Health Inspection ServiceNatural Resources CanadaU.S. Department of Agriculture
KeywordsBiologyObligateBiological pest controlRestriction fragment length polymorphismInternal transcribed spacerRibosomal DNANematodeBotanyEcologyRibosomal RNAZoologyGenotypePhylogenetic treeGeneticsGene

Abstract

fetched live from OpenAlex

The woodwasp Sirex noctilio Fabricius, along with its obligate symbiotic fungus Amylostereum areolatum (Chaillet ex Fr.) Boidin, is amongst the most damaging invasive species to many commercial pine plantations. The most effective biocontrol agent for management of this woodwasp has been the nematode Deladenus siricidicola Bedding. Before this agent can be used in North America, answering key questions about its interaction with native siricids and other strains of the nematode is essential, as would be the need to track its spread after release. The aim of this study was to develop tools to differentiate between the North American D. siricidicola isolates and the Southern Hemisphere Kamona strain of this species. We sequenced a region from ribosomal DNA and the cytochrome oxidase subunit 1 and developed a PCR–RFLP method based on a single nucleotide polymorphism flanking a microsatellite sequence. These markers will be useful for science-based operational biocontrol of S. noctilio.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

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 integrity0.0000.000
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 head0.039
GPT teacher head0.266
Teacher spread0.227 · 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
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
Published2012
Admission routes3
Has abstractyes

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