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Record W2943796589 · doi:10.1111/pce.13571

A molecular and genomic reference system for conifer defence against insects

2019· review· en· W2943796589 on OpenAlexafffund
Justin G. A. Whitehill, Jörg Bohlmann

Bibliographic record

VenuePlant Cell & Environment · 2019
Typereview
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
FundersMinistry of Forests, Lands and Natural Resource Operations
KeywordsWeevilBiologyHost (biology)Resistance (ecology)InsectEcologyDisturbance (geology)Forest ecologyEcosystemBotany

Abstract

fetched live from OpenAlex

Insect pests are part of natural forest ecosystems contributing to forest rejuvenation but can also cause ecological disturbance and economic losses that are expected to increase with climate change. The white pine or spruce weevil (Pissodes strobi) is a pest of conifer forests in North America. Weevil-host interactions with various spruce (Picea) species have been explored as a genomic and molecular reference system for conifer defence against insects. Interactions occur in two major phases of the insect life cycle. In the exophase, adult weevils are free-moving and display behaviour of host selection for oviposition that is affected by host traits. In the endophase, insects live within the host where mobility and development from eggs to young adults are affected by a complex system of host defences. Genetic resistance exists in several spruce species and involves synergism of constitutive and induced chemical and physical defences that comprise the conifer defence syndrome. Here, we review conifer defences that disrupt the weevil life cycle and mechanisms by which trees resist weevil attack. We highlight molecular and genomic aspects and a possible role for the weevil microbiome. Knowledge of this conifer defence system is supporting forest health strategies and tree breeding for insect resistance.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.003

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 head0.024
GPT teacher head0.213
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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations26
Published2019
Admission routes2
Has abstractyes

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