MétaCan
Menu
Back to cohort
Record W2562298289 · doi:10.4039/tce.2015.17

The influence of Canadian research on semiochemical-based management of forest insect pests in Canada

2015· article· en· W2562298289 on OpenAlexafffundabout
Maya L. Evenden, Peter J. Silk

Bibliographic record

VenueThe Canadian Entomologist · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsCanadian Forest ServiceUniversity of Alberta
FundersCanadian Forest ServiceNatural Sciences and Engineering Research Council of CanadaU.S. Forest ServiceUniversity of Alberta
KeywordsSemiochemicalIntegrated pest managementEcologyBiologyPest controlForagingForest managementAgroforestryPheromone

Abstract

fetched live from OpenAlex

Abstract Insects use semiochemicals to mediate important behaviours such as mating, oviposition, and foraging for resources. Chemical ecology research aims to identify these message-bearing chemicals and develop synthetic copies of semiochemicals for use in integrated pest management (IPM). There has been, and continues to be, an extensive research effort to understand the chemical ecology of various insects considered to be pests of forests in Canada. Canadian chemical ecology research has had an impact on IPM of forest insect pests in Canada and around the world. Canadian researchers have been involved in the identification of semiochemicals used by forest insects and the development and implementation of semiochemical-based management tactics for forest pest management. Semiochemicals have been incorporated into forest pest management for a variety of insect taxa primarily as tools to monitor and control forest insect pests in Canada. The goals of the current review are to: (1) highlight research conducted on semiochemical-based management of forest pests in Canada; (2) discuss the current and potential uses of semiochemicals in IPM of forest pests in Canada; and (3) evaluate potential areas for increased research and implementation of semiochemicals into the management of forest pests in Canada.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.362
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.059
GPT teacher head0.278
Teacher spread0.219 · 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.

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

Citations13
Published2015
Admission routes3
Has abstractyes

Explore more

Same venueThe Canadian EntomologistSame topicForest Insect Ecology and ManagementFrench-language works237,207