MétaCan
Menu
Back to cohort
Record W807572259 · doi:10.1079/9780851996868.0205

Integrated pest management in forestry: potential and challenges.

2004· book-chapter· en· W807572259 on OpenAlexaffabout
I. S. Otvos

Bibliographic record

VenueCABI Publishing eBooks · 2004
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsCanadian Forest ServiceNatural Resources Canada
Fundersnot available
KeywordsLymantria disparGypsy mothIntegrated pest managementAgroforestryBiologyPEST analysisSpruce budwormTussockForestryPest controlBiological pest controlForest managementEcologyGeographyLepidoptera genitaliaBotanyTortricidae

Abstract

fetched live from OpenAlex

This paper summarizes the events leading to the development of integrated pest management (IPM). Due to the vastness of the subject, only the stages and progression towards IPM in forestry are illustrated by giving examples from Canadian experience. It covers the biological control of forest insects in Canada (mainly parasitoid introductions and work with insect viruses), and illustrates the evolution of IPM with three examples, two involving native species and one involving an introduced species, i.e. the spruce budworm Choristoneura fumiferana (illustrating the transition from the use of chemicals to biological pesticides), the Douglas fir tussock moth Orgyia pseudotsugata (development of the first truly IPM for a defoliator), and the gypsy moth Lymantria dispar (an introduced species that became established in eastern North America, but is still treated as a quarantine pest in western North America). Management of bark beetles, contributions in forest weed and plant pathogen control, and a perspective on the future potentials and challenges of IPM in forestry, exotic insects, decreasing pesticide use, genetic engineering of entomopathogens and transgenic trees are discussed.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.005

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 head0.019
GPT teacher head0.193
Teacher spread0.174 · 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 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

Citations5
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueCABI Publishing eBooksSame topicForest Insect Ecology and ManagementFrench-language works237,207