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Record W2562304456 · doi:10.4039/tce.2015.21

Historical trends in Canadian forest entomology

2015· article· en· W2562304456 on OpenAlexafffundabout
Dan T. Quiring, Vanessa Quiring, Anne-Marie Quiring, Sara Edwards

Bibliographic record

VenueThe Canadian Entomologist · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsMcGill UniversityUniversity of ManitobaUniversity of New Brunswick
FundersCanadian Forest ServiceU.S. Forest Service
KeywordsEntomologyBuprestidaeCurculionidaeGeographyBark beetleBark (sound)Longhorn beetleEcologyBiologyForestry

Abstract

fetched live from OpenAlex

Abstract Canada has a distinguished history of research in forest entomology. The number of peer-reviewed publications emanating from studies in forest entomology in Canada greatly increased following the Second World War. Much of the outstanding historical success in Canadian forest entomological research is attributable to the work of entomologists employed by the Canadian Forest Service, who authored the majority of studies until the mid 1970s and usually published them in The Canadian Entomologist. Since that time the majority of studies have been published by Canadian universities in a broad range of journals. Most early research in forest entomology in Canada was carried out by men, but since that time the proportion of forest entomological research carried out by women has increased significantly. The majority of research in central and eastern Canada focussed on defoliators and their natural enemies and host plants whereas the majority of research in western Canada examined bark beetles (Coleoptera: Curculionidae: Scolytinae) and their natural enemies and host plants. Although publications on defoliators and their natural enemies have occurred continuously throughout the historical development of forest entomology in Canada, the numbers of publications on wood borers (Coleoptera: Buprestidae, Cerambycidae) and bark beetles and their natural enemies have never been higher than they are presently.

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)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.996
Threshold uncertainty score0.714

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0140.027
Science and technology studies0.0050.002
Scholarly communication0.0050.002
Open science0.0020.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0230.002

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 head0.031
GPT teacher head0.243
Teacher spread0.213 · 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.

Study designObservational
DomainMethods
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

Citations4
Published2015
Admission routes3
Has abstractyes

Explore more

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