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Record W2012393035 · doi:10.4039/tce.2013.67

An individual-based phenology model for western spruce budworm (Lepidoptera: Tortricidae)

2013· article· en· W2012393035 on OpenAlexaffabout
Vincent G. Nealis, Jacques Régnière

Bibliographic record

VenueThe Canadian Entomologist · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsNatural Resources CanadaCanadian Forest Service
Fundersnot available
KeywordsSpruce budwormTortricidaePhenologyChoristoneura fumiferanaLepidoptera genitaliaEcologyBiologyPEST analysisPopulationForestryGeographyBotanyDemography

Abstract

fetched live from OpenAlex

Abstract An individual-based phenology model for western spruce budworm, Choristoneura occidentalis Freeman (Lepidoptera: Tortricidae), was developed using stage-specific rates of development, oviposition, and egg hatch observed under controlled conditions at several temperatures. Model output was compared with age distributions estimated by sampling field populations of budworm at several locations in British Columbia, Canada, over many years. The fit of the model was very good for the entire life cycle of the insect. We further validate the model by comparing output with independent observations of moth flight phenology of C. occidentalis and Choristoneura fumiferana (Clemens) in populations of Cypress Hills, Canada and illustrate spatial variation in the seasonal occurrence of early-stage feeding western spruce budworm over most of its range in western Canada. In addition to serving as the underlying structure for the modelling of population dynamics at the seasonal level, the model can be used to predict the time of occurrence of different life stages for precise timing of pest management operations.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score0.418

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.244
Teacher spread0.222 · 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 designSimulation or modeling
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

Citations18
Published2013
Admission routes2
Has abstractyes

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