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Record W4206612253 · doi:10.4039/tce.2021.56

Methods for estimating and modelling spruce budworm development rates at constant temperatures

2021· article· en· W4206612253 on OpenAlexaff
Ashlyn A. Wardlaw, K. Perrault, Amanda D. Roe, John Dedes, Courtney Irwin, Chris J.K. MacQuarrie, Jean‐Noël Candau

Bibliographic record

VenueThe Canadian Entomologist · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsNatural Resources CanadaCanadian Forest Service
Fundersnot available
KeywordsSpruce budwormLarvaInstarBiologyLepidoptera genitaliaEcologyDevelopmental stageTortricidae

Abstract

fetched live from OpenAlex

Abstract We describe an experimental protocol for measuring the response of spruce budworm postdiapause larval development to temperature. This protocol is specifically designed to include measurements of development near their upper and lower thermal thresholds. The application of this protocol to a laboratory colony allowed for the first experimental evidence that spruce budworm larval development occurs at temperatures as low as 5 °C and as high as 35 °C, and it provides data to fit stage-specific development models. Our protocol is also designed to minimise mortality near the thermal development thresholds, thus allowing for multigenerational studies. We observed developmental plasticity in larvae reared at constant temperatures, particularly the occurrence of up to 42% of some individuals requiring only five instars to complete development compared to the expected six instars. The occurrence exhibited no clear relation to temperature. Although this protocol is specifically designed for spruce budworm, it provides a template for the study of other species’ developmental responses to temperature.

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)0.003
metaresearch head score (Gemma)0.008
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: Methods · Consensus signal: Methods
Teacher disagreement score0.952
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.029
GPT teacher head0.296
Teacher spread0.267 · 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
GenreMethods

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
Published2021
Admission routes1
Has abstractyes

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