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Record W2963369594 · doi:10.1139/cjfr-2019-0115

The predicted effect of the polar vortex of 2019 on winter survival of emerald ash borer and mountain pine beetle

2019· article· en· W2963369594 on OpenAlexafffundvenueabout
Chris J.K. MacQuarrie, Barry J. Cooke, Rémi Saint‐Amant

Bibliographic record

VenueCanadian Journal of Forest Research · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsNatural Resources CanadaCanadian Forest Service
FundersNatural Resources CanadaAlberta Agriculture and Forestry
KeywordsOverwinteringEmerald ash borerMountain pine beetleDendroctonusAgrilusBuprestidaeBiologyEcologyPopulationFraxinusCurculionidaeBark beetleDemography

Abstract

fetched live from OpenAlex

We use simulation models of the winter biology of two forest insects — emerald ash borer (Agrilus planipennis Fairmaire, 1888) and mountain pine beetle (Dendroctonus ponderosae Hopkins, 1902) — to illustrate the anticipated effect of the polar vortex of the winter of 2019 on overwintering survival. Cold spells in late January and early and mid-February were cool enough that relatively high levels of mortality of both species may be expected in many parts of northern Canada. However, the high mortality response is not ubiquitous, and neither is it particularly severe compared with winter weather patterns from earlier decades. Forest insect pest managers will be required to carry on their usual work of population assessment and response. As Earth’s climate continues to warm, overwintering survival should, on average, increase in both species. However, the common occurrence of a split polar vortex associated with increasingly meridional jet stream flows should bring the odd winter of heavy mortality.

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)0.003
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 score0.103
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.254
Teacher spread0.245 · 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

Citations24
Published2019
Admission routes4
Has abstractyes

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