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Record W2413438998 · doi:10.1111/een.12324

Cold snaps, heatwaves, and arthropod growth

2016· article· en· W2413438998 on OpenAlexafffund
Bernard D. Roitberg, Marc Mangel

Bibliographic record

VenueEcological Entomology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsPoikilothermCold stressHeat stressBiologyAsymmetryClimate changeArthropodFunction (biology)EcologyAtmospheric sciencesEvolutionary biologyPhysics

Abstract

fetched live from OpenAlex

1. Arthropod performance is a non‐linear function of temperature, and thus global climate change may impact arthropods in a variety of non‐obvious ways. 2. In this paper, the well‐known thermal performance curve is reviewed briefly and attention is drawn to the importance of variance in temperature, particularly major weather events such as cold snaps and heatwaves. 3. A model is developed that considers the asymmetry between cold and heat stress and, particularly, the different timescales of recovery from these stressors: near‐instantaneous for cold and lagged effects from heat. 4. Growth rate is evaluated as a function of weather‐event intensity and length. Including the timescale asymmetry exacerbates both heat stress and, to a much lesser degree, cold stress.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.908
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.001

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 head0.011
GPT teacher head0.213
Teacher spread0.202 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
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

Citations52
Published2016
Admission routes2
Has abstractyes

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