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Record W4281553984 · doi:10.1016/j.cois.2022.100939

The importance of eco-evolutionary dynamics for predicting and managing insect range shifts

2022· review· en· W4281553984 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCurrent Opinion in Insect Science · 2022
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of British ColumbiaConcordia University
FundersAgence Nationale de la RechercheNatural Environment Research CouncilSight Research UK
KeywordsScope (computer science)BiologyRange (aeronautics)EcologyBiodiversityEvolutionary dynamicsEnvironmental resource managementEcosystemEconomicsComputer science

Abstract

fetched live from OpenAlex

Evolutionary change impacts the rate at which insect pests, pollinators, or disease vectors expand or contract their geographic ranges. Although evolutionary changes, and their ecological feedbacks, strongly affect these risks and associated ecological and economic consequences, they are often underappreciated in management efforts. Greater rigor and scope in study design, coupled with innovative technologies and approaches, facilitates our understanding of the causes and consequences of eco-evolutionary dynamics in insect range shifts. Future efforts need to ensure that forecasts allow for demographic and evolutionary change and that management strategies will maximize (or minimize) the adaptive potential of range-shifting insects, with benefits for biodiversity and ecosystem services.

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.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.979
Threshold uncertainty score0.821

Codex and Gemma teacher scores by category

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

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 head0.190
GPT teacher head0.333
Teacher spread0.143 · 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