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Record W2763666316 · doi:10.4039/tce.2017.47

Impacts of the agricultural transformation of the Canadian Prairies on grassland arthropods

2017· article· en· W2763666316 on OpenAlexaffabout
Meghan A. Vankosky, Héctor A. Cárcamo, Haley A. Catton, Alejandro C. Costamagna, Rosemarie De Clerck-Floate

Bibliographic record

VenueThe Canadian Entomologist · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of ManitobaAgriculture and Agri-Food Canada
Fundersnot available
KeywordsEcologyArthropodGrasslandBiological pest controlBiologyBiodiversityAgroforestryAbiotic componentAgricultureGrazingGeography

Abstract

fetched live from OpenAlex

Abstract The prairie grasslands have been transformed to become the primary source of agricultural production in Canada. Soon after its establishment, the Biological Survey of Canada recognised the urgent need to document the arthropods of the prairie grasslands, especially in the few pristine remnants. Although this initiative has yielded considerable progress in documenting the species present in the Prairies Ecozone, comprehensive ecological studies are sparse. Landscape effects on arthropods are well studied elsewhere, but no equivalent studies have been published for the Canadian Prairies. Crop rotation varies landscape composition annually, changes host plant resources in fields, and interacts with other agricultural inputs to disturb pest and beneficial arthropods. Despite only a handful of studies on grazing, there is an emerging pattern: moderate grazing increases arthropod diversity and benefits certain arthropod guilds. Abiotic inputs elicit variable responses from different arthropod taxa; Carabidae (Coleoptera) are best studied, with some information available for ants (Hymenoptera: Formicidae) and aquatic arthropods. Biotic inputs include arthropods released for biocontrol of weed and insect pests; evidence indicates that biocontrol agents of insects have a greater potential for impact on native communities of arthropods. The studies reviewed here reveal important trends and research gaps to be addressed in the future.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.013
GPT teacher head0.239
Teacher spread0.226 · 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 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

Citations13
Published2017
Admission routes2
Has abstractyes

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