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Record W2939290052 · doi:10.1093/jisesa/iez027

Poecilus lucublandus (Coleoptera: Carabidae) and Pterostichus mutus Do Not Feed on Hair Fescue, Red Sorrel, and Poverty Oatgrass Seeds

2019· article· en· W2939290052 on OpenAlexafffund
Alexandre M. M. C. Loureiro, G. Christopher Cutler, Vilis O. Nams, Scott N. White

Bibliographic record

VenueJournal of Insect Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyEricaceaeBotanyWeedAgronomy

Abstract

fetched live from OpenAlex

Poecilus lucublandus (Say), Pterostichus mutus (Say), and Harpalus rufipes (De Geer) are abundant Carabidae in lowbush blueberry fields and may contribute to weed seed predation. We used laboratory no-choice test experiments to determine if these beetles feed on seeds of hair fescue (Festuca filiformis Pourr., Poales: Poaceae), poverty oatgrass (Danthonia spicata L.), and red sorrel (Rumex acetosella L., Caryophyllales: Polygonaceae), which are common weeds in lowbush blueberry (Vaccinium angustifolium Ait., Ericales: Ericaceae) fields. Poecilus lucublandus and P. mutus did not feed on seeds of the test weed species, but H. rufipes consumed on average over 30 seeds of each species. There are other weed seeds in blueberry fields that could be palatable to P. lucublandus and P. mutus, which warrants further research on the granivory potential of these important carabid species.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.011
GPT teacher head0.208
Teacher spread0.197 · 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

Citations7
Published2019
Admission routes2
Has abstractyes

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