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Record W2100658703 · doi:10.4039/n04-014

Effect of shading on trap nest utilization by hole-nesting aculeate Hymenoptera

2004· article· en· W2100658703 on OpenAlexaff
Hisatomo Taki, Jeffrey W. Boone, Blandina Felipe Viana, Fabiana Oliveira da Silva, Peter G. Kevan, Cory S. Sheffield

Bibliographic record

VenueThe Canadian Entomologist · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of Guelph
Fundersnot available
KeywordsHymenopteraShadingNesting (process)Nest (protein structural motif)MegachilidaeEcologyTrap (plumbing)MicroclimateHabitatPollinationBiologyGeographyEnvironmental sciencePollinatorMeteorologyArtEngineeringVisual arts

Abstract

fetched live from OpenAlex

For many years, trap nests have been used to study hole-nesting bees and wasps (aculeate Hymenoptera) and to monitor their diversity and abundance (Krombein 1967; Danks 1971; Godfrey and Hilton 1983; Frankieet al.1998). Trap nests are valuable for environmental assessment (Tscharntkeet al.1998) and for agriculture through improved pollination by bees (Bosch 1994; Stubbset al.1997; Hallett 2001) and biological control by wasps (Harris 1994). Frankieet al.(1988) indicated that shaded environments might be preferred habitats for some solitary bees that use tree holes for nesting. Shading could offer protection from natural enemies as well as wind, rain, and sunlight, resulting in stabilized humidity and temperature. As far as we are aware, ours is the first experimental study to consider the effect of shading of trap nests.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.059
GPT teacher head0.246
Teacher spread0.187 · 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

Citations11
Published2004
Admission routes1
Has abstractyes

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