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Record W2148462266 · doi:10.4039/n02-121

Are bumble bee colonies in tomato greenhouses obtaining adequate nutrition?

2003· article· en· W2148462266 on OpenAlexafffund
Robin Whittington, Mark L. Winston

Bibliographic record

VenueThe Canadian Entomologist · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsSimon Fraser University
FundersAgriculture and Agri-Food CanadaNatural Sciences and Engineering Research Council of CanadaSimon Fraser University
KeywordsBiologyBroodGreenhousePollinatorPollenPollinationApidaeBombus terrestrisApoideaLongevityHymenopteraEcologyBotany

Abstract

fetched live from OpenAlex

Abstract Managed bumble bees are important pollinators of greenhouse crops, but few studies have examined factors that affect the health and productivity of commercially produced colonies. We investigated whether supplemental feeding with diverse pollens affected worker longevity and colony size of Bombus occidentalis Greene (Hymenoptera: Apidae) colonies in tomato (Solanaceae) greenhouses. We found no differences in colony worker populations, brood production, or queen and drone production between supplemented and nonsupplemented treatments, suggesting that B. occidentalis colonies obtain adequate nutrition from the tomato pollen available in greenhouses. Adult populations did not increase in any treatment, but either remained stable or declined after colonies were placed in greenhouses. Because brood-rearing increased in all treatments but adult populations did not, adult mortality due to a non-nutritional factor such as disease or disorientation appears to be an important problem limiting the size of bumble bee colonies, and thus the effectiveness of bumble bees for greenhouse tomato pollination.

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 score0.005
Threshold uncertainty score0.009

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 head0.077
GPT teacher head0.230
Teacher spread0.153 · 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
Published2003
Admission routes2
Has abstractyes

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