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Record W1977904285 · doi:10.4039/n06-032

Manipulating pollen supply in honey bee colonies during the fall does not affect the performance of winter bees

2007· article· en· W1977904285 on OpenAlexaff
Heather R. Mattila, Gard W. Otis

Bibliographic record

VenueThe Canadian Entomologist · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPollenBroodBiologyTemperate climateNest (protein structural motif)ApidaeWorker beeApoideaHymenopteraEcologyHoney beeBeekeeping

Abstract

fetched live from OpenAlex

Abstract Each fall, honey bee ( Apis mellifera L. (Hymenoptera: Apidae)) colonies in northern temperate regions rear a population of long-lived winter bees that maintains a broodless nest throughout the winter and resumes brood-rearing activities in the spring. Pollen supply in colonies is closely tied to this phenomenon; winter bees sequester large reservoirs of pollen-derived nutrients in their bodies and the brood-rearing capacity of colonies is dictated by the availability of pollen. We determined the effects of manipulating pollen supply during the fall on the number of winter bees present in colonies by spring, their mass and protein content before and after winter, and their capacity to rear brood during the spring. Colonies were either supplemented with or partially deprived of pollen during the fall, while a third group of colonies was not manipulated (control). We found that the performance of winter bees was not enhanced by supplementing colonies with pollen in the fall, nor did worker function suffer if pollen supply was restricted. Similar numbers of winter bees survived to spring in colonies and workers had similar physiology and brood-rearing efficiencies. These results suggest that beekeepers would not benefit by investing in fall pollen supplements to maximize colony growth in early spring.

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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.710
Threshold uncertainty score0.726

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.029
GPT teacher head0.219
Teacher spread0.189 · 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 teacher head, 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

Citations16
Published2007
Admission routes1
Has abstractyes

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