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Record W2173419955 · doi:10.1603/0022-0493-99.3.604

Influence of Pollen Diet in Spring on Development of Honey Bee (Hymenoptera: Apidae) Colonies

2006· article· en· W2173419955 on OpenAlexafffund
Heather R. Mattila, Gard W. Otis

Bibliographic record

VenueJournal of Economic Entomology · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Guelph
FundersUniversity of Guelph
KeywordsBiologyApidaeHymenopteraPollenBee pollenHoney beeSpring (device)BotanyApoideaHoney BeesPollinatorBeekeepingPollination

Abstract

fetched live from OpenAlex

The effects of changes in spring pollen diet on the development of honey bee, Apis mellifera L. (Hymenoptera: Apidae), colonies were examined in a 3-yr study (2002-2004). Pollen-supplemented and pollen-limited conditions were created in colonies every spring, and brood rearing and honey yields were subsequently monitored throughout the summer. In all 3 yr, colonies that were supplemented with pollen or a pollen substitute in the spring started rearing brood earlier than colonies in other treatment groups and produced the most workers by late April or early May. In 2002, these initial differences were reflected by a two-fold increase in annual honey yields by September for colonies that were pollen-supplemented during the spring compared with pollen-limited colonies. In 2003 and 2004, differences between treatment groups in the cumulative number of workers produced by colonies disappeared by midsummer, and all colonies had similar annual honey yields (exception: in one year, productivity was low for colonies supplemented with pollen before wintering). Discrepancies between years coincided with differences in spring weather conditions. Colonies supplemented with pollen or a substitute during the spring performed similarly in all respects. These results indicate that an investment in supplementing the pollen diet of colonies would be returned for situations in which large spring populations are important, but long-term improvement in honey yields may only result when spring foraging is severely reduced by inclement weather. Beekeepers should weigh this information against the nutritional deficiencies that are frequently generated in colonies by the stresses of commercial management.

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)0.000
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 score0.296
Threshold uncertainty score0.297

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.024
GPT teacher head0.222
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 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

Citations105
Published2006
Admission routes2
Has abstractyes

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