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Record W3081243244 · doi:10.4039/tce.2020.50

Effect of nest microclimate temperatures on metabolic rates of small carpenter bees, <i>Ceratina calcarata</i> (Hymenoptera: Apidae)

2020· article· en· W3081243244 on OpenAlexaff
Miriam H. Richards, Andrea Cardama Garate, Mary Shehata, Derrick J. E. Groom, Glenn J. Tattersall, Kenneth C. Welch

Bibliographic record

VenueThe Canadian Entomologist · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect and Arachnid Ecology and Behavior
Canadian institutionsUniversity of TorontoBrock University
Fundersnot available
KeywordsApidaeNest (protein structural motif)HymenopteraBiologyPupaMicroclimateLarvaEcologyZoologyApoideaHorticulture

Abstract

fetched live from OpenAlex

Abstract Small carpenter bees (Ceratina calcarata Robertson) (Hymenoptera: Apidae) build their nests in both sunny and shady sites, so maternal decisions about nest sites influence the thermal environment experienced by juveniles throughout development. A previous study demonstrated that when larvae and pupae were raised in the laboratory at room temperature, those from sunny nests developed more slowly than those from shady nests. This suggested that bees developing in sunny nests slowed their metabolism or that bees developing in shady nests increased their metabolism. To test this hypothesis, we performed a field experiment in which bees nested in full sun, full shade, or semi-shade. We brought larvae and pupae into the laboratory to be raised to adulthood at room temperature and measured their metabolic rates (VCO2) at 10 °C, 25 °C, and 40 °C. As expected, bees had higher VCO2 at higher test temperatures, but significant interaction also occurred between test temperature and field treatment, such that bees from sunny nests exhibited higher metabolic rates at 40 °C. Because small carpenter bees frequently nest in full sun, adaptation to high nest temperatures may involve activation of thermal protection mechanisms at the cost of slower development.

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 score0.005
Threshold uncertainty score0.010

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)0.0010.000

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 head0.014
GPT teacher head0.257
Teacher spread0.243 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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