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Bee Systematics and Conservation

2025· article· en· W4410511713 on OpenAlexaff
Eduardo A. B. Almeida, Margarita M. López‐Uribe, Laurence Packer, Diego S. Porto, Gabriela P. Camacho

Bibliographic record

VenueSociobiology · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsYork University
FundersFundação de Amparo à Pesquisa do Estado de São PauloU.S. Department of AgricultureNational Institute of Food and AgricultureNational Science Foundation
KeywordsBiologySystematicsEvolutionary biologyZoologyEcologyTaxonomy (biology)

Abstract

fetched live from OpenAlex

Diversity can be examined and interpreted from various perspectives, including species richness, genetic and phenotypic differences, variation in behaviors and natural history, and phylogenetic history. Centuries of taxonomic research have revealed approximately 21,000 bee species worldwide. These can be subdivided into a hierarchy of subgroups that reflects their evolutionary history, thanks to the increasingly more comprehensive phylogenetic hypotheses available. Advances in bee systematics have enhanced our understanding of how their diversity has evolved, including their origin in the Cretaceous, shifts in their geographical distribution, the evolution of social and parasitic behaviors, and changes in relationships between bees and the plants they visit throughout a 120-million-year shared evolutionary history. An important outcome of the enduring relationship with flowering plants is the vital role bees play in pollination in both natural and agricultural ecosystems. Habitat loss, climate change, and other anthropogenic environmental alterations have led to declines in bee populations, which have sparked concerns about bee conservation and highlighted the importance of understanding the complementary aspects of diversity, including the evolutionary and geographical components of this variation. The availability of increasingly reliable and comprehensive phylogenetic hypotheses has led to significant advancements, enabling assessments of the phylogenetic diversity of bee communities and predictions regarding their vulnerability to habitat change and their ecological functions. This review explores perspectives of documenting and interpreting bee diversity in a changing world and summarizes the current bee classification while discussing the phylogenetic advances in contemporary research.

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)0.001
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.006
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.040
GPT teacher head0.228
Teacher spread0.188 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

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