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Record W4416370824 · doi:10.1656/045.032.m2701

An Annotated Checklist of the Bees (Hymenoptera: Apoidea) of Vermont with Conservation Status and Natural History Notes

2025· article· en· W4416370824 on OpenAlexaff
Spencer Hardy, Michael Veit, Joan Milam, John S. Ascher, Nathaniel Sharp, Michael T. Hallworth, M. S. Ferguson, Leif L. Richardson, Charlie Nicholson, Taylor H. Ricketts, Jason Gibbs, Kent P. McFarland

Bibliographic record

VenueNortheastern Naturalist · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsChecklistFaunaNatural historyBiodiversityCitizen scienceDigitizationConservation statusNatural (archaeology)

Abstract

fetched live from OpenAlex

This is the first comprehensive checklist and conservation assessment of the bee (Hymenoptera: Apoidea) fauna of the State of Vermont. This checklist of 351 species (plus 1 morphospecies) is based on 79,206 open-access data records available from the Global Biodiversity Information Facility (GBIF), nearly all (98%) of which were identified by an author or trusted collaborator, including 100% of the 24,270 research-grade observations from the community science platform iNaturalist. Through fieldwork and digitization of museum collections, we documented 9 species previously unreported from New England and as many as 24 novel host–parasite relationships. Overall, Vermont shares much of the bee fauna of neighboring states, with a notable contingent of northern and western species not regularly found elsewhere in New England or New York. Conservation rankings indicate that as many as 60% of the bee species in the state are vulnerable (S3 or lower). Detailed species accounts are provided as supplementary material, which cover the phenology, state-wide distribution, conservation status, and floral preferences of Vermont's bee fauna.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.137
Threshold uncertainty score0.272

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.005
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0360.004

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 head0.016
GPT teacher head0.205
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2025
Admission routes1
Has abstractyes

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