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Record W4377139282 · doi:10.3897/bdj.11.e103982

Agapostemon fasciatus Crawford (Hymenoptera, Halictidae), a valid North American bee species ranging into southern Canada

2023· article· en· W4377139282 on OpenAlexaffabout
Cory S. Sheffield

Bibliographic record

VenueBiodiversity Data Journal · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsRoyal Saskatchewan Museum
FundersAmerican Museum of Natural History
KeywordsHalictidaeTaxonHymenopteraGeographyEcologyZoologyRange (aeronautics)BiologyApoidea

Abstract

fetched live from OpenAlex

Sweat bees of the genus Agapostemon Guérin-Méneville, 1844 (Hymenoptera: Halictidae) are common and widespread in the Americas. Despite distinct morphological characters that were recognised in earlier taxonomic treatments, Agapostemon fasciatus Crawford, 1901 has been considered a variety of A. melliventris Cresson, 1874 since the 1930s and later placed into synonymy under A. melliventris in the early 1970s. A more detailed study of morphology (including examination of type materials), distribution and genetic data (i.e. DNA barcodes) of these two taxa suggests they are not conspecific. As such, A. fasciatus is resurrected as a valid North American bee species. Agapostemon fasciatus ranges further north in North America than A. mellivenrtis , reaching the southern Prairies Ecozone of Canada (Alberta, Saskatchewan), while most records of A. melliventris are from the south-western United States and northern Mexico. More accurate distributions for both species can be modelled as specimens in collections are identified using the diagnostic features provided. However, additional work is required on the A. melliventris species complex in the southern United States as genetic data suggest that multiple taxa could be present.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.813
Threshold uncertainty score0.371

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.076
GPT teacher head0.211
Teacher spread0.135 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

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