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Record W4353074363 · doi:10.5852/ejt.2023.862.2079

Seven new species of Lasioglossum (Dialictus) Robertson, 1902 (Hymenoptera: Halictidae: Halictini) from the Yucatán Peninsula, Mexico

2023· article· en· W4353074363 on OpenAlexaff
Patricia Landaverde‐González, Joel Gardner, Humberto Moo‐Valle, José Javier G. Quezada‐Euán, Ricardo Ayala, Martin Husemann

Bibliographic record

VenueEuropean Journal of Taxonomy · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Manitoba
FundersConsejo Nacional de Ciencia y TecnologíaNational Museum of Natural HistoryUniversität HohenheimUniversity of KansasFondo de Cooperación Internacional en Ciencia y TecnologíaSmithsonian Institution
KeywordsHalictidaeSubgenusTaxonomy (biology)BiologyZoologyGenusEcologyHymenopteraApoidea

Abstract

fetched live from OpenAlex

Lasioglossum is a large genus of halictid bees with high species diversity in morphologically rather cryptic species groups. With more than 1900 described species, the taxonomy of the genus is complex and largely unresolved in many regions. For practical reasons, systematic reviews are restricted in scope either geographically or to particular species groups. In this study we focus on the subgenus Dialictus of the genus Lasioglossum from the Yucatán Peninsula in Mexico. In previous studies we identified members of the genus as important pollinators of cash crops in the region, and genetic analyses suggested the existence of seven molecular taxonomic units (mOTU). Based on additional morphological differences, we here describe these mOTUs as novel species, Lasioglossum (Dialictus) yucatanense Landaverde-González sp. nov., L. (D.) paxtoni Landaverde-González sp. nov., L. (D.) ameshoferi Landaverde-González sp. nov., L. (D.) aureoviride Landaverde-González & Husemann sp. nov., L. (D.) paralepidii Gardner sp. nov., L. (D.) milpa Landaverde-González sp. nov. and L. (D.) nanotegula Landaverde-González & Husemann sp. nov., and provide keys and images to assist in their identification.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score0.712

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.083
GPT teacher head0.209
Teacher spread0.126 · 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 designNot applicable
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
Published2023
Admission routes1
Has abstractyes

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