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Record W6962142299 · doi:10.15482/usda.adc/1529232

AnthWest, occurrence records for wool carder bees of the genus Anthidium (Hymenoptera: Megachilidae, Anthidiini) in the Western Hemisphere

2023· dataset· en· W6962142299 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2023
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsBiodiversityGenusWestern hemisphereHistorical recordRange (aeronautics)Northern HemisphereGlobal biodiversity

Abstract

fetched live from OpenAlex

AnthWest is a large dataset, one of the outcomes of a comprehensive, broadly comparative study on the diversity, biology, biogeography, and evolution of Anthidium Fabricius in the Western Hemisphere. In this dataset a total of 22,648 adult occurrence records comprising 9,657 unique events are documented for 92 species of Anthidium, including the invasive range of two introduced species from Eurasia, A. oblongatum (Illiger) and A. manicatum (Linnaeus). The geospatial coverage of the dataset extends from northern Canada and Alaska to southern Argentina, and from below sea level in Death Valley, California, USA, to 4,700 m a.s.l. in Tucumán, Argentina. The majority of the records in the dataset correspond to information recorded from individual specimens examined by the authors during this project, and deposited into 60 biodiversity collections located in Africa, Europe, North and South America. A fraction (4.8%) of the occurrence records were taken from the literature, largely California records from a taxonomic treatment with some additional records for the two introduced species. The temporal scale of the dataset represents collection events recorded between 1886 and 2012. The data underpinning the analysis reported in this paper are deposited at GBIF, the Global Biodiversity Information Facility, http://ipt.pensoft.net/ipt/resource.do?r=anthidium.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.010
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0050.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.014

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 head0.065
GPT teacher head0.323
Teacher spread0.258 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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 routes1
Has abstractyes

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