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Record W6924804014 · doi:10.15468/mvhaj3

The World Checklist of Vascular Plants (WCVP): Fabaceae

2021· dataset· en· W6924804014 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueOpen MIND · 2021
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsFabaceaeChecklistTaxonomy (biology)NomenclatureDocumentationPlant taxonomySystematicsSpecies name

Abstract

fetched live from OpenAlex

The World Checklist of Vascular Plants (WCVP) is a global consensus view of all known vascular plant species (flowering plants, conifers, ferns, clubmosses and firmosses). The Fabaceae subset contains names that have been peer reviewed by external experts from the Legume Phylogeny Working Group’s (LPWG) and internal experts, as well as names that are in the process of being edited and reviewed. WCVP aims to represent a global consensus view of current plant taxonomy by reflecting the latest published taxonomies while incorporating the opinions of taxonomists based around the world, and following the International Code of Nomenclature for algae, fungi, and plants. WCVP is built on the nomenclatural data provided by the International Plant Names Index (IPNI), which is the product of a collaboration between The Royal Botanic Gardens, Kew, The Harvard University Herbaria, and the Australian National Herbarium, combined with the taxonomic data provided by an international collaborative programme with a large number of contributors from around the world. Our thanks go to the compilers and editors of IPNI and WCVP and in particular the thousands of users who have contributed corrections over the past decades, improving those data for the global user community. We acknowledge the long term contribution of the International Legume Database and Information Service (ILDIS), which provided a species naming infrastructure that was used over many decades by the legume systematics community and which remains the foundation for the taxonomy of many legume species. The WCVP Fabaceae checklist includes the data from WorldWideWattle (Maslin and Wilson, 2025). Donald Hobern is acknowledged for his technical assistance with the alignment between the two datasets. Our particular thanks for the WCVP Fabaceae subset go to: Bob Allkin (Kew), Nick Black (Kew), Markus Döring (GBIF), Joe Miller (GBIF) and Carole Sinou (Canadensys, Université de Montréal) for their help setting up the project and publishing the data. The initiative to update legume species names on WCVP was led by Marianne le Roux (LPWG, South African National Biodiversity Institute), Anne Bruneau (LPWG, Université de Montréal), and Juliana Rando (LPWG, Universidade Federal do Oeste da Bahia). The LPWG Taxonomy Working Group is the Taxonomic Expert Network for the legumes in World Flora Online and Alan Elliott is thanked for his assistance.

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.

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)0.002
metaresearch head score (Gemma)0.000
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 score0.031
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0040.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0160.029

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 head0.035
GPT teacher head0.322
Teacher spread0.287 · 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

Quick stats

Citations9
Published2021
Admission routes1
Has abstractyes

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