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Record W6925210237 · doi:10.15468/rb7kky

Update on the Brassicaceae Species Checklist

2020· dataset· en· W6925210237 on OpenAlexaff

Bibliographic record

VenueOpen MIND · 2020
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBrassicaceaeChecklistSystematicsTaxonomic rankTaxonomy (biology)

Abstract

fetched live from OpenAlex

Here we present a revised species checklist for the Brassicaceae updated from Warwick SI, Francis, A., Al-Shehbaz IA (2006). Brassicaceae: Species checklist and database on CD-ROM. Plant Systematics and Evolution 259: 249─25. This update of the checklist was initiated on the basis of recent taxonomic and molecular studies on the Brassicaceae that have resulted in new species names, combinations and associated synonyms. New data has been added indicating tribal affiliations within the family and where type specimens have been designated. In addition, information from many early publications was checked and added to the database. The database now includes information on 14,980 taxa, 4,634 of which are currently accepted and divided into 340 genera and 52 tribes. A selected bibliography of recent publications on the Brassicaceae is included.

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)0.003
metaresearch head score (Gemma)0.012
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.095
Threshold uncertainty score0.317

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0120.021
Science and technology studies0.0010.000
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0950.075

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 head0.092
GPT teacher head0.289
Teacher spread0.197 · 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
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
Published2020
Admission routes1
Has abstractyes

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