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Record W6887389813 · doi:10.15468/jsab2y

Aggregated occurrence records of invasive European frog-bit (Hydrocharis morsus-ranae L.) across North America

2022· dataset· en· W6887389813 on OpenAlexaffabout

Bibliographic record

VenueGlobal Biodiversity Information Facility · 2022
Typedataset
Languageen
Field
Topic
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsInvasive speciesRange (aeronautics)HabitatEcosystemAgricultureIntroduced species

Abstract

fetched live from OpenAlex

European frog-bit (Hydrocharis morsus-ranae L.) is an invasive aquatic plant of growing concern in the Laurentian Great Lakes region. This species has the potential to continue to spread throughout North America and may threaten coastal and inland ecosystems and native species. Central to management of European frog-bit is an understanding of the historic and current distribution, which can inform efforts to predict future spread and establishment, determine habitat suitability and the factors that drive invasion, and identify high-priority areas for targeted monitoring and management. We created an aggregated dataset of European frog-bit occurrence records from 1932 to 2021 across the invasive range of North America. A total of 23,985 records were initially obtained from eight observation-based data providers and forty specimen-based data providers. Two datasets were mobilized for this project, including 2,874 records from a targeted university research effort and 150 unpublished specimens from Agriculture and Agri-Food Canada National Collection of Vascular Plants. After data cleaning, standardization, and validation, this dataset contains 12,037 unique presence and absence records spanning thirteen U.S. states and two Canadian provinces.

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)0.001
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 score0.237
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.003
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0030.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0140.252

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 head0.018
GPT teacher head0.234
Teacher spread0.215 · 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
Published2022
Admission routes2
Has abstractyes

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