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Record W2008547428 · doi:10.3391/ai.2011.6.1.11

Water hyacinth (Eichhornia crassipes) and water lettuce (Pistia stratiotes) in the Great Lakes: playing with fire?

2011· article· en· W2008547428 on OpenAlexafffundabout
Abisola A. Adebayo, Elizabeta Briski, Odion Kalaci, M. C. Hernández, Sara Ghabooli, Boris Beric, Farrah T. Chan, Aibin Zhan, Eric Fifield, Todd A. Leadley, Hugh J. MacIsaac

Bibliographic record

VenueAquatic Invasions · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBiological Control of Invasive Species
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of CanadaU.S. Department of Agriculture
KeywordsPistiaStratiotesEichhornia crassipesHyacinthBiologyAquatic plantBotanyAgronomyEcologyMacrophyte

Abstract

fetched live from OpenAlex

The Laurentian Great Lakes have been successfully invaded by at least 182 nonindigenous species. Here we report on two new species, water hyacinth Eichhornia crassipes and water lettuce Pistia stratiotes, that were found at a number of locations in Lake St. Clair and Detroit River during autumn 2010. Both species are commonly sold in the water garden and aquarium trade in southern Ontario and elsewhere. While it is not clear whether these species are established or can establish in the Great Lakes, the historic assumption that neither of these subtropical to tropical plants pose an invasion risk must be questioned in the light of changing environmental conditions associated with climate warming that may render Great Lakes' habitats more suitable for these species and increase the likelihood of their successful establishment. © 2011 The Author(s).

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.926
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.060
GPT teacher head0.202
Teacher spread0.142 · 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 designObservational
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

Citations58
Published2011
Admission routes3
Has abstractyes

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