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<i>Cabomba caroliniana</i> Gray (Cabombaceae)

2009· book-chapter· en· W182880712 on OpenAlexaboutno aff
Shon Schooler, Guillermo Cabrera Walsh, Mic H. Julien

Bibliographic record

VenueCambridge University Press eBooks · 2009
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicCoastal wetland ecosystem dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyPetalEcologyGeography

Abstract

fetched live from OpenAlex

Introduction Cabomba ( Cabomba caroliniana Gray, Cabombaceae), or water fanwort, is a fast-growing submerged aquatic plant that has the potential to infest permanent water bodies in a range of regions – from tropical to cool temperate – throughout the world. It is considered a serious pest in the United States, Canada, the Netherlands, Japan, India, China, and Australia, and is present in Hungary, South Africa, and the United Kingdom. Cabomba grows well in slow-moving water bodies, preferring areas of permanent standing water less than 4 m deep; however, it can also grow at depths up to 6 m in Australia (Schooler and Julien, 2006). The weed is recognized by its opposing pairs of finely dissected underwater leaves that are feathery or fan-like in appearance (Fig. 6.1 and Fig. 6.2). Small white flowers bearing three petals and three sepals extend above the water surface, making infestations more visible in summer months. Reproduction is almost entirely vegetative throughout most of the introduced localities and any fragment that includes nodes can grow into a new plant (Sanders, 1979). Cabomba originates from South America (Orgaard, 1991). The plant's tolerance of fragmentation and delicate appearance make it a desirable aquarium plant (Hiscock, 2003) and consequently it was brought into many countries through the aquarium trade. Cabomba was subsequently introduced into lakes and streams both accidentally, through the dumping of aquarium water, and on purpose, to enable cultivation for later collection and sale.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.021
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0210.006

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 head0.009
GPT teacher head0.169
Teacher spread0.160 · 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
GenreOther

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

Citations19
Published2009
Admission routes1
Has abstractyes

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Same venueCambridge University Press eBooksSame topicCoastal wetland ecosystem dynamicsFrench-language works237,207