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Record W1992437433 · doi:10.1614/ipsm-d-14-00028.1

North-East, North-Central, Mid-Atlantic United States and Southern Canada: Japanese Hedgeparsley (<i>Torilis japonica</i>)—A New Invasive Species in the United States?

2014· article· en· W1992437433 on OpenAlexaffabout
Antonio DiTommaso, S. J. Darbyshire, Caroline Marschner, Kristine M. Averill

Bibliographic record

VenueInvasive Plant Science and Management · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsAgriculture and Agri-Food Canada
FundersWisconsin Department of Natural Resources
KeywordsRuderal speciesBiological dispersalGeographyInvasive speciesEcologyIntroduced speciesHabitatHabitHerbariumForbBiologyDemographyPopulation

Abstract

fetched live from OpenAlex

Abstract Japanese hedgeparsley is an annual (or sometimes biennial) forb introduced from Eurasia and found throughout much of the eastern United States and parts of extreme southern Canada. In North America, Japanese hedgeparsley is commonly found in ruderal habitats, such as roadsides, railroad rights-of-way, forest edges, and urban waste spaces. This species has not yet been listed as a noxious invasive, but its expanding populations have caused concern in several Midwestern states. The primary threat from Japanese hedgeparsley is its vigorous growth habit, which creates dense patches, and its dispersal ability, facilitated by its clinging, burr-like fruits. Some confusion on identification exists within the Torilis genus, with similar species (particularly T. arvensis ) frequently misidentified in herbaria and the literature. Here, we review aspects of the etymology, taxonomy, biology, distribution, and management of Japanese hedgeparsley with the objective of increasing awareness of the potential threat posed by this species and its closely related congeners.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.588
Threshold uncertainty score0.909

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.192
Teacher spread0.180 · 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 teacher head, 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

Citations1
Published2014
Admission routes2
Has abstractyes

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