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Record W7075328197

A Review of Garlic Mustard (Alliaria petiolata) as an Allelopathic Plant

2017· article· en· W7075328197 on OpenAlexaboutno aff

Bibliographic record

VenueJournal of Bioresource Management · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Resources Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAllelopathyHerbPlant speciesInvasive speciesPlant ecology
DOInot available

Abstract

fetched live from OpenAlex

Alliaria petiolata is a widespread biennial herb from Eurasia that is one of the most recognizable invasive plants of forests in the eastern United States and southern Canada. After two decades of intensive study on its physiology, ecology, and impacts, this plant has come to be known in both the scientific and gray literature as an allelopathic plant capable of exerting negative, chemically mediated effects on plants and microbes in its environment. A critical review of the literature reveals that there is evidence both supporting and failing to support this assertion, and that conclusions can be affected greatly by the experimental approaches taken, the target species examined, the sources of allelopathic inputs, and environmental factors. The objective of this review is to provide a history of allelopathy research in A. petiolata, describing the various approaches that have been taken and conclusions drawn, and to summarize the current standing of A. petiolata as an allelopathic plant using the most ecologically relevant data on this phenomenon. Finally, we discuss the degree to which allelopathy, versus other mechanisms, may contribute to the invasive success of this plant.

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)0.002
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.482
Threshold uncertainty score0.575

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.044
GPT teacher head0.272
Teacher spread0.228 · 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 designNot applicable
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

Citations0
Published2017
Admission routes1
Has abstractyes

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