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Record W4405439563 · doi:10.1139/cjps-2024-0173

The Biology of Canadian Weeds: 160. <i>Poa pratensis</i> L.

2024· article· en· W4405439563 on OpenAlexafffundvenueabout
Emily M. Holden, Jessica Grenke, Kerry Holden, Raytha de Assis Murillo, Cedric Villasor, Viktoria Wagner

Bibliographic record

VenueCanadian Journal of Plant Science · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotany and Plant Ecology Studies
Canadian institutionsUniversity of Alberta
FundersRangeland Research Institute, University of AlbertaNatural Sciences and Engineering Research Council of Canada
KeywordsPoa pratensisBiologyPoa annuaAgronomyWeedHerbicide resistanceBotanyPoaceae

Abstract

fetched live from OpenAlex

Kentucky bluegrass ( Poa pratensis L.) is a perennial, cool-season grass that is widespread across all provinces and territories and first mentioned as an invasive species in 1879. It is represented in Canada by six subspecies, three of which are native, two introduced, and one native and introduced. As a group, the subspecies are found across a wide range of habitat types, including prairie grasslands, woodlands, tundra, and disturbed sites. The introduced subspecies have been intensively used in forage and turf breeding and production. The most invasive subspecies, Poa pratensis ssp. angustifolia, is native to temperate Eurasia and was introduced to North America as a forage and cover crop. Invasions by Kentucky bluegrass result in fewer and less abundant native grass and forb species, reducing plant diversity in native prairie grasslands, and creating cascading negative effects on the ecosystem goods and services provided by these systems. Rhizomatous growth and its ability to reproduce asexually through aposporous apomixis likely enhance Kentucky bluegrass invasiveness. It is effectively controlled using glyphosate herbicide. Early-season prescribed burns are also emerging as a potential management strategy. Despite its detrimental impacts on grassland diversity, Kentucky bluegrass remains a valuable turf and forage grass in all Canadian provinces and territories.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.790
Threshold uncertainty score0.835

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.020
GPT teacher head0.197
Teacher spread0.176 · 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

Citations2
Published2024
Admission routes4
Has abstractyes

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