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Record W7128322922

Genetic variation in populations of reed canarygrass, <i>Phalaris arundinacea</i> L.

2013· dissertation· cs· W7128322922 on OpenAlexaboutno aff
Tereza Kávová

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2013
Typedissertation
Languagecs
FieldAgricultural and Biological Sciences
TopicBioenergy crop production and management
Canadian institutionsnot available
Fundersnot available
KeywordsPhalaris arundinaceaHabitatWetlandPopulationLivestockBiomass (ecology)Invasive speciesVegetation (pathology)
DOInot available

Abstract

fetched live from OpenAlex

The spread of invasive plant species in natural habitats has become a worldwide problem with negative environmental and economic impacts. An increasing number of invasive organisms are responsible for adverse environmental and economic impacts worldwide, including species extinction, crop failures, reduced water supply, and damage to industrial infrastructures (KERCHER et al., 2007). Phalaris arundinacea L. is widespread throughout the world, except Antarctica and Greenland. Center of diversity of this genus is in the Mediterranean. Members of the genus Phalaris occurs in moist habitats from lower to alpine altitudes (ANDERSON, 1997). Phalaris has a plethora of uses. Its most frequent use is as the root wastewater treatment plants. Phalaris grown as feed for livestock and is also used as an ornamental grass. Phalaris have recently received a lot of attention as a new biomass source for the production of renewable energy in USA. In recent years there has been a massive spread of P. arundinacea across North America (currently occurs in 43 states) and Canada (ZEDLER & KERCHER, 2004). Phalaris represents a significant threat to its original wetland vegetation and is classified as a harmful agens in nine state of U.S. states (LAVERGNE & MOLOFSKY, 2004). It is believed that these aggressive population have European origin.

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 score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.222
Teacher spread0.211 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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