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Record W2139118468 · doi:10.1614/ipsm-07-048.1

Predicting Potential Occurrence and Spread of Invasive Plant Species along the North Platte River, Nebraska

2008· article· en· W2139118468 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInvasive Plant Science and Management · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsnot available
Fundersnot available
KeywordsInvasive speciesPhragmitesRiparian zoneHabitatThistleTamarixEnvironmental scienceEcologyIntroduced speciesAbundance (ecology)EcosystemGeographyWetlandBiology

Abstract

fetched live from OpenAlex

Abstract Riparian habitats are important components of an ecosystem; however, their hydrology combined with anthropogenic effects facilitates the establishment and spread of invasive plant species. We used a maximum-entropy predictive habitat model, MAXENT, to predict the distributions of five invasive plant species (Canada thistle, musk thistle, Russian olive, phragmites, and saltcedar) along the North Platte River in Nebraska. Projections for each species were highly accurate. Elevation and distance from river were most important variables for each species. Saltcedar and phragmites appear to have restricted distributions in the study area, whereas Russian olive and thistle species were broadly distributed. Results from this study hold promise for the development of proactive management approaches to identify and control areas of high abundance and prevent further spread of invasive plants along the North Platte River.

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.

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 score0.015
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.028
GPT teacher head0.206
Teacher spread0.178 · 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