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Record W4407114943 · doi:10.58578/ajstea.v3i2.4896

Impact Assessment of Invasive Alien Plant Species on Chimdi (Barju) Lake of Eastern Nepal

2025· article· en· W4407114943 on OpenAlexaff
Bishnu Dev Das, Upasana Sharma

Bibliographic record

VenueAsian Journal of Science Technology Engineering and Art · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Biodiversity
Canadian institutionsThe Journal of Student Science and Technology
Fundersnot available
KeywordsAlienGeographyInvasive speciesAlien speciesEcologyBiologyPolitical science

Abstract

fetched live from OpenAlex

The present study has been carried out to evaluate the impact assessment of invasive alien plant species on Chimdi Lake using focus group discussion method. Chimdi (Barju) Lake is an important wetland in Eastern Nepal, faces ecological challenges due to the rapid spread of invasive alien plant species. Assessing the impact of these species is essential to understand their effects on the lake's biodiversity and ecosystem services and to develop effective management strategies for the conservation of the lake. The lake was found to be dominated by two aquatic IAPS, Pontederia crassipes followed by Ipomoea carnea. Additionally, eight other terrestrial IAPS (Ageretina adenophora, Chromolaena adorata, Lantana camara, Mikania micrantha, Mimosa pudica, Senna occidentalis., Senna tora, and Xanthium strumarium) were also recorded from the lake. Apart from these, there were several more macrophytes and hydrophytes, such as Nelumbo nucifera, Nymphaea alba, Ipomoea aquatica, etc., which created a thick layer of peat over lake water. These IAPS characteristics encourage growth and cover in water bodies, which block sunlight, change the chemistry of the water, and also reduce the habitat quality of native water animals and plants.

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 score0.047
Threshold uncertainty score0.228

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 studies0.0000.001
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 head0.005
GPT teacher head0.214
Teacher spread0.208 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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