Impact Assessment of Invasive Alien Plant Species on Chimdi (Barju) Lake of Eastern Nepal
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".