Mapping invasive alien plants through citizen science: shortlisting species of concern for the Nilgiris
Bibliographic record
Abstract
Species introduced from elsewhere are known as alien species. They may be introduced as crop plants or ornamental plants, or for timber. A small proportion of introduced species can become invasive thereby spreading at the cost of native species and habitats, negatively affecting biodiversity, food security, and human wellbeing. Despite the growing recognition of the threat of invasive alien species, we still lack information about the distribution and abundance of species widely accepted to be invasive. To address this information gap regarding invasive alien species distributions, we initiated a pilot citizen science effort to create an atlas of invasive plants in the Moyar-Bhavani landscape of the Nilgiri District. We aimed, through this pilot effort, to develop and test user-friendly mapping protocols and develop an interface for citizen scientists to use. Ultimately, we hope to create a model that can be scaled up to large conservation landscapes, such as the Western Ghats, the central Indian Highlands, and the Himalaya.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".