Collecting critically endangered cliff plants using a drone-based sampling manipulator
Bibliographic record
Abstract
Kaua'i, an island within the Hawai'i archipelago, is home of a unique flora that contains 250 single-island endemic plant species. Threats have led to a significant population decrease where 97% of these plant species are now listed as endangered, critically endangered, or extinct. Vertical cliff habitats on Kaua'i work as refugia to protect plants from their stressors. However, this habitat makes conservation work particularly difficult, forcing scientists, and botanists to use risky and time-consuming methods such as abseiling to access remote plant populations. Here we present the Mamba, the first aerial system capable of sampling plants on cliffs. This system is operated by two pilots and consists of an actively controlled platform suspended by a long cable under a lifting drone. Eleven otherwise inaccessible samples from five critically endangered species were collected during the first field trials on Kaua'i Island. The samples are currently surviving in nurseries, demonstrating that the Mamba can be used to complete the conservation life cycle for organisms located in difficult areas, from location to collection, then cultivation and outplanting.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".