Multi-rotor unmanned aerial vehicles (UVAs) and high-resolution compact digital cameras: a promising new method for monitoring changes to surface karst resources
Bibliographic record
Abstract
In the course of doctoral research, the authors required a quick and accurate means of documenting the real-time state of surface karst features at a variety of scales in remote and challenging field conditions. The main difficulty was finding an aerial platform that was 1) consistently effective; 2) versatile; and 3) relatively inexpensive. High resolution vertical images obtained during recreational use of a small multi-rotor unmanned aerial vehicle (UAV) seemed to have the potential to answer this need. Using five case studies, the authors examine the potential of these images for mapping, documenting, and monitoring changes to surface karst resources following forestry-related activities in the coastal temperate rainforest of British Columbia (B.C.). Possible applications, strengths and limitations of this technology are discussed. The authors conclude that mini quadcopter UAVs equipped with high-resolution compact digital cameras are a promising and cost-effective new tool for karst scientists and karst managers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".