An assessment of thermal-image acquisition with an unmanned aerial vehicle (UAV) for direct counts of coastal marine mammals ashore
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We investigated the efficacy of infrared thermal imaging devices for detecting coastal marine mammals in forested coastal environments. Our objective was to determine whether pinnipeds could be detected through the forest canopy using thermal imagery. We used a UAV-mounted and a ground-mounted infrared camera to survey New Zealand fur seals (Arctocephalus forsteri) located in Ohau Stream and Point Kean coastal shrub forest on the east coast of New Zealand. These methods were compared to paired photographs and walk-through counts. Ground-mounted thermal images detected more seals than paired photographs during the cooler times of the day (morning and evening). In contrast, aerial thermal videos were successful in detecting fur seals in open areas, but were less successful in areas of high canopy cover (>80%). We discuss the advantages and limitations of thermal imaging for population sampling and provide some recommendations for future research.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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 it