Mobile Distributed Temperature Sensing of the Air/Water Interface of an Aquatic Environment with an Unmanned Surface Vehicle
Bibliographic record
Abstract
Aquatic habitats have a boundary layer near the air–water interface (AWI) that governs mass transport. Little is known about temperature profiles and boundary layers at the AWI. We used a high-resolution distributed temperature sensing (HR-DTS) system onboard an unmanned surface vehicle (USV) to resolve temperature profiles from about 1 m above and 1 m below the surface of the water. Our USV–HR-DTS system resolved a temperature differential of about 5.5 °C at the AWI, spanning a distance of approximately 13 cm. DTS profiles were similar for stationary holds and forward and reverse transects in the water. There was a significant change in temperature as a function of height, with an exponential decrease in temperature starting around 13 cm down to the AWI (P = 2 × 10−16). This is the first application of a HR-DTS onboard a USV to examine temperature profiles across the AWI. To our knowledge, these are the first high-resolution temperature profiles of the AWI captured from a mobile platform. Because our USV–HR-DTS system is mobile, it could be used to profile temperatures at the AWI at multiple locations in a large body of water. This technology could also find unique applications in the measurement of meteorological drivers of hazardous agent dispersal for source localization efforts.
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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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.001 | 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".