Remote sensing of salt concentration in rivers using VIPA-based Brillouin spectrometers on unmanned aerial vehicles
Bibliographic record
Abstract
A significant fraction of North American rivers and streams are becoming salter and this has a variety of negative environmental and socio-economic consequences. Improving our ability to monitor water quality remotely is highly desirable. Combining Brillouin spectroscopy and LIDAR was been suggested to be a promising avenue for airborne or spaceborne temperature profiling of oceans, but much work remains to be done. We propose to employ VIPA-based Brillouin spectrometers to monitor salt concentration in rivers, streams, and pounds remotely from unmanned aerial vehicles. We present preliminary remote sensing measurements from 2 m away in which we measure the concentration of sodium chloride with a precision on the order 1 g/L. We also present simulations of a depth-resolving confocal scheme, demonstrating <0.5 m axial resolution from 50 m altitude. Finally, we demonstrate the ability to measure Brillouin spectra on a vibrating platform.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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".