Acoustic measurements of the spatial distribution of suspended sediment at three sites on the Lower Mekong River
Bibliographic record
Abstract
The Mekong River spans thousands of kilometers, flows through six countries, and its basin is one of the world’s richest in terms of biodiversity. However, land-use changes, dredging of the river bed, and the construction of dams are changing its sediment dynamics and morphology. The resultant increases in bank erosion and reduction in sediment supply to floodplains may have adverse effects on the economical and biological productivity of the region. In order to monitor these changes, the current conditions must be well understood. Comprehensive measurements of the spatial distribution of sediment (both suspended and bed load) were made at three locations in different physiographic regions of the Lower Mekong at the end of the 2012 rainy season. Acoustic Doppler Current Profilers and a multifrequency acoustic backscatter system, the AQUAscat, were used in combination with water sampling to provide high resolution measurements of concentration and grain size. The AQUAscat consisted of four monostatic transducers operating at 0.5, 1, 2.5, and 4 MHz. At each site, it was deployed horizontally at five across-stream positions and 5–10 depths per vertical; a 10 m profile was recorded at each point. The spatial distribution of particle size and concentration were determined using multifrequency inversions of (1) backscattered intensity and (2) attenuation calculated from the intensity profiles. This data set provides a baseline to which to compare future measurements at these sites.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".