Variability of Suspended Particle Properties Using Optical Measurements Within the Columbia River Estuary
Bibliographic record
Abstract
Abstract Optical properties are used to understand the spatial and temporal variability of particle properties and distribution within the Columbia River Estuary, especially in the salinity transition zone and in the estuarine turbidity maximum region. Observations of optical properties in the Columbia River Estuary are consistent with the established model that the river water brings more organic, smaller particles into the estuary, where they flocculate and settle into the salt wedge seaward of the density front. Large tidal currents resuspend mineral‐rich, larger aggregates from the seabed, which accumulate at the density front. Optical proxies for particle size (beam attenuation exponent γ and backscattering exponent γbb) are compared to conventional measurements. The γ and γbb are different to the expected trend with Sauter mean diameter Ds of suspended particles from low‐ to medium‐salinity waters (LMW). Ds increases in the LMW as does the γ derived from a WET Labs ac‐9, which indicates that the particle population dominating the ac‐9 is decreasing in size. The most likely explanation is that flocculation acting at LMW transfers mass preferentially from medium‐sized particles to large‐sized particles that are out of the size range to which the ac‐9 is most sensitive; γbb shows no trend in the LMW. Since γbb is a proxy of proportion of fine particles versus large flocs, the variation of γbb may be insensitive to changes in the medium‐sized particles. The overall results demonstrate that γbb is a reliable proxy for changes in particle size in a stratified environment.
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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 | 0.000 |
| 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 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".