The optical volume scattering function in a surf zone inverted to derive sediment and bubble particle subpopulations
Bibliographic record
Abstract
The effects of particle fields including bubbles on the optical volume scattering function (VSF) were investigated in the surf zone off Scripps Pier as part of an ongoing effort to better understand the underlying dynamics in the VSF in the subsurface ocean. VSFs were measured at 20 Hz at angles spanning 10°–170° in 10° increments with a device called the Multiangle Scattering Optical Tool (MASCOT). Modification of the phase function was observed in passing suspended sediment plumes, wave‐injected bubble plumes, and combinations of these particle populations relative to the background. Phase function enhancement in the 60°–80° range was observed in association with bubble plumes, consistent with theoretical predictions. VSFs were inverted to infer size distributions and composition using a least squares minimization fitting procedure applied to a library of phase functions, each representing a lognormally distributed subpopulation with refractive index and coating, where applicable. Phase functions representative of nonspherical mineral particle subpopulations were computed using discrete dipole approximation (DDA) and improved geometric optics method (IGOM) techniques for randomly oriented, asymmetric hexahedra. Phase functions for coated bubbles were computed with the Lorenz‐Mie theory. Inversion results exhibited stable solutions that qualitatively agreed with concurrent acoustical measurements of bubbles, aggregate particle size distribution expectations, and anecdotal videography evidence from the field. Although a comparable inversion with a library that assumed spherical shaped particles alone provided less stable results with some incorrectly assigned subpopulations, several dominant subpopulation trends were consistent with the results obtained using nonspherical representations of mineral particles.
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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 | 0.000 | 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 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".