Comparison of optically derived particle size distributions: scattering over the full angular range versus diffraction at near forward angles
Bibliographic record
Abstract
The volume scattering function (VSF) of particles in water depends on the particles' size distribution and composition as well as their shape and internal structure. Inversion of the VSF thus provides information about the particle population. The commercially available LISST instrument measures the scattering at near forward angles to estimate the bulk size distribution of particles larger than about 1 μm. By using scattering over the full angular range (0°-180°), the recently improved VSF-inversion method [X. Zhang, M. Twardowski, and M. Lewis, Appl. Opt. 50, 1240 (2011).] can characterize particles in terms of particle subpopulations, which are described by their unique size distribution and composition. Concurrent deployments of the Multispectral Volume Scattering Meter and the LISST in three coastal waters (i.e., Chesapeake Bay, Mobile Bay, and Monterey Bay) allowed us to compare the size distributions derived from these two different methods. We also obtained indirect validation of the results for submicrometer particles and for the composition of particles provided by the VSF-inversion method. For particle sizes ranging from 1 to 100 μm, the concentration was shown to vary over 10 orders of magnitude, and excellent agreement was found between the two methods with a mean relative difference less than 10% for the total size distributions. The inversion results also reproduced spectral variations in the shape of the VSF, although these spectral variations were not frequently observed in our study. The increased backscattering towards the shorter wavelengths was explained by the stronger influence of submicrometer particles affecting the backscattering. Based on published measurements of cell sizes and intracellular chlorophyll-a [Chl] concentrations over a wide range of phytoplankton species and strains, [Chl] was estimated for the inverted subpopulations that were identified as phytoplankton based on their refractive index and mean sizes. The estimated [Chl] agreed well with the fluorescence-based estimates in both magnitude and trend, thus reproducing a bloom event observed at a time series station.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".