Observations of the sensitivity of beam attenuation to particle size in a coastal bottom boundary layer
Bibliographic record
Abstract
[1] The goal of this study was to test the hypothesis that the aggregated state of natural marine particles constrains the sensitivity of optical beam attenuation to particle size. An instrumented bottom tripod was deployed at the 12-m node of the Martha's Vineyard Coastal Observatory to monitor particle size distributions, particle size-versus-settling-velocity relationships, and the beam attenuation coefficient (cp) in the bottom boundary layer in September 2007. An automated in situ filtration system on the tripod collected 24 direct estimates of suspended particulate mass (SPM) during each of five deployments. On a sampling interval of 5 min, data from a Sequoia Scientific LISST 100x Type B were merged with data from a digital floc camera to generate suspended particle volume size distributions spanning diameters from approximately 2 μm to 4 cm. Diameter-dependent densities were calculated from size-versus-settling-velocity data, allowing conversion of the volume size distributions to mass distributions, which were used to estimate SPM every 5 min. Estimated SPM and measured cp from the LISST 100x were linearly correlated throughout the experiment, despite wide variations in particle size. The slope of the line, which is the ratio of cp to SPM, was 0.22 g m−2. Individual estimates of cp:SPM were between 0.2 and 0.4 g m−2 for volumetric median particle diameters ranging from 10 to 150 μm. The wide range of values in cp:SPM in the literature likely results from three factors capable of producing factor-of-two variability in the ratio: particle size, particle composition, and the finite acceptance angle of commercial beam-transmissometers.
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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 | 0.000 | 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 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".