Biogeochemical origins of particles obtained from the inversion of the volume scattering function and spectral absorption in coastal waters
Bibliographic record
Abstract
Abstract. In the aquatic environment, particles can be broadly separated into phytoplankton (PHY), non-algal particle (NAP) and dissolved (or very small particle, VSP) fractions. Typically, absorption spectra are inverted to quantify these fractions, but volume scattering functions (VSFs) can also be used. Both absorption spectra and VSFs were used to estimate particle fractions for an experiment in the Chesapeake Bay. A complete set of water inherent optical properties was measured using a suite of commercial instruments and a prototype Multispectral Volume Scattering Meter (MVSM); the chlorophyll concentration, [Chl] was determined using the HPLC method. The total scattering coefficient measured by an ac-s and the VSF at a few backward angles measured by a HydroScat-6 and an ECO-VSF agreed with the LISST and MVSM data within 5%, thus indicating inter-instrument consistency. The size distribution and scattering parameters for PHY, NAP and VSP were inverted from measured VSFs. For the absorption inversion, the "dissolved" absorption spectra were measured for filtrate passing through a 0.2 μm filter, whereas [Chl] and NAP absorption spectra were inverted from the particulate fraction. Even though the total scattering coefficient showed no correlation with [Chl], estimates of [Chl] from the VSF-inversion agreed well with the HPLC measurements (r = 0.68, mean relative errors = −20%). The scattering associated with NAP and VSP both correlated well with the NAP and "dissolved" absorption coefficients, respectively. While NAP dominated forward, and hence total, scattering, our results also suggest that the scattering by VSP was far from negligible and dominated backscattering. Since the sizes of VSP range from 0.02 to 0.2 μm, covering (a portion of) the operationally defined "dissolved" matter, the typical assumption that colored dissolved organic matter (i.e., CDOM) does not scatter may not hold, particularly in a coastal or estuarine environment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".