Particle optical backscattering along a chlorophyll gradient in the upper layer of the eastern South Pacific Ocean
Bibliographic record
Abstract
Abstract. The particulate scattering, bp, and backscattering, bbp, coefficients are determined by the concentration and physical properties of suspended particles in the ocean. They provide a simple description of the influence of these particles on the scattering of light within the water column. For the remote observation of ocean color, bbp along with the total absorption coefficient govern the amount and spectral qualities of light leaving the sea surface. However, for the construction and validation of ocean color models measurements of bbp are still lacking, especially at low chlorophyll a concentrations ([Chl]). Here, we examine the relationships between spectral bbp and bp vs. [Chl] along an 8000 km transect crossing the Case 1 waters of the eastern South Pacific Gyre. In these waters, over the entire range of [Chl] encountered (~0.02–2 mg m3), both bbp and bp can be related to [Chl] by power functions (i.e. bp or bbp=α[Chl]β). Regression analyses are carried out to provide the parameters α and β for several wavelengths throughout the visible for both bbp and bp. When applied to the data, these functions retrieve the same fraction of variability in bbp and bp (coefficients of determination between 0.82 and 0.88). The bbp coefficient fall within the bounds of previous measurements at intermediate and high [Chl] recently published. Its dependence on [Chl] below ~0.1 mg m−3 is described for the first time with in situ data. The backscattering ratio (i.e. bbp/bp) with values near 0.01 for all stations appears to be spectrally neutral and not significantly dependent on [Chl]. These results should foster the development of improved forward models of the mean optical properties for oceanic Case 1 waters as well as inverse models based upon them.
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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 | 0.000 |
| 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) | 0.001 | 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".