Predicting Dissolved Lignin Phenol Concentrations in the Coastal Ocean from Chromophoric Dissolved Organic Matter (CDOM) Absorption Coefficients
Why this work is in the frame
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Bibliographic record
Abstract
Dissolved lignin is a well-established biomarker of terrigenous dissolved organic matter (DOM) in the ocean, and a chromophoric component of DOM. Although evidence suggests there is a strong linkage between lignin concentrations and chromophoric dissolved organic matter (CDOM) absorption coefficients in coastal waters, the characteristics of this linkage and the existence of a relationship that is applicable across coastal oceans remain unclear. Here, 421 paired measurements of dissolved lignin concentrations (sum of nine lignin phenols) and CDOM absorption coefficients [a g ()] were used to examine their relationship along the river-ocean continuum (0-37 salinity) and across contrasting coastal oceans (sub-tropical, temperate, high-latitude). Overall, lignin concentrations spanned four orders of magnitude and revealed a strong, non-linear relationship with a g (). The characteristics of the relationship (shape, wavelength dependency, lignin-composition dependency) and evidence from degradation indicators were all consistent with lignin being an important driver of CDOM variability in coastal oceans, and suggested physical mixing and long-term photodegradation were important in shaping the relationship. These observations were used to develop two simple empirical models for estimating lignin concentrations from a g () with a 20% error relative to measured values. The models are expected to be applicable in most coastal oceans influenced by terrigenous inputs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it