Unraveling the size‐dependent optical properties of dissolved organic matter
Bibliographic record
Abstract
Abstract The size‐dependent optical properties of dissolved organic matter (DOM) from four Swedish lakes were investigated using High Performance Size Exclusion Chromatography (HPSEC) in conjunction with online characterization of absorbance (240–600 nm) and fluorescence (excitation: 275 nm, emission: 300–600 nm). The molecular size of chromophoric DOM (CDOM) was consistently higher than that of fluorescent DOM (FDOM), with an average difference of 0.37 kDa. The relative abundance of FDOM vs. CDOM ranged from 0.3 to 0.7 across lakes, and increased with decreasing average molecular size. Across sites, the CDOM spectral slopes of the large molecular size fraction were highly similar while the low molecular size fraction differed and contributed to different bulk spectral slopes. Our results indicate structural congruence of high molecular size DOM across systems while lake trophic status determined the characteristics of the low size range. Furthermore, the combination of HPSEC and parallel factor analysis (HPSEC‐PARAFAC2) allowed the decomposition of DOM fluorescence chromatograms. Three humic‐like components and one protein‐like component with broadly overlapping molecular size distributions were identified. This overlap provides further evidence for the supramolecular assembly hypothesis since fluorophores, as revealed by PARAFAC2, occur in aggregates of overlapping molecular size. Our results further suggest a link between the molecular size of these fluorophores and the associated supramolecular assemblies. This study demonstrates the potential for HPSEC and novel mathematical approaches to provide unprecedented insights into the relationship between optical and chemical properties of DOM in aquatic systems.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".