Investigating aggregation in Suwannee River, USA, dissolved organic matter using diffusion-ordered nuclear magnetic resonance spectroscopy
Bibliographic record
Abstract
Aggregation of the Suwannee River (USA) dissolved organic matter (SRDOM) is studied using nuclear magnetic resonance spectroscopy. Diffusion-ordered spectroscopy identifies two distinct bands, one corresponding to smaller components and the other to larger components. At lower concentrations (500 ppm), the dissolved organic matter (DOM) is present mainly as small components; however, with increasing concentration, the larger components become more pronounced as a result of aggregation. Calibrations indicate the small materials behave in a manner similar to that of maltodextrins of approximately 180 to 950 Da or proteins of 100 to 1000 Da. The aggregated species show behavior similar to that of maltodextrins of approximately 1000 to 21,000 Da or proteins of 1050 to 70,000 Da. The mean diffusivity of the aggregated components in SRDOM is consistent with that of maltodextrins of approximately 4500 Da and proteins of approximately 8000 Da at the highest concentration measured. At the lowest concentration (closest to environmental concentrations), little to no aggregation is observed. Diffusion profiles show an increase in large-molecular-weight material, with a simultaneous decrease in small-molecular-weight components with increasing DOM concentration. This suggests aggregates in SRDOM may be weak dispersive associations of low-molecular-weight material. Additionally, with a decrease in temperature, aggregates show faster diffusion, suggesting a tighter, more condensed arrangement. Further evidence supports DOM aggregation as conglomerations of numerous components in DOM rather than a more organized self-association. Carboxyl-rich alicyclic molecules (CRAM) play a prominent role in aggregation of SRDOM and, to a lesser extent, material-derived from linear terpenoids (MDLT). The role of lignin and carbohydrates is less clear, although at least some of the lignin is present as macromolecules and tends to show interactions with both the MDLT and CRAM components.
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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) | 0.006 | 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".