Molecular Characterization of Dissolved Organic Matter in Glacial Ice: Coupling Natural Abundance <sup>1</sup>H NMR and Fluorescence Spectroscopy
Bibliographic record
Abstract
Glaciers and ice sheets are the second largest freshwater reservoir in the global hydrologic cycle, and the onset of global climate warming has necessitated an assessment of their contributions to sea-level rise and the potential release of nutrients to nearby aquatic environments. In particular, the release of dissolved organic matter (DOM) from glacier melt could stimulate microbial activity in both glacial ecosystems and adjacent watersheds, but this would largely depend on the composition of the material released. Using fluorescence and (1)H NMR spectroscopy, we characterize DOM at its natural abundance in unaltered samples from a number of glaciers that differ in geographic location, thermal regime, and sample depth. Parallel factor analysis (PARAFAC) modeling of DOM fluorophores identifies components in the ice that are predominantly proteinaceous in character, while (1)H NMR spectroscopy reveals a mixture of small molecules that likely originate from native microbes. Spectrofluorescence also reveals a terrestrial contribution that was below the detection limits of NMR; however, (1)H nuclei from levoglucosan was identified in Arctic glacier ice samples. This study suggests that the bulk of the DOM from these glaciers is a mixture of biologically labile molecules derived from microbes.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".