Detection and Structural Identification of Dissolved Organic Matter in Antarctic Glacial Ice at Natural Abundance by SPR-W5-WATERGATE <sup>1</sup>H NMR Spectroscopy
Bibliographic record
Abstract
Dissolved organic matter (DOM) is ubiquitous in aquatic ecosystems and is derived from various inputs that control its turnover. Glaciers and ice sheets are the second largest water reservoir in the global hydrologic cycle, but little is known about glacial DOM composition or contributions to biogeochemical cycling. Here we employ SPR-W5-WATERGATE (1)H NMR spectroscopy to elucidate and quantify the chemical structures of DOM constituents in Antarctic glacial ice as they exist in their natural state (average DOC of 8 mg/L) without isolation or preconcentration. This Antarctic glacial DOM is predominantly composed of a mixture of small recognizable molecules differing from DOM in marine, lacustrine, and other terrestrial environments. The major constituents detected in three distinct types of glacial ice include lactic and formic acid, free amino acids, and a mixture of simple sugars and amino sugars with concentrations that vary between ice types. The detection of free amino acid and amino sugar monomer components of peptidoglycan within the ice suggests that Antarctic glacial DOM likely originates from in situ microbial activity. As these constituents are normally considered to be biologically labile (fast cycling) in nonglacial environments, accelerated glacier melt and runoff may result in a flux of nutrients into adjacent ecosystems.
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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) | 0.000 | 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".