Composition of dissolved organic matter within a lacustrine environment
Bibliographic record
Abstract
Environmental context Freshwater dissolved organic matter is a complex chemical mixture central to many environmental processes, including carbon and nitrogen cycling. Questions remain, however, as to its chemical characteristics, sources and transformation mechanisms. We studied the nature of dissolved organic matter in a lake system and found that it is influenced by anthropogenic activities. Human activities can therefore influence the huge amounts of carbon sequestered in lakes as dissolved organic matter. Abstract Freshwater dissolved organic matter (DOM) is a complex mixture of chemical components that are central to many environmental processes, including carbon and nitrogen cycling. However, questions remain as to its chemical characteristics, sources and transformation mechanisms. Here, we employ 1- and 2-D nuclear magnetic resonance (NMR) spectroscopy to investigate the structural components of lacustrine DOM from Ireland, and how it varies within a lake system, as well as to assess potential sources. Major components found, such as carboxyl-rich alicyclic molecules (CRAM) are consistent with those recently identified in marine and freshwater DOM. Lignin-type markers and protein/peptides were identified and vary spatially. Phenylalanine was detected in lake areas influenced by agriculture, whereas it is not detectable where zebra mussels are prominent. The presence of peptidoglycan, lipoproteins, large polymeric carbohydrates and proteinaceous material supports the substantial contribution of material derived from microorganisms. Evidence is provided that peptidoglycan and silicate species may in part originate from soil microbes.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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 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".