Investigating the structure and aggregation of dissolved organic matter using NMR spectroscopy
Bibliographic record
Abstract
Dissolved organic matter (DOM) represents one of the largest and least understood pools of organic carbon on Earth. Despite its importance in many environmental processes, fundamental aspects, such as the structure and associations of DOM, still remain ambiguous. This thesis provides findings on aspects of DOM research that are necessary for a greater understanding of DOM reactivity and interactions in the environment, including structural components and self-associations (i.e. aggregation). A new passive isolation technique is described, which combines a selectively-permeable membrane and an ion-exchange resin to filter and concentrate DOM. The passive sampler removes the need for active sampling (i.e. pumping of large volumes of water) and isolates material similar to traditional methods. A newly-developed NMR water suppression technique permits the analysis of DOM at natural abundance, and validates that isolation techniques yield similar material to DOM from the environment. This new water suppression technique also permits characterization of DOM without concentration or pretreatment, allowing the analysis of limited or precious samples (e.g. pore water, ice cores).
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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) | 0.001 | 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".