Elemental, Isotopic, and Spectroscopic Assessment of Chemical Fractionation of Dissolved Organic Matter Sampled with a Portable Reverse Osmosis System
Bibliographic record
Abstract
Portable reverse osmosis (RO) systems are increasingly being used for isolating dissolved organic matter (DOM) from freshwater aquatic systems because of their high volume processing capacity and high absolute DOM recoveries. However, obtaining complete recoveries implies the rinsing of the reverse osmosis system with a solution of dilute NaOH and combining the rinse solution and the DOM concentrate. Because of the potential chemical alterations that can affect the integrity of the organic pool leached from the RO system at high pHs, this approach is not compatible with studies based on the molecular-level analysis of DOM. The potential for elemental, isotopic, and chemical fractionation was thus evaluated on a series of freshwater DOM samples concentrated in the field with a portable RO system when the concentrate and the rinse solution are not combined. DOC recoveries in the concentrate varied between 81.6 and 88.8%, and total balance calculations showed total recoveries of dissolved and particulate organic carbon ranging between 96.4 and 106.9%. Despite similar delta13C signatures, differences in N content and FTIR-based chemical composition between the concentrate and the rinse DOM solutions suggest some degree of chemical fractionation.
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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".