Asymmetrical flow field-flow fractionation and excitation-emission matrix spectroscopy combined with parallel factor analyses of riverine dissolved organic matter isolated by tangential flow ultrafiltration
Bibliographic record
Abstract
Asymmetrical flow field-flow fractionation (AF4) with sequential on-line UV/visible and fluorescence detectors was used to investigate the composition of dissolved organic matter (DOM) in permeate and retentate fractions isolated by tangential flow ultrafiltration (TFF) at various concentration factors (i.e. ratio of initial volume to the retentate volume; CF). The permeation coefficient model, which defines the log-log relationship between DOM in the permeate fractions and CFs, described the permeation behaviour of DOM with regression coefficients r 2 > 0.99. The dominance of higher-molecular weight retentate chromophoric DOM (CDOM) observed in TFF was consistent with the results of AF4. The weight-averaged molecular weights (M w) of the integral permeate and retentate at CF = 20 were determined to be 1160 and 2320 by AF4, respectively, while their molecular weight distributions (MWD) were centered at 1120 and 1600 Da. M w, MWD, and aromaticity (i.e. ratio of absorbance at 250 and 365 nm; E2/E3) in permeate fractions were altered significantly during the early stages of TFF (CF < 9). These changes, however, were not evident in excitation-emission matrix fluorescence properties as determined using the parallel factor analysis model. The application of AF4 to TFF fractions suggests that the choice of CF may have an important impact on the size distribution and aromaticity of permeate fractions, whereas fluorescence properties appear insensitive to concentration factor. These results suggest that the choice of CF is crucial only in the study of the permeate fraction where similar CF (i.e. > 9) should be used to obtain meaningful comparison among samples.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".