Evaluation of high‐flow rate continuous‐flow centrifugation and filtration devices for sampling and concentrating fine‐grained suspended sediment
Bibliographic record
Abstract
Abstract Fine‐grained (<63 μm) suspended sediment is an important vector for transporting contaminants in aquatic systems. Characterization of physical and biogeochemical properties of suspended sediment usually requires bulk samples to assess its quality and to determine its source. Low‐flow rate (~2 to 4 L min −1 ) continuous‐flow centrifugation (CFC) systems may need a time period from several hours to one day to collect such samples, and thus, due to their low inflow rate, limits application of these devices. A field study was conducted in three different freshwater systems in Manitoba, Canada to examine and compare the performance of two high‐flow rate systems as alternative approaches: the M512 continuous‐flow centrifuge (M512); and continuous filtration using PENTEK 1 μm filtration bags (filtration system). It was determined that the mass collection efficiency (MCE) for the M512 (in absolute terms) was similar to low‐flow rate CFC systems. As with low‐flow rate CFC systems, the M512 preferentially collected particles of a certain size range (i.e., in the case of M512, particles ≥ 0.83 μm) and accordingly this may affect the collection of a truly geochemically and physically representative sample in waters containing a high proportion of finer particles (≤1 μm). Several filtration systems in series improved its MCE performance and, in terms of total collected mass, this configuration appears to be as efficient as the low‐flow rate CFC systems in an equivalent sampling time. The results of this study confirmed that, in nearly all cases, the filtration system collected a representative sample of ambient suspended sediment, in terms of particle size composition, and geochemical and colour properties. In practice, it is suggested that the filtration systems in series have advantages over M512 as the filtration system is more portable and cost‐effective with a lower power demand.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".