Challenges in using 0.45 µm filters to assess potentially bioavailable trace elements in the dissolved fraction of river and peat bog waters of the Boreal Zone
Bibliographic record
Abstract
Passing through a 0.45 µm filter can significantly alter the concentrations of dissolved trace elements (TEs) in organic-rich waters of the Boreal Zone. However, little evidence has been provided about the impacts of filtration on the size distribution of dissolved TEs. This limitation hinders our comprehension of how filtration affects the assessment of the potentially bioavailable forms of dissolved TEs (i.e. ions and small molecules). Using AF4-UV-ICP-MS, this study systematically investigates such artefacts and their influence on the concentrations of dissolved, primarily ionic, and colloid-associated TEs in river waters and peat bog waters of the Boreal Zone. In river waters (circumneutral pH), membrane filtration had a significant impact on TEs that are associated with inorganic colloids such as Al, Mn, Fe, As, the rare earth elements, Pb, and Th. Approximately 20-80 % of primarily ionic TEs (< 0.5 kDa) and 100 % of large inorganic (ca. 40-300 nm) TEs were excluded from the filtrates under clogged conditions. In contrast, little impact of filtration was observed for bog waters (pH 4). Similarly, cartridge filtration of river waters also led to a decrease in concentrations and size distributions of dissolved TEs. However, cartridge filtration demonstrated a higher efficiency in allowing the passage of ions and excluding colloids than membrane filtration. On average, the ratio of the dissolved concentrations between a cartridge and a membrane filtrate was 1.0 ± 0.2. For primarily ionic species, the average ratio was 1.4 ± 0.4, while for colloidal species, it was 0.4 ± 0.1. Therefore, despite having similar dissolved concentrations, filtration methods with the same nominal pore size can yield different concentrations of bioavailable forms of TEs. These findings may be important for studies of the environmental relevance of dissolved TEs in surface waters of the Boreal Zone, and organic-rich waters elsewhere.
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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 | 0.022 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".