Trace metal dynamic speciation studied by scanned stripping chronopotentiometry (SSCP)
Bibliographic record
Abstract
Environmental context. Natural aquatic systems are subject to changing conditions and practically never reach chemical equilibrium. Therefore, a quantitative understanding of the interaction of the trace metals with heterogeneous samples and their kinetic characteristics requires the dynamic characterisation of trace metal speciation. We show that scanned stripping chronopotentiometry (SSCP) is able to discriminate the dynamic nature of the complexes, although it still overestimates the average stability constants obtained from the SSCP wave characteristics using the Freundlich isotherm to account for the chemical heterogeneity. Abstract. The ability of scanned stripping chronopotentiometry (SSCP) to obtain dynamic information for metal complexation with heterogeneous colloidal ligands was evaluated by measurements of lead(II) and cadmium(II) complexation by humic and fulvic acids extracted from an ombrotrophic peat bog. Average stability constants were calculated, using a first order chemical heterogeneity approach, and compared with those obtained by an ion selective electrode (ISE). SSCP average stability constants were overestimated in comparison to those obtained by the ISE, which suggests that the first order heterogeneity approach did not fully account for the ligand heterogeneity. However, the comparison of the stability constants obtained from the two SSCP signals (the shift of the half-wave potential and the decrease of transition time) provides information about the dynamic nature of the metal complexes formed with the humic matter. These results were in reasonable agreement with the theoretical predictions of the dynamic theory for colloidal systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.003 | 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 teacher head, 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".