Complexation of Lead in Model Solutions of Humic Acid: Heterogeneity and Effects of Competition with Copper, Nickel, and Zinc
Bibliographic record
Abstract
Environmental Context. Metal bioavailability and toxicity are often related to free metal concentration rather than total metal concentration. Humic substances are chemically and physically heterogeneous complexants for metals in natural waters, and play an important role in trace metal transport, fate, and bioavailability. Metal bioavailability, which depends on chemical speciation of metals, is greatly influenced by the presence of other trace metals and major cations in natural waters. In this work, the effects of heterogeneity of humic substances, and of competition of trace metals on lead speciation in model solutions have been studied to gain a better understanding of these effects on complexation of trace metal lead and its bioavailability. Abstract. Physicochemical heterogeneity of a well characterized humic acid (HA) in its complexation with a trace metal lead in model solutions was investigated using pseudo-polarography at a stationary mercury drop electrode, and the differential equilibrium function (DEF) of Pb(ii)–HA complexes was determined. The complexation of Pb(ii) by HA was determined by taking into account the dependence of the strength of the binding on the metal (Pb) loading. Also investigated were the effects of competition of the trace metals copper, nickel, and zinc on the DEF of Pb(ii)–HA complexes in model solutions. The results showed that these trace metals competed with trace metal lead for binding by HA even when present at the same concentrations as that of lead.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".