Determination of cupric ion concentrations in marine waters: an improved procedure and comparison with other speciation methods
Bibliographic record
Abstract
Environmental context A Cu ion-selective electrode is potentially an excellent tool for cupric ion measurements in salt water, but it is prone to poor reproducibility. We show that dramatic improvements can be obtained by using a Cu ion-selective electrode and a one-point calibration method that corrects for electrode fouling. The method shows promise to be used to collect data on toxic cupric ion concentrations in saltwater environments. Abstract Free Cu is often used as an indicator for potential Cu toxicity. Free ionic Cu2+ was measured using a flow-through ion-selective electrode (ISE). Four different marine samples were collected from various locations and analysed during a fixed-pH Cu titration using an external standard calibration ISE method. Free cupric determinations in the range 10–12 to 10–7 mol L–1 were consistent with published literature but replicate measures showed up to four orders of magnitude variability. To improve reproducibility, an internal calibration method was developed. The new method was validated using artificial seawater with added tryptophan as the model ligand. The free Cu measured using the improved method showed the same trends as the external calibration data but reproducibility increased to an order of magnitude or better. The potential applicability of this new method was also highlighted in that it matches, in the environmentally and regulatory significant range of total Cu, with a fluorescence quenching method applied to one of the four samples. The ISE data do not agree with free ion concentrations estimated from anodic stripping voltammetry (ASV) though. This suggests that, at least for these samples, ASV responded to a larger fraction of total Cu than simply the inorganic complexes. Caution should be exercised when using ASV as a proxy for bioavailability because the trends in ASV-derived free Cu did not match the free Cu as estimated by ISE. This ability to more reliably measure free Cu is significant for predicting and measuring toxicity on Cu exposure.
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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) | 0.000 | 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".