One-Pot Speciation Method for Cr(III) and Cr(VI) with APCD/DIBK Extraction System Based on Difference in Rate of Complex Formation
Bibliographic record
Abstract
Abstract A simple speciation of chromium oxidation states based only on the difference in reaction rates of Cr(III) and of Cr(VI) has been developed. This speciation, which was carried out in an ammonium 1-pyrrolidinecarbodithioate (APCD)/diisobutyl ketone (DIBK) extraction system, required no sample splitting. At the first extraction, Cr(VI) was extracted into a DIBK phase, and Cr(III) remaining in the sample was extracted secondly after replacement of the phase by fresh DIBK. Inert Cr(III) was extracted directly without the oxidation process. The concentration of chromium in the extract was measured by AAS. In the first extraction, 0.4–0.5% of Cr(III) was extracted and 0.2% of Cr(VI) was carried over to the second extraction. Using artificial seawater, the detection limit (3σ) and the relative standard deviation (n = 5, at 100 μg/L) were 10 μg/L and ca. 4% (concentration factor = 2). Interferences of heavy metal ions were examined; 5-fold cation group (Mn2+, Fe3+, Ni2+, Cu2+ and Zn2+) and 1-fold anion group (VO3−, Mo7O246− and WO42−) exhibited negative errors of 5 and 10% in Cr(III) determination respectively. Validity of the method was checked with the standard reference material JAC-0032 (river water); total chromium was determined as 11.0 μg/L (certified value is 10.1 ± 0.2 μg/L).
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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 | 0.001 | 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".