Determination of trace metals in high-salinity petroleum produced formation water by inductively coupled plasma mass spectrometry following on-line analyte separation/preconcentration
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Bibliographic record
Abstract
A procedure is detailed for the determination of trace metals in high salinity petroleum produced formation water (PFW) by inductively coupled plasma mass spectrometry (ICP-MS) coupled with flow injection (FI) on-line matrix separation and preconcentration. High salinity PFW waters present complex composition containing various organic and inorganic substances. Mini-columns packed with Toyopearl AF-Chelate-650M iminodiacetate resin were used for the analyte separation/preconcentration of Cd, Pb, Ni, Zn, V, Co and U; Toyopearl 8-hydroxiquinoline resin for Fe, and silica immobilized 8-hydroxyquinoline resin for Mo. A Doehlert matrix and desirability function was used to generate response surfaces to optimize the column separation/preconcentration parameters. Using 7.5 mL aliquots of PFW, method limits of detection of 0.0007, 0.009, 0.017, 0.024, 0.0002, 0.047, 0.058, 0.002, 0.013 and 0.041 ng ml−1 were obtained for Cd, Pb, Ni, Zn, U, Mo, Fe, Co, V and Mn, respectively. Vanadium, Co and Mn were determined by the method of standard additions whereas Cd, Pb, Ni, Zn, Mo, Fe and U were quantitated using isotope dilution. CASS-4 (coastal seawater) certified reference material was used for method validation and high-salinity PFW (39–120‰) from Brazilian offshore platforms examined. The concentration ranges found in these waters were 0.013–1.47, 0.057–0.80, 0.229–5.1, 0.096–3360, 0.001–0.081, 0.244–69, 0.84–1419, 0.004–3.5, 0.088–0.85 and 4.2–6230 ng ml−1 for Cd, Pb, Ni, Zn, U, Mo, Fe, Co, V and Mn, respectively.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it