Determination of trace metals in high-salinity petroleum produced formation water by inductively coupled plasma mass spectrometry following on-line analyte separation/preconcentration
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".