Determination of subnanomolar concentrations of vanadium in environmental water samples using flow injection with luminol chemiluminescence detection
Bibliographic record
Abstract
A flow injection chemiluminescence method is described for the determination of subnanomolar concentrations of vanadium in environmental water samples. The procedure is based on the oxidation of luminol in the presence of dissolved oxygen catalyzed by vanadium(IV). Vanadium(V) reduction and preconcentration of vanadium(IV) was carried out using in-line silver reductor and 8-hydroxyquinoline chelating columns at pH 3.15, respectively. The calibration graph for vanadium(IV) was linear in the concentration range of 0.025-10 µg/L with relative standard deviation in the range of 0.4-5.58%. The detection limit (3s blank) was 3.8 × 10(-3) µg/L without preconcentration; when the vanadium(IV) was preconcentrated with an 8-HQ column for 1 min (2.0 mL of sample loaded), the detection limit of 5.1 × 10(-4) µg/L was achieved. One analytical cycle can be completed in 2.0 min. The analysis of certified reference materials (CASS-4, NASS-5 and SLRS-4) by the proposed method showed good agreement with the certified values. The method was successfully applied to the determination of total dissolved vanadium in environmental water samples.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".