Thin film hydride generation: determination of ultra-trace copper by flow injection in situ hydride trapping graphite furnace AAS
Bibliographic record
Abstract
A novel system which significantly enhances copper hydride generation efficiency was used for the determination of trace copper by coupling a flow injection system to a graphite furnace for in situ collection of the analyte and subsequent AAS detection. A single device integrated the functions of hydride generator and gas liquid separator. Solutions of the sample containing 0.0005% (m/v) phenanthroline and 1% formic acid were merged with tetrahydroborate reductant to yield a thin film wetting a reaction surface from which product vapor was efficiently liberated and transported to the heated furnace. Optimum operating conditions provided for a generation/transport/collection efficiency of 8–12%. Interferences from common transition and noble metals were effectively eliminated. A limit of detection of 100 pg ml−1 was obtained based on processing a 1 ml sample volume. A precision of better than 4% (RSD) at 1 ng ml−1 was typical. The methodology was successfully applied to the determination of Cu in several NRCC natural water and biological tissue Certified Reference Materials.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".