Simultaneous cloud point extraction of low levels of Cd, Cr and Hg in seaweed species prior to neutron activation analysis
Bibliographic record
Abstract
A one-step preconcentration cloud point extraction (CPE) method has been developed for the simultaneous determination of Cd, Cr, and Hg using a mixture of 1-(2-pyridylazo)-2-naphthol (PAN) and 1-(2-thiazolylazo)-2-naphthol (TAN) chelating agents and polyoxyethylene nonylphenylether-20 (PONPE-20) surfactant. The pH, concentration of PAN and TAN, concentration of PONPE-20, ionic strength and temperature affecting the sepa-ration were optimized. The recoveries of each of the elements under the optimum conditions of pH 8.6, [PAN/ TAN] = 1 x 10-4 M, [PONPE-20] = 0.1 % (m/v), ionic strength = 0.05 M KNO3, and temperature of 41 oC were > 98 %. The concentrations of the elements were determined by neutron activation analysis using the Dalhousie University SLOWPOKE-2 reactor (DUSR) facility. The detection limits of Cd, Cr, and Hg were 6.0, 3.6 and 1.2 ng g-1 respectively, and precision and accuracy of measurements were evaluated. The method was success-fully applied to the simultaneous determination of Cd, Cr, and Hg in fifteen Ghanaian seaweed species. Journal of Applied Science and Technology Vol. 13 (1 & 2) 2008: pp. 48-54
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 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".