Simultaneous determination of copper, lead, cadmium, zinc, and selenium in cow liver by differential pulse polarography
Bibliographic record
Abstract
A fast and simple method was established for the determination of trace elements in liver. DP polarograms of wet digested liver samples were taken in acetate buffer, pH about 4, for lead, cadmium, and zinc determinations. For copper, addition of EDTA at pH 4 was needed for a better separation from the iron peak. Selenite ion was determined using the hydrogen catalytic peak after the addition of Mo(VI) to the same solution. Trace element levels were different for two separate sections of liver. For the first section (S1) the quantities were found to be 8.12 ± 0.21 mg g1 Cu, 1.16 ± 0.12 mg g1 Zn, 1.09 ± 0.11 mg g1 Cd, 0.59 ± 0.07 mg g1 Pb, and 2.05 ± 0.22 mg g1 Se, in dry liver. For the second section (S2) the results were the same for selenium, but Cd was too small to be detected. The other trace element quantities were 0.48 mg g1 Cu, 0.22 mg g1 Pb, and 0.29 mg g1 zinc. The validity of the method was demonstrated with a synthetic sample resembling liver composition. This method enabled the simultaneous determination of heavy trace elements such as copper, lead, cadmium, molybdenum, selenium, and zinc by using an inexpensive instrument and without any separation or pre-concentration procedures.Key words: cow liver, determination, differential pulse polarography, trace elements.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".