ICP-MS AND ICP-AES ANALYSIS OF PLANT REFERENCE MATERIALS
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Two methods — ICP-MS and ICP-AES are used for certification of the new reference material — needles of Siberian pine (NSP-1). Techniques of the analysis include decomposition of plant samples in two different ways: acid digestion in a microwave system MARS-5 and lithium metaborate fusion followed by ICP-MS and ICP-AES analysis of the solutions. Simultaneous determinations of all the elements were carried out in low, medium and high resolution using SF-mass-spectrometer ELEMENT and atomic-emission spectrometer IRIS Advantage with external calibrations and internal standards (In — ICP-MS, Sc —ICP-AES). Middle and high resolutions of ICP mass spectrometer were used for interference corrections. Data obtained by ICP-MS and ICP-AES with different decomposition techniques are in good agreement. The ICP-MS and ICP-AES techniques have been validated by the analysis of three plant reference materials: LB-1 (leaf of a birch), Tr-1 (grass mixture) and EK-1 (Canadian pondweed). These techniques were used for the determination of 38 elements in the new reference material NSP-1. Relative standard deviations for most of the determined elements were below 10%. Combination of ICP-MS and ICP-AES techniques for certification of the new reference material makes it possible to expand the set of elements to be determined and to reduce the total analysis time.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.012 | 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 it