Tandem calibration methodology: dual nebulizer sample introduction for ICP-MS
Bibliographic record
Abstract
The application to inductively coupled plasma mass spectrometry (ICP-MS) of a calibration method called the TCM (tandem calibration method) is described. The TCM involves simultaneous introduction of sample and standard into the plasma by two nebulizers operated in parallel. Figures of merit were determined by comparing the results obtained with those produced using the method of standard additions and external standard calibration was used as a probe of the severity of the matrix effect induced. The test solutions in this study contained Cu, Y, Pt and Pb as analytes and 10 mM Ba and 35 mM Na as matrix effect generators. Classical standard addition verified the validity of the TCM and the two methods were shown to be statistically equivalent. The precision of the results obtained was limited by the noise of the sample introduction device (about 4% RSD on difficult samples versus roughly 1% on clean standards), while the accuracy was only slightly limited by the short and long term stability of the arrangement, typically around 2% relative error. The method was easy to implement on existing equipment, inexpensive and potentially suited to automation.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.010 |
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".