Prediction of Multiple Matrix Interferences in Inductively Coupled Plasma Mass Spectrometry
Bibliographic record
Abstract
Matrix effects for pairs of interferents (Al, Na, K, Ba, and Cs) were investigated and compared to predictions of the amount of interference determined by single interferent experiments in order to test a model called the total interference level (TIL), which assumes that the effects of different interferents add linearly. The TIL model is part of an Autonomous Instrument and is designed to indicate when a simple default calibration, such as external calibration or internal standardization, is inadequate for the desired accuracy of analysis. The performance of the TIL model was examined in terms of a daily calibration basis, which should be more accurate, and an occasional calibration basis, which is more convenient, considering simple external standardization and internal standardization as the techniques to be tested for desired accuracy. The results are encouraging for multiple interferences and show that the TIL model can serve a useful function in predicting calibration errors, even given the presence of instrument drift on ICP-MS.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".