Assessing the potential of online ICP–MS analysis to optimize Ca/matrix separation using DGA Resin for subsequent isotopic analysis
Bibliographic record
Abstract
Abstract Ca isotopes have gained increasing interest as a diagnostic tool for bone diseases due to the variations in abundances as a consequence of changes in bone-mineral balance. Optimized Ca/matrix separation prior to analysis is a prerequisite for reliable isotope ratio measurements in complex biological matrices such as blood, serum, or urine. The online analysis of analyte/matrix separation by ICP-MS enables direct assessment of elution profiles supporting the optimization process. The integration of transient signals and signal suppression challenge the quantification and interpretation of the elution profiles. Mn and Co remain unretained by the DGA Resin (TrisKem International) from nitric acid. Hence, in the present study, these elements were investigated for their application as standards to monitor signal suppression. Successful analyte quantification was accomplished using a dynamic correction strategy applying a linear gradient of a suppression factor based on Mn and Co intensities. An optimized Ca/matrix separation procedure using DGA Resin is proposed based on the results during online ICP-MS analysis. Graphic abstract
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| 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 teacher head, 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".