Accurate and precise determination of isotopic ratios by MC‐ICP‐MS: A review
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
For many decades the accurate and precise determination of isotope ratios has remained a very strong interest to many researchers due to its important applications in earth, environmental, biological, archeological, and medical sciences. Traditionally, thermal ionization mass spectrometry (TIMS) has been the technique of choice for achieving the highest accuracy and precision. However, recent developments in multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS) have brought a new dimension to this field. In addition to its simple and robust sample introduction, high sample throughput, and high mass resolution, the flat-topped peaks generated by this technique provide for accurate and precise determination of isotope ratios with precision reaching 0.001%, comparable to that achieved with TIMS. These features, in combination with the ability of the ICP source to ionize nearly all elements in the periodic table, have resulted in an increased use of MC-ICP-MS for such measurements in various sample matrices. To determine accurate and precise isotope ratios with MC-ICP-MS, utmost care must be exercised during sample preparation, optimization of the instrument, and mass bias corrections. Unfortunately, there are inconsistencies and errors evident in many MC-ICP-MS publications, including errors in mass bias correction models. This review examines "state-of-the-art" methodologies presented in the literature for achievement of precise and accurate determinations of isotope ratios by MC-ICP-MS. Some general rules for such accurate and precise measurements are suggested, and calculations of combined uncertainty of the data using a few common mass bias correction models are outlined.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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