Determination of the Isotopic Composition of Indium by MC-ICP-MS Using an Improved Measurement Model for the Gravimetric Isotope Mixture Method
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Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide In this study, we report the first independent and primary isotope ratio measurement of indium by MC-ICP-MS, utilizing gravimetric isotope mixtures of two near-pure enriched indium isotopes. Consistent with previous findings, we observe that the traditional one-mixture-at-a-time calibration approach can introduce a strong dependence of the resulting isotope ratio correction factors on the composition of the mixtures. Our analysis suggests that this is due to biases inherent in measuring the isotopic composition of pure isotopic materials. To address this issue, we propose an improved calibration strategy that omits the use of isotope ratios measured in the two near-pure indium isotopes, at the expense of measuring additional isotope mixtures. The revised calibration approach yields an indium isotope ratio n ( 113 In)/ n ( 115 In) = 0.044 655 ± 0.000 009 (95% confidence level) for the high-purity indium isotopic reference material (NRC HIIN-1). This result is in agreement with our 2010 result (0.044 72 ± 0.000 19, 95% confidence level), obtained using the regression method with NIST SRM978a silver as a calibrator, while showing an improvement in measurement uncertainty by an order of magnitude.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 0.000 |
Machine scores (provisional)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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