Matrix Corrections and Error Analysis in High‐Precision <scp>SIMS</scp><sup>18</sup><scp>O</scp>/<sup>16</sup><scp>O</scp> Measurements of <scp>C</scp>a–<scp>M</scp>g–<scp>F</scp>e Garnet
Why this work is in the frame
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Bibliographic record
Abstract
We report technical and data treatment methods for making accurate, high‐precision measurements of 18 O / 16 O in C a– M g– F e garnet utilising the C ameca IMS 1280 multi‐collector ion microprobe. Matrix effects were similar to those shown by previous work, whereby C a abundance is correlated with instrumental mass fractionation ( IMF ). After correction for this effect, there appeared to be no significant secondary effect associated with M g/ F e 2+ for routine operational conditions. In contrast, investigation of the IMF associated with M n‐ or C r‐rich garnet showed that these substitutions are significant and require a more complex calibration scheme. The C a‐related calibration applied to low‐ C r, low‐ M n garnet was reproducible across different sample mounts and under a range of instrument settings and therefore should be applicable to similar instruments of this type. The repeatability of the measurements was often better than ± 0.2‰ (2 s ), a precision that is similar to the repeatability of bulk techniques. At this precision, the uncertainties due to spot‐to‐spot repeatability were at the same magnitude as those associated with matrix corrections (± 0.1–0.3‰) and the uncertainties in reference materials (± 0.1–0.2‰). Therefore, it is necessary to accurately estimate and propagate uncertainties associated with these parameters – in some cases, uncertainties in reference materials or matrix corrections dominate the uncertainty budget.
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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 | 0.011 | 0.063 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.004 | 0.012 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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