Calcium Isotopic Compositions of Sixteen <scp>USGS</scp> Reference Materials
Bibliographic record
Abstract
Calcium isotopic compositions of sixteen Ca‐bearing USGS geological reference materials including igneous and sedimentary rocks are reported. Calcium isotopic compositions were determined in two laboratories ( GPMR , State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan; and CIG , Centre for Isotope Geochemistry, University of California, Berkeley) using the 42 Ca‐ 48 Ca double‐spike technique by thermal ionisation mass spectrometry. As opposed to common cation exchange resin, a micro‐column filled with Ca‐selective resin ( DGA resin) was used in order to achieve high recovery (> 96%) and efficient separation of Ca from the sample matrix. The intermediate measurement precision was evaluated at 0.14‰ (2 s ) for δ 44/40 Ca SRM915a at GPMR , based on replicate measurements of pure Ca reference material NIST SRM 915a, NIST SRM 915b and seawater. Overall, the measurement uncertainties in both laboratories were better than 0.15‰ at the 2 s level. Result validation was carried out for all available data sets. The Ca isotopic compositions of USGS reference materials are not only in agreement between GPMR and CIG , but also in agreement with previously published data within quoted uncertainties. The comprehensive data set reported in this study serves as a reference for both quality assurance and interlaboratory comparison of high precision Ca isotopic study.
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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 | 0.002 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".