A new Chinese national reference material (GBW04481) for calcite oxygen and carbon isotopic microanalysis
Bibliographic record
Abstract
Carbonate oxygen (O) and carbon (C) isotopes are widely used as proxies for tracing the processes and physicochemical conditions of many geological events and environmental changes in Earth Science. In particular, O and C isotopic variations at micrometer scales revealed by modern microbeam analytical techniques such as SIMS and NanoSIMS are robust archives for reconstructing palaeoenvironment and paleoclimate changes at annual and seasonal resolution or even higher temporal resolution. Widespread application of carbonate O and C isotopic microanalysis in Earth Sciences, however, has been restricted due to limitation of high‐quality carbonate reference materials for O and C isotopic microanalysis. We introduce in this paper a new calcite reference material for calcite O and C isotopic microanalysis. This calcite is collected from a drill‐core of the Oka carbonatite complex (Quebec, Canada). We demonstrated that the Oka calcite is fairly homogeneous in O and C isotopic compositions at micrometer scales based on homogeneity test by hundreds of SIMS O and C isotopic analyses. Precise determinations by using conventional gas‐source IRMS yield the recommended value of δ 18 O VPDB = −23.12 ± 0.15‰ (1SD) and δ 13 C VPDB = −5.23 ± 0.06‰ (1SD) for the Oka calcite, which has been certified as the first class of Chinese national certified reference material (GBW04481) for O and C isotopic microanalysis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.006 |
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 source (direct Gemma or distilled Codex), 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".