Strontium isotope dating influenced by Rubidium contamination from terrestrial material: A case study from the Cenozoic dolomite in the Xisha Islands, South China Sea
Bibliographic record
Abstract
Abstract Strontium isotopes (87Sr/86Sr) are commonly used to assess the age of Cenozoic dolostones found on many isolated oceanic islands. The possible influence of Rubidium (Rb) content on the 87Sr/86Sr ratios, however, has generally been ignored. This critical issue is assessed by examining the 87Sr/86Sr ratios and elements (Rb, Sr, Al, Ti and K) of seventy‐one samples that came from a ca 339 m thick cored interval of Cenozoic dolomite on the Xisha Islands, South China Sea. For the dolomite from the upper Pliocene Yinggehai Formation (180.5 to 308.5 m; average 23% dolomite) there is a positive correlation between the 87Sr/86Sr ratios and Rb concentrations, whereas for the dolomite from the lower late Miocene Huangliu Formation (308.5 to 519 m; average >98% dolomite) such a correlation is not evident. Combined with high‐temperature experiments, correlation between Al, Ti, K, Rb and 87Sr/86Sr indicates that Rb containing old 87Rb from terrestrial materials modified the 87Sr/86Sr ratios of the Yinggehai dolomite, but not those from the Huangliu dolomite. This is mainly attributed to the different sources of terrestrial dust carried by different East Asian monsoon systems between the late Miocene and Pliocene, and probably also influenced by the dolomitization process to some extent. To test for 87Rb contamination, extrapolation of results from the Yinggehai dolomite and Huangliu dolomite indicate that concentrations of Rb < 1 ppm, Al < 1000 ppm, Ti < 15 ppm and K < 250 ppm in the dolomite indicates that terrestrial inputs are minimal and that the measured 87Sr/86Sr ratios can be used for determining the dolomitization age. Potentially, these concentration thresholds may serve as a screening criterion for assessing the reliability of Sr isotope chronostratigraphy of other island dolostones throughout the world.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".