δ26Mg-δ13C-δ18O systems as geochemical tracers for dolomite recrystallization: A case study of lower Ordovician dolomite from Tarim Basin
Bibliographic record
Abstract
Widespread replacement dolomite occurs commonly in the geologic record. These dolomites are generally characterized by different crystal sizes and shapes that have at times been interpreted to represent multistage dolomitization; although the variation of dolomite texture could also have resulted from the recrystallization of precursor dolomite. It is important, but challenging, to differentiate these two scenarios to better understand the nature of dolomite and the associated processes of dolomitization. Our study explores this problem by using δ26Mg, δ13C, and δ18O isotopes to characterize the different crystal morphologies exhibited by Ordovician dolomites from the Tarim Basin, China. Although the dolomites show distinct textures and crystal morphologies, there are no discernible trends in their δ26Mg values (from −1.66 to −2.39‰), suggesting that these dolomites were formed by the same dolomitizing fluid. This interpretation is supported by an overlapping range of δ13C values (from 0.46 to −1.89‰). By contrast, the δ18O data demonstrate a wide range of values, from −3.8‰ to −8.8‰, reflecting the different degree of recrystallization with increasing burial temperatures. We suggest that the Mg and C isotopes remained unchanged during recrystallization because Mg and C were rock-buffered, so the recrystallized dolomite inherited Mg and C from the precursor dolomite. Based on these results, it appears that Mg isotopes, together with conventional OC isotopes, can provide a diagenetically robust geochemical tracer for identifying dolomite recrystallization in the geological record.
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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) | 0.001 | 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".