Microbialite Textures and Their Geochemical Characteristics of Middle Triassic Dolomites, Sichuan Basin, China
Bibliographic record
Abstract
Microbialite textures, such as microbial mats and biofilms, were observed in the Middle Triassic dolomite in the Sichuan Basin, western China, using core examination, thin section petrography, scanning electron microscopy (SEM), and geochemical analyses. The dolomite texture, consisting of fibrous and spherulitic structures, is similar in morphology and size distribution to those observed in microbial culture experiments. Extracellular polymeric substances (EPS) were identified based on the occurrence of fibers forming a reticular pattern and nanometer-sized spheroids. The rare earth element (REE) and stable isotope (C, O, and Sr) compositions of the Middle Triassic dolomite were measured to determine their geochemical characteristics. Using seawater as a standard, the dolomitic microbialites (MD) exhibited significantly positive La and Eu anomalies and higher REE concentrations and (Nd/Yb)sn values than associated limestones, and these patterns are inferred to be related to initial complexation on organic ligands in the biofilm, as proposed by previous researchers. The ambient temperature during dolomite precipitation was estimated to be within the 23 °C to 50 °C range, as indicated by the δ18O values of the dolomite. This study suggests that various microbial effects can significantly affect diagenetic processes in the Middle Triassic dolomite.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".