A New Approach To Quantify the Ordering State of Protodolomite Using XRD, TEM, and Z-Contrast Imaging
Bibliographic record
Abstract
Abstract Dolomite, an ordered Ca-Mg-carbonate mineral, is abundant in the sedimentary record but found only rarely found in Holocene and modern marine settings. Instead, protodolomite, a partially ordered Ca-Mg-carbonate with a composition close to ideal dolomite, and disordered dolomite occur in specific modern sedimentary settings. In this study, the protodolomite in a late Holocene stromatolite collected from Manito Lake, Saskatchewan, Canada, was examined using X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and Z-contrast imaging from scanning-transmission electron microscopy (STEM). The protodolomite is characterized by nano-domains exhibiting a weak to moderate degree of Ca-Mg ordering based on attenuated and diffuse “b” reflections in selected-area diffraction patterns. The stromatolite also contains disordered dolomite that lack “b” reflections. Using Z-contrast images and image simulations, a quantitative approach was developed to calculate and constrain the ordering state of protodolomite, a parameter that is generally difficult to determine. With ordering contour lines constructed from this study, the ordering state of a weakly ordered dolomite can be quantified based on its d104 value and composition.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".