Non‐classical crystallization of very high magnesium calcite and magnesite in the Coorong Lakes, Australia
Bibliographic record
Abstract
Abstract The Coorong Lakes, South Australia, are one of the models for unravelling the ‘Dolomite Problem’. Critically, today only a few modern environments remain where large quantities of very high magnesium calcite (VHMC; Ca0.5Mg0.5CO3; also described as protodolomite or disordered dolomite) and magnesite (MgCO3) precipitate. Previously conducted laboratory studies demonstrate that carbonate minerals can precipitate via classical and non‐classical crystallization pathways. This study uses the preserved crystal sizes, morphologies and microstructures of Ca–Mg carbonates in the Coorong Lakes (Milne Lake, Pellet Lake and North Stromatolite Lake) to evaluate which crystallization pathway most likely occurred. In the fine‐grained sediments of these lakes, very high magnesium calcite and magnesite occur as aggregate particles of nanocrystals (<100 nm). Rietveld refinements using X‐ray diffraction data give modelled Lvol–IB crystallite size values of <120 nm for all carbonates. Transmission electron microscopy shows that, within VHMC and magnesite particles, nanocrystals have an almost identical orientation of their crystal lattice fringes. This is morphologically similar to Ca–Mg carbonates formed via an amorphous carbonate precursor in non‐classical crystallization laboratory experiments. Precipitation of carbonate minerals via an amorphous‐to‐crystalline pathway requires the water to be supersaturated relative to both crystalline and amorphous phases. In the Coorong Lakes, surface water likely only becomes supersaturated relative to amorphous carbonate phases in the late summer after extensive evaporation. Observations suggest that VHMC and dolomite do not directly precipitate from bulk modern seawater, despite oversaturation relative to the crystalline phases, because seawater is undersaturated with respect to amorphous calcium magnesium carbonate, thus limiting the precipitation through a non‐classical crystallization pathway.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".