Composition and Genesis of Temperate, Shallow-Marine Carbonate Muds: Spencer Gulf, South Australia
Bibliographic record
Abstract
Abstract: The origin of carbonate muds (grain sizes < 63 µm) in shallow, nontropical marine environments is poorly documented. Coarse-grained carbonates often characterize coastal temperate seafloors, but many such deposits also have abundant carbonate muds. Spencer Gulf, a large, shallow embayment along the southern Australian margin (< 60 m water depth), contains mixtures of carbonate gravels, sands, and muds, with muds constituting up to 84% volumetrically. Benthic environments include dense seagrass meadows, sand barrens, and rhodolith pavements where bivalves, benthic foraminifera, coralline algae, and bryozoans dominate heterozoan carbonate assemblages. Mud grain morphologies were investigated using scanning electron microscopy, leading to the conclusion that muds are predominantly composed of skeletal fragments (bivalves, benthic foraminifera, ascidians, echinoderms, and coralline algae), interpreted to have formed due to breakdown of rigid material via maceration. X-ray diffraction analysis confirms that these muds contain combinations of intermediate-Mg calcite, low-Mg calcite, and aragonite; with concentrations varying among locations according to skeletal grain types. Spencer Gulf muds differ in mineralogy and composition from those of classic models of tropical and deep-water carbonate mud deposition. Unlike shallow-water, tropical carbonate muds, these temperate muds are not dominated by aragonite and there is no evidence of carbonate precipitation from seawater. Pelagic organisms contribute only trivial amounts to these deposits, in contrast to deep-water muds.
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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 | 0.000 |
| Scholarly communication | 0.000 | 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".