Chemical Composition of Carbonate Hardground Cements as Reconstructive Tools for Phanerozoic Pore Fluids
Bibliographic record
Abstract
Abstract In this study, we report the chemical composition of early carbonate cement precipitates in carbonate hardgrounds to understand the geochemical signature of near‐surface carbonate mineral precipitation. As carbonate hardgrounds lithify at or near the sediment‐water interface, they acquire cements that may be minimally evolved from paleoseawater. Using a suite of chemical measurements, we explore the potential of carbonate hardground cements as paleoenvironmental proxies. Trace metal and isotopic ratios, including some rare earth elements, Mg/Ca, manganese, and strontium concentrations, δ 18 O, δ 13 C, and 87 Sr/ 86 Sr, were analyzed in the carbonate cements from 17 Phanerozoic carbonate hardgrounds. The sensitivity of the geochemical signal to alteration depends on the geochemical analysis in question and the environmental water‐rock ratio. Of these samples, only our modern sample has measurements consistent with primary precipitation from seawater; all other samples precipitated from chemically evolved seawater or were influenced by meteoric water, even if only minimally changed. The more recent samples from the Cenozoic had seawater 87 Sr/ 86 Sr. The Mesozoic samples, in contrast, did not preserve seawater 87 Sr/ 86 Sr, even though the Mg/Ca, δ 18 O, and δ 13 C values were consistent with precipitation from seawater. Finally, the Paleozoic samples preserved expected seawater 87 Sr/ 86 Sr, though rare earth element and δ 18 O suggest primary precipitation was from evolved seawater. Additionally, we place our results in the context of open versus closed system precipitation using transects of the Mg/Ca ratios across individual cements. Overall, we stress that one geochemical measurement provides only a partial record of fluid composition, but multiple measurements allow a potential understanding of the seawater geochemical signal.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".