A review of microbial‐environmental interactions recorded in Proterozoic carbonate‐hosted chert
Bibliographic record
Abstract
The record of life during the Proterozoic is preserved by several different lithologies, but two in particular are linked both spatially and temporally: chert and carbonate. These lithologies capture a snapshot of dominantly peritidal environments during the Proterozoic. Early diagenetic chert preserves some of the most exceptional Proterozoic biosignatures in the form of microbial body fossils and mat textures. This fossiliferous and kerogenous chert formed in shallow marine environments, where chert nodules, layers, and lenses are often surrounded by and encased within carbonate deposits that themselves often contain kerogen and evidence of former microbial mats. Here, we review the record of biosignatures preserved in peritidal Proterozoic chert and chert-hosting carbonate and discuss this record in the context of experimental and environmental studies that have begun to shed light on the roles that microbes and organic compounds may have played in the formation of these deposits. Insights gained from these studies suggest temporal trends in microbial-environmental interactions and place new constraints on past environmental conditions, such as the concentration of silica in Proterozoic seawater, interactions among organic compounds and cations in seawater, and the influence of microbial physiology and biochemistry on selective preservation by silicification.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".