Sedimentary process control on carbon isotope composition of sedimentary organic matter in an ancient shallow‐water shelf succession
Bibliographic record
Abstract
Source and delivery mechanisms of organic matter are rarely considered when interpreting changing δ 13 C through sedimentary successions even though isotope excursions are widely used to identify and correlate global perturbations in the carbon cycle. Combining detailed sedimentology and geochemistry we demonstrate how organic carbon abundance and δ 13 C values from sedimentary organic matter from Carboniferous‐aged mudstones are influenced by the proportion of terrestrial versus water column‐derived organic matter. Silt‐bearing clay‐rich shelf mudstones that were deposited by erosive density flows are characterized by 1.8–2.4% organic carbon and high δ 13 C values (averaging −22.9 ± 0.3‰, n = 12). Typically these mudstones contain significant volumes of terrestrial plant‐derived material. In contrast, clay‐rich lenticular mudstones, with a marine macrofauna, are the products of the transport of mud fragments, eroded from pre‐existing water‐rich shelfal muds, when shorelines were distant and biological productivity in the water column was high. Higher organic carbon (2.1–5.2%) and lower δ 13 C values (averaging −24.3 ± 0.5‰, n = 11) characterize these mudstones and are interpreted to reflect a greater contribution by (isotopically more negative) amorphous organic matter derived from marine algae. Differences in δ 13 C between terrestrial and marine organic matter allow the changing proportions from different sources to be tracked through this succession. Combining δ 13 C values with zirconium (measured from whole rock), here used as a proxy for detrital silt input, provides a novel approach to distinguishing mudstone provenance and ultimately using δ 13 C to identify oil‐prone organic matter in potential source rocks. These results have important implications for using bulk organic matter to identify and characterize global C‐isotope excursions.
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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 | 0.001 |
| 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".