Distribution of Diagenetic Alterations in Fluvial, Deltaic, and Shallow Marine Sandstones Within a Sequence Stratigraphic Framework: Evidence from the Mullaghmore Formation (Carboniferous), NW Ireland
Bibliographic record
Abstract
Abstract The distribution of diagenetic alterations in the fluvial, deltaic and shallow marine, arkosic to subarkosic sandstones (average Q72F26L02) of the Mullaghmore Formation (Carboniferous, NW Ireland) can be predicted within a sequence stratigraphic framework. Eogenetic calcite (δ18OPDB = −13.3‰ to −6.5‰, δ13CPDB = −3.0 to +3.4‰, and 87Sr/86Sr = 0.706721 to 0.709227) and ferron dolomite (FeCO3 = 8-12 mol%; δ18OPDB = −14.2‰ to −7.8‰, δ13CPDB = −1.4‰ to −1.0‰, and 87Sr/86Sr = 0.709051 to 0.709167) occur in bioclast-rich, transgressive lag deposits at parasequence boundaries and transgressive surfaces, and in wave-influenced, deltaic, highstand systems tract (HST) deposits. Mesogenetic illite, chlorite, baroque dolomite (FeCO3 = 16 mol%; δ18OPDB = −14.2‰ to −12.7‰, δ13CPDB = −3.8‰ to −1.0‰), quartz, and calcite (δ18OPDB = −15.7‰ to −12.5‰, δ13CPDB = −5.8‰ to −3.7‰, and 87Sr/86Sr = 0.709016 to 0.709122) were formed mainly in the bioclast-poor deposits, which were not pervasively cemented by carbonates during near-surface eodiagenesis. These deposits include fluvial, incised-valley sandstones of lowstand systems tract (LST), and fluvial-dominated, deltaic sandstones of transgressive systems tract (TST) and HST. Illite is the dominant diagenetic clay mineral in the fluvial, incised-valley sandstones of LST, possibly because of simultaneous albitization of K-feldspars. Conversely, chlorite, dominates in the fluvial-dominated, deltaic sandstones of TST and HST, because of the presence of suitable precursor clays. The integration of diagenesis into sequence stratigraphic framework of clastic sequences should improve the ability to predict the spatial and temporal distribution of diagenetic alterations and related reservoir-quality modifications of sandstone deposits.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".