Predictive diagenetic clay-mineral distribution in siliciclastic rocks as a tool for identifying sequence boundaries in non-marine successions: the Coalspur Formation, west-central Alberta
Bibliographic record
Abstract
Predictive diagenetic clay-mineral distribution in siliciclastic rocks as a tool for identifying sequence boundaries in non-marine successions: the Coalspur Formation, west-central Alberta The study of upper Cretaceous-lower Tertiary fluvial deposits of the Coalspur Formation in the Foothills region of west-central Alberta reveals that the distribution of early authigenic kaolinite has a well-defined relation to the sequence stratigraphic framework. In this context, it has been observed that the kaolin mineral content increases in sandstones lying below subaerial unconformities, which mark the most significant stratigraphic hiatuses and hence the sequence boundaries in fully fluvial successions. The increased abundance of authigenic kaolinite immediately below sequence boundaries may have been caused by the infiltration of meteoric water during times of subaerial erosion, resulting in the dissolution of unstable minerals (e.g., micas and feldspar) and the formation of kaolinite and secondary porosity. It is therefore suggested that the change in clay mineral assemblages in the stratigraphic section depends in part on the position of the analyzed sandstone samples relative to the sequence boundaries. In a larger context, the method of using authigenic clays to delineate depositional sequences in non-marine successions needs to be evaluated on a case-by-case basis, as the diagnostic early diagenetic minerals underlying the sequence boundary may change as a function of palaeoclimate and also as a function of late diagenetic processes.
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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 | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".