Facies architecture, paleodischarge, and the variability of confluence scours in Cretaceous Rivers: Ferron Sandstone, Utah and Torrivio Sandstone, New Mexico, USA
Bibliographic record
Abstract
This thesis is focused on the integration of facies architectural analysis with 3D drone imagery, to provide quantitative analysis of ancient North American Cretaceous river systems. Paleo-digital elevation models were used for estimating drainage area, consistent with previous paleogeographic reconstructions. Monte-Carlo simulations, in combination with physics-based, empirically-derived equations, were used to estimate paleodischarge and downstream sediment volumes. This represents novel use of datasets and methods in quantitative estimation of ancient fluvial systems. This quantitative approach has broad implications for source-to-sink scaling relationships, such as predicting ancient drainage areas, that can be important in paleotectonic and paleogeographic reconstructions, as well as prediction of downstream sink volumes, which have economic importance, as these estimations can be used in hydrocarbon exploration in predicting the volumes of both the reservoir as well as the source rocks. These are also useful for characterizing aquifers to assess aquifer volume and flow pathways. This thesis also addresses a number of on-going scientific debates. The lack of braided rivers imaged using 3D seismic data has raised questions about the preservability of braided river deposits. This thesis provides an unequivocal example of a braided fluvial system from the late Cretaceous Torrivio Sandstone in New Mexico, USA. There is also some debate on how to distinguish autogenic scours from allogenic scour surfaces in ancient systems, with implications for identifying regional sequences. This thesis presents examples of a wide variety of autogenic fluvial scour surfaces, including bar-top hollows, bar-scale confluence scours and channel scours, ranging from normal small-scale channel confluence scours to larger tributary junction scours. The criteria described in this thesis enable the distinction of autogenic scours from regional allogenic incised valley surfaces that define sequence boundaries. The thesis also addresses the long debated concept of “Big River” systems. Integration of qualitative facies architecture analysis with quantitative estimates, derived using novel datasets and methods, show that the scale of major depositional elements can be used to estimate the size and scale of formative rivers and help to distinguish deposits of continental-scale river systems from the smaller rivers documented herein.
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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 | 0.000 | 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".