Classification of paralic channel sub-environments in an ancient system using outcrops: The Cretaceous Gallup system, New Mexico, U.S.A.
Bibliographic record
Abstract
ABSTRACT Distinguishing trunk channels and delta-plain distributary channels in ancient systems can be difficult due to poor or incomplete data (e.g., limited outcrop or sparse well data). Accurate channel classification is required to reconstruct the plan view of channel networks in a paralic fluvio-deltaic system and to quantify source-to-sink systems. Channel formative mechanisms, such as allogenic versus autogenic and avulsion versus bifurcation, also remain equivocal. In this paper we classify channel types and quantify their discharge and dimensions in an ancient paralic depositional system of the Late Cretaceous Gallup system, New Mexico, in a recently developed high-resolution sequence stratigraphic framework. Six key facies associations are identified and integrated into a detailed facies architectural analysis using bedding diagrams from two outcrop cliffs. Backwater lengths are calculated and used for interpretation of channel forming mechanisms and classification of channel types. Two types of channels are interpreted in the study area: meandering fluvial avulsive distributary channels formed in the upstream backwater region in an upper delta plain with a paleodischarge of 280–410 m3/s, and terminal distributary channels in a subaqueous lower delta plain with a paleodischarge of 80–190 m3/s. The results show that upper-delta-plain fluvial distributary channels are formed by erosive avulsion and resemble fluvial meandering rivers characterized by laterally accreting point bars and a wide range of paleocurrents, whereas terminal distributary channels are formed by both avulsion and bifurcation and show more aggradation with lateral confinement and relatively larger width-to-depth ratios of individual channel stories. The quantification of channels and their depositional system provides new data from a well-known ancient system for the global database and comparison with other modern and ancient systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".