Hyperpycnal flow depositional characteristics and model in an ancient continental basin: a record from the Oligocene Lower Huagang Formation in the Xihu Sag, East China Sea Shelf Basin
Bibliographic record
Abstract
Modern observations have determined the presence of hyperpycnal flows; however, their presence in ancient rocks is scarcely reported in the literature, particularly with respect to continental strata. The present study is the first to use core and thin-section analyses and examination of physical reservoir properties to identify hyperpycnal flow sediment from the lower section of the Oligocene Huagang Formation in the central Xihu Sag, East China Sea Shelf Basin. The multiple fine sandy layers are characterized by lower reverse-graded and upper normal-graded bedding with horizontal bedding, climbing-ripple lamination, wavy bedding, and small foreset laminae. Microerosion surfaces are occasionally present between the reverse-graded and normal-graded bedding, and plant fragments are sometimes visible in the deposits. The same grain size sequence changes are observed in the thin sections. This lithologic combination is considered to be related to hyperpycnal flow sedimentation caused by flood events. The lower reverse-graded and upper normal-graded bedding sequences indicate that the flood energy first increased then decreased and the microerosion surfaces were formed through erosion of lower sediments by the flood. Hyperpycnal flows can directly transport deposits from an estuary to a deep-water basin, which distinguishes them from typical turbidity currents. This study also establishes a sedimentary model of the hyperpycnal flow in lacustrine basin, which can be used as a reference for future hyperpycnal deposit studies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".