Identification of sequence stratigraphy in the Dongying Formation of the Liaoxi low uplift, Bohai Bay Basin, China
Bibliographic record
Abstract
A change in sea level (or lake level) causes a change in accommodation space and sediment compensation, which then controls the formation and evolution of sequences. A multidisciplinary approach based on the integration of clay minerals, major and trace elements, paleosalinity, and three-dimensional seismic data were applied to interpret the stratigraphic sequence of the Dongying Formation in the Liaoxi low uplift. The sequence surface indicates that multistage tectonic action, paleoclimate, paleosalinity, and lake level change jointly controlled the sequence stratigraphy. The illite and illite–smectite mixed layers indicate an arid to semi-arid climate, whereas kaolinite implies humid conditions. Based on this principle, it is clear that the stratigraphic sequence is closely related to paleoclimate. Interpretation of the continental or marine character of the sediments via paleosalinity is increasingly based on the concentration of some trace elements. Hence, the sequence surface can be better evaluated through paleosalinity data. Based on the Sr/Ba and boron content, paleosalinity was evaluated and the sequence boundary was identified. Analysis of the concentration of major and trace elements was used to identify the lithology of the sedimentary region and further discern the stratigraphic sequence. These sequences are composed of lowstand, transgressive, and highstand system tracts. The work herein aimed to understand the reasons for the changes in sequences under the paleoclimate. In addition, major and trace elements, studied together with paleosalinity and clay mineral content, result in the determination of implications for sequence stratigraphy in many other basins. This paper can provide a novel method for comprehensively discerning a sequence surface.
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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 | 0.001 |
| 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 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".