Unraveling stratigraphic complexities of transgressive surfaces with trace fossil omission suites and juxtaposed softground suites
Bibliographic record
Abstract
Recognizing stratigraphically important bounding surfaces relies on assessing the facies that juxtapose these surfaces as well as the trace fossil omission suite associated with the surface. The ability to differentiate between purely transgressive surfaces and those that conceal earlier stratigraphic surfaces that allude to a more complex history of development regarding the identification of allogenic surfaces of sequence stratigraphic significance that might have otherwise been overlooked. This study analyzes four examples of transgressive surfaces of erosion from Cretaceous-aged strata, with three of the examples representing a TSE/SB (amalgamated transgressive surface of erosion with a sequence boundary) that mask earlier base level falls. Consideration of variable omission suites along depositional strike and dip highlights the influence of substrate rheology on the nature of omission suites. In this study we demonstrate marked changes in the omission suite along bounding surfaces along proximal to distal trends that arise due to changes in underlying rheology. Finally, detailed core analysis is shown to be an imperative asset to subsurface investigation to address the limitations of using wireline well data alone in identifying stratigraphically important surfaces for more accurate regional mapping and characterization of transgressive surfaces. This study highlights that many stratigraphically important surfaces such as those that correspond to a TSE/SB may go unnoticed if utilizing wireline data alone. Overall, this study provides a comprehensive approach to further understanding and identifying transgressive surfaces in the rock record, especially those that demarcate a more complex history other than simple transgressive ravinement.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".