Mechanics of fault and expulsion rollover systems developed on passive margins detached on salt: insights from analogue modelling and optical strain monitoring
Bibliographic record
Abstract
Abstract Scaled analogue experiments with layered brittle and ductile materials have been used to simulate the development of listric growth-fault and expulsion rollover systems during gravitational spreading of a passive margin sedimentary wedge detached on salt. The experiments were performed with varying sedimentation patterns and rates to simulate different depositional scenarios. Deformation monitoring with 3D optical image correlation techniques was used to quantify the 3D surface evolution and strain history of model structures. Our results indicate that rollover structure kinematics is strongly coupled to sedimentation patterns and rates. Whereas differential loading governs the margin-scale state of stress and extensional spreading in the experiments, more localized feedback between the dynamic depositional systems, fault-controlled subsidence, and salt mobilization control the strain history of local fault structures. This is reflected in the characteristic succession of extensional structures that evolve from symmetrical grabens through early, mature and late (collapsed) basinward listric growth-fault and rollover systems into landward listric growth-fault and rollover systems. A lack of sedimentation enhances reactive diapir rise and passive diapirism, whereas low sedimentation rates favour development of long-lived basinward listric growth-fault or expulsion rollover systems. Conversely, high sedimentation rates lead to the development of landward listric growth-fault and rollover systems.
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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 | 0.000 | 0.000 |
| 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".