Depositional architecture and processes of sediment gravity flows: a 3D seismic case study from offshore Angola
Bibliographic record
Abstract
Deepwater environments are characterised by the deposits of mass flows (e.g. debrites, slumps, slides), sediment density flows (turbidites), and background hemipelagic and pelagic suspension fallout. ‘Mass transport’ is a general term used for the failure and downslope movement of sediment under the influence of gravity in both subaerial and subaqueous environments, the products of which are called Mass Transport Deposits (MTDs). The aims of this study are: (i) to investigate the temporal and spatial development of sediment gravity flows, particularly the coupling of MTDs, turbidites and hemipelagites (ii) to characterise and interpret the seismic facies present within a well-imaged deep-water succession, offshore Angola, with particular focus on the external morphology and distribution of MTDs and associated sediment gravity flows; (iii) to document the geometry, scale, distribution and kinematic importance of structures within the MTDs and relate these to the emplacement of these deposits, in order to understand the impact of seafloor bathymetry on the distribution of the deep-water deposits; and (iv) to characterise and classify the development of pockmarks that are formed contemporaneously or successive to the emplacement of the MTDs. Key results of this study are that: (1) the grade of the submarine slope is a primary intra-basinal control on the emplacement and depositional patterns of MTDs and associated sediment gravity flows, (2) the emplacement of MTDs in upper slope environments promotes the capturing and trapping of sediments, (3) strain indicators genetically linked to MTDs record kinematic information related to the initiation, translation and ultimate deposition of the MTDs, (4) pockmarks may develop from the dewatering of MTDs due to their rapid transportation and consequent entrapment of fluid, and (5) the distribution of pockmarks in slope sediments may be haphazard, but pockmarks may also form preferentially along fault traces and along the evacuation planes of MTDs.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".