Rift processes in the Westralian Superbasin, North West Shelf, Australia: insights from 2D deep reflection seismic interpretation and potential fields modelling
Bibliographic record
Abstract
Acquisition of long-offset (8–10 km), long-record length (12–18 sec), 2D reflection seismic and ship-borne potential fields data (WestraliaSpan by Ion/GXT and New Dawn by PGS) on the North West Shelf of Australia provide the opportunity to study rift processes in the context of modern models for rifted margins (Manatschal, 2004). Basement and Moho surfaces were interpreted on seismic reflection data. Refraction models from Geoscience Australia constrain Moho depth and initial densities for gravity modelling through standard velocity-density transformation. 2D joint inversion of seismic reflection and gravity data for Moho depth and basement density constrain depth to basement on seismic. 2D gravity and magnetic intensity forward modelling of key seismic lines constrain basement thickness, type and density. Late Permian and Jurassic–Early Cretaceous rift zones were mapped on seismic reflection data and constrained further by inversion and forward modelling of potential fields data. The Westralian Superbasin formed as a marginal basin in Eastern Gondwana during the Late Permian rifting of the Sibumasu terrane. Crustal necking was localised along mechanically-weak Proterozoic suture belts or Early Paleozoic sedimentary basins (such as Paterson and Canning). Mechanically-strong cratons (such as Pilbara and Kimberley) remained intact, resulting in necking and hyper-extension at their edges. Late Permian hyper-extended areas (such as Exmouth Plateau) behaved as mechanically-strong blocks during the Jurassic to Early Cretaceous continental break-up. Late Permian necking zones were reactivated as failed-rift basins and localised the deposition of the Jurassic oil-prone source rocks that have generated much of the oil discovered on the North West Shelf.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".