Geodynamic modelling of aspects of the Bowen, Gunnedah, Surat and Eromanga Basins from the perspective of convergent margin processes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Geodynamic modelling of selected aspects of the Bowen, Gunnedah, Surat and Eromanga Basins provides possible explanations of the mechanisms that were operating during their formation. For the Bowen and Gunnedah Basins, a quantitative analysis of the early Late Permian to Middle Triassic foreland loading phase examined the relative roles of static loading vs dynamic loading associated with the convergent plate margin. Subsidence in the initial foreland phase in the early Late Permian is consistent with platform tilting due to corner flow in the mantle associated with west-directed subduction. Later in the Late Permian, platform tilting probably continued to be the dominant cause of subsidence, but increasing amounts of subsidence due to foreland loading occurred as the thrust front in the New England Orogen migrated westward. In the latest Permian and Early Triassic, static flexural loading due to foreland loads is dominant and may be the sole cause for basin subsidence. For the Surat and Eromanga Basins, the tectonic subsidence across an east–west transect is modelled to assess the contribution of dynamically induced platform tilting, due to viscous mantle corner flow, in basin subsidence. The modelling suggests that subsidence was again controlled by dynamic platform tilting, which provides a mechanism for both the near-field and far-field effects. Uplift of the Eastern Highlands in the mid-Cretaceous may also be related to viscous corner flow driven by west-directed subduction beneath eastern Australia, with the uplift being due to rebound of the lithosphere after the cessation of subduction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it