Integrated tectonic basin modelling as an aid to understanding deep-water rifted continental margin structure and location
Bibliographic record
Abstract
An integrated workflow has been devised for the investigation of deep-water rifted continental margins. At a margin this allows us to predict the crustal structure, the distribution of continental-lithosphere thinning and the location of the ocean–continent transition with a new degree of confidence. The workflow combines the analytical techniques of 2D or 3D gravity inversion, 2D or 3D flexural backstripping with reverse thermal subsidence modelling, upper-crustal fault analysis and rifted margin forward modelling. No one technique on its own can provide all of the required answers, nor can it provide answers without some degree of uncertainty. The use of a combination of techniques, however, provides answers to several different problems and, crucially, more confidence in these answers. The workflow provides direct information on the present-day geometry of rifted margins and leads towards a better understanding of the geodynamic evolution of these margins. It also provides information which can inform the exploration process by making predictions about crustal structure at the ocean–continent transition, the location of the continent–ocean boundary, stretching-factor, heat-flow magnitude and history, palaeobathymetric history and subsurface palaeostructure. Application of the workflow is illustrated here with reference to the continental margins of West India, Brazil, West Australia, Norway and Newfoundland–Iberia.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".