Deformable Plate Reconstructions: Modelling the Relationship between Hyperextension, Basin Evolution and Flexural Uplift
Bibliographic record
Abstract
Summary Deformable plate reconstructions combined with thermal subsidence and flexural uplift modelling help give us a clearer understanding of the relationship between hyperextension, sedimentary basin evolution, and basin margin uplift. These new methods of evaluating hyperextended and continental margins provide input for environment of deposition interpretations and for basin modelling. We use a palinspastic deformable-margin plate reconstruction modelling method for the Central and North Atlantic, and Circum-Arctic to evaluate some emerging deep-water provinces. These include exciting new areas such as Guyana/Suriname-Mauritania/Senegal conjugate margins in the Central Atlantic, the Porcupine and Orphan Basins in the North Atlantic, and the southwest Barents Shelf and Labrador Sea circum-Arctic basins. Many of these areas share characteristic structural features associated with hyperextension such as high rates of subsidence, uplift of the basin margins, the development of submarine escarpments, perched basins, highly rotated fault blocks and localised shear zones. The structural features that characterize hyperextended margins are not well documented are often overlooked, but when the structural processes are fully understood they can provide us with potential new petroleum plays.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".