Lower crustal rheological expression in inverted basins
Bibliographic record
Abstract
Abstract Although lithospheric modelling has provided extraordinary insights into the processes that shape the continental crust, considerable uncertainty surrounds the basic rheology that governs behaviour at geological timescales. In part, this is because it has proved difficult to identify the geological observations that might discriminate, or unify, models of lithospheric rheology. In particular, the relative strength of lower crust and upper mantle remains a contentious aspect of continental lithospheric rheology. We show that various models for lower crustal rheology may produce distinct patterns of inversion in extensional sedimentary basins, consistent with some of the observed natural variability of inversion styles. Inversion of basin interiors, as is common in European Mesozoic basins, is favoured by a lithospheric rheology more sensitive to lateral thermal structure than to changes in the depth of the Moho, consistent with there being little strength contrast between the lower crust and upper mantle in these settings. In contrast, inversion of basin margins, particularly involving basinward verging structures, is consistent with a rheological sensitivity to the depth of Moho as would apply for a lower crust much weaker than the upper mantle. We use an example from central Australia to demonstrate this latter response, together with thermochronologic data that suggests that a relatively weak lower crust in this setting may reflect abnormally high geothermal gradients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".