Models of large, hot orogens containing a collage of reworked and accreted terranesThis article is one of a series of papers published in this Special Issue on the theme<i>Lithoprobe — parameters, processes, and the evolution of a continent</i>.
Bibliographic record
Abstract
We describe a classification scheme for orogens using Temperature–Magnitude (T–M) diagrams and use this framework for modelling large, hot orogens that evolve in continents comprising cratonic nuclei bordered by a series of juvenile accreted, reworked, and metamorphosed terranes. Modelling the complete evolution of an orogen is difficult, particularly large orogens with multiple orogenic phases. Early phases during which a continent is assembled produce a tectonic and metamorphic fabric that needs to be taken into account when modelling the main collisional orogeny. This inherited fabric is represented in a simple way in models described here by a series of lower crustal blocks that are arranged to be systematically stronger toward the cratonic continental interiors. We investigate how this fabric influences the development of the model orogen during the main collisional phase using upper-mantle-scale (UMS) and crustal-scale (CS) finite element models. The models exhibit a diachronous three-phase evolution: crustal thickening, thermal incubation, and lower crustal indentation. The UMS and CS models are shown to give comparable results in regard to crustal deformation. The UMS models exhibit additional features including single- and double-slab breakoffs and corresponding episodes of uplift and gravitational spreading within the orogenic crust. Protracted postconvergent gravitational spreading of the hot, decoupled crust is also demonstrated. Lastly, we demonstrate the application of this type of model to natural orogens, the Grenville orogen in western Ontario and the southern Canadian Cordillera, and in terms of the T–M diagram.
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.
How this classification was reachedexpand
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 | 0.002 | 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) | 0.001 | 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 teacher head, 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".