Crustal flow modes in large hot orogens
Bibliographic record
Abstract
Abstract Crustal-scale channel flow numerical models support recent interpretations of Himalayan—Tibetan tectonics proposing that gravitationally driven channel flows of low-viscosity, melt-weakened, middle crust can explain both outward growth of the Tibetan Plateau and ductile extrusion of the Greater Himalayan Sequence. We broaden the numerical model investigation to explore three flow modes: homogeneous channel flow (involving laterally homogeneous crust); heterogeneous channel flow (involving laterally heterogeneous lower crust that is expelled and incorporated into the mid-crustal channel flow); and the hot fold nappes style of flow (in which mid-/lower crust is forcibly expelled outward over a lower crustal indentor to create fold nappes that are inserted into the mid-crust). The three flow modes are members of a continuum in which the homogeneous mode is driven by gravitational forces but requires very weak channel material. The hot fold nappe mode is driven tectonically by, for example, collision with a strong crustal indentor and can occur in crust that is subcritical for homogeneous flows. The heterogeneous mode combines tectonic and gravitationally driven flows. Preliminary results also demonstrate the existence and behaviour of mid-crustal channels during advancing and retreating dynamical mantle lithosphere subduction. An orogen temperature—magnitude (T-M) diagram is proposed and the positions of orogens in T-M space that may exhibit the flow modes are described, together with the characteristic positions of a range of other orogen types.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".