Interpretation of deformation fabrics of infrastructure zone rocks in the context of channel flow and other tectonic models
Bibliographic record
Abstract
Abstract Infrastructure zones are essentially horizontal to shallowly dipping crustal-scale zones of non-coaxial flow, with two possible interpretations: (a) a crustal-scale shear zone, transporting upper crust over lower crust and/or mantle (transport flow); or (b) a zone of channel flow in which there is a flux of weak crust between relatively strong upper and lower crust and/or mantle, away from the centre of the orogen. Transport flow has a constant shear sense across the zone, whereas in channel flow the sense of shear reverses across the zone. Channel flow may be driven by extrusion (extrusive channel flow), due to the two channel walls approaching one another, or by a pressure gradient along the channel (normal channel flow), with no convergence of the walls necessary. Arguments based on strain compatibility and mechanics suggest that extrusive channel flow is unlikely. Kinematic vorticity numbers have been used to show that infrastructure and other shear zones have undergone flattening strains, but we show that the numbers are incompatible with extrusion. We also show that in addition to the problems inherent in determining kinematic vorticity numbers from fabric, the numbers cannot be related to bulk flow in mechanically heterogeneous zones, because of flow partitioning. Drag folds are a better indication, albeit qualitative, of whether a zone is thinning or not. They also give a conservative estimate of the minimum accumulated shear strains, and may inhibit strain localization. Like snowball garnets, they indicate shear strains that are so large that the pure-shear-thinning component for a steady-shear zone has to be small.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".