Grain-scale and outcrop-scale distribution and movement of melt in a crystallising granite
Bibliographic record
Abstract
The distribution of melt has been mapped in a granite pluton deformed whilst it contained melt. At the outcrop scale, leucomonzogranite melt was segregated from hornblende monzogranite when the rigid crystal framework was tectonically compacted. The melt collected in well-defined, structurally controlled sites that formed during dextral, non-coaxial, strike-slip shearing. The segregations are generally isolated, but locally they link to form extensive branched arrays which drained larger volumes of granite in a two-step process. First, melt drained from the compacting matrix through the array and pooled along dilatant foliation planes; later, the melt moved farther away when a single planar melt-transfer channel formed. Thin section maps show that most melt was distributed in the foliation plane and along the lineation in the crystallising matrix. The location of melt at the grain scale is primarily controlled by the feldspar-dominated shape fabric of the crystal framework, and not by tectonic stresses as at the outcrop scale. Tectonic stresses account for the relatively small proportion of melt films located in grain boundaries normal to the lineation. The distribution of melt-bearing grain boundaries outlines larger domains in the thin sections that form a linked three-dimensional network through which melt moved within the crystallising framework.
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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 | 0.000 |
| 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 | 0.000 |
| 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 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".