Impact of melt segregation on tonalite-trondhjemite-granodiorite (TTG) petrogenesis
Bibliographic record
Abstract
Abstract “In searching for the origin of granites, it is tempting to view them as purely chemical systems” (Pitcher 1979, p. 90) Although sophisticated geochemical studies tell us that tonolite-trondhjemite-granodiorite (TTG) plutonic complexes must be formed by partial melting of metabasaltic source material, they cannot tell us the tectonic regime in which this crust was formed, nor how large volumes of TTG magma can be generated. This study suggests that a solution to TTG arc crust formation requires a strongly interdisciplinary approach, to resolve the tectonic setting (slab melt verses mafic lowermost crust sources), the time and length scales for melting and extraction, and the role of melt segregation mechanisms in the formation of both Archean TTGs and more recent adakite-like magmas. The aim of this paper is to present an experimental approach which, when coupled with numerical models, allows some of these issues to be addressed. The experiments are designed to reproduce the local changes in bulk composition that are predicted to occur in response to buoyancy-driven melt segregation along grain edges and associated compaction of the solid residue. The preliminary study presented here documents the changes we observe in the melt composition and melt and solid phase modes between earlier direct partial melting and the new segregation equilibration experiments on metabasalt bulk compositions. The results suggest that if dynamic melt segregation and equilibrium processes are active, they may modify the normally robust geochemical indicators, such as Mg-numbers, which are typically used to develop models of TTG petrogenesis.
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 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 | 0.000 | 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".