Linking petrographic and geochemical indicators of melt reactions in pelitic migmatites and leucogranites
Bibliographic record
Abstract
Anatexis in orogenic systems has wide-reaching implications for the structure, mechanical strength, and later exhumation of the middle crust during orogeny. Previous studies of melt reactions in metapelitic rocks have identified three major melt-producing reactions: fluid-present incongruent melting, fluid-absent muscovite dehydration melting, and fluid-absent biotite dehydration melting. Due to the composition of the reacting phases and the formation of peritectic phases, each of these reactions has implications for element mobilisation. Petrographic and geochemical signatures of melt reactant and product minerals allow different reactions to be identified and distinguished. Migmatites and leucogranites occur across the Himalaya in the Greater Himalayan Sequence (GHS). Using samples from the Alaknanda valley, near Badrinath in the Garhwal Himalaya, we identify petrographic and mineral compositional characteristics that suggest a progressive thermal sequence through the fluid-present, muscovite-dehydration, and later biotite-dehydration melting reaction fields, but a differential record. Samples from a single outcrop only preserve records for one reaction type, despite having experienced the same thermal history. Our observational and in-situ chemical data from feldspars, micas, and garnet reveal melt reaction systematics through peritectic crystallisation textures and large-ion lithophile element concentrations. Our results show that the mineral chemistry and petrographic observations are similar between (source) migmatites and (sink) granites, and that together these datasets provide more powerful insight into migmatite and granite melting reaction history than bulk-rock data alone.
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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 | 0.001 |
| 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".