Experimental study of the differentiation of gabbro-syenite melt under superliquidus conditions
Bibliographic record
Abstract
ABSTRACT In this work we present the results of experimental interaction of gabbro-syenite melt, corresponding to the average composition of Northern Timan rocks, with a complex hydrogen-containing fluid. The composition of the magmatic fluid was controlled to be close to natural conditions using a special cell in a high gas-pressure vessel. Under superliquidus conditions, the initial melt exsolves into melts of different composition, forming contrast, cryptic, and rhythmic melt stratifications. The experimental results agree with natural data in the petrochemical diagram. It follows from our experimental data that fluid-saturated melts in magmatic chambers are completely differentiated in the liquid state. In the absence of temperature gradients in the magma, gravitational migration of nanoclusters of different densities forms flotation, sedimentation, and rhythmic types of melt stratification. Transmission electron microscopy of the glasses formed in the cell was used to study the formation of nanoclusters in a fluid-saturated superliquidus anorthosite-granite model melt. Clusters with a size of 6 nm consist of a pseudo-crystalline anorthite core surrounded by fluid-saturated shells of the melt. The migration of fluid and fluid-enriched clusters to the upper part of the magmatic chamber results in the activation, from bottom to top, of the processes of crystallization in the magma.
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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 | 0.000 | 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) | 0.002 | 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".