Variation of plagioclase shape with size in intermediate magmas: a window into incipient plagioclase crystallisation
Bibliographic record
Abstract
Abstract Volcanic rocks commonly display complex textures acquired both in the magma reservoir and during ascent to the surface. While variations in mineral compositions, sizes and number densities are routinely analysed to reconstruct pre-eruptive magmatic histories, crystal shapes are often assumed to be constant, despite experimental evidence for the sensitivity of crystal habit to magmatic conditions. Here, we develop a new program ( ShapeCalc ) to calculate 3D shapes from 2D crystal intersection data and apply it to study variations of crystal shape with size for plagioclase microlites ( l < 100 µm) in intermediate volcanic rocks. The smallest crystals tend to exhibit prismatic 3D shapes, whereas larger crystals ( l > 5–10 µm) show progressively more tabular habits. Crystal growth modelling and experimental constraints indicate that this trend reflects shape evolution during plagioclase growth, with initial growth as prismatic rods and subsequent preferential overgrowth of the intermediate dimension to form tabular shapes. Because overgrowth of very small crystals can strongly affect the external morphology, plagioclase microlite shapes are dependent on the available growth volume per crystal, which decreases during decompression-driven crystallisation as crystal number density increases. Our proposed growth model suggests that the range of crystal shapes developed in a magma is controlled by the temporal evolution of undercooling and total crystal numbers, i.e., distinct cooling/decompression paths. For example, in cases of slow to moderate magma ascent rates and quasi-continuous nucleation, early-formed crystals grow larger and develop tabular shapes, whereas late-stage nucleation produces smaller, prismatic crystals. In contrast, rapid magma ascent may suppress nucleation entirely or, if stalled at shallow depth, may produce a single nucleation burst associated with tabular crystal shapes. Such variation in crystal shapes have diagnostic value and are also an important factor to consider when constructing CSDs and models involving magma rheology.
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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 | 0.000 | 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".