Nucleation Delay and the Textural Development during Crystalization of a Hydrous Felsic Melt
Bibliographic record
Abstract
We conducted experiments on hydrous, boron-bearing rhyolitic composition prepared from Lake County Obsidian (LCO).The experiments were conducted at 600 MPa and temperatures of 500-800 ℃.The durations were 9 h to 2 months.The experiments were compared to recently developed nucleation delay study [1].The delay time varied between ~1 month at undercooling of 340 ℃ (500 ℃) and ~12 h at undercooling of 40 ℃ (800 ℃).The textures produced in the experiments were quantified using fractal analysis.In all the experiments, nucleation occurred heterogeneously on the capsule walls.The experimental results at different degrees of undercooling and with different nucleation delays produced different textures.In all experiments, except for the lowest undercooling (ΔT=40 ℃), quartz and alkali feldspar produced different types of intergrowths.In experiments at the highest experimental undercooling (ΔT=340 ℃) quartz and feldspar form vermicular intergrowths where the width of the crystals is 1μm and less.At moderate undercooling the quartz and felspar intergrowths resemble graphic granite seen in granitic pegmatites.At the lowest undercoolings in an experiment conducted for 24 h, only quartz nucleated and formed euhedral crystals.To quantify the textural observations, we conducted the fractal analysis of the backscattered electron images of the experimental run products following the techniques of Baker et al. (2018, [2]).The measurements of the textures produced at 500 ° C plot close together at relatively high fractal dimensions, and low lacunarity (0.2-0.35), when compared to the results of Baker et al. (2018, [2]).The measurements of the textures formed at 700 ° C plot at similar fractal dimensions but show much more variation in lacunarity (0.25-0.6).
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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) | 0.001 | 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".