SIMULATION AND ANALYSIS OF NONLINEAR AND SELF-ORGANIZING GROWTH COURSE IN PLAGIOCLASE ZONING THROUGH CELLULAR AUTOMATA
Bibliographic record
Abstract
The purpose of this paper is to discuss the kinetic mechanism of zoning in plagioclase through simulation based on some models.In the period of 1980 s to 1990 s,some Chinese scholars started studying on zoning growth in plagioclase in the perspective of nonlinear science and self-organization,which was initiated by some foreign scholars.Recent years,some scholars consider that the formation of oscillatory zoning occurs only when plagioclase grows up under the condition of later magma intrusions.In this paper,a new research approach of Cellular-Automata analysis tool in the platform of Matlab as the analytic method of nonlinear and self-organization is introduced.Based on Fick′s diffusion law and Cellular-Automata analysis,this study simulates several different magmatic settings to understand zoning growth courses.It is indicated that the formation of oscillatory zoning not only relates to the magmatic setting of later magma intrusion,but also to the resaturation of concentration of CaAl2Si2O8 in the magmatic liquid around the crystalline plagioclase.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".