Raman Geobarometry of Quartz Inclusions in Kyanite: Application to Quartz Eclogite from the Gongen Area of the Sanbagawa Belt, Southwest Japan
Bibliographic record
Abstract
ABSTRACT Residual pressure values of quartz inclusions in host kyanite were estimated using Raman spectroscopy and show that the quartz-inclusions-in-kyanite system can be used as a geobarometer for estimating peak metamorphic conditions. Samples of quartz eclogite, a pelitic high-pressure metamorphic rock composed mainly of garnet, omphacite, and quartz, with subordinate kyanite, were obtained for analysis from the Gongen area in the Sanbagawa metamorphic belt, southwest Japan. Residual pressure in the 236 analyzed quartz inclusions within kyanite grains varies from 0.12 to 0.76 GPa. Values are independent of inclusion size and inclusion aspect ratio, and the distribution of residual pressure within the inclusions is homogeneous, except at inclusion-host interfaces. Numerical calculations based on elastic modeling with the equations of state of quartz and kyanite were applied using the highest residual pressure value of 0.76 GPa, with the calculated isopleth being consistent with previous results obtained by conventional thermodynamic geothermobarometry. We conclude that the quartz-inclusions-in-kyanite system can be used as a reliable new Raman geobarometer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.000 | 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".