Integrated geochemical modeling of magmatic degassing and hydrothermal interaction at Kaway Ijen volcano, Indonesia
Bibliographic record
Abstract
Poster presentation at the International Union of Geodesy and Geophysics (IUGG) conference, Montreal, Canada (July 8-18, 2019).\n\n Monitoring active volcanoes requires an understanding of magmatic degassing in relation to magma depth, temperature, composition, style of degassing (open vs closed) and interactions with hydrothermal systems. This conference presentation combines results of subsurface degassing (interpreted from melt inclusions) with measurements of fumarole gases and acid spring waters from Kawah Ijen volcano, Indonesia. Kawah Ijen is a stratovolcano with a growing rhyolite dome on the shore of a hyperacidic crater lake. The dome is emitting sulfur-rich gases from high temperature fumaroles (350-450°C). Matrix glass and melt inclusion compositions (including H2O, CO2, S, Cl and F) were measured for basaltic, dacitic and rhyolitic magmas. The behavior of the volatile species (Dvap-melt) during ascent, degassing and crystallization were modeled for an open system (including vapor fluxing) assuming Rayleigh fractionation, and for closed system processes assuming batch degassing and crystallization. The variable H2O-CO2 contents of the melt inclusions suggest that open system vapor fluxing (XH2Ovapor = 0.25-0.95 for basalt; 0.9-0.95 for dacite) is the dominant degassing style. The modeled S Dvap-melt values for basalt remain low (2-10) as the melt ascends (P= 400 to 100 MPa), then increase sharply to 200 at pressures.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".