Effect of alkalinity on sulfur concentration at sulfide saturation in hydrous basaltic andesite to shoshonite melts at 1270 °C and 1 GPa
Bibliographic record
Abstract
We have measured the effect of alkalis on S concentration at sulfide saturation (SCSS) in an underexplored compositional space of natural hydrous arc melts (basaltic andesite to shoshonite) at 1270 °C and 1 GPa. At an oxygen fugacity approximately 2.5 log units below the fayalite-magnetite-quartz (FMQ) buffer, SCSS increases with Na2O (562 ppm S/wt% Na2O), K2O (98 ppm S/wt% K2O), and total alkalis (88 ppm S/wt% Na2O+K2O) over the compositional range we have studied (1.6–3.1 wt% Na2O; 0–6.5 wt% K2O; 1.9–6.3 wt% FeOtot). Experiments with ~1.3 wt% H2O show approximately half the increase in SCSS with alkalinity compared to those with ~3.0 wt% H2O. Our results show a possible limit to the increase in SCSS solely by increasing alkali concentration at ~7.5 wt% total alkali concentration. Using our results and published data, we retrained earlier SCSS models to provide a better fit to test data. We also developed a new empirical model using theoretical optical basicity as a compositional parameter that predicts SCSS in the overall data set with slightly better accuracy compared to previous models:
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".