Bibliographic record
Abstract
This study presents a numerical method to estimate the mole fractions of sulfate species in magmatic rocks using sulfur isotopes, which can be illustrated in a δ-δ diagram. The mole sulfate ratio in an igneous rock sample can be calculated from the δ34Srock value of the whole-rock sample and the δ34Ssulfide (or δ34Ssulfate) value of a sulfide and (or) a sulfate mineral (species) in the sample on the basis of S-isotope fractionation and mass balance under the conditions of magmatic equilibrium. This method can be used to test if magmatic equilibrium between sulfate and sulfide species in magmatic rocks is retained, and to predict the δ34S value of one of them at a certain temperature if sulfur isotopic equilibrium is maintained. The initial sulfur isotope composition of the system in question may be estimated based on a set of samples from an igneous suite. Mole sulfate ratio in the magmatic rocks is then used to estimate redox conditions under which they are formed. This practice is important in understanding the genesis of mineral deposits associated with magmatic rocks.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".