Experiments and Models Bearing on the Role of Magma Mixing and Contamination on Chromite Crystallization in Ultramafic Magmas
Bibliographic record
Abstract
Abstract To better understand the origin of stratiform chromitites, we experimentally evaluate the role of bulk compositional shifts arising from mixing or contamination of a mafic magma on both the liquid line of descent and the chromite saturation state. Experiments equilibrated synthetic Cr-bearing komatiite containing 0–50 wt % Cr-free contaminants (granodiorite (GD), Fe-rich shale (Fe-shale), metasediment (MS), natural magnetite (NM)) on Fe-pre-saturated Pt or Ir loops at 1192–1462 °C and 0.1 MPa at the fayalite-magnetite-quartz (FMQ) oxygen buffer. Experimental run products involving mixtures of komatiite with silicate contaminants produced some combination of euhedral olivine, chromite and glass, whereas initial cubes of NM nearly completely dissolved to produce Fe-enriched melt plus Cr-rich magnetite. The addition of contaminants results in the chromium content of the melt at chromite saturation (CCCS) to decrease with increasing melt FeO or decreasing melt SiO2 abundance. Assessment of the temperature dependence reveals that the log of the CCCS decreases linearly with inverse temperature, allowing for the chromite crystallization temperature to be predicted for a given melt Cr concentration. The addition of any of the studied contaminants decreases the modal abundance of olivine.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".