Ferric Iron in CaTiO3 Perovskite as an Oxygen Barometer for Kimberlitic Magmas I: Experimental Calibration
Bibliographic record
Abstract
A method to estimate the oxygen fugacity (fO2) during the crystallization of kimberlites is developed using the Fe content of CaTiO3 perovskite (Pv), a common groundmass phase in these rocks. With increasing fO2, more Fe exists in the kimberlitic liquid as Fe3þ, and thus partitions into Pv. Experiments to study the partitioning of Fe between Pv and kimberlite liquid were conducted at 100 kPa on simple and complex anhydrous kimberlite bulk compositions from 1130 to 13008C over a range of fO2 from NNO 5 to NNOþ 4 (where NNO is the nickel^nickel oxide buffer), and atNb and rare earth element (REE) contents in the starting materials of 0^5 wt % and 1500 ppm, respectively.The partitioning of Fe between Pv and kimberlite liquid is influenced mostly by fO2, although the presence of Nb increases the partition of Fe3þ into perovskite at a given T and fO2. Multiple linear regression (MLR) of all the experimental data produces a relationship that describes the variation of Fe andNbinPvwith fO2relative to theNNObuffer: NNO 050ð0021Þ Nb Feð0031Þ þ 0030ð0001Þ=0004ð00002Þ (uncertainties at 2s, and Nb and Fe as cations per three oxygens). Over the range of conditions of our experiments, this relationship shows no temperature (T) dependence, is not affected by the bulk Fe content of the kimberlite starting material and reproduces experimental data to within 1 log fO2 unit. KEY WORDS: kimberlites; oxygen fugacity; perovskite; ferric iron; magma
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".