Mineral Chemistry of Melanite from Calcitic Ijolite, the Oka Carbonatite Complex, Canada： Implications for Multi-Pulse Magma Mixing
Bibliographic record
Abstract
Ti-rich garnet is found within calcitic ijolite from the Oka carbonatite complex in Canada, which is characterized by 58%–73% andradite component（2.12 wt.%–4.18 wt.% TiO2） and classified as melanite. The garnet displays complex zoning and contains abundant high field strength elements（HFSEs） and rare earth elements（REEs）. Three groups（Ⅰ, Ⅱ, Ⅲ） have been identified based on their petrographic nature. Compared to groups Ⅱ and Ⅲ, Group Ⅰ garnet cores contain higher TiO2, Mg O, HFSE, and REE and lower SiO2 abundances. The distinct chemical and petrographic signatures of the investigated garnets cannot be attributed to simple closed system crystallization, but they are consistent with the multi-pulse magma mixing. Combined with previously reported U-Pb ages for apatite from the calcitic ijolite, at least three stages of magma evolution and subsequent mixing have been involved in the generation of calcitic ijolite at Oka. The early-formed melt that generated Group I garnet core was later mixed with at least two small-volume, more evolved melts. The intermediate stage melt formed the remaining garnet along with some pyroxene, calcite, nepheline, and apatite at 127±3.6 Ma. The youngest, most evolved melt generated the majority of pyroxene, calcite, nepheline, and apatite within the calcitic ijolite at 115±3.1 Ma.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".