Geochemical composition of chromite from Alexo komatiite in the western Abitibi greenstone belt: Implications for mineral exploration
Bibliographic record
Abstract
This study, which focuses on the composition of chromite from mineralized and unmineralized komatiitic flows and sills from the Alexo Mine area in Dundonald Township, within the western Abitibi greenstone belt, aims to develop new exploration tools for poorly exposed mineralized komatiitic systems. It is possible to clearly identify chromite derived from massive sulphide (having very high Cr# and depleted Ru content) from chromite derived from barren and poorly mineralized samples based on its composition. LA-ICPMS analyses show that chromite from massive sulphide are depleted in Al, Ni, and Mg, and are enriched in Ti, Zn, Mn, Fe and V compared to chromite from barren samples; however, alteration can also modify chromite chemistry. Samples from the Hart deposit are pervasively altered and their chromite compositions are enriched in Fe, Zn, Co, and Mn, and are depleted in Mg. We propose a binary diagram of Ni/Mn versus Ni/Cr ratios which can be used to clearly discriminate between sulphide segregation prior to chromite crystallization and later superimposed alteration. Mass balance calculations show that chromite does fractionate and concentrate Ir-group platinum-group elements (IPGE: Os, Ir, Ru) and Rh but that chromite contribution to the whole-rock IPGE and Rh budget is rather limited, and for mineralized samples, this contribution is even smaller. From these results, it is clear that IPGE+Rh-rich phases (nano- to micro- platinum-group minerals) are needed to account for the IPGE and Rh contents in whole-rock geochemistry.
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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 | 0.001 |
| 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".