Geochemistry of komatiites in the Eastern Goldfields Superterrane, Western Australia and the Abitibi Greenstone Belt, Canada, and implications for the distribution of associated Ni–Cu–PGE deposits
Bibliographic record
Abstract
The Abitibi Greenstone Belt (AGB) of the Superior Province in Canada, and the extensive greenstone sequences of the Eastern Goldfields Superterrane (EGS) of the east Yilgarn Craton in Western Australia, both contain widespread and well-studied komatiite sequences. Both of these 2˙7 Ga belts contain broadly similar assemblages of volcanic rocks ranging from komatiites to rhyolites, and both contain abundant lode gold mineralisation. Despite this similarity, the two belts have widely differing metal endowments. The EGS is heavily endowed with magmatic Ni–Cu–PGE deposits, but contains only minor volcanogenic massive Cu–Zn sulphide occurrences, whereas the situation in the AGB is the reverse. The komatiite assemblages of the two belts are compared using a locality-weighted analysis of large whole-rock geochemical datasets. The EGS contains a higher relative proportion of highly olivine-rich cumulate rocks relative to the AGB, and shows more extensive evidence for crustal contamination of komatiite magmas. The most highly mineralised region of the AGB, the Shaw and Bartlett Dome area, is the most similar to the EGS in the distribution of komatiite rock types and also the presence of a crustal contamination signature. The bulk of samples in both data sets show no evidence for extensive PGE depletion attributable to sulphide liquid segregation, indicating that the komatiite suites in both belts were undersaturated in sulphide during partial melting, ascent and eruption. The combination of abundant thick cumulate-rich komatiite units and widespread crustal contamination in the EGS can be attributed to a predominance of rapid, high volume eruptions, relative to generally lower eruption rates in the AGB. Differences in lithospheric structure are likely to be the cause.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".