Discrimination of carbonatite and Mississippi Valley-type deposits by partial least squares-discriminant analysis of trace elements and Mg isotope compositions in dolomite
Bibliographic record
Abstract
Carbonatite-related rare earth element (REE), Nb, fluorite, and phosphate deposits and Mississippi Valley-type (MVT) deposits containing Zn, Pb, Ag, and Ge are increasingly important sources of critical metals and minerals. Geochemical classification of carbonatite-related and MVT deposits using chemical compositions of dolomite, the most common gangue mineral in such deposits, is potentially useful for tracing the deposit types and assisting in mineral exploration. Here, we studied variations in elemental contents (42 elements) and δ 26 Mg of dolomite from deposits in the eastern Canadian Cordillera, where carbonatite-related and MVT deposits coexist, to examine its usefulness for geochemical discrimination. Our dataset showed systematic differences between carbonatite and MVT deposits: dolomites from carbonatites were enriched in Fe, Ga, Sr, As, Ba, REEs, and Th and had high δ 26 Mg values, whereas dolomites from MVT deposits were enriched in Zn and Pb, but there were obvious overlaps. We developed an accurate discrimination model by performing a partial least squares regression-discriminant analysis (PLS-DA) that considered all variables simultaneously. The results of PLS-DA showed that two components were sufficient for accurate classification of dolomites from the two deposit types in the study area in comparison with the results of principal component analysis and liner discriminant analysis (PCA-LDA). The δ 26 Mg, Sr/Mg, Zn/Mg, Ba/Mg, and Pb/Mg yielded the highest variable importance on projection (VIP) scores, which is consistent with the geochemical parameters expected from previous studies on carbonatites and MVT deposits. Furthermore, we applied the developed discrimination model to a dataset of dolomite from other deposit (Rock Canyon Creek deposit) and unmineralized dolomite from the host rocks. The dolomites from the Rock Canyon Creek deposit were classified as carbonatite-related deposits, consistent with recent research, although their elemental signatures differ greatly from those of typical carbonatite-related deposits. The unmineralized dolomite plotted separately from the mineralized dolomite samples in the PLS-DA score plots. Our results suggest that PLS-DA score plots of dolomite chemistry are useful for classifying deposit types and probably applicable to exploration for critical metals and minerals associated with carbonatite-related and MVT deposits.
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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 | 0.001 |
| 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) | 0.000 | 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".