Predicting Archaean volcanogenic massive sulphide deposit potential from lithogeochemistry: application to the Abitibi Greenstone Belt
Why this work is in the frame
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Bibliographic record
Abstract
Archaean greenstone belts are prime exploration targets for volcanogenic massive sulphide deposits and the use of lithogeochemistry plays an important role in detecting and mapping hydrothermal alteration zones and in recognizing the massive sulphide potential of volcanic assemblages. This study reviews the state of existing lithogeochemical databases and the use of new geochemical analyses for the identification of alteration associated with massive sulphide deposits. This paper also provides a new methodology for the prediction of missing values in geochemical compositions. Through the application of statistical methods, combined sets of lithogeochemical data can be used to create predictive maps of prospective massive sulphide successions. Predictive maps are created through the use of multivariate statistical methods, lithogeochemical alteration indices and normative minerals from which areas of multi-element enrichment and depletion are defined. These indices, when combined in an exploration programme, are potentially useful for massive sulphide discovery. Additionally, the use of rare earth elements can be used to characterize differences in the various supracrustal assemblages and provide a better regional understanding of potential metal endowment. Supplementary material: Provides details on the datasets selected in this study and is available at http://www.geolsoc.org.uk/SUP18712
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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 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 it