Exploration geophysics for intrusion-hosted rare earth metals
Bibliographic record
Abstract
Intrusion-related deposits of rare earth metals are characteristically associated with alkaline and carbonatitic intrusions, pegmatites and intrusive veins. Historically, intrusion-related rare earth metals have been discovered using a variety of exploration techniques and occasionally by chance. Geophysical methods have featured prominently. Here we present examples of geophysical signatures and case histories. Critical to the success of any geophysical method is the presence of a sufficiently large contrast in the rock properties of the investigated geological units. Rock properties of 28 minerals that may contain rare earth elements (REEs) in economic or potentially economic deposits (Castor and Hedrick, 2006) are indicated in the figure to the left. Properties are mainly from the Mineralogical Society of America (2010). Noticeable are the high densities of practically all of the minerals, with a 3 general range of 3.26 - 5.90 g/cm , significantly higher than that of common 3 crustal rocks 2.60 - 3.30 g/cm . Notable also are the facts that many minerals are radioactive, and practically all are non-magnetic. Based on these properties it seems that the gravity and radiometric techniques have the greatest potential for direct detection of REEs, but it must be recognized that such direct detection is very much dependant on the concentration of these minerals and the size of the deposit. It would appear, more commonly, that detection of rare earth metals, like detection of several other commodities, is achieved by first locating a prospective host for the mineralization. In this respect, as will be demonstrated following, the gravity, magnetic and radiometric techniques are all important exploration tools.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.005 | 0.001 |
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; both teacher heads agree on what is shown here.
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".