Spatial patterns of geochemical elements measured on rock surfaces by portable X-ray fluorescence: application to hand specimens and rock outcrops
Bibliographic record
Abstract
Spatial distribution of geochemical elements at hand-specimen and outcrop scale provides significant evidence for the processes of formation and alteration of rocks. Portable X-ray fluorescence (pXRF) analyses is a non-destructive and cost-effective methodology to rapidly measure multi-elemental concentrations in-situ , and its application makes the study of the distribution of geochemical elements efficient. In this paper two pXRF instruments, the Tianrui EDX-P730S and the Niton XL3t 950, were employed for measuring geochemical data for two samples of Pb and Zn ore hand specimens and at outcrop scale in an area of skarn formation. The data are processed by GIS and principal component analysis (PCA) for interpreting element associations involved in mineralization processes. The first three principal components obtained by PCA for the data measured on the rock surface of the two hand specimens may represent early stage Zn-dominated mineralization, superimposed Zn and Pb mineralization and late stage Pb-dominated mineralization. These three zones of mineralization can be delineated by the scores of multiple elements on the first three principal components. The first four principal components obtained from the outcrop surface data were found to be related to the marble, diorite, and two stages of skarn-type mineralization (Cu and Zn mineralization and Pb, Zn and Fe mineralization).
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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 | 0.000 | 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) | 0.001 | 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".