Vertical distribution of elements in regolith over mineral deposits and implications for mapping geochemical weak anomalies in covered areas
Bibliographic record
Abstract
Several case studies are presented to demonstrate that significant migration of elements in regolith over mineral deposits can reach the earth surface through thick layers of superimposed regolith. Data obtained from drill-holes in Mo-W and Mo-Ag mineral deposits in Eastern Inner Mongolia, China using portable X-ray fluorescence (pXRF, Niton XL3t 950) and data from other areas reported in the literature have been modeled using power-law decay functions that describe the regolith decay trends with increasing distance from the underlying altered rocks or saprocks. The results demonstrate that the element concentration in the surface media can be very low due to decay and mask effects, even if a thin layer of overburden exists. In order to characterize the decay behaviour of geochemical concentration of an element in a vertical regolith profile caused by complex mechanisms, a new non-linear differential equation was proposed which assumes the decay rate of concentration is negatively proportional to the concentration itself, with a functional coefficient dependent on vertical distance from the underlying surface of mineralised rocks. Applying Taylor series expansion to the coefficient function, the differential equation can be approximated by four simple dynamic systems, each with explicit solutions including Gaussian functions, exponential functions, power-law functions and exponential functions with inverse distance. These functions can be utilized as either separate or combined models to fit observed data by means of simple linear regression or multivariate regression. The combined mode is useful for evaluating the comprehensive effect of element concentration distribution due to various mechanisms.
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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 | 0.001 |
| 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) | 0.000 | 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 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".