High-Speed, Coupled Micro-Beam XRD/XRF/XAFS Mapping at GSECARS
Bibliographic record
Abstract
Abstract The present study describes new instrumentation developments at the GSECARS 13-ID-E hard X-ray microprobe beamline at the Advanced Photon Source that allows for high-speed, coupled micro-beam X-ray diffractions/X-ray fluorescence/X-ray absorption fine structure mapping. These new methodologies provide Earth and environmental scientists with unique coupled tools for evaluating microscale mineralogical and chemical heterogeneities in fine-grained sediments, soils, shales, and mine tailings and associated secondary precipitates. In particular, new technologies and approaches for integrating fast µXRD mapping into routine X-ray microprobe beamline operations are described and several real-world examples are given of how this approach provides unique insights with regards to micrometer-scale heterogeneities in mineralogy and chemistry that are difficult to obtain by other methods. Examples described here include waste streams associated with mine tailings from the McClean Lake mining facility located on the eastern edge of the Athabasca Basin in northern Saskatchewan, Canada, and from mine-drainage waters from the epithermal Au-Ag-Cu deposits of the Lagunas Norte mine in the Peruvian Andes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.008 |
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".