Arsenic mineral and compound data as analyzed by X-ray absorption spectroscopy and X-ray diffraction
Bibliographic record
Abstract
Here, we present As K-edge X-ray absorption spectroscopy (XAS) data for 28 arsenic minerals and compounds. These minerals and compounds were obtained from mineral dealers, museum collections, and chemical suppliers, and were positively identified by synchrotron-based powder X-ray diffraction (XRD). All samples were analyzed for both XRD and XAS at the Canadian Light Source synchrotron (Saskatoon, Canada). The As K-edge XAS data were collected in both transmission and fluorescence modes and cover the extended X-ray absorption fine structure (EXAFS) region. Raw XAS data in both modes are provided to support XAS analysis obtained for geological or environmental research. Furthermore, As K-edge EXAFS spectra, the k3 weighted oscillatory χ(k) functions, and the Fourier-transforms in χ(R) of these K-edge data are processed and presented graphically. Corresponding XRD data was collected to confirm phase identity. Two-dimensional powder diffraction images were collected against an area detector and integrated to produce line scans. The XRD data were either collected at a wavelength of 0.68866 Å (18 keV) or 0.3497 Å (35.45 keV). Raw, tabulated asc files are available, while the patterns are also presented graphically over a 0-40 °2Θ range or 0-26.5 °2Θ range, respectively. The intent of this dataset is to provide reference XAS spectra to researchers conducting environmental or geological research on As.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.001 | 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) | 0.024 | 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".