ARSENIC INCORPORATION IN COLEMANITE FROM BORATE DEPOSITS: DATA FROM ICP-MS, -SXRF, XAFS AND EPR ANALYSES
Bibliographic record
Abstract
World-class borate deposits in Turkey and California contain elevated concentrations of arsenic, with adverse effects to not only local suppliers of water, but also the commercial exports of boron products. Most previous studies and remediation efforts of arsenic contamination in borate deposits have focused on sulfarsenides. Inductively coupled plasma – mass spectrometry (ICP–MS) analysis and synchrotron micro-X-ray fluorescence (μ-SXRF) mapping reveal that colemanite, a major borate ore mineral, contains up to 125 ppm arsenic. Arsenic K-edge X-ray absorption near-edge structure (XANES) spectra suggest the presence of both As 3+ and As 5+ species in colemanite. The data on K-edge extended X-ray absorption fine structure (EXAFS) show preferential occupancies of As 5+ and As 3+ at the tetrahedral B2 site and the triangular B1 site, respectively. Single-crystal electron paramagnetic resonance (EPR) spectra of gamma-ray-irradiated colemanite measured at 40 K contain an [AsO 3 ] 2− center, providing further support for the presence of As 5+ . Therefore, colemanite is a significant source of arsenic contamination, not only in commercial boron products, but also aquifers associated with borate deposits.
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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".