Potassium and Calcium <i>K</i>‐Edge XANES in Chemical Compounds and Minerals: Implications for Geological Phase Identification
Bibliographic record
Abstract
Potassium (K) and calcium (Ca) K‐edge X‐ray adsorption near‐edge (XANES) spectroscopy were performed on thirty‐three chemical compounds and geological materials, including chemical reagents, organometallic compounds, silicates, carbonates and igneous rock reference materials. The results confirm that the fine structure of the K‐edges for specimens is unique and distinguishable. The results suggest that compositional and local atomic variations strongly regulate spectral characteristics. Acquired XANES spectra with the library of distinctive spectral features of model references approve the fingerprint identification of different phases of K and Ca involved in geological materials. Moreover, this reveals that typical compositional changes in geological samples could strongly affect spectral features. As an example, we quantitatively determined the silicate species of K and Ca in two igneous rock reference materials by linear combination fitting. The dominant hosts and molecular environments of K and Ca can be interpreted based on pre‐edge/post‐edge peak position, intensity, shifts and resonance features, thus improving the understanding of the (bio)geochemical cycling, partitioning and isotopic fractionation of K and Ca. The outcomes serve as a complementary database for a vast number of scientific contexts, including aspects of geological and environment sciences.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".