The <i>f</i>-Ratio Quantification Method for X-ray Microanalysis Applied to Mg–Al–Zn Alloys
Bibliographic record
Abstract
The f-ratio quantitative X-ray microanalysis method has been recently developed for binary systems based on a scanning electron microscope/energy dispersive spectroscopy (SEM/EDS) system. This method incorporates traditional EDS experiments and Monte Carlo simulations, and calibration factors are calculated with standard samples to evaluate the differences between them. In this work, the f-ratio method was extended to Mg-Al-Zn multi-element systems using a cold field emission SEM and a tungsten emission SEM. Results show that the stability of the beam current does not influence the f-ratio quantification accuracy. Thus, the f-ratio method is suitable for quantitative X-ray mapping with a long-time acquisition or even an unstable beam current. Comparing with other quantitative techniques including the routine standardless analysis and the standard-based k-ratio method, the f-ratio method is a simple and accurate quantification method.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".