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 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".