Use of Chemometrics and Laser-Induced Breakdown Spectroscopy for Quantitative Analysis of Major and Minor Elements in Aluminum Alloys
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Bibliographic record
Abstract
In the present work, quantitative analysis of major and minor elements in aluminum alloys is investigated using chemometrics and laser-induced plasma spectroscopy with a commercially available laser-induced breakdown (LIBS) spectrometer. Multivariate calibrations use the entire signal matrix for all elements in a single multivariate regression model. This enables accounting for the correlation between variables often referred to as matrix effects in conventional univariate modeling. Modeling the entire signal matrix improves robustness over traditional univariate calibration since it can compensate for matrix effects. Several nonlinear data pretreatment methods have been used to correct for nonlinear behaviors of the analytical signals prior to performing the multivariate calibration. The use of multivariate calibration in combination with cubic implicit nonlinear data pretreatment showed the most accurate results. The accuracy reported with the developed multivariate calibration is better than 5% for the major alloying elements. Based on the results obtained, the use of chemometrics and laser-induced plasma spectroscopy have been successfully applied to the quantitative analysis of major and minor alloying elements in aluminum.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.000 | 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 it