Determination of ternary solutions concentration in liquid–liquid extraction by the use of attenuated total reflectance‐Fourier transform infrared spectroscopy and multivariate data analysis
Bibliographic record
Abstract
Abstract A simple and rapid Fourier transform infrared‐attenuated total reflectance (FTIR‐ATR) spectroscopic chemometric method was developed to determine the concentration of solute and solvent in the raffinate layer in a liquid–liquid extraction (LLE) process using partial least squares (PLS) regression. Five type I extraction systems were used with different solute–solvent affinity. The developed model (correlation coefficient from 0.91 to 0.99) was validated with known concentration samples, and in all cases the difference was not larger than 0.5%w. The LLE for the five extraction systems was carried out in a three‐stage crosscurrent extraction process, quantifying the solute and solvent with the chemometric model developed. The results were used to calculate the stage and overall stage efficiencies for the five systems. This method showed to be fast and precise for the quantification of ternary systems in LLE.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".