Rigorous correlations for predicting the solubility of H<sub>2</sub>S in methylimidazolium‐based ionic liquids
Bibliographic record
Abstract
Abstract Two general and simple models, a group contribution correlation (model I) and an empirical relation (model II), were proposed to predict the solubility of H2S in methylimidazolium based ionic liquids (ILs) over wide range of temperatures (303.15‐363.15 K) and pressures (60.8‐2016.8 kPa). The constants of the suggested functionality relations were found via the Nelder‐Mead simplex algorithm. Both correlations were trained with 407 data points of H2S solubility in 9 methylimidazolium based ILs and tested through 121 H2S solubility data points of 3 different methylimidazolium based ILs to ensure generality. A comprehensive statistical evaluation showed that both suggested correlations are vigorous and have satisfactory error trends. The dataset was subjected to a statistical outlier diagnostic test and the validity of the database was confirmed. In addition, the sensitivity analysis revealed that the experimental data and both models have the same responses toward pressure and temperature, which indicates the reliability of the proposed correlations.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.000 |
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".