A polemic on the use of reversed-phase liquid chromatography to determine descriptors for the solvation parameter model
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Bibliographic record
Abstract
Revised descriptors for 74 varied compounds recommended for the characterization of reversed-phase silica columns using the solvation parameter model are assigned by the Solver method from experimental retention factors for calibrated gas-liquid and reversed-phase liquid chromatographic (RPLC) and biphasic liquid-liquid partition systems. These descriptors are taken as the best estimate of the true descriptor values and used to evaluate several RPLC systems as a single-technique approach for descriptor assignments. Various combinations of isocratic single column and multiple mobile phase compositions, multiple columns with a single mobile phase composition, and multiple columns and multiple mobile phase compositions are evaluated. A multicolumn (Discovery HS C18 and HS F5, Fluophase-RP, and XBridge Shield RP18, Phenyl, and C18) with acetonitrile- and methanol-water mobile phases provided the best results with an absolute average deviation (AAD) of 0.043 for the electron lone pair interaction descriptor E, 0.047 for the dipole-type interaction descriptor S, 0.020 for the hydrogen-bond acid descriptor A, and 0.010 for the hydrogen-bond base descriptor B° for 46 varied compounds. These values compare favorably with the larger all columns and mobile phase composition RPLC dataset with the best estimate of the true descriptors, or all data set, with AAD = 0.026 for E, 0.044 for S, 0.027 for A, and 0.011 for B° for 74 varied compounds. The preferred RPLC systems for descriptor assignments contain columns identified as belonging to different selectivity groups that maximize the relative magnitude of the dipole-type contribution, s system constant, hydrogen-bond basicity, a system constant, and electron lone pair interactions, e system constant. RPLC systems are well suited to assigning the B° descriptor and, with proper system selection, the A and S descriptors. The E descriptor for compounds unavailable by calculation is more problematic and a few extreme values with an AAD > ± 0.1 were observed and can affect the reliability of the S descriptor assignments. The likelihood of poor descriptor assignments using the Solver method can be identified by evaluating descriptor wells.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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