In Silico Chromatography: Modeling a New Support for Alkyl-Bonded Phases and a Solvent Phase
Bibliographic record
Abstract
Chromatography is a tool to measure molecular interactions, and computational chemistry is a tool to explain molecular interactions. Therefore, reversed-phase liquid chromatography of acidic drugs using a pentyl- and an octyl-bonded silica gels was quantitatively analyzed in silico. A model pentyl- and an octyl-bonded silica gel and a methanol phases were constructed for docking with acidic drugs. Molecular interaction energy values based on van der Waals energy were obtained after docking an acidic drug into the model pentyl- or octyl-phases. Solvent effects, hydrogen bonding, and electrostatic energy values were obtained after docking an acidic drug onto the model methanol phase. Chromatographically measured log k values were correlated with the sum of van der Waals, hydrogen bonding, and electrostatic energy values. The correlation coefficient between the log k values measured using the pentyl-bonded silica gel phase and the molecular interaction energy values was 0.95 (n = 20); that between the log k values measured using the octyl-bonded silica gel and the molecular interaction energy values was 0.95 (n = 20).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".