PREDICTION OF THE LIPOPHILICITY OF EIGHT NEW<i>P-</i>TOLUENESULFONYL-HYDRAZINOTHIAZOLE AND HYDRAZINE-BIS-THIAZOLE DERIVATIVES: A COMPARISON BETWEEN RP-HPTLC AND RP-HPLC
Bibliographic record
Abstract
Using RP-HPTLC and RP-HPLC and a methanol-water mixture as the mobile phase, eight new p-toluenesulfonyl-hydrazinothiazole and hydrazine-bis-thiazole derivatives were studied. The linear correlation between RMw, kW and methanol/water ratios showed high values, for the correlation coefficient R2. The chromatographic hydrophobic index ϕ0 was determined by using intercept and slope, the obtained values ranging between 60 and 98. A good linear correlation was obtained between RMw, log kw, and slope. The log P values were calculated using database (Toronto, Canada). The matrices were formed with RMw, log kw and log P and were subjected to principal component analysis (PCA). The best way to extract information from PCA was graphically, by plotting the obtained matrices. By analyzing the scores, the compounds can be grouped in two: the first group contains three compounds that have a phenyl moiety while the second group comprises other five compounds that contain: methyl, chlor-methyl, acetyl, and ethylic ester.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".