QSAR Studies of HEPT Derivatives Using Support Vector Machines
Bibliographic record
Abstract
Abstract Human Immunodeficiency Virus type 1 reverse transcriptase is an important target for chemotherapeutic agents against the AIDS disease. 1‐[2‐Hydroxyethoxy‐methyl]‐6‐(phenylthio) thymine] derivatives are potent nonnucleoside reverse transcriptase inhibitors. In the present work, quantitative structure‐activity relationship analysis for a set of 79 HEPT derivatives has been investigated by means of support vector machines. The relationships between structure and activity were examined quantitatively using descriptors encoding the steric, hydrophobic, electronic and structural features of 1‐[2‐hydroxyethoxy‐methyl]‐6‐(phenylthio) thymine] derivatives. The performance and predictive capability of support vector machines method are investigated and compared with other methods such as artificial neural network and multiple linear regression methods. The obtained results indicate that the support vector machines model with the kernel radial basis function can be employed as a forceful tool for quantitative structure‐activity relationship studies. The contribution of each descriptor to the structure‐activity relationships was evaluated.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".