Bibliographic record
Abstract
As a member of the benzodiazepines, Clobazam is used in some neurological disorders in CNS including epilepsy, schizophrenia and anxiety. Even though clobazam has been marked as an anticonvulstant since 1984, it was approved for adjunctive therapy in tonicchlonic, complex partial and myoclonic seizures in 2005 (in Canada) [1]. Recently, computational tools have been used to define some important properties such as pharmacokinetics and ADME properties in early stages of drug design [2]. We have tried to produce electronic and structural descriptions of this molecule by using computational methods because the results will be very useful to understand its mechanism of action. Allmolecular orbital calculations have employed Gaussian 09W [3]. Geometry optimization and frequency calculations have been performed with HF and DFT methods and several basis sets, including 6-31g* and 6-311++g**. In addition to estimates based on Koopmans’s theorem, EPT calculations with the P3 and OVGF approximations have been performed to obtain energy gap values and vertical ionization energies. We also have calculated partial atomic charges by the MPA, NPA, CHELPG, and ESP (which are given for only O and Cl atoms at below) methods to show electronic properties.
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 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 | 0.000 | 0.000 |
| 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 teacher head, 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".