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Record W4362665120 · doi:10.21203/rs.3.rs-2767196/v1

Computational study and quantum – chemical investigation on bambuterol hydrochloride compound drug: ADFT approach

2023· preprint· en· W4362665120 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldMaterials Science
TopicNonlinear Optical Materials Research
Canadian institutionsnot available
FundersAssiut UniversityCompute Canada
KeywordsNatural bond orbitalBasis setDensity functional theoryComputational chemistryHOMO/LUMOReactivity (psychology)ChemistryHydrogen bondFukui functionMoleculeHalogenOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

Abstract The main objective of the study is to provide deep knowledge of structural and reactivity features of bambuterol hydrochloride (BB.HCl) drug compound. Theoretical calculations are done by the density functional theory (DFT) method with RB3LYP/6–31 + G (d) level and basis set. The computational study by DFT was used to explore HOMO –LUMO energies, global reactivity parameters, NLO using the aforementioned level of theory and basis set. The nature of the hydrogen and halogen bonding interactions was analyzed by NBO, AIM, and RDG analysis. Electron localization function (ELF) analysis provides new insight into the chemical bonding of bambuterol hydrochloride. The pharmaceutical potential of the drug has been considered by molecular docking procedure.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.612
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.004
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.159
GPT teacher head0.407
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it