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Record W3166219958 · doi:10.1139/cjc-2021-0042

Study of nitrazepam interaction with alcohol: an ultrasonic and physiochemical investigation

2021· article· en· W3166219958 on OpenAlexvenueno aff
Chandra Kant Bhardwaj, Suraj Prakash, Anjana Kumari Bhardwaj

Bibliographic record

VenueCanadian Journal of Chemistry · 2021
Typearticle
Languageen
FieldChemical Engineering
TopicThermodynamic properties of mixtures
Canadian institutionsnot available
Fundersnot available
KeywordsNitrazepamChemistryIntermolecular forceAlcoholSolventSolvationRelaxation (psychology)ViscosityUltrasonic sensorMoleculePhysical chemistryOrganic chemistryThermodynamicsDiazepam

Abstract

fetched live from OpenAlex

The intermolecular interaction between the constituent components of liquid mixtures can be revealed by ultrasonic analysis. In the present study, interaction of nitrazepam with methyl alcohol has been studied and presented using ultrasonic tools. The investigation involves calculation of ultrasonic velocity (υ), density (ρ), viscosity (η), and the associated derived parameters. The specific acoustic impedance (Z), isentropic compressibility (β), relaxation time (τ), intermolecular free length (L f ), and solvation number (S n ) are calculated to reveal the interaction information. The solvent–solvent and solute–solvent interaction between nitrazepam and alcohol molecules is considered. To see the impact of nitrazepam with alcohol in an ordinary day to day scenario, the investigation was carried out under normal temperature (303–313 K) and pressure conditions. The results indicate increased molecule association of nitrazepam in the presence of alcohol. This study suggests the presence of a synergistic depressants effect when nitrazepam is used with alcohol.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.353

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.215
Teacher spread0.202 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2021
Admission routes1
Has abstractyes

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