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Record W2187129673

KINETIC ESTIMATION OF GABAPENTIN AND ETORICOXIB IN PHARMACEUTICALS

2011· article· en· W2187129673 on OpenAlexvenueno aff
B.S. Virupaxappa, Kengunte Halappa Shivaprasad

Bibliographic record

VenueInternational Journal of Chemistry · 2011
Typearticle
Languageen
FieldChemistry
TopicAnalytical Methods in Pharmaceuticals
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryPermanganatePotassium permanganateManganateAbsorbanceInorganic chemistryManganeseEtoricoxibNuclear chemistryChromatographyOrganic chemistry
DOInot available

Abstract

fetched live from OpenAlex

Kinetic spectrophotometric methods have been developed and validated for the determination of Analgesics drugs, Gabapentin and Etoricoxib in their pharmaceutical dosage forms. The method is based on the oxidation of Gabapentin and Etoricoxib with alkaline and acidic potassium permanganate respectively. In alkaline medium permanganate (Mn+7) oxidizes Gabapentin and undergoes one electron reduction to give a green colored manganate ions (Mn+6) which has wavelength maximum at 610 nm, and unreacted permanganate at 526 nm. In acidic medium the course of the reaction was conveniently followed by measuring the absorbance of permanganate at 526 nm, as the permanganate undergoes five electrons reduction to give divalent manganese ions (Mn+2) . The calibration graphs for both drugs are linear in the concentration ranges from 17.2 – 86 µg/ml and 35.9 – 35 µg/ml for fixed time and rate constant methods respectively.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.069
GPT teacher head0.394
Teacher spread0.325 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2011
Admission routes1
Has abstractyes

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