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Record W4313464250 · doi:10.22270/ajprd.v10i4.1153

Simultaneous Estimation of Metoprolol and Telmisartan in Combined Tablet Dosage Form by Using RP-HPLC and UV Spectrophotometry

2022· article· en· W4313464250 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAsian Journal of Pharmaceutical Research and Development · 2022
Typearticle
Languageen
FieldChemistry
TopicAnalytical Methods in Pharmaceuticals
Canadian institutionsTrinity College
Fundersnot available
KeywordsTelmisartanMetoprololChromatographyDosage formChemistryAbsorbanceSpectrophotometryPhosphate buffered salineHigh-performance liquid chromatographyMethanolMedicineAnesthesia

Abstract

fetched live from OpenAlex

An accurate, precise and reproducible RP-HPLC and UV Spectrophotometric method was developed and validated for the simultaneous estimation of Metoprolol and Telmisartan in tablet dosage form. The chromatographic separation was carried out on X-tera C8 column (100mm*4.6mm*5µ), by using the mobile phase (0.05M Sodium phosphate buffer pH 2.8 and methanol) in the ratio 35:65, at a flow rate 1.2ml/min. The detection was carried out at a wave length of 226nm. The retention time for Metoprolol and Telmisartan was found to be 2.338 and 5.559 respectively. UV method involves solving simultaneous equations based on measurement of absorbance at two wavelengths 223nm and 296nm λmax of Metoprolol and Telmisartan respectively. Beer’s law was obeyed in the concentration range of 1.25-6.25μg/ml and 2-10μg/ml for Metoprolol and Telmisartan respectively. The developed methods were validated according to ICH guidelines.

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)0.003
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.586
Threshold uncertainty score0.885

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.097
GPT teacher head0.449
Teacher spread0.352 · 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