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Record W3140583945 · doi:10.5267/j.ccl.2020.12.002

Development and validation of a short runtime method for separation of trace amounts of 4-aminophenol, phenol, 3-nitrosalicylic acid and mesalamine by using HPLC system

2021· article· en· W3140583945 on OpenAlexvenueno aff
Seyyed Amir Siadati, Mohammad Amin Rezvanfar, Meghdad Payab, Abolghasem Beheshti

Bibliographic record

VenueCurrent Chemistry Letters · 2021
Typearticle
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryPhenolChromatographyHigh-performance liquid chromatographyPhenol redTrace AmountsOrganic chemistry

Abstract

fetched live from OpenAlex

In a short runtime process (about 6 minutes), with isocratic method without need of reconditioning before the next run, a mixture of some molecules containing 4-aminophenol (4APh), phenol, 3-nitrosalicylic acid (3NSA), and mesalamine (5-aminosalicylic acid) (MLZ), were separated and detected by means of HPLC/UV-Vis system. The resolutions of the separated and sharp peaks referring to the mentioned compounds were at least more than 2, and the tailing factor (TF) was about 1, even in 1 µg/l (ppm) concentration. In order to optimize the method, the effects of the pH, eluent percentage, flow rate, and buffer concentration, and wavelength on the chromatogram were investigated. Also, the results of the validation processes showed that the method trustable to be used in laboratories.

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)0.003
metaresearch head score (Gemma)0.003
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: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
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 head0.023
GPT teacher head0.298
Teacher spread0.275 · 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
GenreMethods

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

Citations6
Published2021
Admission routes1
Has abstractyes

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