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Record W2320194520 · doi:10.1139/cjc-2012-0381

Ethyl lactate as an environmentally friendly HPLC mobile-phase modifier in the analysis of acetaminophen, caffeine, and ASA

2013· article· en· W2320194520 on OpenAlexaffvenue
Michael D. Judge, Curtis Aab

Bibliographic record

VenueCanadian Journal of Chemistry · 2013
Typearticle
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsRed River College
Fundersnot available
KeywordsChemistryAcetic acidChromatographyHigh-performance liquid chromatographyCaffeineEnvironmentally friendlyAnalyteEthyl lactateAcetaminophenResolution (logic)Phase (matter)Extraction (chemistry)Organic chemistryCatalysis

Abstract

fetched live from OpenAlex

Ethyl lactate (EL) has been investigated as an environmentally friendly organic modifier for use in HPLC mobile phases. EL shows significant promise in this regard when used under optimal conditions. In conjunction with a standard C18 column at a temperature of 60 °C, a mobile phase composed of 87% water, 10% EL, and 3% acetic acid is capable of baseline resolution of three standard pharmaceutical analytes (acetaminophen, caffeine, and acetylsalicylic acid) in under three minutes. This same mobile phase was found to be capable of extraction of these same analytes from consumer pain relief tablets with essentially 100% efficiency. Using a core-shell C18 column at 40 °C, similar resolution and run times with these analytes are possible using the same mobile phase but with a reduced EL content of only 2.5%.

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 categoriesInsufficient payload (model declined to judge)
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 score0.015
Threshold uncertainty score0.995

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.006
GPT teacher head0.227
Teacher spread0.221 · 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.

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

Citations19
Published2013
Admission routes2
Has abstractyes

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