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Record W2112654602 · doi:10.1093/chromsci/42.7.354

Computational Chemical Analysis of the Retention of Acidic Drugs on a Pentyl-Bonded Silica Gel in Reversed-Phase Liquid Chromatography

2004· article· en· W2112654602 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

VenueJournal of Chromatographic Science · 2004
Typearticle
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsHealth Research Foundation
Fundersnot available
KeywordsChemistryChromatographyPhase (matter)Reversed-phase chromatographySilica gelHigh-performance liquid chromatographyAdsorptionRetention timeOrganic chemistry

Abstract

fetched live from OpenAlex

A fast method to obtain a quantitative structure-retention relationship is required in chromatography for the rapid optimization of chromatographic separation conditions. Chromatographic data of acidic drugs are analyzed by a computational chemical method to simulate chromatographic simulation. The direct interaction between a model phase and a drug is calculated as an energy value using the molecular mechanics calculation of CAChe. Computational chemistry using a model adsorbent is a new method for quantitative analysis of retention in reversed-phase liquid chromatography. The correlation coefficient is 0.878 (n = 19) between the retention factors of acidic drugs and interaction energy values of the final structure (DeltaFS) between an acidic drug and model pentyl-bonded phase.

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)0.001
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 score0.009
Threshold uncertainty score0.834

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.011
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.269
Teacher spread0.259 · 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