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Record W2927670091 · doi:10.1039/c9an00329k

Recent advances in open tubular capillary liquid chromatography

2019· article· en· W2927670091 on OpenAlex
Shing Chung Lam, Estrella Sanz Rodríguez, Paul R. Haddad, Brett Paull

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

VenueThe Analyst · 2019
Typearticle
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsAlberta Science and Technology Leadership Foundation
FundersAustralian Research Council
KeywordsChromatographyCapillary actionChemistryMaterials scienceComposite material

Abstract

fetched live from OpenAlex

This review covers advances and applications of open tubular capillary liquid chromatography (OT-LC) over the period 2007-2018. Under the right conditions OT-LC columns have the potential to offer superior column efficiency, higher overall peak capacity, and higher column permeability compared to packed capillary and monolithic columns. However, such advantages are highly dependent upon column format and dimensions, and to date in liquid chromatography the advantages of open tubular format columns have been most widely discussed and applied in the field of proteomics. In this review we have focused on the wider variety of separation mechanisms and applications which can be achieved following the modification of the inner wall of the capillary with a thin-layer stationary phase. In particular the latest advances in stationary phase development and formation, together with new column formats and dimensions are reviewed. Detection options for OT-LC are also discussed and recent advances in this area highlighted. Finally, this review summarises existing applications of OT-LC and illustrates the future potential for this technique.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.758
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
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.254
Teacher spread0.245 · 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