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Record W2056915197 · doi:10.1093/chromsci/48.4.289

Rapid Method for Determination of Residual tert-Butanol in Liposomes Using Solid-Phase Microextraction and Gas Chromatography

2010· article· en· W2056915197 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Chromatographic Science · 2010
Typearticle
Languageen
FieldChemistry
TopicAnalytical chemistry methods development
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChromatographyChemistrySolid-phase microextractionAnalyteGas chromatographyChloroformSample preparationButanolDetection limitHexaneResidualExtraction (chemistry)Analytical Chemistry (journal)Gas chromatography–mass spectrometryMass spectrometryEthanol

Abstract

fetched live from OpenAlex

A simple, rapid, and reliable method to detect residual levels of tert-butanol in liposomes using sec-butanol as an internal standard has been developed. Solid-phase microextraction (SPME) followed by gas chromatographic analysis was used to quantify the amount of residual tert-butanol in freeze-dried liposome material. Only 1 min was necessary for reproducible amounts of analyte to absorb onto the SPME fiber, and because this method requires very little sample preparation, a single analysis can be completed in less than 15 min. This method had a linear range of 10-600 microg/mL. Careful control of times of temperature equilibration and exposure to headspace was necessary to ensure reproducible results. This method can easily be applied to other applications in the food and pharmaceutical industries where detection of residual solvents, such as hexane and chloroform, is necessary.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.305
Threshold uncertainty score0.699

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.386
Teacher spread0.359 · 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