MétaCan
Menu
← Back to cohort

Technical Note: Improved Extraction Method with Hexane for Gas Chromatographic Analysis of Conjugated Linoleic Acids

2006· article· en· W2013515907 on OpenAlexaff
Mun Yhung Jung, G.-B. Kim, Eun-Kyung Jang, Yun-Kyoung Jung, S.Y. Park, B.H. Lee

Bibliographic record

VenueJournal of Dairy Science · 2006
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsAgriculture and Agri-Food CanadaMcGill University
Fundersnot available
KeywordsHexaneChromatographyExtraction (chemistry)ChemistryChloroformMethanolLinoleic acidConjugated linoleic acidGas chromatographyFatty acidOrganic chemistry

Abstract

fetched live from OpenAlex

Extraction properties of different solvents (chloroform/methanol, hexane/isopropanol, and hexane) were studied for the gas chromatographic analysis of conjugated linoleic acids (CLA) from probiotic bacteria grown in de Man, Rogosa, and Sharpe medium. As compared with chloroform/methanol and hexane/isopropanol, hexane showed comparable extraction efficiency for CLA from unspent de Man, Rogosa, and Sharpe medium, but showed minimal extraction of oleic acid originated from the emulsifier in broth. The extraction efficiency of CLA by hexane was influenced by the broth pH, showing the optimal pH of 7.0. Repeated extraction with hexane increased the yield. Extraction with hexane showed excellent recovery of spiked CLA from the spent broth with up to 97.2% (standard deviation of 1.74%). This represents the highest recovery of CLA from culture broth ever reported. The sample size was also successfully reduced to 0.5 mL to analyze CLA from the broth without impairment of analytical data. This smaller sample size in the 1.5-mL microcentrifuge tube using a small bench-top centrifuge reduced analytical time significantly.

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)0.002
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 score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.008

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 head0.020
GPT teacher head0.362
Teacher spread0.342 · 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

Citations15
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Dairy Science→Same topicFatty Acid Research and Health→French-language works237,207→