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Record W2809683134 · doi:10.1515/hf-2018-0031

Determination of pinene content in black liquor by solvent-assisted/pyrogallol-protected headspace gas chromatography (HS-GC)

2018· article· en· W2809683134 on OpenAlexaff
Hui‐Chao Hu, Tong Zeng, Shaokai Zhang, Lihui Chen, Liulian Huang, Yonghao Ni

Bibliographic record

VenueHolzforschung · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant biochemistry and biosynthesis
Canadian institutionsUniversity of New Brunswick
FundersFujian Provincial Department of Science and TechnologyNational Natural Science Foundation of China
KeywordsChemistryPyrogallolChromatographyGas chromatographyPineneExtraction (chemistry)SolventOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract A solvent-assisted and pyrogallol (PG)-protected headspace gas chromatography (HS-GC) method was developed to determine the pinene (α- and β-pinene) content in the kraft pulping black liquor (BL). Ethanol (EtOH) addition eliminated pinene’s micelles in BL by complete dissolution in the EtOH/BL medium. PG was applied to protect pinene from oxidation during the sample storage and measurement. The results showed that, with a 25% (v/v) of EtOH content and a 0.1 g of PG in 5-ml of sample solution, a rapid and stable pinene HS extraction can be obtained in 20 min at 80°C. The method has high precision with relative standard deviations within 4.2%. The sensitivity [limits of quantification (LOQ) are ~140 μg l −1 ] was high, and a good accuracy (recovery=96.0–104%) was typical for the pinene detection. The presented method is simple, rapid, accurate and is suitable for pinene quantification in biorefinery related processes and it leads to the preparation of high-value chemicals.

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 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 score0.007
Threshold uncertainty score0.911

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 science0.0000.000
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 head0.017
GPT teacher head0.238
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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2018
Admission routes1
Has abstractyes

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