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Record W2079801852 · doi:10.1080/01496395.2012.665408

Methanol-Water Extraction of Saponins From Seeds of<i>Saponaria Vaccaria L.</i>— Calibration Equation, Extraction Condition Analysis, and Modeling

2012· article· en· W2079801852 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

VenueSeparation Science and Technology · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNatural product bioactivities and synthesis
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryExtraction (chemistry)MethanolSaponinChromatographyYield (engineering)Mass transferAnalytical Chemistry (journal)Organic chemistryThermodynamics

Abstract

fetched live from OpenAlex

Abstract Bisdesmosides, monodesmosides, and other bisdesmosidic saponins were observed in the particles of Saponaria vaccaria L seeds (15.35% dry basis) with diameter of 0.044 to 1.19 mm and an average thickness of 124 µm as investigated with liquid chromatography-mass spectroscopy at methanol concentration of 30%, 50%, 70%, and 90% (vol., aq.), temperature of 30°C, 45°C, and 60°C, and eight extraction time intervals between 1 and 180 min. The saponins yield increased significantly with temperature (45°C to 60°C) and methanol concentration (50% to 70%) with negligible effect of moisture content. The maximum yield was obtained at 60°C for 70% methanol concentration and 30 min of extraction time. The mass transfer properties of the test material may have potentials for modeling, simulation and optimization of similar products and processes. A diffusional mathematical model simulated extraction kinetics, and estimated partition coefficient, and effective diffusivity of saponins very well. Keywords: bio-kineticskinetics parametersliquid-liquid extractionmodelingSaponins ACKNOWLEDGEMENTS We thank Dr. John Balsevich at Plant Biotechnology Institute, NRC for allowing us to access database and equipment to identify saponins as well as for his technical guidance. The financial support provided by NSERC to conduct this research is highly appreciated. Notes a Quillaic acid, b Gypsogenin, c Trisaccharide, d Disaccharide, e = New Saponin, f Unknown.

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 score0.065
Threshold uncertainty score0.292

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.021
GPT teacher head0.317
Teacher spread0.296 · 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