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Record W4399199974 · doi:10.5650/jos.ess24027

Unsaponifiable Compounds and Phenols Content, Antioxidant and Antitrypsin Activities of <i>Prunus persica</i> Kernel Oil

2024· article· en· W4399199974 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.

Bibliographic record

VenueJournal of Oleo Science · 2024
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsCarleton University
Fundersnot available
KeywordsPrunusFood scienceChemistryPhenolsUnsaponifiableAntioxidantBotanyOrganic chemistryBiology

Abstract

fetched live from OpenAlex

Although peach kernels are rich in oil, there is a lack of information about its chemical and biological properties. Therefore, the purpose of this study was to determine the lipid profile, antioxidant capacity, and trypsin inhibitory propriety of peach oil extracted from two varieties (sweet cap and O'Henry) cultivated in Tunisia. The investigated peach kernel oil contains significant amount of unsaponifiable (2.1±0.5-2.8±0.2% of oil) and phenolic compounds (45.8±0.92-74.6±1.3 mg GAE/g of oil). Its n-alkane profile was characterized by the predominance of tetracosane n-C24 (47.24%) followed by tricosane n-C23 (34.43%). An important total tocopherol content (1192.83±3.1 mg/kg oil) has been found in sweet cap cultivar. Although rich in polyphenols and tocopherols, the tested oil did not display an inhibitory effect on trypsin. However, all peach oil samples showed effective antioxidant capacity and the highest values (86.34±1.3% and 603.50±2.6 μmol TE/g oil for DPPH test and ORAC assay, respectively) were observed for sweet cap oil. Peach oil has an excellent potential for application in the food and pharmaceutical industries as source of naturally-occurring bioactive substances.

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 score0.088
Threshold uncertainty score0.611

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
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 head0.024
GPT teacher head0.268
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