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Record W2982654935 · doi:10.33224/rrch/2019.64.8.10

LC-MS AND ESI-MS QTOF-MS ANALYSIS OF GLYCEROPHOSPHOLIPID AND TRIACYLGLYCEROL SPECIES IN DEVELOPING WILD ARTICHOKE ACHENES

2019· article· en· W2982654935 on OpenAlexafffund
Moufida A. OUESLATI, Justin B. Renaud, Ghayth Rigane, Aynur Gunenc, Ridha Ben Salem, Sadok Boukhchina, Farah HUSSAINIAN, P. Mayer

Bibliographic record

VenueRevue Roumaine de Chimie · 2019
Typearticle
Languageen
FieldMedicine
TopicMedicinal plant effects and applications
Canadian institutionsCarleton UniversityUniversity of Ottawa
FundersUniversity of Ottawa
KeywordsGlycerophospholipidFood sciencePhospholipidAcheneChemistryLinoleic acidBeeswaxPalmitic acidBiologyBotanyFatty acidBiochemistryWax

Abstract

fetched live from OpenAlex

The present study, aimed at presenting comprehensive data on the content of storage and structure lipids of the unexploited wild Onopordum acanthium vegetable oil during achenes development.By using ESI-MS, and Total mass spectral intensities, we identified and determined the proportions of sixteen TAG species.POP, SOP, OLS, GLL, ALO and PLLn were detected for the first time.In addition five phospholipid (PL) classes were discerned.Interestingly, each stage of maturation was characterized by the dominance of one or two phospholipid classes with generally Phosphatidylglycerol as the prominent form in all collection dates (48.2% of total PLs).Various PL molecular species were detected in each class of glycerophospholipid.The main acyl chains were found to be palmitic; linoleic and linolenic acids.Unexpectedly, linolenic acid was found more frequently in phospholipids than in triglycerides.Our findings provide useful information about a new source of vegetable oil that can be exploited in food or non-food applications.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.262
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

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
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
Published2019
Admission routes2
Has abstractyes

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