Triacylglycerols and Phospholipids Composition of Caper Seeds (<i>Capparis spinosa</i>)
Bibliographic record
Abstract
Abstract The goal of this study is to evaluate for the first time the composition of triacylglycerols (TAG) using ESI‐TOF‐MS and phospholipids species using HPLC–ESI‐TOF‐MS of two Capparis spinosa seed oil populations. Results show that LOO, LOP, LLO, OOO, PLL and POO were the major molecular species of triacylglycerol detected in caper seeds; where L represents linoleic acid; O, oleic acid; and P, palmitic acid. The TAG composition was significantly different among the two C. spinosa populations. In Ghar el Melh population, LOO (15.7%) was detected as the dominant TAG molecular species, followed by LOP (13.2%), LLO (12.0%) and OOO (11.4%); while, the dominant fraction was LLO (14.2%) followed by LOO (14.1%), LOP (11.5%) and PLL (10.5%) in Chouigui samples. The major component in the phospholipids fraction was phosphatidylinositol (ca. 54–91%), followed by phosphatidylglycerol, phosphatidylethanolamine and phosphatidic acid. A variety of molecular species within each class were identified. The major component in all phospholipids species contains a C‐18:1 lipid chain. C16:0/C18:2‐PI (ca. 28–31%) was the most abundant PI. PG species were mainly C18:2/C18:1‐PG (25–32%). The major PE was C18:1/C18:1‐PE (44–75%). The major PA species was C18:1/C18:1‐PA (22–24%).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".