Is the Profile of Fatty Acids, Tocopherols, and Amino Acids Suitable to Differentiate <i>Pinus armandii</i> Suspicious to Be Responsible for the Pine Nut Syndrome from Other <i>Pinus</i> Species?
Bibliographic record
Abstract
Pinus armandii is suspicious to be responsible for the Pine Nut Syndrome, a long lasting bitter and metallic taste after the consumption of pine nuts. To find chemical characteristic features for the differentiation of P. armandii from other Pinus species, 41 seed samples of the genus Pinus from 22 plant species were investigated regarding the content and the composition of fatty acids, tocopherols, and amino acids. The predominant fatty acids in the seed oils were linoleic acid (35.2 – 58.2 g/100 g), oleic acid (14.6 – 48.5 g/100 g), and pinolenic acid (0.2 – 22.4 g/100 g), while the vitamin‐E‐active compounds were dominated by γ‐tocopherol. The amino acid composition was mainly characterized by arginine and glutamic acid with amounts between 0.9 and 8.9 g/100 g as well as 2.1 g/100 g and 8.3 g/100 mg. On the basis of this investigation, a Principle Component Analysis has been used to identify the most important components for the differentiation of P. armandii from other Pinus species. Using the data for glutamic acid, 20:2Δ5,11, 18:3Δ5,9,12, 18:1Δ9, and oil content, a classification of the 41 samples into four different groups by cluster analysis was possible, but the characteristic features of P. armandii were too close to some other members of the genus Pinus, making a clear differentiation of this species difficult. Nevertheless, the investigation showed the similarities of different members of the genus Pinus with regard to fatty acids, vitamin‐E‐active compounds, and amino acids.
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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".