Valorization of Carapa guianensis Aubl. seeds treated by compressed n-propane
Bibliographic record
Abstract
This study evaluated the oil content obtained from andiroba seeds by pressurized n-propane at different conditions of temperature (25, 35, and 45 °C) and pressure (40, 60, and 80 bar), and conventional extraction technique using n-hexane as the solvent. Kinetic extraction curves were fitted using Sovová's mathematical model. The chemical characterization of the oil was reported as well as the protein content in the extraction by-product. Pressurized extractions conducted at 25 °C provided the highest oil recovery (~45 wt%) from the seeds. The increase in pressure at 25 ºC favored obtaining oil with higher Stigmasterol contents, however, the Squalene content was higher in the oil obtained at 40 bar. The oils with the highest concentration phenolic compounds and antioxidant activity were obtained at 80 bar. Extraction with n-propane provided oils with higher levels of phenolic compounds, however, with antioxidant activity similar to conventional extraction. For all evaluated extractions, the product showed a predominance of oleic and palmitic acids, with similar values of oxidative stability. The extraction of the by-product with the highest soluble protein content was obtained under mild processing conditions (25 °C and 40 bar) with n-propane.
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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 | 0.000 | 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".