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Record W4400475644 · doi:10.1590/0001-3765202420230435

Valorization of Carapa guianensis Aubl. seeds treated by compressed n-propane

2024· article· en· W4400475644 on OpenAlexafffund
Djéssica Tatiane Raspe, IZABELLY FULY DA SILVA, Edson Antônio da Silva, Marleny D.A. Saldaña, Camila da Silva, Lúcio Cardozo‐Filho

Bibliographic record

VenueAnais da Academia Brasileira de Ciências · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGrowth and nutrition in plants
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaUniversidade Estadual de Maringá
KeywordsChemistry

Abstract

fetched live from OpenAlex

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.

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 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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.389

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.244
Teacher spread0.223 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations4
Published2024
Admission routes2
Has abstractyes

Explore more

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