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Record W2895603177 · doi:10.3989/gya.0114181

Tendency of lipid radical formation and volatiles in lose or vacuum-packed Brazil nuts stored at room temperature or under refrigeration

2018· article· en· W2895603177 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGrasas y Aceites · 2018
Typearticle
Languageen
FieldNursing
TopicNuts composition and effects
Canadian institutionsAgriculture and Agri-Food Canada
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsChemistryHexanalVacuum packingBrazil nutRefrigerationChemical engineeringFood scienceThermodynamics

Abstract

fetched live from OpenAlex

The Brazil nut is an important product from the Amazonian region and its productive chain is an income source for local communities. The effect of combinations of packaging atmospheres (loose or vacuum-packed) and storage temperatures (4±1 °C or 24±2 °C) on the tendency of lipid radical formation and on volatiles was investigated for the first time in shelled Brazil nut kernels. It was observed that refrigeration, whether combined with lose packing or vacuum packing, was effective to reduce the tendency for lipid radical formation, as detected by spin-trapping electron spin resonance (ESR) spectroscopy, as well as peroxides, conjugated dienes and 3-octen-2-one. However, the combination of refrigeration with vacuum packing, even using low-density polyethylene (LDPE) pouches with a high oxygen transmission rate (OTR), also reduced the formation of hexanal, which is a major off-flavor volatile, and thus should be recommended for the storage of Brazil nut kernels for the studied period.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.163
Threshold uncertainty score0.538

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.015
GPT teacher head0.287
Teacher spread0.272 · 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