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Record W2061581723 · doi:10.1081/drt-120021688

Effect of Drying Methods on Quality of Pistachio Nuts

2003· article· en· W2061581723 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

VenueDrying Technology · 2003
Typearticle
Languageen
FieldNursing
TopicNuts composition and effects
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPeroxide valueFood sciencePalatabilityChemistryPistaciaSweetnessFlavorBinWater contentMathematicsBotanyBiology

Abstract

fetched live from OpenAlex

Abstract The effect of various methods of drying (sun drying, bin drying, vertical continuous drying, vertical cylindrical drying, and funnel cylindrical drying) on moisture content, lipid quality (peroxide value, thiobarbituric acid value, and free fatty acids), sensory attributes (firmness, sweetness, rancidity, roasted flavor, split shell, shell appearance, and overall palatability), and percent split shell of pistachio nuts (Pistacia vera L.) were studied. Sun drying and bin drying resulted in higher split shell percent on pistachio nuts than other drying methods. The different drying methods used in this study did not have any significant influence on the free fatty acids, peroxide value, and thiobarbituric acid of lipids in pistachio nuts. Drying significantly affected shell appearance and split shell. Overall, the bin drying method produced pistachio nuts with the best quality.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.100
Threshold uncertainty score0.639

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.022
GPT teacher head0.404
Teacher spread0.383 · 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