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Record W60353435 · doi:10.5281/zenodo.1323606

Chemical Composition Of Whiskies Produced In Brazil Compared To International Products

2013· article· en· W60353435 on OpenAlexaboutno aff
Ian C. C. Nóbrega, Sonia P. A. Oliveira, Yulia B. Monakhova, Elainy V. S. Pereira, Adelia C. P. Araújo, Danuza L. Telles, Marileide Silva, Dirk W. Lachenmeier

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFermentation and Sensory Analysis
Canadian institutionsnot available
FundersConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsEthyl carbamateEthyl acetateIsobutanolAcetaldehydeChemistryEthyl lactateMethanolAlcoholEthanolOrganic chemistryFood scienceWineCatalysis

Abstract

fetched live from OpenAlex

Alcoholic strength, volatile acidity, acetaldehyde, methanol, ethyl acetate, higher alcohols (n-propanol, isobutanol, and amyl alcohols), ethyl carbamate, and copper were investigated in 7 brands of blended whiskies produced and bottled in Brazil (BWB) from a wide range of prices, and two brands of blended Scotch whiskies bottled in Brazil (SWB) were investigated for comparison. All brands complied with limits established by Brazilian regulations. The cheapest BWB brand was the most analytically diverse and the only one containing ethyl carbamate above the quantification limit, at 0.09 mg/L. When compared to SWB as well as Scotch, Bourbon, Irish or Canadian whiskies, BWB showed much lower concentrations of methanol, ethyl acetate, n-propanol, and isobutanol. The use of highly rectified ethyl alcohol in the blending process is the most likely explanation for the BWB results.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.240
Teacher spread0.207 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2013
Admission routes1
Has abstractyes

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