MétaCan
Menu
Back to cohort
Record W4390932559 · doi:10.61855/jds0201.04

Blending Canadian Whisky – A Review

2023· review· en· W4390932559 on OpenAlexaboutno aff
Don Livermore

Bibliographic record

Venuenot available
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicFermentation and Sensory Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessGovernment (linguistics)ExciseBottling lineProduction (economics)CommerceEngineeringEconomicsPolitical scienceLaw

Abstract

fetched live from OpenAlex

Political events and technological advances caused the evolution of blending Canadian whisky. The American civil war naturally created an environment for Canadian whisky to become popular. The distilleries in the United States closed their facilities and the Canadian distillers took advantage of the situation. Canadian whisky production became quite profitable. This led to government control over the distilling industry, which required meticulous record keeping by excise officers. Canadian distillers took the opportunity to invest in their own infrastructure by adding tanks, bottling, and ageing facilities. These technological advances naturally lead to blending recipes. Blending was simple at first, combining a prescribed number of barrels as per formula, but through industry regulation and innovation blending evolved to become a very precise science that considers grains, fermentation parameters, distillation method, cask type, age, and strength of alcohol.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.006
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.222
GPT teacher head0.361
Teacher spread0.139 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2023
Admission routes1
Has abstractyes

Explore more

Same topicFermentation and Sensory AnalysisFrench-language works237,207