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Record W7106310258 · doi:10.61784/cit3007

OVERVIEW OF TRADITIONAL MEDICINAL ALCOHOLIC BEVERAGE CONSUMPTION IN CHINA

2025· article· W7106310258 on OpenAlexaff

Bibliographic record

VenueChemical Innovation & Technology · 2025
Typearticle
Language
FieldMedicine
TopicAlcohol Consumption and Health Effects
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsChinaConsumption (sociology)Range (aeronautics)

Abstract

fetched live from OpenAlex

This paper examines the traditional context of alcoholic beverages like Baijiu in Chinese medicine, where they have historically functioned as a medium for herbal preparations. Contemporary scientific inquiry has directed attention toward understanding the health implications of alcohol consumption. A proposed "dual-activation" brewing theory, which suggests a potential method for influencing physiological responses to alcohol, is presented as a subject for further scientific validation. The review identifies several methodological considerations for future research, including the need to investigate specific biochemical pathways and to verify preliminary findings through population-level studies. The establishment of standardized analytical frameworks is also noted. The conclusion suggests that further evidence-based methodologies would contribute to a more comprehensive understanding of this traditional practice within its contemporary context.

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)0.000
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 score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.010
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.159
GPT teacher head0.410
Teacher spread0.251 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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