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Record W4383818890 · doi:10.33423/jabe.v25i3.6206

Countermeasures for Developing the Wuyi Rock Tea Industry in Fujian Province in the Post-COVID-19 Era

2023· article· en· W4383818890 on OpenAlexvenueno aff
Yanyu Wang, Wei Shi

Bibliographic record

VenueJournal of Applied Business and Economics · 2023
Typearticle
Languageen
FieldMedicine
TopicTea Polyphenols and Effects
Canadian institutionsnot available
FundersDepartment of Education, Fujian Province
KeywordsPromotion (chess)Closure (psychology)BusinessCoronavirus disease 2019 (COVID-19)OutbreakAgricultural economicsAdvertisingMarketingEconomicsMarket economyPolitical scienceBiologyMedicineLaw

Abstract

fetched live from OpenAlex

As a famous variety of oolong tea in Fujian Province, Wuyi Rock Tea enjoys high brand recognition nationwide for its unique field and complex tea-making process. However, the production and sales of tea commodities were significantly affected by the global outbreak of the COVID-19 pandemic in 2019. The market for Wuyi Rock Tea was hit heavily by consumers’ reduced income and the closure of small and medium-sized enterprises. In response to the problems of Wuyi Rock Tea, it proposes countermeasures from the perspectives of cultivation, tea-making processes, market expansion, and brand promotion.

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 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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.523
Threshold uncertainty score0.253

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.031
GPT teacher head0.274
Teacher spread0.242 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2023
Admission routes1
Has abstractyes

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