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Record W4396934988 · doi:10.5539/ass.v20n3p54

Traditional Chinese Medicine Culture, Senior Tourism and Elderly Care Industry: Analysis and Discussion on the Integrated Development Under the Background of Big Health

2024· article· en· W4396934988 on OpenAlexvenueno aff
Xia Yingjie, Xia Huayao

Bibliographic record

VenueAsian Social Science · 2024
Typearticle
Languageen
FieldMedicine
TopicMedical Research and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsTourismHealth careBusinessEconomic growthPolitical scienceEconomics

Abstract

fetched live from OpenAlex

In the era of the rise of the concept of Big Health, traditional Chinese medicine culture, senior tourism and elderly care industry show a trend of integration. Combining traditional Chinese medicine health and ecological tourism, a new form of business is taking shape in the elderly care industry, which is the "cross-border" cooperation between traditional Chinese medicine and tourism. This paper sought to analyze the integrated development and potential of traditional Chinese medicine culture, senior tourism and elderly care industry; discuss the realistic dilemma of the integrated development under the background of big health. This Thesis makes an in-depth study on the standardization degree and influence of the integration of traditional Chinese medicine culture and Senior Tourism and Elderly Care Industry through literature review method, and reveals the problems and challenges in the current traditional Chinese medicine culture and Senior Tourism and Elderly Care Industry .The feasibility of traditional Chinese medicine culture and Senior Tourism and Elderly Care Industry was studied in depth by means of various evaluation indicators and sample survey.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.945
Threshold uncertainty score0.458

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
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 head0.055
GPT teacher head0.377
Teacher spread0.322 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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