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Record W2081751808 · doi:10.5539/jsd.v3n1p104

Study on Sustainable Development of Ecotourism in the Northern Piedmont in the Qinling Mountains

2010· article· en· W2081751808 on OpenAlexvenueno aff
Hongmei Dong

Bibliographic record

VenueJournal of Sustainable Development · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsEcotourismTourismStatus quoUnificationSustainable developmentBusinessEnvironmental planningEnvironmental resource managementGeographyEnvironmental protectionEcologyPolitical scienceEconomicsComputer science

Abstract

fetched live from OpenAlex

Tourism resources in the Northern Piedmont in the Qinling Mountains (NPQM) are quite abundant and play an important role in the development of the tourist industry in Shaanxi Province. Based on reviewing the status quo of ecotourism in the NPQM and existing issues, this paper puts forward countermeasures and recommendations for sustainable development of ecotourism in the NPQM. Firstly, a systemic tourism resources investigation should be conducted; secondly, a comprehensive assessment should be made on tourism resources; thirdly, suitable and reasonable principles of protective development should be established, considering to facilitate organic unification of ecological environmental protection and exploitation of tourism. All steps are helpful to realize scientific and sustainable development of ecological economy and tourism zone in the NPQM.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.151
Threshold uncertainty score0.301

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
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 head0.025
GPT teacher head0.322
Teacher spread0.296 · 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 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
Published2010
Admission routes1
Has abstractyes

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