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Record W2521656420 · doi:10.5539/ass.v12n10p27

Assessment of Tourism Resource Potential at Buriram Province, Thailand

2016· article· en· W2521656420 on OpenAlexvenueno aff
Mayuree Nasa, Fatimah Hassan

Bibliographic record

VenueAsian Social Science · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicCruise Tourism Development and Management
Canadian institutionsnot available
Fundersnot available
KeywordsTourismRecreationResource (disambiguation)GeographyDestinationsTourist destinationsNatural resourceSocioeconomicsEnvironmental protectionEcologySociologyArchaeologyComputer scienceBiology

Abstract

fetched live from OpenAlex

<p>The objective of this paper is to assess the resource potentials for tourism and potential tourist destinations in the province of Buriram, Thailand. Buriram province is located in the North-eastern part of Thailand, about 410 km northeast of Bangkok. Indicators and evaluative standards for resource potential assessment were determined, and altogether the total of 31 sites were assessed by a simple weighted score method, one of the popular methods for evaluating the potential of tourism sites. The total number of indicators used was 45. The results revealed that eight sites were categorized into the natural tourist destination, ten sites were the historical tourist destination, ten sites were the cultural tourist destination, and another three were the sport-recreational tourist destination. These three sport-recreational sites, known as I-Mobile Stadium, Chang International Circuit, and Play La Ploen Boutique Resort and Adventure Camp, were the latest attractions because there were built within the last five years, but consequently have become among the most popular tourist attractions in the area. The site assessment revealed that tourism sites in Buriram province had a potential overall score of 2.23 (moderate level) from the highest score of 3.00. Approximately 39% of the total tourism sites have higher potential. According to the analysis of sites and tourism activities, Buriram is highly suitable for the educational tour in historical and cultural sites, and sports destination.</p><p> </p>

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)0.001
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 score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.010
GPT teacher head0.290
Teacher spread0.280 · 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

Citations10
Published2016
Admission routes1
Has abstractyes

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