MétaCan
Menu
Back to cohort
Record W4386988293 · doi:10.5604/01.3001.0053.8863

RURAL TOURISM IN THE BIALA POWIAT

2023· article· en· W4386988293 on OpenAlexaboutno aff
Agnieszka Siedlecka, Kamil Treska

Bibliographic record

VenueAnnals of the Polish Association of Agricultural and Agribusiness Economists · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPolish socio-economic development
Canadian institutionsnot available
Fundersnot available
KeywordsTourismQuarter (Canadian coin)GeographyEnvironmental pollutionEnvironmental planningEnvironmental protectionArchaeology

Abstract

fetched live from OpenAlex

The purpose of the article is to present the possibilities of developing rural tourism in Biala County. Biala County is one of the counties in the Lublin Voivodeship where tourism potential may be an important element of its development. It is an area characterised by high environmental and cultural values and a low level of environmental pollution. In order to assess the environmental and cultural potential of the district, a study was conducted using the author’s survey questionnaire. The research was carried out in the second quarter of 2023, among 108 tourists visiting Biala County during the study period or within the last 12 months. The results of the research confirmed the previously stated assumptions that the Biala County area is an important object of interest for tourists. The respondents highly rated the tourist potential of the district and pointed out the significant role of attractive elements of the natural environment. Recent years have also seen an increase in interest in tourism in the area. However, the survey results indicate that steps should be taken to make greater use of the opportunities created by the environment and cultural resources.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.227
Teacher spread0.196 · 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
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

Explore more

Same venueAnnals of the Polish Association of Agricultural and Agribusiness EconomistsSame topicPolish socio-economic developmentFrench-language works237,207