Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose: In the Solok in West Sumatra, This study aims to determine how infrastructure, local knowledge, and digital marketing affect visitors' desire to travel. Theoretical framework: Along with characteristics that are specific to destinations or the tourism industry, it is important to consider elements that have an impact on the businesses and organizations that provide the "products" that tourists use to plan their trips. Or, to put it another way, a tourist destination may draw and satisfy potential tourists if it is competitive, and this competitiveness is impacted both by factors specific to the tourism sector and by more general traits that affect tourism service providers. Design/methodology/approach: The structural equation model, also known as the structural equation (SEM), was used in this work to change the sample size. This indicates that the SEM research that employs the MLE estimate model must use a minimum of 200 samples. Findings: The findings of this study show that visitor interest is significantly influenced by facilities. This shows that offering sufficient facilities in a tourist area can encourage interest in going as people anticipate feeling content or happy after visiting a tourist attraction. Research, Practical & Social implications: The study concludes that to keep tourism objects competitive in the face of competition from other tourist attractions, tourism managers must also pay high importance to developments in the industry. Originality/Value: There is a gap in this study because of the sharp decline in tourist numbers at Solok, West Sumatra. Therefore, the analysis of the aspects that are thought to be significant to impact the choice to visit, namely product, pricing, and digital marketing, is the main emphasis of this research. The uniqueness of this study resides in the item being investigated, which is every existing tourist site, and the research subjects, who are visitors who are visiting these locations while employing the Structural Equation Modeling (SEM) methodology. The research's conclusions are anticipated to advance marketing science, particularly in the tourist industry.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it