Design of Nature Tourism Route in Chimborazo Wildlife Reserve, Ecuador
Bibliographic record
Abstract
The design of new routes is a specific strategy to improve tourism management and to increase the attractiveness of landscape features, promoting activities as a part of sustainable development. This study proposes the design of alternative multi-parameter tourist routes in the Chimborazo Wildlife Reserve based on spatial network analysis implemented in ArcGIS 10.5® software. Tourist interest points were identified and mapped using spatial analysis software, then two routes for bicycles and hiking were defined as being the most efficient, based on the most frequented tourist attractions. The main contribution of this study is the identification of optimal routes for vehicular, bicycling, and hiking traffic through tourist attractions, considering variables such as the time, distance, average circulation speed, road state, and tourist facilities. As a result, two routes were identified. Route one includes 17 tourist attractions, five lodging establishments, four food centers, and one health center. On the other hand, route two includes 11 tourist attractions, two lodging and food establishments, and one health center. The final contribution of this research is to maximize tour satisfaction by presenting new routes of visiting tourist attractions due to the growing demand in the Chimborazo Reserve.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".