Geotechnical Characterization for Territorial Planning of a Special Economic Zone at a University Campus in Ecuador
Bibliographic record
Abstract
Special Economic Zones (SEZs) facilitate heightened free trade logistics, enabling companies to expand their operations and product development within a nation.This study seeks to geomechanically characterise a pilot area within the Special Economic Zone Development Zone (ZEDE) at ESPOL Polytechnic University, Ecuador.The area has been marked by limited information concerning the geotechnical properties of the soil and rock formations.The goal of the study is to inform referential zoning for constructions, thereby fostering sustainable development of businesses and industries in the area.The methodology utilised in this study was threefold: (i) an inquiry into existing data and an on-site inspection, (ii) a geophysical campaign encompassing Vertical Electrical Soundings, seismic refraction, and geotechnical characterisation for result correlation, and (iii) an assessment of slope stability, on-site response spectrums, soil profile classifications, safety factors, and construction risk zoning.The study area, approximately 28 ha, was characterised by soils and rock formations, such as lapilli tuffs and tuffaceous shales, with resistive loads reaching up to 26.10 MPa.These geotechnical attributes permit the construction of structures exceeding four stories.The integration of geological and geotechnical data revealed that 75% of the study area presents low to medium construction risk related to instability, thereby indicating suitable areas for territorial planning.The methodology proposed in this study provides a replicable tool for application across the ZEDE, facilitating the creation of strategies for a land-use plan within an innovative university campus.Future large-scale studies could incorporate hydrogeological analysis, evaluation of environmental impact, and the development of mitigation plans for anthropogenic activities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".