Design of a Prefabricated Concrete Element Using Tailings Material from the Mining Extraction Area of the Portovelo Canton
Bibliographic record
Abstract
The cantons of Zaruma and Portovelo, located in the province of El Oro, are key mining areas in Ecuador, with mining being one of their main economic activities.However, this industry is controversial due to the waste it generates, known as mining tailings.To minimize the environmental impact caused by these byproducts, this research focuses on developing a precast element incorporating tailings material as one of its components.A physical, chemical, and mineralogical characterization of the material was conducted, and three mix designs were formulated, replacing 20%, 30%, and 40% of the fine aggregate with tailings material.The element underwent compression tests to determine its strength, revealing that the mixture containing 30% tailings was the most suitable for use.Based on this dosage, pavers were manufactured for residential streets and parking areas, meeting the required strength standard of 300 kg/cm².Compression tests confirmed a final strength of 313.4 kg/cm².The results indicate that using tailings material as a fine aggregate substitute is a viable alternative for manufacturing concrete elements.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".