Diagnóstico de los factores clave a considerarse por los subcontratistas para cumplir los requerimientos del proyecto: “Construcción de la Fase 1 de la Primera Línea del Metro de Quito”.
Bibliographic record
Abstract
El presente trabajo de tesis para la obtención de la Maestría de Gerencia Empresarial tiene como objetivo diagnosticar los factores clave a considerarse por los subcontratistas para cumplir los requerimientos del proyecto “Construcción de la Fase 1 de la Primera Línea del Metro de Quito”. Su aplicación fortalecerá el valor agregado que la empresa contratista busca en las empresas subcontratistas para desarrollar el proyecto objeto de estudio. El concejo metropolitano de Quito el 20 de abril de 2012 a través de la ordenanza metropolitana No. 237 dispone la creación de la empresa Pública Metropolitana Metro de Quito con el fin de desarrollar, implementar y administrar el subsistema “Metro de Quito” el cual forma parte del Sistema Integrado de Transporte Masivo que permitirá la movilización ágil y oportuna de los quiteños a través de “un eje longitudinal norte-sur desde El Labrador hasta Quitumbe con una distancia de 23 kilómetros, 15 estaciones y será complementado con la red de actuales corredores como son el Trolebús, Ecovía, Metrovía, corredor Sur Oriental, corredor Sur Occidental y buses convencionales” (Empresa Pública Metropolitana Metro de Quito, 2011).
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".