Las ciudades inteligentes: meta-sistemas de información, desde una aproximación
Bibliographic record
Abstract
Resumen: Las ciudades inteligentes se caracterizan por optimizar la eficiencia de los medios y servicios a partir del análisis de los datos generados por los sensores tecnológicos, los cuales se encuentran instalados en el espacio urbano, sin embargo, su presencia y propósito puede variar de acuerdo con las circunstancias políticas, tecnológicas y sociales en cada territorio. El objetivo de esta investigación se enfoca en comparar a grandes rasgos los contextos de las ciudades de Toronto, Wichita, Chicago, San Diego, Dehradun y Shanghái; para realizar su abstracción como meta-sistemas de información que se adaptan a sus determinados entornos, a través de la retroalimentación. La metodología se fundamentó en un panorama basado en la consulta de contenidos concernientes a las seis ciudades inteligentes. De acuerdo con los datos, los proyectos enfocados en transformar a las ciudades presentan propósitos encausados a la optimización de recursos económicos, pero sobre todo en el control de las infraestructuras para garantizar la certidumbre a través de la retroalimentación.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".