Identificación de morfologías urbanas en la ciudad de Valencia : una aproximación a un método de delimitación sistemático
Bibliographic record
Abstract
La ciudad de Valencia cuenta, como muchas otras, con divisiones urbanas basadas en distritos, \n barrios y secciones que proviene de una larga tradición histórica. La necesidad de \n conocer con detalle la ciudad llevó, ya a finales del siglo XIX, a que la administración municipal \n estableciera una división en distritos con el fin de obtener datos relacionados con dicha \n delimitación. \n La delimitación de sectores urbanos, atendiendo exclusivamente a parámetros históricos o \n estilísticos, se considera insuficiente cuando se trata de aplicar determinados criterios de \n transformación o establecer normas de actuación para un determinado tejido urbano. De \n este modo, esta investigación trata de dar respuesta a la intuición inicial de que la forma \n urbis, compuesta por la edificación y sus espacios libres asociados, y la manera en la que \n ésta se dispone, termina influyendo en el desarrollo de la ciudad.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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 teacher head, 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".