Organización y distribución de los flujos de tráfico en Logroño
Bibliographic record
Abstract
El objetivo principal de este trabajo es analizar el reparto del trcífr`co en el interior de la ciudad (le Logroño, haciendo hincapié en las diférencias entre lasf ranjas horarias (hora punta v hora llana) y los días laborables v festivos. La expansión.física (le /ti ciu- dad a partir de los años setenta del .siglo precedente, la concentración de nrcfs (le la -itad de la población ele la comrmidad N, su condición ele capital son, entre otros,facto- re s, los responsables de las trarrsfórrnaciones que la ciudad ha eipe rintentado. La movi- lidad Iza crecido al ritmo de los cambios sociales i, el reparto de las actividades económicas dentro del casco urbano condiciona losf lujos (le vehículos (le manera clara, tanto a nivel espacial como temporal. = The aim of this paper is to analvse traffic distribution in inner Logroño, focttsing on the différences between rush-hour and off peak hour and weekdavs and holidavs. The phisical expansion of tlre town from de 1970s in the XX` century, the concen-tration of half the region population and the.fact of being the capital cite are, among other ftctors, responsible for the changes that the town has gone through. Mobilitv has visen with the rhythrn of social changes and the distribution qf econo-mic .sectors in the inner part, determine traffic flows in a big way regarding, both, spa-tial and temporal aspects.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".