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Record W6986184431

Organización y distribución de los flujos de tráfico en Logroño

2001· article· es· W6986184431 on OpenAlexaboutno aff

Bibliographic record

VenueRIUR (Universidad de La Rioja) · 2001
Typearticle
Languagees
FieldMedicine
TopicFetal and Pediatric Neurological Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsPopulationDistribution (mathematics)Capital (architecture)Inner cityWork (physics)Quarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.163
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.006
GPT teacher head0.252
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2001
Admission routes1
Has abstractyes

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