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Record W7028335186

Evaluación superficial mediante el método PCI del pavimento flexible, carretera Jaén – San Ignacio, tramo San Lorenzo – Santa Elena, Jaén – 2021

2023· dissertation· es· W7028335186 on OpenAlexaboutno aff

Bibliographic record

Venuerenati · 2023
Typedissertation
Languagees
FieldEngineering
TopicGeotechnical and construction materials studies
Canadian institutionsnot available
Fundersnot available
KeywordsConventional PCIContext (archaeology)Quarter (Canadian coin)Cover (algebra)
DOInot available

Abstract

fetched live from OpenAlex

La presente investigación tuvo como objetivo evaluar el estado superficial mediante la metodología PCI del pavimento flexible de la carretera Jaén - San Ignacio, tramo San Lorenzo – Santa Elena, la metodología de investigación es de tipo cuantitativa y diseño no experimental, la muestra fueron 5km de pavimento, se evaluaron un total de 80 unidades de muestreo, se aplicó el método PCI para determinar la condición superficial del pavimento en estudio. Como resultado se obtuvo un IMD de 1991 vehículos por día, la falla con mayor porcentaje es la conocida como grieta de borde con un 27%, seguida de exudación con un 24% y piel de cocodrilo con un 22%, los daños con nivel de severidad leve representan el 72% y los daños con un nivel de severidad medio representan un 28% y un PCI promedio de 70. Concluyendo que la condición del pavimento flexible es de buena, presenta fallas de severidad media pero en menor cantidad, por lo que se recomienda aplicar otros métodos de evaluación que permitan contrastar o establecer las diferencias con respecto a los resultados obtenidos mediante el método PCI y realizar un mantenimiento rutinario para seguir garantizando la transitabilidad.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.281
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.017
GPT teacher head0.285
Teacher spread0.267 · 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 designBench or experimental
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
Published2023
Admission routes1
Has abstractyes

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