MétaCan
Menu
Back to cohort
Record W285206332

Updates To Software for Estimating Damage due to Superheavy Loads

2013· article· en· W285206332 on OpenAlexaboutno aff
Cesar Tirado

Bibliographic record

VenueDigitalCommons@UTEP (The University of Texas at El Paso) · 2013
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsTruckAxleSoftwareSoftware packageEngineeringTransport engineeringComputer scienceAutomotive engineeringStructural engineering
DOInot available

Abstract

fetched live from OpenAlex

The implementation of North American Free Trade Agreement (NAFTA) opened the borders to international traffic coming from both Canada and Mexico. As a consequence, highway networks will be subjected to trucks with new axle configurations and heavier axle loads, causing concern on the impact of super-heavy vehicles on highway’s infrastructure. This pooled fund study is aimed at providing these tools. A software package with the capacity to calculate pavement distress for flexible pavements under any type of traffic load, and to make a comparison of the level of distress caused by a standard and a non-standard truck has been developed and reported in the previous reports. In this report the refinements to that software including the addition of damage to rigid pavements are described.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.012
GPT teacher head0.213
Teacher spread0.201 · 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; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
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

Citations4
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueDigitalCommons@UTEP (The University of Texas at El Paso)Same topicAsphalt Pavement Performance EvaluationFrench-language works237,207