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Record W659407045

City of Saskatoon's Pavement Management System: Network Level Structural Evaluation (Poster)

2012· article· en· W659407045 on OpenAlexaboutno aff
Curtis Berthelot, Colin Prang, Diana Podborochynski, Roanne Kelln

Bibliographic record

Venue2012 CONFERENCE AND EXHIBITION OF THE TRANSPORTATION ASSOCIATION OF CANADA - TRANSPORTATION: INNOVATIONS AND OPPORTUNITIES · 2012
Typearticle
Languageen
FieldEngineering
TopicInfrastructure Maintenance and Monitoring
Canadian institutionsnot available
Fundersnot available
KeywordsPavement managementAsset managementRoad surfaceTransport engineeringEngineeringCivil engineeringBusiness
DOInot available

Abstract

fetched live from OpenAlex

Pavement management systems (PMS) combine economics and engineering to derive cost-effective solutions for road maintenance and reconstruction. Since 1993, the City of Saskatoon (COS) has employed a PMS that focuses on pavement surface deterioration and ride quality to measure the performance of the city's road network. However, reliably predicting the structural condition of roads based on surface distress information can be very difficult, and structural deterioration is the most operationally intensive and costly road asset failures to rehabilitate. The COS started using heavy weight deflectometer (HWD) measurements to assess the structural condition of the COS road network in 2006. Since it is difficult to distinguish between certain surface distresses from structural distresses, HWD structural information may be beneficial in assessing the condition of the road structure and the corresponding treatment needed. Therefore, using COS network level PMS surface distress data and condition ratings, the effect of using structural data as measured by HWD is examined in this study. For the covering abstract of this conference see ITRD record number 201211RT334E.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.585
Threshold uncertainty score0.983

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.036
GPT teacher head0.220
Teacher spread0.184 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2012
Admission routes1
Has abstractyes

Explore more

Same venue2012 CONFERENCE AND EXHIBITION OF THE TRANSPORTATION ASSOCIATION OF CANADA - TRANSPORTATION: INNOVATIONS AND OPPORTUNITIESSame topicInfrastructure Maintenance and MonitoringFrench-language works237,207