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Record W596644842

Evolution of Flexible Pavement Recycling in Ontario - An Agency's Perspective

2006· article· en· W596644842 on OpenAlexaboutno aff
T Kazmierowski, Shing Tak Chan

Bibliographic record

Venue10TH INTERNATIONAL CONFERENCE ON ASPHALT PAVEMENTS - AUGUST 12 TO 17, 2006, QUEBEC CITY, CANADA · 2006
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsGreenhouse gasAgency (philosophy)Resource (disambiguation)EngineeringChristian ministrySustainabilityRenewable energyLimitingEnvironmental planningTransport engineeringCivil engineeringBusinessEnvironmental scienceComputer science
DOInot available

Abstract

fetched live from OpenAlex

In consideration of present and anticipated future environmental and resource challenges, in-situ flexible pavement recycling provides an important alternative to conventional pavement rehabilitation. The Ministry of Transportation of Ontario (MTO) encourages the use of pavement recycling to provide economical rehabilitation techniques that conserve non-renewable resources including road-building materials and energy, while minimizing greenhouse gas (GHG) emissions, limiting pollution and reducing waste. This paper describes MTO's experience in adopting innovative in-place pavement recycling techniques, focusing on the recent improvements and current practices. Detailed discussion on these technologies and their impact on long-term pavement performance are presented, as well as a historical perspective of the ministry's pavement recycling program achieved over the past 10 years. The paper concludes by discussing how transportation agencies can move towards a sustainable future by incorporating flexible pavement recycling into their capital construction program.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.099
Threshold uncertainty score0.719

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0050.002
Scholarly communication0.0050.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.038
GPT teacher head0.279
Teacher spread0.241 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2006
Admission routes1
Has abstractyes

Explore more

Same venue10TH INTERNATIONAL CONFERENCE ON ASPHALT PAVEMENTS - AUGUST 12 TO 17, 2006, QUEBEC CITY, CANADASame topicAsphalt Pavement Performance EvaluationFrench-language works237,207