MétaCan
Menu
Back to cohort
Record W645948713

Full depth reclamation on existing asphalt pavements

2008· article· en· W645948713 on OpenAlexaboutno aff
Nicole Nielsen, Ben Hauser, T Preber, Peter E. Sebaaly, Daniel P. Johnston, Dave Huft, Sanchul Bang

Bibliographic record

VenuePROCEEDINGS OF THE 4TH EURASPHALT AND EUROBITUME CONGRESS HELD MAY 2008, COPENHAGEN, DENMARK · 2008
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsLand reclamationAsphaltRutCrackingAsphalt pavementEnvironmental scienceForensic engineeringGeotechnical engineeringCivil engineeringEngineeringMining engineeringGeographyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Full depth reclamation is considered when the pavement is highly deteriorated or has deep cracking due to design deficiencies or has an inadequate base. Other indications that a road could be improved by full depth reclamation are frequent transverse and lateral cracking, reflective cracking, severe rutting, and frost heaves. Full depth reclamation is also a popular technique used when upgrading a low volume road that has a low asphalt surface. Included in this paper are brief summaries on the mechanism of full depth reclamation; economics; field testing methods; and additives with corresponding laboratory testing procedures. This paper also includes a brief summary of surveys by the US Federal Highway Administration and the South Dakota Department of Transportation which ask questions to determine the extent of the use of full depth reclamation throughout the US and Canadian provinces. For the covering abstract see ITRD E157233

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)0.000
metaresearch head score (Gemma)0.001
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.040
GPT teacher head0.258
Teacher spread0.217 · 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

Citations1
Published2008
Admission routes1
Has abstractyes

Explore more

Same venuePROCEEDINGS OF THE 4TH EURASPHALT AND EUROBITUME CONGRESS HELD MAY 2008, COPENHAGEN, DENMARKSame topicAsphalt Pavement Performance EvaluationFrench-language works237,207