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Record W1988680622 · doi:10.1061/9780784413197.003

Permeable Pavement Design and Construction: What Have We Learned Recently?

2013· article· en· W1988680622 on OpenAlexaff
David Hein, Lori Schaus

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsGolder Associates (Canada)
Fundersnot available
KeywordsPervious concreteSubbaseStormwaterStormwater managementCivil engineeringGroundwater rechargeRetention basinEngineeringEnvironmental scienceGroundwaterGeotechnical engineeringSurface runoff

Abstract

fetched live from OpenAlex

Permeable pavements have been gaining popularity throughout North America. Permeable pavements typically consist of pervious concrete, porous asphalt, or permeable interlocking concrete block paving units over an open grade base/subbase layer(s). Permeable pavements are designed to infiltrate stormwater, reduce peak flows, filter and clean contaminants in the water stream, and promote groundwater recharge. They have become an integral part of low-impact design and best management practices for stormwater management. To be effective, permeable pavements must be designed to provide sufficient structural capacity to accommodate the anticipated vehicle loadings and deal with stormwater flowing into and out of the permeable pavement. While there have been many well designed and constructed permeable pavements, this is a relatively new technology and there have been some "issues" with their performance. This paper describes some of the basics of best practices, design, construction, and maintenance considerations for permeable pavement design and construction and focuses on best practices of permeable pavement design and construction in North America.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score0.998

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0310.003

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 head0.031
GPT teacher head0.212
Teacher spread0.182 · 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 designNot applicable
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

Citations10
Published2013
Admission routes1
Has abstractyes

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