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Record W1943483516 · doi:10.2166/wqrj.2009.007

Characteristics of Sediment Removal in Two Types of Permeable Pavement

2009· article· en· W1943483516 on OpenAlexaff
Chris Brown, Angus Chu, Bert van Duin, Caterina Valeo

Bibliographic record

VenueWater Quality Research Journal · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSuspended solidsEffluentSedimentTotal dissolved solidsEnvironmental scienceEnvironmental engineeringAsphalt pavementTotal suspended solidsAsphaltGeotechnical engineeringGeologySewage treatmentWastewaterMaterials scienceComposite materialGeomorphologyChemical oxygen demand

Abstract

fetched live from OpenAlex

Abstract This study investigates the processes and characteristics of solids removal in two types of permeable pavement: UNI Eco-Stone and porous asphalt. The mechanisms and processes behind solids removal within permeable pavement structures was studied for these two types of permeable pavements using both field installations and laboratory experiments. Results from the study showed that both pavement types are capable of excellent total suspended solids removal, in the range of 90 to 96% removal of solids from influent. Particle size distribution analysis of accumulated sediment within the pavement structure and in the influent and effluent showed that the particles in the effluent of the pavements are substantially finer than that in the influent. Laboratory results involving no crust formation indicated that, although solids removal occurs throughout the entire structure, the "sieving action" occurs primarily at the geotextile interface.

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)0.000
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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.098
GPT teacher head0.391
Teacher spread0.293 · 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

Citations70
Published2009
Admission routes1
Has abstractyes

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