MétaCan
Menu
Back to cohort
Record W2810970914 · doi:10.1002/hyp.13213

Stormwater capture and antecedent moisture characteristics of permeable pavements

2018· article· en· W2810970914 on OpenAlexafffund
Rui Guo, Yiping Guo, Jun Wang

Bibliographic record

VenueHydrological Processes · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship Council
KeywordsAntecedent (behavioral psychology)Antecedent moistureStormwaterEnvironmental scienceWater contentHydrology (agriculture)Event (particle physics)Range (aeronautics)Surface runoffMoistureSoil scienceGeotechnical engineeringMeteorologyRunoff curve numberGeologyEngineering

Abstract

fetched live from OpenAlex

Abstract An approach based on individual rainfall events is introduced to mathematically describe the hydrologic responses and estimate the stormwater capture efficiencies of permeable pavement systems (PPSs). A stochastic model describing the instantaneous dynamic water balance of a PPS is established, from which the probability distribution of the antecedent moisture content of the PPS at the beginning of a rainfall event is analytically derived. Based on this probability distribution and the event‐based approach, an analytical equation that can be used for estimating the stormwater capture efficiencies of PPSs is also derived. The derived analytical equation is verified by comparing its results with those from continuous simulations for a wide range of PPSs with different sizes and underlying soils and operating under various climate conditions. It was found that the antecedent moisture contents of PPSs at the test locations are usually fairly close to zero, suggesting that PPSs at these locations are always almost empty at the start of a rainfall event. The derived analytical equation accounts for many key processes influencing the behaviour and operation of PPSs; it may serve as an easy‐to‐use tool that is essential for the planning and design of PPSs.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.999

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 studies0.0000.001
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 head0.013
GPT teacher head0.214
Teacher spread0.201 · 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.

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

Citations22
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueHydrological ProcessesSame topicUrban Stormwater Management SolutionsFrench-language works237,207