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Record W2303601957 · doi:10.14796/jwmm.r228-19

Evapotranspiration and Related Calculations for Bioretention Devices

2008· article· en· W2303601957 on OpenAlexvenueno aff
Robert E. Pitt, Shirley E. Clark, Pauline Johnson, John Voorhees

Bibliographic record

VenueJournal of Water Management Modeling · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsnot available
FundersU.S. Geological SurveyMonash University
KeywordsBioretentionEvapotranspirationEnvironmental scienceBiologyEcologyStormwaterSurface runoff

Abstract

fetched live from OpenAlex

Bioretention devices are becoming increasing popular stormwater management controls. However, there are many soil processes that affect their performance, and knowledge of these processes and soil characteristics are necessary in order to determine the expected performance of these devices under various conditions. This chapter stresses evapotranspiration (ET) and how it affects the water balance. Other processes discussed in this chapter include clogging from the capture of sediment on the bioretention facility device, cation exchange capacity (CEC) which is one measure of dissolved pollutant retention to protect groundwater, and sodium adsorption ratio (SAR) which can help identify adverse infiltration rate effects due to destabilized clay fractions in the soil. The steps for these analyses outlined here are being integrated into the Source Loading and Management Model (WinSLAMM)

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.253
Threshold uncertainty score0.290

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)0.0000.000

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 head0.031
GPT teacher head0.226
Teacher spread0.196 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations7
Published2008
Admission routes1
Has abstractyes

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