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Record W2299351234 · doi:10.14796/jwmm.r241-08

Modeling Green Infrastructure Components in a Combined Sewer Area

2011· article· en· W2299351234 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Water Management Modeling · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsnot available
FundersOffice of Research and DevelopmentU.S. Environmental Protection Agency
KeywordsGreen infrastructureCombined sewerEnvironmental scienceBusinessEnvironmental planningStormwaterSurface runoffEcology

Abstract

fetched live from OpenAlex

The purpose of the project described in this chapter is to evaluate the water quality and quantity improvement benefits of a large scale application of green infrastructure control practice retrofits in an entire monitored subcatchment. These green infrastructure controls have been shown, when implemented and maintained properly, to increase retention at the runoff source. This increased retention decreases the runoff volume entering the drainage system and the demand on a drainage system. Many researchers have reported findings that support these observations for individual or small neighborhood applications at LID (low impact development) conferences. This project is unique in that a large area is being retrofitted and will be monitored for many different scales to measure these benefits. This chapter describes a preliminary modeling effort that is being used to assist in the design of the practices at the site, showing how complementary practices that can be constructed on private property which will enhance the performance of the curb-side biofilters to be constructed in the public right-of-way.

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.

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)0.001
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 score0.136
Threshold uncertainty score0.821

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.001
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 head0.045
GPT teacher head0.204
Teacher spread0.159 · 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