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Record W4402058449 · doi:10.1061/9780784485590.025

Integrated Infrastructure Transformation: Leveraging Multi-Departmental Goals for Efficient Urban Improvements

2024· article· en· W4402058449 on OpenAlexaff
Keith W. Gardner, David VanHoven, Daniel Amelin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsStantec (Canada)
Fundersnot available
KeywordsTransformation (genetics)Computer scienceModel transformationProcess managementEngineering managementRisk analysis (engineering)BusinessEngineering

Abstract

fetched live from OpenAlex

The Spring Hill Sewer Separation and Streetscapes Phase 1 project, located in Somerville, MA, was initially programmed as a straightforward sewer separation project. It is one of the five key projects in the City of Somerville’s Union Square Stormwater Mitigation Program designed to reduce the risk associated with aging infrastructure, solve existing system deficiencies, achieve regulatory compliance, and create system capacity to accommodate planned development. The underground challenges of separating 65 acres of 100-year-old combined sewers cause a significant impact on a residential neighborhood. Recognizing this early, the City pushed to incorporate many multi-departmental goals, including green stormwater infrastructure, renewal of an aging water distribution system, safer streets through multi-modal infrastructure improvements, increase to the urban forest canopy, as well as critical third party utility upgrades. By starting the community engagement and inter-departmental coordination process early in the planning phase of a project and returning to that coordination at multiple junctures throughout design and construction, the City of Somerville was able to achieve the initial goal of the project to remove clean stormwater from the combined sewer system and mitigate downstream flooding in Union Square while also achieving many of the aforementioned City goals within the neighborhood.

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: none
Teacher disagreement score0.856
Threshold uncertainty score0.598

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 communication0.0000.000
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 head0.011
GPT teacher head0.250
Teacher spread0.239 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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