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Record W4391367730 · doi:10.2175/193864718825159105

Louisville MSD's Data Driven Digital Transformation Journey Over 20 Years

2023· article· en· W4391367730 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueProceedings of the Water Environment Federation · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEconomic and Technological Systems Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsTransformation (genetics)Digital transformationComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Louisville MSD's Data Driven Digital Transformation Journey Over 20 YearsAbstractThe Louisville and Jefferson County Metropolitan Sewer District (MSD) in Kentucky has been at the national forefront of using innovative engineering practices, data-driven advanced analytics as well as automated systems to effectively protect local community waterways. Setting a bold vision of being the innovative regional utility for safe, clean waterways, MSD understood early on that cultural and organizational transformation is paramount to the success of embracing and integrating new technologies to meet utility goals and regulatory compliance. This paper showcases concrete examples of MSD’s digital and organizational transformation journey over the last two decades which include the timelines required to implement the projects, the projects outcome, and a summary of the resulting value which includes expanding the system and assets while improving workforce and operational efficiency, saving of over $200M in capital costs, and reducing overflows by more than two billion gallons per typical year.This paper showcases the digital and organizational transformation journey of MSD with examples: from incorporating real-time sensing data into the digital twin model which allows operators to monitor and control their facilities remotely, to developing performance metrics to shine light on the performance and functionality of the system and to provide other insights into operability and predictive maintenance, and to creating a blueprint for strategically transforming the organization.SpeakerMiller, WolffiePresentation time13:30:0014:00:00Session time13:30:0015:00:00SessionStories of Digital Transformation: It's Not About the Journey but the DestinationSession locationRoom S403b - Level 4TopicIntermediate Level, Utility Management and LeadershipTopicIntermediate Level, Utility Management and LeadershipAuthor(s)Miller, WolffieAuthor(s)W. Miller 1; S. Laughlin 2 ; D. Tao 3; T. Luking 4; O. Fradet 5; W. Miller 1;Author affiliation(s)Louisville MSD 1; Louisville MSD 2 ; Tetra Tech 3; Tetra Tech, Louisville, KY 4; Tetra Tech, Quebec City, QC 5; Louisville MSD, Louisville, KY 1;SourceProceedings of the Water Environment FederationDocument typeConference PaperPublisherWater Environment FederationPrint publication date Oct 2023DOI10.2175/193864718825159105Volume / Issue Content sourceWEFTECCopyright2023Word count11

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.526
Threshold uncertainty score0.522

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 communication0.0000.002
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 head0.022
GPT teacher head0.189
Teacher spread0.167 · 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