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Record W4288435363 · doi:10.1061/9780784484296.001

A Universal Framework for Implementation of an Assess and Fix Water Main Rehabilitation Program

2022· article· en· W4288435363 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePipelines 2022 · 2022
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsManitoba Beekeepers' AssociationAecom (Canada)
Fundersnot available
KeywordsRehabilitationComputer sciencePhysical therapyMedicine

Abstract

fetched live from OpenAlex

The assess-and-fix approach was developed as an economical alternative assessment and rehabilitation strategy to optimize short- and long-term investment into water mains with a lower failure consequence, typically, distribution mains ≤300 mm (12″). As presented in AWWA M77, it introduces the concept of utilizing electromagnetic tool condition assessment techniques in a contiguous program operation with cleaning and lining to tailor the rehabilitation technique selection to the specific needs of the main. While the technologies that support an assess and fix approach are a collection of mature, well understood technologies and the potential economic benefits can be profound (e.g., the same level of investment could increase annual rehabilitation coverage by 40%–50% on a length basis), widespread implementation progress has been impeded by a lack of understanding of the framework required to support program implementation from a logistical perspective.

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)0.002
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 score0.424
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.081
GPT teacher head0.531
Teacher spread0.450 · 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