MétaCan
Menu
Back to cohort
Record W3047970104 · doi:10.1061/9780784483190.029

Assessment and Application of Trenchless Technologies for the Rehabilitation of Sewer Laterals

2020· article· en· W3047970104 on OpenAlex
Joanne B. Carroll, David P. Kozman, Carl Marc-Aurele

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 2020 · 2020
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsInstitut universitaire en santé mentale de Montréal
Fundersnot available
KeywordsTrenchless technologyPipeline transportSanitary sewerSeal (emblem)EngineeringCivil engineeringConstruction engineeringMechanical engineeringWaste management

Abstract

fetched live from OpenAlex

Several studies have confirmed that many of the lateral pipes in typical collection systems have reached their life expectancy and are either failing and/or contributing large amounts of infiltration and/or inflow (I/I) to the main sewer pipeline. In response, technology providers developed a number of products and technologies to line and seal lateral pipes and their connections to the mainline sewer. Lateral pipes often have multiple bends, diameter changes, offset joints, cracks, deposits, and roots, which create considerable challenges when lining or sealing. The lateral pipe connection to the sewer main also poses problems due to leaks, cracks, and poor alignment often created by improper connection procedures. Trenchless rehabilitation can address these issues while minimizing the impact to property owners and sewer providers. These technologies also provide an effective service life through proven, tested materials, and refined installation procedures to meet owner expectations.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.893
Threshold uncertainty score0.168

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 head0.008
GPT teacher head0.245
Teacher spread0.237 · 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