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Record W2074148812 · doi:10.1080/1573062x.2013.763996

Potential and limitations of modern equipment for real time control of urban wastewater systems

2013· article· en· W2074148812 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

VenueUrban Water Journal · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality Monitoring Technologies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsFlexibility (engineering)ImplementationContext (archaeology)Risk analysis (engineering)Systems engineeringComputer scienceControl (management)Field (mathematics)SustainabilityReal-time Control SystemEngineeringBusiness

Abstract

fetched live from OpenAlex

Real Time Control (RTC) has become an accepted technique for improving the performance of Urban Drainage Systems (UDS) due to its flexibility and sustainability. Numerous implementations of RTC have been reported during the last decades. At the same time, guideline documents and state-of-the-art reports have been published. Whereas the general aspects and challenges of planning and installation of RTC systems are well covered, there is a lack of information about the adequate equipment for RTC of UDS. After identifying and briefly discussing the basic components of RTC systems for UDS, this paper describes the specific components in detail. This comprises the introduction of available technologies for sensors, actuators, controllers and telemetry systems in the context of RTC and the discussion of their potential and limitations. Lessons learned from the field operational experiences and future trends and challenges are identified.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score0.306

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 head0.025
GPT teacher head0.217
Teacher spread0.191 · 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