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Record W4387309845 · doi:10.2175/193864718825159186

Mr. Floatie Has Retired: Lessons Learned During Commissioning of a Greenfield Wastewater Treatment Plant in Victoria BC

2023· article· en· W4387309845 on OpenAlexaboutno aff
Sophia Gupta, Randy Craig, Mike McCoy

Bibliographic record

VenueProceedings of the Water Environment Federation · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Reuse
Canadian institutionsnot available
Fundersnot available
KeywordsProject commissioningScheduleEngineeringFlexibility (engineering)Operations managementPublishingManagementEconomicsPolitical science

Abstract

fetched live from OpenAlex

Mr. Floatie Has Retired: Lessons Learned During Commissioning of a Greenfield Wastewater Treatment Plant in Victoria BCAbstractThe McLoughlin Point Wastewater Treatment Plant (MPWWTP) in Victoria, British Columbia, Canada, is a greenfield tertiary treatment plant that services the Capital Regional District. The MPWWTP was commissioned and brought into service in autumn 2020, replacing an existing preliminary treatment system. During the commissioning effort at MPWWTP, challenges were posed by the small plant footprint and compact design, combinations of treatment technologies, stringent regulatory compliance requirements, decentralized facilities for residuals handling and screening, and the tight timeline for startup and commissioning. These challenges incited fastpaced problem solving, collaboration, and real-time learning for the project team. The successful commissioning of the MPWWTP was a result of strategic planning, consistent and thorough communication, and practiced flexibility. Despite various hurdles, the project was delivered to the client on schedule, and the resulting lessons learned are widely applicable to future full-scale commissioning efforts.The McLoughlin Point Wastewater Treatment Plant in Victoria, British Columbia, Canada, is a greenfield tertiary treatment plant servicing the Capital Regional District. The plant was successfully commissioned in autumn 2020 as a result of strategic planning, consistent and thorough communication, and practiced flexibility. Despite encountering several challenges, the project was delivered on schedule; the resulting lessons learned should be considered for future full-scale commissioning efforts.SpeakerGupta, SophiaPresentation time11:00:0011:30:00Session time10:30:0011:30:00SessionProject Delivery Challenges: Continued Operations and CommissioningSession locationRoom S404c - Level 4TopicFacility Operations and Maintenance, Intermediate Level, Municipal Wastewater Treatment Design, Utility Management and LeadershipTopicFacility Operations and Maintenance, Intermediate Level, Municipal Wastewater Treatment Design, Utility Management and LeadershipAuthor(s)Gupta, SophiaAuthor(s)S. Gupta 1; R. Craig 2 ; M. McCoy 3; S. Gupta 1;Author affiliation(s)AECOM 1; AECOM 2 ; Onyx Environmental Ltd. 3; AECOM 1;SourceProceedings of the Water Environment FederationDocument typeConference PaperPublisherWater Environment FederationPrint publication date Oct 2023DOI10.2175/193864718825159186Volume / Issue Content sourceWEFTECCopyright2023Word count18

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.901
Threshold uncertainty score0.197

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.002
Scholarly communication0.0040.002
Open science0.0020.004
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0320.010

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 head0.036
GPT teacher head0.229
Teacher spread0.194 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2023
Admission routes1
Has abstractyes

Explore more

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