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Record W2047995589 · doi:10.1139/l01-024

Scale model testing and calibration of City of Ottawa sewer weirs

2001· article· en· W2047995589 on OpenAlexvenueaboutno aff
J Bettez, R. D. Townsend, Adrien Comeau

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2001
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsWeirCalibrationHydraulicsDischarge coefficientHydrology (agriculture)Flow (mathematics)Geotechnical engineeringSanitary sewerFlow measurementEngineeringGeologyMechanicsEnvironmental engineeringGeographyMathematics

Abstract

fetched live from OpenAlex

This paper reports the results of a laboratory study of the effects of (i) manhole proximity to installation site, (ii) pipe slope (i.e., approach velocity), (iii) upstream head measurement location, and (iv) submergence on the "hydraulics" of two types of sewer weirs used by the City of Ottawa. The City's streamlined form of broad-crested weir and its compound-shaped sharp-crested weir were initially calibrated for a "pipe straight"-arrangement (no upstream manhole is present) for a wide range of flow conditions at 0.2%, 0.4%, and 1.0% pipe slopes. The calibration tests were then repeated with the weirs positioned immediately downstream of a model manhole structure ("manhole"-arrangement). Corresponding data sets were compared to determine the effects of (i) approach velocity and (ii) manhole proximity (for two different shapes of manhole "benching") on the respective weir discharge coefficients.Key words: sewer weirs, broad-crested weir, compound sharp-crested weir, calibration, sewer benching, discharge coefficients.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.245
Threshold uncertainty score0.486

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.161
Teacher spread0.151 · 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 designSimulation or modeling
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

Citations5
Published2001
Admission routes2
Has abstractyes

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