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Record W1969053202 · doi:10.2495/rm090261

Design of stream barbs for field scale application at Sawmill Creek, Ottawa

2009· article· en· W1969053202 on OpenAlexaffabout
E. C. Jamieson, Colin D. Rennie, R. D. Townsend

Bibliographic record

VenueWIT transactions on ecology and the environment · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsThalwegErosionChannel (broadcasting)Shear stressBank erosionSTREAMSStream flowFlow (mathematics)Computer simulationHydrology (agriculture)Environmental scienceGeotechnical engineeringMarine engineeringGeologyEngineeringGeographyComputer scienceMathematicsGeomorphologySimulationTelecommunications

Abstract

fetched live from OpenAlex

A three-dimensional numerical model Simulation in Intakes with Multiblock option (SSIIM) was used to model the effects of placing a series of barbs along an unstable section of Sawmill Creek, a small urban stream in the city of Ottawa, Canada. Stream barbs (a type of submerged groyne) are low-profile linear rock structures that prevent the erosion of stream banks by redirecting high velocity flow away from the bank. As they can be built at a relatively low cost and also provide significant ecological benefit, these structures are an important and relatively new method of stream bank protection. The numerical model was used to assess various design alternatives for a series of seven stream barbs at two consecutive channel bends requiring stabilization measures along their outer banks. Design criteria were principally based on the goals of reducing local velocities, shear stress and subsequent erosion at the outside bank of each bend, and on moving the thalweg away from the (existing) outside bank regions towards the centre of the channel. This paper reports on (i) the unique site conditions and environmental protection requirements, (ii) the results of the numerical simulation, and (iii) the design methodology.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.698
Threshold uncertainty score0.999

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)0.0010.000

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 head0.005
GPT teacher head0.190
Teacher spread0.185 · 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 teacher head, not a consensus.

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
Published2009
Admission routes2
Has abstractyes

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Same venueWIT transactions on ecology and the environmentSame topicHydrology and Sediment Transport ProcessesFrench-language works237,207