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Record W4404843852 · doi:10.1016/j.jglr.2024.102489

Hydraulic characteristics of effective sea lamprey barriers

2024· article· en· W4404843852 on OpenAlexfundvenueno aff
Miki Hondzo, Vaughan R. Voller, Daniel P. Zielinski

Bibliographic record

VenueJournal of Great Lakes Research · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoastal and Marine Dynamics
Canadian institutionsnot available
FundersFisheries and Oceans CanadaU.S. Fish and Wildlife ServiceGreat Lakes Fishery Commission
KeywordsLampreyEnvironmental scienceFisheryBiology

Abstract

fetched live from OpenAlex

A network of 494 lowermost barriers on tributaries of the Laurentian Great Lakes prevents invasive sea lamprey ( Petromyzon marinus ) from accessing upstream spawning habitat and is critical to the success of the sea lamprey control program. The design goal of purpose-built barriers for sea lamprey control at low-head dams was to maintain a minimum vertical separation of 45 cm between the crest and downstream water level and a 15-cm overhanging lip. Due to physical site constraints limiting barrier design height and fluctuating stream water levels, many barriers cannot meet the design criteria. However, some barriers continue to block the passage of the sea lamprey even when the design criteria are not fulfilled. We conducted a physical modeling study of three sea lamprey barriers of varying historical efficacies to understand the hydraulic characteristics of effective barriers better. Results showed that time-averaged and horizontally averaged streamwise velocity, energy dissipation rate, and eddy length scale in the vertical direction strongly correlate with barrier efficacy. We combined the resulting variables into a dimensionless Barrier number that can be used to categorize barrier efficacy. Ineffective barriers generally had higher Barrier numbers than effective barriers. Our experimental investigation suggests that the fluid flow and turbulence conditions near the riverbed are not as crucial to barrier efficacy as those above the riverbed at 50 % of the crest height. Our work improves understanding of how existing barriers block sea lamprey movement, which could aid in the design of future sea lamprey barriers.

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)0.000
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.019
GPT teacher head0.288
Teacher spread0.269 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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